Influenza and influenza like illness in human populations in Uganda

TABLE OF CONTENTS

ANISE AGENDA

6 Meeting Agenda

ANISE ORAL ABSTRACTS

12 Samuel Bel-Nono Troop Education and Avian Influenza Surveillance in Military Barracks in Ghana

13 Yolanda Cardoso Respiratory Disease Surveillance in Angola? Which way to follow?

14 Deborah Caselton Does the length of refrigerated specimen storage affect influenza testing results by RT-PCR? An analysis of surveillance specimens in Kenya, 2008 – 2011

15 Cheryl Cohen Increased Risk of Death amongst HIV-infected Persons hospitalized with Influenza-confirmed illness in South Africa, 2009 – 2010

16 Ibrahim Dalhatu A Survey of Knowledge, Attitudes, and Practices Related to Reporting of Avian Influenza and other Notifiable Infectious Diseases by Public Sector Physicians in Nigeria, 2008

17 Manal Fahim Multiple Laboratory-based Approaches to Monitor Influenza Activity in Egypt, 1998 – 2011

18 Cardia Fourie Distribution of Pandemic Influenza A/nH1N1 in Patients presenting with Influenza like Illness, South Africa 2009 – 2010

19 Orienka Hellferscee Genetic and Phenotypic characteristics of Influenza viruses from the 2011 Influenza season in South Africa

20 Marie A. Muhimpundu Integrated Disease Surveillance and Response System Improves Influenza Surveillance in Rwanda

21 Emmanuel Nakouné Molecular Epidemiology of Viruses Responsible for Acute Respiratory Illnesses in Infants and Children from Bangui and Rural Areas in Central African Republic

22 Henry Njuguna Are smart phones better than paper-based questionnaires for surveillance data collection? A comparative evaluation using influenza sentinel surveillance sites in Kenya, 2011

23 Nancy Otieno Demographic, Socioeconomic and Geographic Determinants of Seasonal Influenza Vaccine Uptake in Rural Western Kenya, 2011

24 Soatiana Rajatonirina Influenza-like Illness Sentinel Surveillance using a Reporting System, Madagascar, 2008 – 2010

ANISE PROGRAM BOOK | 2 ANISE PROGRAM BOOK | 3

TABLE OF CONTENTS

25 Aimee Summers Methodology to Calculate the Annual Disease Burden of Influenza- Associated Severe Respiratory Illness in Kenya Using Population-Based and Sentinel Surveillance Data

26 John Victor Immunogenicity of trivalent inactivated influenza vaccine among rural Senegalese children

27 Sibongile Walaza Risk of Death amongst TB Patients hospitalized with Influenza in South Africa, 2009 – 2010

28 Nicole Wolter Increased risk of pneumococcal pneumonia among HIV and influenza co-infected patients hospitalized with pneumonia in South Africa, 2009 – 2010

ANISE POSTER ABSTRACTS

30 Adebayo Adedeji Virologic features of Influenza Cases investigated under the National Influenza Sentinel Surveillance System, Nigeria (2008 – 2011)

31 Ayoade Adedokun Prevalence of Pandemic A(H1N1)2009 Influenza virus in samples collected in Lagos: A report from the National Influenza Sentinel Surveillance-Lagos Site

32 William Ampofo Influenza-Like Illness (ILI) Surveillance in the Military Health Delivery Setting in Ghana

33 Workenesh Ayele A Review of Laboratory-Confirmed Cases of Influenza A(H1N1)pdm2009 in Ethiopia

34 Kossi Badziklou Data on Virological Surveillance of Influenza in Togo during Year 2011

35 Amal Barakat Viral Etiology and Seasonal Distribution of Respiratory Viruses in Patients Presenting with Severe Acute Respiratory Illness and Influenza like illness in Morocco, 2009 – 2011

36 Janeil Belle Comparative Assessment of Oxygen Capacity in Pre- and Post-pandemic (H1N1) sub-Saharan Africa: An Urgent Need for Oxygen Prioritization in Low-resource Health Systems

37 Terry Besselaar The WHO Global Influenza Surveillance and Response System

38 Karhemere Shamamba Sentinel Surveillance for Laboratory-confirmed Influenza in Kinshasa, Democratic Republic of Congo (2009 – 2011)

39 Joseph Bonney Virological Surveillance of Influenza-Like Illness among Children in Ghana, 2008 – 2010

40 Denis Byarugaba Paucity of complete influenza virus genomes from Sub-Saharan Africa limits full understanding of the virus evolutionally dynamics in the region

ANISE PROGRAM BOOK | 3

41 Ishata Conteh Establishing Sentinel Influenza Surveillance in Sierra Leone

42 Hugues Cordel A(H1N1)pdm Influenza in a semi-rural area in Madagascar: could the social patterns explain the spatial distribution?

43 Ndongo Dia Detection of Respiratory Viruses other than Influenza in Children leaving in a Suburb of Dakar

44 Ekanem Ekanem Health Workers’ Knowledge and Risk Perception to the 2009 Pandemic Influenza and Vaccine Acceptability: A Case Study of Two Tertiary Health Institutions in Lagos, Nigeria

45 George Gachara Analysis of Antigenic Drift in the Neuraminidase (NA) Gene of Pandemic H1N1 Influenza A Virus in Kenya

46 Aishatu Gubio Co-morbidity Factors associated with Influenza in Nigeria, November, 2011

47 Kondwani Jambo Influenza-Specific CD4+ T-Cell Responses are Impaired in Asymptomatic HIV-Infected African Adults

48 Bertin Kouakou Impact of Sample Quality on the Results of PCR and Virus Isolation in the Network of Influenza Surveillance in Cote d’Ivoire

49 Mark Katz Seasonal Influenza Vaccine Effectiveness in Refugee Children in Kenya, 2010 – 2011: A Retrospective, Case-control Study using Test-negative Controls

50 Halid Kirunda Risk Factors for Introduction and Spread of Avian Influenza in Live Bird Markets in Uganda

51 Essoya Dadja Landoh Influenza Sentinel Surveillance System in Togo: Trends of Circulating Influenza Strains, June 2010 – May 2011

52 Emmaculate Lebo Prevalence and clinical features of influenza virus infections and co- infections involving influenza and other respiratory viruses in Kenya, 2006 – 2011

53 Leopold Lubula Surveillance de la grippe en RDC

54 Janet Majanja Molecular Characterization of Human Influenza B Viruses circulating in Kenya during the Period 2008 – 2009

55 Jane Mallewa Seasonality and Burden of Influenza among Children and Adults Presenting to Queen Elizabeth Central Hospital with Influenza-like Illness or Severe Acute Respiratory Illness—Blantyre, Malawi, January – September 2011

56 Miriam Matonya Influenza Virological Surveillance in Tanzania between January – October 2011

57 Mazyanga Liwewe Epidemiology of Influenza in Zambia post Influenza A,H1N1 pandemic 2009

58 Keneth Mitei Human Parainfluenza Viruses Infections in Children, Kenya (2007 – 2011)

59 Peninah Munyua Pandemic Influenza H1N1 in Pigs Raised in Small Holder Farms in Kenya, 2010


60 Edison Mworozi Surveillance of Influenza and Influenza like Illness in Humans in Uganda

61 Dhamari Naidoo Current and Future Plans for Enhancing Influenza Laboratory Capacity in Africa by WHO and Partners

62 Richard Njouom Viral Etiology of Influenza-Like Illnesses in Cameroon, January to December 2009

63 Richard Nkunda Virologic Surveillance of Influenza Viruses in Rwanda, 2008 – 2011

64 Edith Nkwembe About the Seasonality of Influenza in Kinshasa, DRCongo in 2009 – 2011

65 Rachel Ochola Viral Etiologies of Acute Respiratory Infections among Inpatients and Outpatients in Rural Western Kenya, August 01, 2009 – July 31, 2011

66 Amaka Onyiah Virological Patterns of Influenza in Nigeria, March 2009 – September 2011

67 Benjamin Opot Divergent Evolution of Genes in Recent Influenza A (H3N2) Viruses Isolated in Kenya

68 Prisca Oria Do Kenyan Parents Want Their Children Vaccinated Against Influenza? Parental Attitudes towards Childhood Influenza Vaccination Prior to and Following an Influenza Vaccination Campaign, Kenya, 2010 – 2011

69 Nancy Ortiz Human Influenza Surveillance in Cameroon: Differences in Symptoms and Seasonality by Subtype

70 Norosoa Razanajatovo Viral Etiology of Severe Acute Respiratory Infection in Madagascar

71 Samwel Symekher Multiple and Single Infections of Influenza, RSV and Human Bocavirus during the Post Pandemic Period

72 Zekiba Tarnagda Virological Surveillance of Influenza-like Illness in Burkina Faso: Preliminary Results, 2010 – 2011

73 Youssouf Traoré Vaccination Campaign against 2009 Pandemic Influenza A (H1N1) in Côte d’Ivoire in September 2010

74 Alice Yuting Tsai Developing Respiratory and Emerging Infectious Disease Biosurveillance Activities in Resource-Limited Settings

75 Meshack Wadegu Molecular Antiviral Susceptibility Testing of Influenza A Virus Isolates obtained in Kenya in the Year 2008 – 2009

76 Lilian Waiboci Influenza Surveillance in Kenya, 2008 – 2011: A Low Likelihood of Successful Subtyping and Virus Isolation for Influenza Positive Specimens with High Cycle Threshold (CT) Values


ANISE AGENDA


3rd Annual African Network for Influenza Surveillance and Epidemiology (ANISE) Meeting Agenda

February 1-3, 2012 | Nairobi, Kenya

Wednesday, 1 February 2012

08:30 – 08:40 WELCOME AND OPENING REMARKS Kenya Ministry of Public Health and Sanitation World Health Organization Representatives from AFRO, EMRO and Kenya Centers for Disease Control and Prevention

08:40 – 08:50 WHO AFRO Update on Influenza Program, Francis Kasolo

08:50 – 09:00 WHO EMRO Update on Influenza Program, Sk Malik

09:00 – 09:30 Keynote Address: Reducing the Global Burden of Respiratory Illnesses: Successes, Challenges, and Lessons Applicable to Influenza Prevention in Africa Robert Breiman

SESSION I INFLUENZA SURVEILLANCE UPDATES

09:30 – 09:45 Influenza Burden and Prevention in Africa: A CDC Perspective, Marc-Alain Widdowson

09:45 – 10:00 Epidemiology of Influenza in Kenya, Phillip Muthoka

10:00 – 10:15 Influenza Update from WHO, Kaat Vandemaele

10:15 – 10:45 Global Virologic Surveillance, Nancy Cox

10:45 – 11:00 TEA BREAK

SESSION II VIROLOGIC SURVEILLANCE

11:00 – 11:20 Characterization of Influenza Viruses, Wallace Bulimo

11:20 – 11:35 Characterization and Distribution of Influenza Viruses from South African Patients with ILI and SARI during 2009 – 2011 Orienka Hellferscee

11:35 – 11:50 Influenza-like Illness Sentinel Surveillance using a Reporting System, Madagascar, 2008 – 2010 Soatiana Rajatonirina

11:50 – 12:00 Discussion


12:00 – 12:15 Are Smart Phones Better than Paper-based Questionnaires for Surveillance Data Collection? A Comparative Evaluation using Influenza Sentinel Surveillance Sites in Kenya, 2011 Henry Njuguna

12:15 – 12:30 Does the Length of Refrigerated Specimen Storage Affect Influenza Testing Results by RT-PCR? An Analysis of Surveillance Specimens in Kenya, 2008 – 2011 Deborah Caselton


12:40 – 13:40 LUNCH

COUNTRY PRESENTATIONS [A]

13:40 – 13:55 Cote d’Ivoire

13:55 – 14:10 Nigeria

14:10 – 14:25 Egypt

14:25 – 14:40 Morocco

SESSION III ANIMAL-HUMAN INTERFACE

14:40 – 15:00 Animal Influenza Viruses, Peninah Munyua

15:00 – 15:20 Influenza A(H5N1), Erica Dueger

15:20 – 15:50 TEA BREAK

SESSION IV ANIMAL-HUMAN INTERFACE (cont’d)

15:50 – 16:10 AU-IBAR, Speaker TBD

16:10 – 16:25 A Survey of Knowledge, Attitudes, and Practices Related to Reporting of Avian Influenza and other Notifiable Infectious Diseases by Public Sector Physicians in Nigeria, 2008 Ibrahim Dalhatu

16:25 – 16:40 Troop Education and Avian Influenza Surveillance in Military Barracks in Ghana Samuel Bel-Nono



Thursday, 2 February 2012

SESSION I BURDEN OF DISEASE

08:30 – 08:50 Estimate of Global Burden of Disease, Harish Nair

08:50 – 09:05 Methodology to Calculate the Annual Disease Burden of Influenza-Associated Severe Respiratory Illness in Kenya Using Population-Based and Sentinel Surveillance Data Aimee Summers

09:05 – 09:20 Multiple Laboratory-based Approaches to Monitor Influenza Activity in Egypt, 1998 – 2011 Manal Fahim

09:20 – 09:35 Respiratory Disease Surveillance in Angola? Which Way to Follow? Yolanda Cardoso


09:50 – 10:20 TEA BREAK

SESSION II BURDEN OF DISEASE (cont’d)

10:20 – 10:40 Estimating Influenza-associated Mortality in South Africa, Cheryl Cohen

10:40 – 10:55 Integrated Disease Surveillance and Response System Improves Influenza Surveillance in Rwanda Marie Aimee Muhimpundu

10:55 – 11:10 Role of Influenza among Pediatric Hospitalizations for Respiratory Disease: A Review of the Literature, Katie Lafond

11:10 – 11:25 Influenza Surveillance in 15 African Countries: The ANISE Network, Jazmin Duque

11:25 – 11:40 The EMARIS Network, Maha Talaat


12:00 – 13:00 LUNCH

COUNTRY PRESENTATIONS [B]

13:00 – 13:15 Tanzania

13:15 – 13:30 Uganda

13:30 – 13:45 Rwanda

13:45 – 14:00 Ethiopia


SESSION III CO-INFECTIONS AND OTHER RESPIRATORY PATHOGENS

14:00 – 14:30 The Synergistic Relationship of Influenza with Respiratory Bacteria: Transmission and Disease Severity Keith Klugman

14:30 – 14:50 Application of Taqman Array Cards (TAC) to the Diagnosis of Respiratory Diseases at International Emerging Infection Program Sites Barry Fields

14:50 – 15:10 Influenza and Rhinoviruses, Clayton Onyango

15:10 – 15:30 TEA BREAK

SESSION IV CO-INFECTIONS AND OTHER RESPIRATORY PATHOGENS (cont’d)

15:30 – 15:50 Influenza and Tuberculosis, Andrew Noymer

15:50 – 16:05 Increased Risk of Death amongst HIV-infected Persons Hospitalized with Influenza-confirmed Illness in South Africa, 2009 – 2010 Cheryl Cohen

16:05 – 16:20 Molecular Epidemiology of Viruses Responsible for Acute Respiratory Illnesses in Infants/Children from Bangui/Rural Areas, CAR Emmanuel Nakouné Yandoko

16:20 – 16:35 Risk of Death amongst TB Patients Hospitalized with Influenza in South Africa, 2009 – 2010 Sibongile Walaza

16:35 – 16:50 Increased Risk of Pneumococcal Pneumonia among HIV and Influenza Co-infected Patients Hospitalized with Pneumonia in South Africa, 2009 – 2010 Nicole Wolter (presented by Stefano Tempia)

16:50 – 17:10 Discussion and Wrap-up

17:10 – 18:30 POSTER SESSION WITH AUTHORS


Friday, 3 February 2012

SESSION I VACCINES/INTERVENTIONS

08:30 – 09:00 Update on Vaccine Technologies and Vaccination Strategies, Arnold Monto

09:00 – 09:20 Maternal Influenza Vaccine Trial in Mali, Boubou Tamboura

09:20 – 09:40 Ghana Pandemic Vaccine Experience, William Ampofo

09:40 – 09:55 Immunogenicity of Trivalent Inactivated Influenza Vaccine among Rural Senegalese Children John Chris Victor (presented by Mbayame Niang)

09:55 – 10:10 Demographic, Socioeconomic and Geographic Determinants of Seasonal Influenza Vaccine Uptake in Rural Western Kenya, 2011, Nancy Otieno


10:30 – 11:00 TEA BREAK

COUNTRY PRESENTATIONS [C]

11:00 – 11:15 Zambia

11:15 – 11:30 Madagascar

11:30 – 11:45 Angola

11:45 – 12:00 DRC

12:00 – 12:15 South Africa

12:15 – 12:35 Conclusions and Closing Remarks, Marc-Alain Widdowson END OF SCIENTIFIC PORTION OF THE MEETING

12:35 – 13:30 LUNCH

SESSION II INFORMATION SHARING AND NEXT STEPS FORWARD

13:30 – 14:00 Planning 5 Year Sustainability Reviews, Ann Moen

14:00 – 14:20 Considerations for Sustainability - South Africa, Cheryl Cohen

14:20 – 15:00 Roundtable Discussion: Laboratory Issues

15:00 – 15:30 TEA BREAK

15:30 – 16:10 Roundtable Discussion: Influenza Surveillance Issues

16:10 – 16:30 Conclusions and Closing Remarks, Ann Moen



ANISE ORAL ABSTRACTS


Abstract Title Troop Education and Avian Influenza Surveillance in Military Barracks in Ghana

Authors John Kofi Odoom, Samuel Bel-Nono, David Rodgers, Prince G. Agbenohevi, Courage K. Dafeamekpor, Roland M. L. Sowa, Fenteng Danso, Reuben Tettey, Richard Suu-Ire, Joseph H. K. Bonney, Ivy A. Asante, James Aboagye, Christopher Zaab-Yen Abana, Joseph Asamoah Frimpong, Karl C. Kronmann, Buhari A. Oyofo, William K. Ampofo

Background Influenza A viruses that cause highly pathogenic avian influenza (HPAI) also infect humans. In many developing countries such as Ghana, poultry and humans live in close proximity in both the general and military populations, increasing risk for the spread of HPAI from birds to humans. Respiratory infections, such as influenza, are especially prone to rapid spread among military populations living in close quarters, such as barracks, making this a key population for targeted avian influenza surveillance and public health education.

Method Twelve military barracks situated in the coastal, tropical rain forest and northern savannah belts of the country were visited and the troops and their families educated on pandemic avian influenza. The seminars focused on zoonotic diseases, influenza surveillance, pathogenesis of avian influenza, prevention of emerging infections and biosecurity. To help direct public health policies, a questionnaire was used to collect information on animal populations and handling practices from 102 households in the military barracks. Cloacal and tracheal samples were taken from 680 domestic and domesticated wild birds and analysed for influenza A using molecular methods for virus detection.

Results Of the 1028 participants that took part in the seminars, 668 (65%) showed good knowledge of pandemic avian influenza and the risks associated with its infection. Even though no evidence of the presence of avian influenza (AI) infection was found in the 680 domestic and wild birds sampled, biosecurity in the households surveyed was very poor.

Conclusion Active surveillance revealed that there was no AI circulation in the military barracks in the spring of 2011. Though participants demonstrated good knowledge of pandemic avian influenza, biosecurity practices were minimal. Sustained educational programs are needed to further strengthen avian influenza surveillance and prevention in military barracks.

Key words Surveillance, pandemic avian influenza, biosecurity, education, military, Ghana


Abstract Title Respiratory Disease Surveillance in Angola? Which way to follow?

Authors Cardoso, Y., Vasconcelos, J., Oliveira, E., Cohen, A.L.,Valente F.

The Angolan health care system capacity, human and financial resources are overwhelmed by demand of endemic diseases such as Malaria, Tuberculosis (TB), as well as diarrheic infections. While these are the diseases with the highest mortality rates, the burden of acute respiratory infections also creates enormous challenges for the health system in the country. An Integrated Disease Surveillance and Response system was initiated in Angola in 2003. Data is collected throughout the country and sent to the Department of Public Health for analysis and monthly dissemination of the information. The largest provinces are Huambo, Bié, Benguela and Luanda, the latter being the capital city, with an estimate of 3 072 000 inhabitants accounting for 17% of the whole population. The main hospitals in Luanda are Josina Machel (HJM), Américo Boavida (HAB) and Pediátrico David Bernardino (HPDB) which are also part of the Influenza surveillance system.

There are no published data on influenza trends in Angola, where pneumonia is the leading cause of death among young children. This study aims to compare the incidence and mortality rates for Malaria, TB, and diarrheic infections with the rates for acute respiratory diseases among patients of all ages observed during 2010 in HJM, HAB and HPDB in Luanda, to better understand the efficacy of the influenza surveillance system. In 2010 a total 3 687 574 cases of Malaria were reported with 0.2% of mortality; for TB 42 210 cases were reported with 2.6% mortality; and for diarrheic infection 540 554 cases with 0.4% mortality whereas for respiratory infections 987 421 cases with 0.2% mortality. Comparatively with the other provinces Luanda reported 164 651 cases with 0.3% mortality, while Huambo reported 222 576 cases with 0.1% mortality, Bié reported 88 422 with 0.1% and Benguela reported 56 044 cases with 0.1% mortality. In Luanda, the main hospitals reported 1 616 cases with 2.7% mortality (HJM), 1 780 cases with 3.7% mortality (HAB) and 15 350 with 1.5% mortality (HPDB).

However, influenza sentinel surveillance data shows that only HPDB reported 465 cases from which nasal and oral swabs were collected in patients hospitalized or seen in an outpatient clinic with acute respiratory infection. Collected samples were tested following the CDC protocol for Real-Time polymerase chain reaction assays. Of 465 samples collected, twenty-five tested positive for Influenza of which B (n=16), A (H3) (n=9) and A (H1N1) (n=0). Data from the main hospitals in Luanda suggest that the influenza surveillance system is not being efficient as only HPDB reported a low number of cases with no mortality associated. Strengthening of the influenza surveillance system or change in the approach of surveillance is needed to better understand the burden of influenza comparatively to other respiratory diseases for the Angolan population.


Abstract Title Does the length of refrigerated specimen storage affect influenza testing results by RT-PCR? An analysis of surveillance specimens in Kenya, 2008 – 2011

Authors Deborah Caselton1, Geoffrey Arunga1, Gideon Emukule1, Phillip Muthoka2, Abigail Kosgey1, Rachel Ochola1, Lillian W. Waiboci1, Daniel Feikin3, Robert F. Breiman3, Mark A. Katz1

Affiliations 1Influenza Program, Global Disease Detection Division, Centers for Disease Control and Prevention, Kenya 2Kenya Ministry of Public Health and Sanitation 3International Emerging Infections Program, Global Disease Detection Division, Centers for Disease Control and Prevention, Kenya

Background Real time reverse transcription-polymerase chain reaction (rt RT-PCR) is increasingly used for routine influenza surveillance. Extended storage time in the refrigerator may decrease the viability of samples and therefore affect testing outcomes. We conducted a retrospective secondary data analysis to determine the relationship between the number of days a specimen was in refrigeration and the influenza positivity as well as the rRT-PCR Cycle Threshold (Ct) values for influenza-positive specimens using data from an influenza sentinel surveillance system in Kenya.

Methods We collected nasopharyngeal (NP) and oropharyngeal (OP) specimens from outpatients with influenza-like illness and inpatients with severe acute respiratory illness at influenza sentinel surveillance sites in Kenya. Specimens were stored in VTM at 2-8°C, transported to Nairobi, and tested for Influenza A and B using rRT-PCR. We used multivariable logistic regression to determine the relationship between the number of days a specimen was in refrigeration and influenza positivity using three years of influenza surveillance data from Kenya (2008-2011). We also conducted ordinal logistic regression to evaluate the relationship between refrigeration days and the rRT-PCR Cycle Threshold (Ct) values of influenza-positive specimens.

Results Of 17,494 samples collected during the study period, 9,720 had storage data available and were included in the analysis. Of the 9,720 samples, 1113 (11.5%) were positive for influenza, of which 902 (9.3%) were Influenza A, 251 (2.6%) were Influenza B, and 40 (0.4%) were positive for both A and B. 5241 (53.9%) were from male patients. The mean age of patients was 3.4 years, and the majority of samples (63.0%) were from patients 0.05). After 4 days in storage, the mean Ct value of influenza-positive specimens increased; however, ordinal logistic regression showed no statistically significant relationship between days in refrigeration and Ct values (p>0.05).

Conclusion We found that samples could remain in storage at least 5 days without affecting the proportion-positive of samples. Ct values of influenza-positive specimens did not vary significantly by days in storage. Influenza surveillance systems could consider increasing the maximum time a specimen can be stored. This may be especially useful in rural areas, where frequent transport of samples to central laboratories can be challenging.


Abstract Title Increased Risk of Death amongst HIV-infected Persons hospitalized with Influenza-confirmed illness in South Africa, 2009 – 2010

Authors Cheryl Cohen, Jocelyn Moyes, Sibongile Walaza, Michelle Groome, Babatyi Kgokong, Stefano Tempia, Halima Dawood, Kathy Kahn, Ebrahim Variava, Nicole Wolter, Anne von Gottberg, Marthi Pretorius, Marietjie Venter, Shabir A. Madhi

Introduction There are limited published studies on influenza-associated illness in HIV-infected individuals. We aimed to compare the clinical and epidemiologic characteristics of HIV-infected and uninfected patients with influenza infection.

Methods Hospitalised patients presenting with severe acute respiratory infection (SARI) were enrolled prospectively at public hospitals in four provinces of South Africa. Clinical and epidemiologic data were collected. Upper respiratory samples were tested for the presence of influenza virus by real time RT-PCR and blood samples tested for pneumococcal DNA using real time PCR.The study was a cohort study including all patients testing influenza-positive. Characteristics of patients testing HIV-positive were compared to those testing HIV-negative.

Results Influenza was identified in 714 (9%) of 8263 patients enrolled. HIV infection status was available for 501 (70%) subjects including: 11 (2%) influenza A(unsubtyped), 157 (31%) influenza A(H1N1)2009, 161 (32%) influenza A(H3N2) and 172 (34%) influenza B. The HIV-prevalence by age group was: 13% (13/100), 21% (22/104), 38% (8/21), 49% (17/35), 87% (131/151), 58% (40/69)and 20% (4/20) in the <1, 1-4, 5-14, 15-24, 25-44, 45-64 and ≥ 65 years age groups respectively (p<0.01). The prevalence of HIV was greater in cases associated with influenza B than other subtypes (A(H1N1)2009 66/157 [42%], A(H3N2) 56/161 [35%], B 108/171 [63%], p<0.01). HIV-infected patients had a longer mean duration of hospitalisation (8 days [95% confidence interval (CI) 7-9] vs 5 [95% CI 4-6] days, p<0.01) and higher case-fatality ratios (22/211, 9% vs 5/265, 2%, p<0.01). HIV-positive patients were more likely to have evidence of confirmed pneumococcal co-infection (29/225, 13% vs 16/240, 7%, p=0.02) and to have received treatment for tuberculosis in the past year (26/233, 11% vs 5/261, 2%, p<0.01). On multivariable analysis controlling for age group and year, HIV-infected patients were four times more likely to die than HIV-uninfected patients (odds ratio 4, 95% CI 1-12).

Conclusions The HIV prevalence is high amongst patients infected with influenza in South Africa. HIV-infected patients have increased mortality as compared to HIV-negative individuals. HIV-infected patients should receive early antiviral therapy and should receive preventive measures such as annual influenza vaccination.


Abstract Title A Survey of Knowledge, Attitudes, and Practices Related to Reporting of Avian Influenza and other Notifiable Infectious Diseases by Public Sector Physicians in Nigeria, 2008

Authors •IbrahimDalhatu,CentersforDiseaseControlandPrevention,Nigeria •KathrynE.Lafond,CentersforDiseaseControlandPrevention,AtlantaGAUSA •DianeGross,CentersforDiseaseControlandPrevention,AtlantaGAUSA •EkanemE.Ekanem,CentersforDiseaseControlandPrevention,Nigeria •SaiduAhmed,FederalMinistryofHealth,Nigeria •PatrickPeebles,CentersforDiseaseControlandPrevention,AtlantaGAUSA •VivekShinde,WorldHealthOrganization,Geneva,Switzerland •AnthonyMounts,WorldHealthOrganization,Geneva,Switzerland •AbdulsalamiNasidi,NigeriaCentreforDiseaseControl,Nigeria

Introduction The first human case of avian influenza (AI) infection in the African region was identified in Lagos, Nigeria in January 2007. Case finding for human infection with AI and other notifiable diseases relies on the ability of physicians to identify suspected cases, collect specimens for testing, and report to the Ministry of Health. The purpose of this study was to determine physician knowledge, attitudes, and practices (KAPs) pertaining to diagnosis and reporting of AI and other notifiable and epidemic prone infectious diseases in Nigeria.

Methods Between November and December 2008, we surveyed 245 public sector physicians working in six Nigerian cities (Ibadan, Kano, Benin City, Maiduguri, Aba, and Abuja). Survey components included basic respondent demographics, reporting practices for AI and other diseases, obstacles to disease reporting and information sources used by the physicians.

Results All 245 respondents reported that they had heard of AI and that humans could become infected with AI. A majority correctly identified common symptoms (91%) and modes of transmission (89%). Nearly all participating physicians reported having a cell phone that they currently use (99%), with more than 99% sending text messages (SMS) at least weekly. Similarly, 94% reported having a current email address and 84% checked email at least weekly. Internet websites were reported as the single most useful source for learning about AI (26%). Most (67%) participating physicians had previously reported a notifiable disease; the most common disease reported was polio (42%).The most common perceived obstacles to reporting notifiable diseases identified were: lack of infrastructure/logistics or reporting system (31%); doctors not knowing how or to whom to report (26%); and doctors not knowing that they should report (24%).

Conclusion Despite widespread awareness of avian influenza, including common symptoms and modes of transmission, there was no consensus among physicians to whom they should report notifiable diseases, and physicians noted many obstacles to reporting. Since physicians reported widespread use of internet, email and cell phones, future improvements to the reporting system could benefit from increased utilization of the internet, as well as SMS and email-based communication.


Abstract Title Multiple Laboratory-based Approaches to Monitor Influenza Activity in Egypt, 1998 – 2011

Authors Manal Labib, Samir Refae, Mohamed Genedy, Amro Kandeel

Background The Egyptian Ministry of Health and Population (MOHP) has established different laboratory-based surveillance systems to identify the emergent strains of influenza and to follow its trends over time. Systems include: sentinel site outpatients Influenza-like Illness (ILI) surveillance, sentinel site severe acute respiratory illness (SARI) surveillance, National Exhaustive acute respiratory tract (ARI) syndromic surveillance for pandemic H1N1 surveillance and Avian Flu surveillance.

Methods ILI surveillance has been established in 1998 at 8 sites; from each site 15 ILI outpatients are selected, swabbed weekly. SARI surveillance started in October 2007 in 8 sites; swabs from eligible admitted cases. ARI syndromic surveillance for pandemic H1N1 started in 2009, cases are identified, throat swabs taken and tested for pneumonia, SARI cases only, proportions of ILI, SARI and pneumonia cases are reported to MOHP on a weekly basis. National avian flu surveillance started in January 2006; suspect cases detected in all MOHP health care facilities are being isolated, swabbed for testing and treated according to MOHP protocol. For influenza surveillance systems standardized epidemiologic data collection and throat swabs are collected and tested by RT-PCR according to CDC standardized methods at MOHP Central Public Health Laboratory; in collaboration with the US Naval Medical Research Unit #3 laboratory.

To cope with the influenza pandemic, Egypt MOH has established 5 sub-national laboratories, arranged stockpiling of antiviral drug Tamiflu and pandemic H1N1 vaccine.

Results From week 40, 2009- week 40, 2011, 7273 specimens were collected in the ILI surveillance; out of them 408 (6%) were pandemic H1N1, 289 (4%) Flu-B, 118 (2%) Flu-A/H3, 11 (0.2%) seasonal Flu-A/H1, 2 co-infection and 2 Flu-A/H5N1. Through SARI surveillance, 6656 cases were swabbed, 731 (11 %) were pandemic H1N1, 346 (5%) Flu-B, 73 (1 %) Flu-A/H3, 12 (0.2%) seasonal Flu-A/H1, other pathogens were 917 (13.8%) most of them were RSV 579 (8.7%). Case fatality rate from SARI was 5%, including 0.3% from the pandemic H1N1. H1N1 National surveillance has identified 33,013 suspected cases and confirmed 20,329 (61.6%) of them, from which 453 (2%) were fatal, 362 (1%) were Flu-A/H3, and 168 (0.5%) seasonal Flu-A/H1. The Avian flu system has identified 12,382 suspect cases since March 2006, 152 cases have been confirmed as Flu-A/H5N1, 52 (34.2%) of them were fatal.

Conclusion Egypt’s surveillance systems have provided timely data on the circulation, trends and severity of influenza that was used for strategic planning. These systems would ideally undergo regular data audits and systematic field evaluation to maximize its usefulness for decision makers.


Abstract Title Distribution of Pandemic Influenza A/nH1N1 in Patients presenting with Influenza like Illness, South Africa 2009 – 2010 [C]

Authors Buys A, Fourie C, Stuurman X, McAnerney JM, Naidoo D, Pretorius M, Rakgantso A, Howard W, Naicker P, Blumberg L, Venter M

Background Annual global outbreaks of Influenza viruses cause estimated 250 000 to 500 000 deaths per year. World Health Organization leads the global Influenza surveillance network to monitor not only the different subtypes of Influenza, but also the changes occurring within Influenza strains. Influenza is known to undergo antigenic drift or shift emphasizing the importance of active surveillance so that changes in the circulating strains can be reported for annual vaccine updates. In South Africa the NICD forms part of this network as National Influenza Center (NIC). The Viral Watch Influenza Surveillance Program is a sentinel surveillance program and started in SA in 1984 and includes all 9 provinces. Specimens from patients presenting with ILI are collected by participating medical practitioners. In April 2009 a novel Influenza A/ H1N1 strain emerged and WHO declared a pandemic on 11 June 2009. In SA the first case was detected in a traveler on 15 June 2009. The NIC at NICD was the only facility in SA that initially tested for all suspected cases of pandemic Influenza A / nH1N1. Once the pandemic spread throughout SA, testing was decentralized to other NHLS laboratories.

Methods 5288 ILI specimens were collected during 2009 - 2010 by sentinel sites and were screened using rRT-PCR and shell vial technique. The rRT-PCR, which is substantially more sensitive, was implemented to ensure that the impact of the pandemic H1N1 was not underestimated. The Influenza positive specimens were subtyped using the CDC (rRT-PCR) Protocol for Detection and Characterization of Influenza. The Influenza viruses detected were cultured and isolates were provided for sequencing to determine oseltamivir resistance and antigenic drift. Hemagglutinin inhibition assays were used to identify antigenic changes relative to the vaccine strain.

Results During 2009, two distinct peaks of Influenza activity were observed. Influenza A / H3N2 and pandemic Influenza A / H1N1 had activity between May to July and July to October respectively, with minor activity of Influenza B in August. In total 1760 Influenza positives were detected during 2009 with 712 pandemic Influenza A / nH1N1, 863 Influenza A / H3N2, and 122 Influenza B positives. However, in 2010 Influenza B was predominant with peak activity in July and August. There were 446 Influenza B, 220 Influenza A / H3N2 and 199 pandemic Influenza A / nH1N1 positives detected. No oseltamivir resistance and only limited genetic drift were detected in the isolates sequenced during 2009 and 2010. HAI assays suggested that the strains remained antigenically similar to the 2009 vaccine strain.

Conclusion The Viral Watch Influenza Surveillance Program contributed significantly to the success of the National Influenza Centre to respond and monitor the emergence and the subsequent seasonal circulations of a new pandemic Influenza strain in SA.

*[C] – Combined Abstract


Abstract Title Genetic and Phenotypic characteristics of Influenza viruses from the 2011 Influenza season in South Africa [C]

Authors Florette Treurnicht, Orienka Hellferscee, Dhamari Naidoo, Amelia Buys, Marthi Pretorius, Jo Mcanerney, Cheryl Cohen, Lucille Blumberg, Adrian Puren, Barry Schoub, Shabir Madhi, Marietjie Venter

Introduction During 2011 South Africa had an extended Influenza season starting with Influenza A H1N1pdm09 followed with a pronounced second peak of Influenza A(H3N2) and Influenza B activity. Here we present data on the genetic and phenotypic characterization of these Influenza A and B strains.

Methods Nasopharyngeal aspirate and nasopharyngeal or oral swab samples were tested for the presence of influenza virus infection by real time RT-PCR. Genetic characterization was done by PCR and sequencing of the HA and NA genes for phylogenetic analysis to identify genetic drift and drug resistance mutations. Antigenic characterization of influenza virus isolates was done using the hemagglutination inhibition test. We also screened for sensitivity of the Influenza A strains to the neuraminidase inhibitors using a phenotypic assay. Real-time PCR allelic discrimination assays was used to screen for the H274Y oseltamivir resistance signature mutation in Influenza A(H1N1)pdm09 samples (but not in H3N2 isolates) and to subtype Influenza B.

Results Up to October (week 44), 7457 specimens were tested. Influenza was identified in 1695 (22.7%) specimens. The results were as follows: 12 (0.7%) Influenza A (not subtyped, due to too low viral load), 1138 (67.1%) Influenza A(H1N1)pdm09, 287 (16.9%) Influenza A(H3N2) and 263 (15.5%) Influenza B. Subtyping of 125/263 Influenza B positive samples identified 12 (8.5%) as Influenza B/Brisbane/60/2088-like and 65 (46.1%) as Influenza B/Yamagata/16/1988-like. The HA1 gene of 59 Influenza A(H1N1)pdm09 strains were sequenced, and the SA 2011 strains grouped in 2/6 lineages that dominated the Northern hemisphere in 2010/2011. The HA gene of 31 Influenza A(H3N2) strains were sequenced and clustered with the 2010 South African strains that are A/Victoria/208/2009-like. The HA gene of 31 Influenza B strains were sequenced and 8 grouped with B/Brisbane/60/2008 (the current vaccine strain) and 23 were B/Yamagata/16/1988-like. Of 53 A(H1N1)pdm09 isolates, 51 were antigenically similar to the A/California/7/2009 (H1N1) strains and 2 were low reactors. Only 4/12 Influenza A(H3N2) isolates could be characterised antigenically due to low titres in culture of which 3 were A/Perth/16/2009 (H3N2)-like and 1 was a low reactor. Antigenic characterisation of 18 Influenza B isolates showed 5 was reactive with B/Brisbane/60/2008 antisera whereas 13 showed reactivity to the B/Florida/4/2006 antisera but were all low reactors. None of the Influenza A subtypes had the H274Y mutation or showed phenotypic resistance to the neuraminidase inhibitors.

Conclusions For the 2011 Influenza season mainly Influenza A(H1N1)pdm09 were detected, followed by Influenza A(H3N2) and Influenza B. For Influenza A(H1N1)pdm09 strains, limited drift was seen and 2011 strains clustered with 2010 strains. For Influenza A(H3N2) strains, the 2011 strains clustered genetically with A/Victoria/208/2009, similar to the 2010 strains. Of significance was the increased presence of B/Yamagata like strains, which should be monitored in vaccine failures in the next season.

*[C] – Combined Abstract


Abstract Title Integrated Disease Surveillance and Response System Improves Influenza Surveillance in Rwanda

Authors M. A. Muhimpundu, T. Nyatanyi, E. Karuranga, J. Rukelibuga, A. Kabeja

Introduction In July 2008, the Ministry of Health established an influenza sentinel surveillance system in six health facilities (HF) to describe the epidemiology and seasonality of influenza, monitor emergence of novel influenza viruses, describe the circulating influenza types and subtypes, and to promptly detect influenza outbreaks in the country. Despite the fact that, the established influenza surveillance network is achieving its main objectives, it is not able to provide baseline data to determine influenza thresholds and to establish denominator to estimate the burden of disease. In 2011, Rwanda started a process of reviewing and strengthening its Integrated Diseases Surveillance and Response system (IDSR). We used the review process as an opportunity to improve influenza surveillance by integrating influenza like illness (ILI) and severe pneumonia in children < 5 years on the list of priority diseases to be reported in the surveillance system.

Method We developed standard case definitions (SCD) of ILI and severe pneumonia in children < 5 years and included these definitions in IDSR technical guideline and training modules. Both, ILI and severe pneumonia < 5 years are on the weekly reportable diseases. Health workers from all district hospitals (DH) as well as health providers from 72 Health Centers (HC) were trained on how to identify cases using SCD, how to report and analyze data of immediate and weekly reportable diseases using electronic system called “electronic Integrated Diseases Surveillance and Response” (eIDSR) piloted in five DH and 72 HC. SCD were distributed to HF to guide clinicians to identify cases. Facilities are expected to submit weekly epidemiological reports every Monday before 12:00 noon. If this is not done, the electronic system sends to concerned HF data manager an automatic message reminding them to send weekly report.

Results Since October 2011 the pilot health facilities have reported 8,768 cases of ILI and 383 cases of severe pneumonia in children < 5 years. Average completeness of epidemiological weekly reports is 98 % and average timeliness is 90%. During these five weeks, an unusual increase of ILI cases in Kibungo DH (from 219 to 633 cases of ILI) was observed.

Conclusion The integration of surveillance of ILI and severe pneumonia < 5 years in the IDSR in Rwanda improves influenza surveillance in the country. We recommend a roll out of ILI and severe pneumonia surveillance to all health facilities in the country and the triangulation of data from influenza sentinel sites and from IDSR in order to generate national data to determine the true burden of the disease in the country.

Key words Influenza, surveillance, IDSR, Rwanda


Abstract Title Molecular Epidemiology of Viruses Responsible for Acute Respiratory Illnesses in Infants and Children from Bangui and Rural Areas in Central African Republic

Authors Emmanuel Nakouné, Vianney Tricou, Alexandre Manirakiza, Francis Komoyo, Benjamin Selekon, Edgar Dimbele, Chrizostome Gody and Mirdad Kazanji

Background Viral acute respiratory illnesses in children from sub-Saharan Africa have received relatively little attention in spite of being a major cause of morbidity and mortality. An active surveillance is essential to identify etiological agents and then improve the clinical management especially in the context of possible circulation of pandemic viruses.

Methods A prospective study was conducted in infants and children aged from 0 to 15 years consulting sentinel sites in Bangui and 3 rural areas of Central African Republic (CAR) for a suspicion of pandemic influenza A/H1N1 or acute respiratory illness in general. The viral causative agents were identified by molecular methods and amplicons were sequenced for genetic characterization.

Results From January to December 2010, 329 nasopharyngeal swabs were collected. Acute respiratory viruses were detected in 49 children (14, 9%): 29 (8, 8%) were positive for influenza viruses (5 (1, 5%) for the pandemic influenza A/H1N1 virus and 24 (7, 3%) for influenza B viruses), 11 (3,3 %) for parainfluenza viruses type 1 and 3 and 9 (2,7 %) for the respiratory syncytial virus. Two deaths of infant have been recorded, one among those infected by influenza B virus and one among those infected by respiratory syncytial virus. Genetic characterization showed that the sequence of the influenza B virus strain that caused the death of one infant was different from that of other strains circulating in Bangui, while the sequence of respiratory syncytial virus that caused the death of the second infant did not show any difference from those virus found in alive infants.

Conclusion This is the first report of the circulation of the pandemic influenza virus A/H1N1 virus in CAR. This study provides also evidence for involvement of other viruses in acute respiratory illnesses, among which influenza B viruses were predominant, and gives molecular details on strains circulating in CAR compared to circulating strains in other countries.

Key words Molecular Diagnosis, Children, ARI, Pandemic Influenza A/H1N1 2009, Influenza B, RSV, Parainfluenza Virus


Abstract Title Are smart phones better than paper-based questionnaires for surveillance data collection? A comparative evaluation using influenza sentinel surveillance sites in Kenya, 2011

Authors Njuguna Henry1, Caselton Deborah1, Emukule Gideon1, Kinyanjui Dennis2, Muthoka Philip3, Kinkade Carl4, Mott Joshua A.1, Katz Mark1

Affiliations 1Centers for Disease Control- Kenya (CDC-Kenya), 2Kenya Medical Research Institute/Centers for Disease Control Kenya (KEMRI/CDC), 3Ministry of Public Health and Sanitation, Kenya, 4Centers for Disease Control, Atlanta, USA

Background Manual data collection and data entry using paper-based questionnaires can be time consuming and prone to errors. We introduced smartphones in 4 hospital-based influenza sentinel surveillance sites in Kenya. We compared smartphone-collected data to paper-based-collected data previously collected by the same surveillance officer.

Methods Since 2006, the Kenya Ministry of Health and the Kenya Medical Research Institute/Centers for Disease Control have conducted sentinel influenza surveillance at 11 hospitals in Kenya. At each site, surveillance officers identify patients with respiratory illness and administer a brief (18 question) questionnaire that includes demographic and clinical information. From May – June 2011, we pilot-tested an electronic data collection system using Field Adapted Survey Toolkit (FAST) on HTC Touch Pro2 smartphones at four sentinel sites. For each site, we compared data collected using smartphone questionnaires to an equal number of paper-based questionnaires collected prior to introduction of smartphones by the same surveillance officer. We evaluated completeness of data collection, errors in data entry and time taken to enter collected data into the central database. We projected cost of running the two systems for a year and compared them. In addition we sought the surveillance officers’ experiences on using these data collection tools.

Results A total of 1,019 paper-based questionnaires were collected at the four sites from Dec 14, 2010- June 6, 2011 and 1,019 smartphone questionnaires were collected at the same four sites from May 3, 2011-Aug 26, 2011. Seven paper-based questionnaires had duplicated patient identification numbers, while no duplication was seen in smartphone data. Smartphone data was uploaded into the database within 8 hours of collection, and paper-based data took an average of 24 days to be uploaded. Whereas running costs for electronic data collection were not dependent on number of records collected, projected paper-based data collection for 3,662 records costs approximately 16,800 USD compared to 14,500 USD for smart phone data collection for a period of a year. All surveillance officers reported that smartphones were much easier, faster and more convenient to use as data collection tools.

Conclusions At four influenza surveillance sites, electronically collected data was subject to fewer errors and was quickly available for data analysis. Running costs were less for smart-phones when compared to paper-based data collection. Electronic data collection using smart phones has potential to improve data integrity and reduce costs.


Abstract Title Demographic, Socioeconomic and Geographic Determinants of Seasonal Influenza Vaccine Uptake in Rural Western Kenya, 2011

Authors Awuor NO, Nyawanda B, Audi A, Lebo E, Bigogo G, Emukule G, Ochola R, Muthoka P, Widdowson M-A, Shay D, Burton D, Breiman RF, Katz MA, Mott JA

Introduction We examined geographic, socioeconomic and demographic factors that contributed to acceptance of childhood seasonal influenza vaccination among families living in a demographic surveillance system in western Kenya where influenza vaccine was offered to children 6 months to 10 years old.

Methods Vaccinated families were defined as having all eligible children fully vaccinated against influenza. Partially vaccinated families were defined as having some of all eligible children receiving influenza vaccine or children who did not receive all required doses of the vaccine. In non-vaccinated families, no eligible children received influenza vaccine. We mapped homes located within 5KM of vaccination facilities using GPS devices. Demographic variables were analyzed as covariates through linkage to a demographic surveillance system database. Multivariate logistic regression analysis was performed to evaluate associations between maternal and household demographic variables, socioeconomic status, and distance from home to vaccination clinics with family vaccination status. Analyses were performed using the Surveylogistic procedure in SAS to account for clustering of families within households, comparing partially and fully vaccinated to unvaccinated families.

Results Of 3735 families eligible for vaccination, 1054 (28.2%) were fully vaccinated, 671 (18.0%) were partially vaccinated and 2010 (53.8%) were not vaccinated. The overall rate of vaccine uptake among eligible children in the campaign was 44%. While distance to vaccination facilities was not related to vaccination status for families living within 5km of the nearest vaccination facility, families living >5km from the facilities were significantly less likely to have their children vaccinated (aOR=0.69; 95% CI 0.53-0.90; p=0.006). Families with older mothers (25-34 and 35-44 years) were more likely to participate in the vaccination campaign (aOR=1.33; 95%CI 1.12-1.59; p=0.001) and (aOR=1.35; 95%CI 1.12-1.64; p=0.002), respectively, compared to younger mothers (15-24years). Families with mothers whose occupation required them to be away from home were less likely to have their children vaccinated than families that included mothers that did not work, or whose nature of work did not require that they be away from home (aOR=0.75; 95%CI 0.65-0.87; p<.001). Moreover, families with fewer numbers of children were more likely to have their children vaccinated (aOR=1.33; 95%CI 1.24-1.42; p<0.001).

Conclusion Mothers played an important role in vaccination of their children with seasonal influenza vaccine. Future campaigns should be designed with schedules for working mothers, or specifically target alternative family members that may bring children for vaccination if working mothers are unavailable. While distance to vaccination center did not impact the participation in the vaccination campaign for families living within 5km of the vaccination sites, these findings support the notion that future campaigns may need to open additional vaccination centers in settings where the targeted population would have to travel >5 km for vaccination.


Abstract Title Influenza-like Illness Sentinel Surveillance using a Reporting System, Madagascar, 2008 – 2010

Authors Soatiana Rajatonirina, Laurence Randrianasolo, Arnaud Orelle, Norosoa Harline Razanajatovo, Yolande Nirina Raoelina, Lisette Ravolomanana, Fanjasoa Rakotomanana, Robinson Ramanjato, Armand Eugéne Randrianarivo-Solofoniaina, Jean-Michel Heraud, Vincent Richard

Background The recent influenza pandemic had lower impact on population as expected. Nevertheless, the threats of other outbreaks or pandemics with a major impact on population still exist. Implementation of surveillance tools and quality of data collected are necessary to improve public health decision-making. We describe the challenges and steps involved in developing a sentinel surveillance system in Madagascar and the well-timed information it provides.

Methods Influenza-like illness (ILI) surveillance is based on data collected from sentinel general practitioners (SGP). The SGP report weekly epidemiological and clinical data (e.g. sex, age, visit date and time, and symptoms of each new febrile patient), using patient forms addressed to our epidemiologists team. Moreover, we introduced an innovative report system based on the use of cell phone. Indeed, SGP report some data (number of patients with fever, number of ILI cases, etc.) at least every day through encrypted message SMS. Daily data transmission costs less than 2 US$ per month and per centre.

Results In December 2010, the sentinel surveillance system encompassed 31 health centres, and was able to identify and follow the diffusion of A(H1N1)pdm virus in Madagascar. From 2008 to 2010, fever syndromes represented respectively 12.2%, 11.8% and 10.8% of the annual visits. Among them, 8.5% presented ILI symptoms in 2008, 21.3% in 2009 and 20.2% in 2010 (p<0.01).

Conclusion Our ILI sentinel surveillance system represents the first nationwide real-time-like surveillance system ever established in Madagascar. It proved to be a cost-effective system that can be easily establish in medium or low-resources countries.


Abstract Title Methodology to Calculate the Annual Disease Burden of Influenza-Associated Severe Respiratory Illness in Kenya Using Population-Based and Sentinel Surveillance Data

Authors Aimee Summers, Henry Njuguna, James Fuller, Sammy Khagayi, Gideon Emukule, James Nokes, Mwanajuma Ngama, Sidi Kazungu, Marc-Alain Widdowson, Sonja J. Olsen, Joshua Mott, Mark A. Katz, Daniel Feikin

Background Few data exist from developing countries on the disease burden of severe influenza, making it difficult for countries to prioritize influenza treatment and prevention, such as vaccination. Population-based surveillance can provide incidence of influenza-associated severe respiratory illness (SRI), but due to its complexity and cost usually takes place in few sites. Sentinel surveillance in select hospitals around the country can provide the proportion of SRI due to influenza, but cannot provide incidence since denominators are often lacking. Combining population-based and sentinel surveillance allows estimates to be made of the national burden of influenza-associated SRI.

Methods We used the number of cases of SRI presenting to hospitals in two demographic surveillance system sites, Siaya District Hospital (SDH) and Kilifi District Hospital (KDH), from August 1, 2009 to July 31, 2010, to determine a base incidence of SRI in children <5 years (SDH and KDH) and persons ≥5 years (SDH). Incidences of SRI in other provinces were estimated by adjusting the base rates for prevalence for known risk factors of SRI in each province, including underweight children, low-birth weight, non-exclusive breast feeding, exposure to indoor air pollution, household crowding, HIV infection, and Haemophilus Type B immunization. These rates were adjusted for the proportion of persons seeking care for acute respiratory illness in children for each province relative to the base-rate provinces using Demographic Health Surveys. The percent of influenza-associated SRI from sentinel surveillance sites from each province in <5 and ≥5 year olds were applied to province and age stratum specific SRI incidence to determine the incidence of hospitalized influenza-associated SRI by province. To determine incidence of non-hospitalized influenza-associated SRI by province, we used information from a health utilization survey that assessed the percentage of persons with SRI who sought care at hospital. The incidences of hospitalized and non-hospitalized influenza-associated SRI were then applied to census data by province to obtain the annual number of cases of influenza-associated SRI in Kenya.

Results The estimated number of cases of influenza-associated SRI in Kenya among children <5 years during this time period ranged from 13,500 (using KDH base rate) to 14,163 (using SDH base rate) for hospitalized cases and 40,312 (using KDH base rate) to 42,236 (using SDH base rate) for non-hospitalized cases. Among persons ≥5 years, the estimated number of cases of influenza-associated SRI in Kenya during this time period was 4,121 and 23,206 for hospitalized and non-hospitalized cases respectively (SDH base rate). This translates to 9.1-9.5 total (hospitalized and non-hospitalized) cases per 1000 children and 0.8 total cases per 1000 persons ≥5 years old annually.

Conclusion Combining influenza sentinel surveillance data with population-based surveillance data can be a useful way of estimating the national disease burden of influenza-associated SRI.


Abstract Title Immunogenicity of trivalent inactivated influenza vaccine among rural Senegalese children

Authors Mbayame N. Niang, Aldiouma Diallo, Justin R. Ortiz, Doudou Diop, Deborah G. Goudiaby, Cheikh Sokhna, Kathryn E. LaFond, Aicha Diouf-Fall, Kathleen M. Neuzil, Marc-Alain Widdowson, John C. Victor, and Ousmane M. Diop

Introduction Seasonal trivalent influenza vaccine (TIV) is already proven safe and effective for children in developed countries, but its use in Africa has been limited because of questions about effectiveness, feasibility, and cost.

Methods We are conducting a multi-year double-blind randomized trial to evaluate the effectiveness of inactivated TIV versus control vaccine (inactivated poliovirus vaccine, IPV) among Senegalese children 6 months through 10 years of age in a rural population. We conducted a substudy among these children to assess immune responses to TIV (Vaxigrip, Sanofi-Pasteur, Lyon, France) manufactured for the 2008-09 northern hemisphere influenza season and administered according to manufacturer’s instructions. From May through July 2009, serum specimens were collected before dose one of TIV or IPV and either one month after dose one (for those aged 6 through 8 years) or one month after dose two (for those aged 6 months through 5 years). Sera were tested by hemagglutination inhibition assay (HAI) for the presence of antibodies against the three influenza vaccine strains at the Senegal National Influenza Center.

Results Among TIV recipients, humoral immune responses as proportion seropositive, (measured as a post-vaccination HAI titre ≥1:40) among 6-35 month olds (n=45) were 86.7% (A/H3N2), 77.8% (A/H1N1), and 8.9% (influenza B); among 3-5 year olds (n=45) were 93.3% (A/H3N2), 88.9% (A/H1N1), and 31.1% (influenza B); and among 6-8 year olds (n=26) were 96.2% (A/H3N2), 84.6% (A/H1N1), and 57.7% (influenza B). Prevaccination geometric mean titres (GMTs) were 16 (A/H3N2), 15 (A/H1N1), and 6 (influenza B) among 6-35 month olds; 47 (H3N2), 21 (H1N1), and 7 (influenza B) among 3-5 year olds; and 38 (H3N2), 20 (H1N1), and 7 (influenza B) among 6-8 year olds. Postvaccination GMTs were 101 (A/H3N2), 129 (A/H1N1), and 10 (influenza B) among 6-35 month olds; 346 (H3N2), 274 (H1N1), and 16 (influenza B) among 3-5 year olds; and 453 (H3N2), 329 (H1N1), and 31 (influenza B) among 6-8 year olds. Lack of immune responses (no change in pre-vaccination and post-vaccination GMTs) among IPV recipients indicated little or no community circulation of influenza between blood samplings (data not shown).

Conclusions Children in these living conditions in the developing country of Senegal responded comparably to TIV as do children in developed populations. Overall, immune responses were higher to the A subtypes than the B type, and older children responded more favorably than infants and young children. Given the seasonality of influenza in West Africa, usually coincident with the warm rainy season, vaccination prior to this period may provide good benefit to children. Policy makers in Africa will need data like these, as well as on effectiveness, to make effective decisions regarding influenza control considering the substantial cost of annual vaccination.


Abstract Title Risk of Death amongst TB Patients hospitalized with Influenza in South Africa, 2009 – 2010

Authors Sibongile Walaza1, Jocelyn Moyes1, Babatyi Kgokong1, Michelle Groome2, Stefano Tempia3, Halima Dawood4, Adam L. Cohen3, Kathleen Kahn5, Ebrahim Variava6, Marthi Pretorius1, Marietjie Venter1, Shabir A. Madhi1,2, Cheryl Cohen1

Affiliations 1National Institute for Communicable diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa 2Department of Science and Technology/National Research Foundation: Vaccine-Preventable Diseases, 3US Centres for Disease Control and Prevention, Atlanta, GA, USA 4Pietermaritzburg Metropolitan Hospital Complex, KwaZulu Natal, South Africa 5MRC/Wits Rural Public Health and Health Transition Research Unit (Agincourt), South Africa 6Tshepong Hospital, North West Province, South Africa

Introduction There are limited published data on influenza in patients with pulmonary tuberculosis (TB). We aimed to compare the characteristics of patients admitted with TB to those without TB and to determine whether influenza virus co-infection was a risk factor for in-hospital death among patients with suspected or laboratory-confirmed TB.

Methods Patients hospitalized with Severe Acute Respiratory infection (SARI) were enrolled prospectively from 2009-2010 at sentinel sites in 4 provinces in South Africa. Nasopharyngeal swabs or aspirates were tested for influenza by real time RT-PCR. TB cases were defined as patients with either a laboratory-confirmed (microscopy or culture) diagnosis of TB or patients receiving or started on TB treatment at the current admission. TB testing was conducted as part of clinical management.

Results Of the 8,260 enrolled patients, 2236 (27%) had a laboratory test submitted for TB diagnosis. Overall,14% (1,179/8260) of the enrolled patients met the TB case definition, of these 75%, (889/1179) were suspected TB and 25% (290/1179) were laboratory-confirmed TB. The influenza detection rate was similar in patients with (8% (94/1164)) and without ( 9% (620/6,989)) TB (p=0.40). Among TB patients, the prevalence of influenza was 7% (20/285) in those with laboratory-confirmed TB 8% (74/ 874) in those with suspected TB (p=0.5). The majority of patients with TB were aged 25-44 years ( 13% (151/ 1179) <1, 16% (188/1179) 1-4, 11% (125/1179) 5-24, 44% (514/1179) 25-44, 14% (167/1179) 45-64 and 3% (34/1179) ≥65), while proportionately more patients were aged < 1 year in those without TB (36% (2517/7085) <1, 20% (1405/7085) 1-4, 8% (572/7085) 5-24, 23% (1593/7085) 25-44, 12% (812/7085) 45-64, 3% (186/7085) ≥ 65)(p <0.001). 76% of the 869 TB patients tested for HIV were sero-positive compared to 50% (2281/4607) of those without TB, (p<0.001). The case-fatality ratio in patients admitted with TB was 10% (115/1,176) as compared to 5% (316/7045) in patients without TB (p<0.001). Among patients admitted with TB, the case fatality ratio was 7% (20/209) in patients with laboratory confirmed TB compared to 11% (95/887) in patients with suspected TB (p=0.06). On multivariable analysis, amongst patients with TB, controlling for age, laboratory-confirmed TB status and HIV-infection; patients with TB who were co-infected with influenza were two times more likely to die than patients with TB who tested influenza negative (odds ratio 2.07, 95% confidence interval 1.04-4.13, p=0.04).

Conclusions Preliminary data suggest influenza co-infection may be associated with increased mortality amongst patients with TB. Patients with TB are a potential risk group that may be targeted for influenza vaccination.


Abstract Title Increased risk of pneumococcal pneumonia among HIV and influenza co-infected patients hospitalized with pneumonia in South Africa, 2009 – 2010

Authors Nicole Wolter1, Cheryl Cohen1, Stefano Tempia1,2, Mignon du Plessis1, Michelle Groome3, Jocelyn Moyes1, Sibongile Walaza1, Babatyi Kgokong1, Marthi Pretorius1, Marietjie Venter1,4, Halima Dawood5, Kathleen Kahn6, Ebrahim Variava7, Shabir A Madhi1,3, Keith Klugman1,8 and Anne von Gottberg1 for the SARI (Severe Acute Respiratory Illness) Surveillance Group

Affiliations 1National Institute for Communicable Diseases (NICD) of the National Health Laboratory Service (NHLS), Johannesburg, South Africa, 2US Centres for Disease Control and Prevention, Atlanta, GA, USA, 3Department of Science and Technology/National Research Foundation: Vaccine-Preventable Diseases, South Africa, 4Department of Medical Virology, University of Pretoria, South Africa, 5Edendale Hospital, KwaZulu Natal, South Africa, 6MRC/Wits Rural Public Health and Health Transition Research Unit, South Africa, 7Klerksdorp Tshepong Hospital,North West Province,South Africa, 8Hubert Department of Global Health, Rollins School of Public Health, and Division of Infectious Diseases, School of Medicine, Emory University, Atlanta, GA, USA

Background The etiological diagnosis of pneumonia is challenging due to inadequate diagnostic tests and therefore the incidence of pneumococcal pneumonia is underestimated.

Objectives We aimed to identify patients with pneumococcal pneumonia using a polymerase chain reaction (PCR) assay, and to identify risk factors for pneumococcal pneumonia among patients hospitalized with pneumonia.

Methods Patients were enrolled from May 2009 through December 2010 as part of a prospective hospital-based pneumonia surveillance programme covering six hospitals in four provinces in South Africa. Clinical and epidemiologic data were collected. Streptococcus pneumoniae was identified by quantitative real-time PCR detecting lytA from whole blood specimens. Nasopharyngeal swabs/aspirates were tested for influenza virus by real-time reverse-transcription PCR. HIV status was determined by ELISA or PCR depending on patient age. Multivariable logistic regression analysis was performed.

Results Of the 5411 patients with hospitalized pneumonia enrolled, 379 (7%) tested lytA positive on blood for pneumococci. Pneumococcal prevalence was 5% (78/1714), 6% (25/399), 1% (2/174), 9% (193/2082) and 8% (81/1042) in the <2, 2-5, 6-18, 19-44 and ≥ 45 years age groups respectively. On multivariable analysis lytA positive, compared to lytA negative, patients presented at the hospital later (>2 days from symptom onset) [320/379 (84%) vs 3572/5009 (71%); odds ratio (OR): 1.7, 95% confidence interval (CI) 1.3-2.4], had longer hospitalization time (>5 days) [225/378 (60%) vs 2251/5005 (45%); OR: 1.4, CI 1.1-1.8], had higher rates of HIV infection [257/352 (73%) vs 2443/4594 (53%); OR: 1.9, CI 1.5-2.5] and influenza co-infection [49/377 (13%) vs 451/4997 (9%); OR: 1.6, CI 1.1-2.2] and were at higher risk of dying [38/378 (10%) vs 296/5010 (6%); OR: 1.5, CI 1.1-2.2].

Conclusion HIV-infection and influenza co-infection are each independent and significant risk factors for pneumococcal pneumonia. Amongst patients hospitalized with pneumonia, individuals with pneumococcal pneumonia present later, have longer hospitalization and have an increased risk of death.



ANISE POSTER ABSTRACTS


Abstract Title Virologic features of Influenza Cases investigated under the National Influenza Sentinel Surveillance System, Nigeria (2008 – 2011)

Authors Adedeji A. Adebayo, Paul Shilo, Onyiah A. Pamela, Musa Adama, Dalhatu Ibrahim*

Background There is paucity of data on influenza surveillance activities in Nigeria despite the significant contribution of the virus to respiratory diseases burden. The pandemic Avian influenza (H5N1), which spread to Nigeria in mid-2000, led to unavoidable culling of infected birds and gross economic loses. The confirmation of the first human case of H5N1 in Nigeria in 2006 and the potential for further human-to-human spread in the population prompted a series of prevention and control efforts by the Government. Between 2008 and 2009, the Federal Government, in partnership with CDC, established four influenza sentinel surveillance sites across the country and a national influenza reference laboratory (NIRL) in order to understand the dynamics of the disease in the population and monitor the trend through an epidemiologic and virologic data linkage.

Objectives To provide information on influenza types and subtypes associated with cases of Influenza-like Illness (ILI) and Severe Acute Respiratory Infection (SARI) between 2008 and 2011 in Nigeria.

Methods In each of the four sentinel sites, patients meeting with case definitions of ILI and SARI were enrolled into the study four days a week. Epidemiologic data with clinical samples (oropharyngeal and nasopharyngeal) were collected from enrolled cases. The samples were transported, within 72 hours of collection, to and investigated for influenza types and subtypes at NIRL using real-time RT-PCR. Results were analysed using EPI-INFO.

Results Between April 2008 and July, 2011, 5,151 samples were collected from 4,042 ILI and 1,098 SARI cases cutting across all age strata. Of the 5,151 samples tested for influenza, 373 (7.2%) were positive with 315 (7.8%) and 51 (4.6%) positive for ILI and SARI respectively. Of this total, Influenza A constituted 68.9% and B 31.1%. Subtypes A/2009 H1N1, A/H1, A/H3 and A/unsubtyped accounted for 52.1%, 6.2%, 32.7% and 9.0% of Influenza A respectively. Between April 2008 and October 2009, A/H3 predominated and was displaced by A/2009 H1N1 with occasional intermix of B, and A/H3 through to March, 2010. A/H3 became prominent thereafter with B occasionally to the end of 2010 while A/2009 H1N1 and B are dominant during the reporting period of 2011. Increasing viral activity was noticeable as from week 46 in 2009 to week 13 in 2010 and weeks 37 to 49 (2010) which coincided with the dry harmattan season.

Conclusion The period April 2008 to July 2011 witnessed an intense influenza viral activity with type A contributing significantly to the morbidity. The predominance of A/2009 H1N1 in late 2009 and early 2010 coincided with the pandemic occurrence of the virus. The seasonal pattern for 2 consecutive years (2009 and 2010) appears to support the intense influenza viral activity during the dry harmattan seasons in Nigeria.


Abstract Title Prevalence of Pandemic A(H1N1)2009 Influenza virus in samples collected in Lagos: A report from the National Influenza Sentinel Surveillance-Lagos Site

Authors Adedokun A, Idris O, Albert Olayemi, Alake E and Lanlehin A

Objectives 1. To describe the serotypes of the influenza viruses in samples collected. 2. To determine the prevalence of pandemic A(H1N1)2009 virus in the samples collected. 3. To determine the possible areas in Lagos from where subjects came with isolated pandemic A(A1N1)2009 virus.

Background Influenza remains an important public health challenge of global significance responsible for the death of about 500,000 people annually. The World Health Organisation (WHO) in June 2009 declared a level 6 pandemic of a novel virus A/H1N1 (now known as A(H1N1)pdm09) that had emerged largely due to reassortment of the viral genome. The National Influenza Sentinel Surveillance (NISS) is a network of surveillance teams in about 5 centers scattered all over Nigeria. This is a part of the Global Influenza Surveillance and Response System (GISRS) supported by the Center for Disease Control and Prevention (CDC) in Atlanta.

Methods Nasopharyngeal samples were taken from consenting patients that satisfied conditions for case definition for Influenza- like Illness (ILI) or Severe Acute Respiratory Illness (SARI). The case definition for ILI being those with fever (temperature above 38 0C) and cough or sore throat. The case definition (SARI) being symptoms of ILI plus difficulty in breathing, the severity of which warrants admission. Samples were also collected from suspected Avian Influenza cases as well suspected cases of A(H1N1)pdm09, with history of travel or contact with dead poultry. Samples were sent to the WHO reference laboratory in Abuja for analyses.

Results A total of 1186 samples were collected from subjects during a period from February 2009 to September 2011. Only 1123 (94.7%) were analysed as 63 (5.3%) samples were missing. Males were 593 (50%) while females were 530 (44.7%). Mean age was 16.12 SD 2.4 years. Of the samples analysed, 1055 (93.9%) were negative while 16 (1.4%) were positive for A(H1N1)pdm09 and 25 (2.2%) were positive for A/H3 serotype while 2 (0.18%) were positive for A/H1 and 21 (1.8%) were positive for Flu B. Only 4 (0.4%) samples were serotype A-unsubtypable. Most of the positive samples appear to come from subjects from the southern parts of the state.

Conclusion The prevalence of A(H1N1)pdm09 of 1.4% in samples collected in Lagos is a pointer to its continued presence in the region. Although in August 2010 WHO declared an end to (H1N1) pandemic, the virus remained seasonal with other viruses. The importance of surveillance on this virus in Lagos cannot therefore be overemphasised.


Abstract Title Influenza-Like Illness (ILI) Surveillance in the Military Health Delivery Setting in Ghana

Authors John Nii-Ayi Carroll, Prince G. Agbenohevi, David Rodgers, Samuel Otis Bel-Nono, Roland M. L. Sowah, John K. Odoom, Joseph H. K. Bonney, Ivy A. Asante, Joseph A. Frimpong, Michael Adjabeng, Reuben Tettey, Fenteng Danso, Ndahwouh Talla Nzussouo, William K. Ampofo, Buhari A. Oyofo, Karl C. Kronmann.

Objectives In April 2010, the Ghana Armed Forces (GAF) initiated an all-garrison influenza-like illness (ILI) surveillance programme in collaboration with the US Department of Defense, the Ghana National Influenza Centre (NIC), and the Ghana Health Service (GHS).

Methods Training introduced 121 military medical personnel to ILI case recognition and management in clinical settings. Respiratory samples from ILI patients were investigated for influenza virus with rapid diagnostic testing done on site and the NIC conducted further molecular characterization.

Results Between April 2010 and May 2011, 1099 cases were investigated in military medical facilities, contributing 28% of all ILI surveillance done in Ghana. Seventeen percent of these cases were positive for influenza virus, with pH1N1 2009 dominating (66%).

Conclusions The establishment of ILI surveillance in military clinics in Ghana has contributed to an early warning system against existing and emerging influenza threats for the GAF and the GHS. This surveillance has enabled a better understanding of influenza in Ghana and aided clinical management. This illustrates the benefit of including security health systems in overall public health strategies.


Abstract Title A Review of Laboratory-Confirmed Cases of Influenza A(H1N1)pdm2009 in Ethiopia

Authors Workenesh Ayele, Gelila Demissie, Woubayehu Kassa, Mesfin Mengesha, Aklog Afework, Etsehiwot Zemelak, Fseha Kidane, Milliyon Wendabeku, Berhanu Amare, Daddi Jima

Background Influenza type A viruses infect a wide range of avian and mammalian species, are host-specific but may reassort in an intermediate host to create novel variants of pandemic potential. In March/April 2009 a novel A(H1N1) triple reassortant strain of influenza virus emerged in central and northern America. Ethiopia’s index case of influenza A(H1N1)pdm2009 infection was detected in Addis Ababa in June 2009, just 8 months after influenza sentinel surveillance was launched.

Methods From November 2008 to October 31, 2011 we screened patients of all ages fulfilling the standard case definition for influenza-like illness or severe acute respiratory infection at designated sites in Addis Ababa forming part of the national influenza sentinel surveillance system. Beginning in June 2009 we also screened patients presenting to additional health facilities in the city who fulfilled the standard case definition for new influenza A(H1N1) infection. We also included patients from regional sites reporting unusual outbreaks of respiratory illness. Viral RNA was extracted from throat swabs and subjected to realtime PCR amplification with parameters set for influenza testing, according to a set CDC protocol.

Results A total of 657 patients provided specimens for laboratory analysis. Overall influenza positivity was 12.6% (83/657). Influenza A viruses dominated (74/657, 11.3%) compared to influenza B (9/574, 1.8%). Pandemic viruses were present overwhelmingly among influenza A-positive specimens (52/74, 70.3%). The ages of patients with laboratory-confirmed A(H1N1)pdm2009 ranged from 2-65 years, with a median age of 22 years. The majority were from Addis Ababa (n=31), followed by Oromia (n=13) and Amhara (n=8) regions respectively. Most were unvaccinated against influenza. In June 2009 most infections were associated with recent travel to destinations outside of Ethiopia where the virus was present. By late 2009 we detected local transmission of the virus. No case was detected from the routine surveillance until early in 2010. By the end of 2010 influenza A(H1N1)pdm2009 viruses dominated, most from sites outside the routine influenza sentinel surveillance network. Influenza A(H1N1)pdm2009 was virtually absent during 2011 but seasonal influenza viruses (A/H3 and influenza B) circulated. Ethiopian influenza A(H1N1)pdm2009 viruses belonged to the A/California/07/2009-like (H1N1) lineage and all sensitive to Oseltamivir.

Discussion We observed a lower than anticipated number of confirmed cases, a likely indication of our surveillance quality. We credit finding comparatively more cases in Addis Ababa to the fact that there was better surveillance capacity than in the regions rather than to any true effect. Influenza A(H1N1)pdm2009 was not detected through the routine influenza surveillance system until early 2010. It is likely that our findings underestimate the true magnitude of pandemic influenza in Ethiopia, principally due to weak influenza surveillance capacity especially in the regions. Sustained efforts are required to both strengthen the existing surveillance and to expand it.


Abstract Title Data on Virological Surveillance of Influenza in Togo during Year 2011

Authors Badziklou K., Banla A., Maman I., Halatoko J., Ekouhoho A., Issa Z., Komlan K., Koba A., Ettah K., Lawson A., Ahoun D., Amevor K., Alassani, Lare M., Nassoury D., Tamekloe A., Landoh M., Kpante K.

Background The last decade is characterized by the emergence or reemergence of respiratory diseases. In Togo, two episodes of avian flu outbreak, with 3 foci each, occurred in poultry farms in 2007 and 2008. Apart from the high economic loss for the farmers, two suspect cases among animal breeders were detected during the 2008 outbreak. The samples collected from these breeders were sent to Institut Pasteur in Senegal but the result was negative for A/H5N1. However, this scenario revealed the weakness of our national surveillance system with serious delays between the suspicion period and result. The situation became most disastrous with the event of the pandemic A/H1N1 since April 2009. In order to control influenza diseases, the government had made effort by establishing a work plan concerning both animal and human health. Influenza was added to the list of diseases to be surveyed according to integrated diseases surveillance and response “IDSR”. Even so, it clearly appeared that our own experience was too limited. The collaboration between the Togolese Ministry of Health and the Naval Medical Research Unit Number 3 “NAMRU3” of the United States of America in Cairo, Egypt enabled Togo to undertake surveillance of influenza since May 2010.

Objectives The objectives were to: Confirm cases of influenza like infection “ILI” and severe acute respiratory infection “SARI” during year 2011 - identify circulating serotype of influenza agent in 2011.

Methods Suspect samples were collected by swab throat and introduced into the viral transport medium “VTM” by clinicians and kept in the refrigerator of the sentinel site for 24 to 48 hours. Samples were then transported to influenza lab twice a week. The specimens were analyzed by the RT-PCR. Data of circulating serotype of influenza agent is shared with the clinicians, the heads of surveillance and influenza lab, Ministry of Health, WHO and partners.

Results From a total of 313 specimens analyzed from January to November 2011, 79 were influenza positive, representing 25.24%. Within the positive samples: 19 (24.05%) were pandemic A/H1N1; 13 (16.46%) were seasonal A/H3N2 and 45 (56.96%) were Influenza type B and 2 (2, 23%) were influenza A not subtyped.

Conclusion Circulating serotypes of influenza agent in 2011 are dominated by influenza type B (about 57%) followed by pandemic A (H1N1) and seasonal A (H3N2). During year 2010, within a total of 83 samples collected, the first place was occupied by pandemic A (H1N1) representing 89.20%, only 10.80% were influenza type B. The short term perspectives are to: open the second sentinel surveillance site with military health service and undertake cell culture for virus isolation in order to becoming in near future national influenza center.


Abstract Title Viral Etiology and Seasonal Distribution of Respiratory Viruses in Patients Presenting with Severe Acute Respiratory Illness and Influenza like illness in Morocco, 2009 – 2011

Authors Ahmed Oubaha1, Abderahmane Bimouhen2, Youssef Bakri1, Rajae El Aouad2, Amal Barakat2

Affiliations 1Faculty of Sciences, University Mohammed V-Agdal, Rabat, Morocco, 2Centre National de Référence de la grippe (Maroc), Institut National d’Hygiène, Ministry of Health, Rabat, Morocco.

Background In Morocco, Influenza surveillance was established since 1996, but little is known about the etiology of viruses other than influenza causing Severe Acute Respiratory Illness (SARI) and Influenza like illness influenza like illnesses (ILI).

Methodology During two successive seasons, 2009-2010 and 2010-2011, 1853 ILI and 836 SARI samples negative for influenza virus were screened to detect four viral pathogens: adenovirus, parainfluenza viruses (PIV) 1-2, and respiratory syncytial virus (RSV) using singleplex qRT-PCR.

Results We detected (219/836, 26%) respiratory viruses in SARI cases and (228/1835, 12,4%) in ILI cases. Adenovirus and RSV respectively occurred with a higher frequency in SARI cases (114/836, 13,6%), (74/836, 9%) compared with ILI cases (80/1835, 4,3%), (85/1835, 4,6%). The two viruses occurred with higher frequency in both SARI and ILI cases in the children five years of age and under respectively (96/422, 22,7%), (57/422, 13,%) and 31/295, 10,5%), 38/295, 12,8%). Respiratory viruses circulation was seasonal during the winter months of October through April.

Conclusion To our knowledge this is the first study to date the etiologic agents associated with ILI and SARI in different age group and their period of circulation in Morocco. These results demonstrate that the respiratory viruses others than influenza are circulating during winter and this fact needs to be considered by clinicians when treating patients reporting with ILI and SARI.


Abstract Title Comparative Assessment of Oxygen Capacity in Pre- and Post-pandemic (H1N1) sub-Saharan Africa: An Urgent Need for Oxygen Prioritization in Low-resource Health Systems

Authors Janeil Belle, MD1, Nahoko Shindo, MD/PhD2, Meena Cherian, MD3

Affiliations 1Indiana University School of Medicine, Indianapolis, USA, 2,3 World Health Organization Headquarters, Geneva, Switzerland

Background Pre-pandemic (H1N1 2009) reports of oxygen supply in sub-Saharan African countries in the literature demonstrate critical shortages. Populations in this region face serious morbidity and mortality from pandemic influenza not only due to limited public access to preventative resources such as face masks and vaccines, but also from lack of basic oxygen.

Objective This study was undertaken to assess the availability of oxygen and associated resources in sub-Saharan Africa.

Methods Availability of oxygen and related ventilatory resources and infrastructure was assessed using the World Health Organization Tool for Situational Analysis to Assess Emergency and Essential Surgical Care. The tool was distributed to 231 local primary health centers, district health centers, private hospitals, and tertiary hospitals assessed in 2007-2009 by WHO Country officials and Ministries of Health in 12 sub-Saharan African countries. Of the 198 responding health facilities, 44.5% reported uninterrupted access to any oxygen source, 36.5% of health facilities had full-time access to an oxygen concentrator.

Conclusions Access to oxygen and associated ventilatory devices must be prioritized in future influenza preparedness efforts. Although access to oxygen concentrators was significantly higher in 2011 when compared to 2007-2009, oxygen is not present at the majority of health facilities surveyed. Pre-pandemic and present data on availability of oxygen delivery and ventilatory devices demonstrate an urgent need for investment in durable, setting-appropriate oxygen delivery systems for low-resource areas. Expanded oxygen access provides long-term, diagonal health benefits by enhancing capacity to address a spectrum of medical conditions from trauma/emergency respiratory failure; COPD/emphysema; and childhood, HIV and influenza-related pneumonia as well as providing infrastructure for the provision of medical, anesthetic, obstetric and surgical care―ultimately strengthening local health systems.


Abstract Title The WHO Global Influenza Surveillance and Response System

Author Dr. Terry G. Besselaar

Introduction Global influenza virological surveillance has been conducted through the WHO’s Global Influenza Surveillance and Response System (GISRS) for over half a century. The GISRS laboratory network currently comprises six WHO Collaborating Centres, four Essential Regulatory Laboratories and 136 institutions in 106 WHO Member States, which are recognized by WHO as National Influenza Centres, in addition to ad hoc groups established to address specific emerging issues. The GISRS monitors the evolution of influenza viruses and provides recommendations in areas including laboratory diagnostic, vaccines, antiviral susceptibility and risk assessment. The network also serves as a global alert mechanism for the emergence of influenza viruses with pandemic potential and played a key role during the influenza A(H1N1) 2009 pandemic. WHO is engaged in a number of different activities to help strengthen influenza virus surveillance globally and has identified Africa as one of the priority regions. There are currently 14 NICs in 13 counties in Africa. In addition there are influenza reference laboratories in a number of other countries which have the potential to become NICs in the future.

Methods Ways in which WHO strengthens influenza virus surveillance globally include laboratory capacity building, provision of specimen collection materials, the Shipment Fund Project for virus transport, WHO external quality assessment project, training, guidance documents and networking.

Results The capacity of the GISRS laboratories to rapidly detect influenza virus and contribute to outbreak risk assessments has increased greatly over the last decade. This is evident in numerous ways including the increased number of newly recognized NICs in Africa and other parts of the world, improved performance in the WHO external quality assessment project, greater virus sharing for vaccine and diagnostics updating and improved communication within the network.

Conclusions The GISRS is a collaborative network with great technical expertise in influenza. Strengthening the network will continue to raise the quality and standard of the national and global capacity to rapidly detect newly emerging influenza viruses and respond to outbreaks.


Abstract Title Sentinel Surveillance for Laboratory-confirmed Influenza in Kinshasa, Democratic Republic of Congo (2009 – 2011)

Authors JJ Muyembe Tamfum1, E. Nkwembe1, S. Karhemere1, F. Bankoshi1, B. Kebela3, K. Katz 4, A. Cohen5, J. Kabamba6, and W.Okito2

Affiliations 1National Reference Laboratory for Influenza, Institut National de Recherche Biomedicale (INRB), Kinshasa, Democratic Republic of Congo, 2Kinshasa School of Public Health (KSPH), Kinshasa, Democratic Republic of Congo, 3Diseases Control Direction, Ministry of Health (DLM), Kinshasa, Democratic Republic of Congo, 4Centers for Disease Control and Prevention—South Africa, Pretoria, South Africa, 5Centers for Disease Control and Prevention, Atlanta, USA, 6Centers for Disease Control and Prevention, Kinshasa, Democratic Republic of Congo

Background The burden of influenza is not well documented in most cental african countries. In 2007, the DRCongo Ministry of Heath launched implementing a sentinel surveillance of influenza in Kinshasa, country capital city. The objectives of the network were to monitor epidemiologic characteristics of influenza cases, and to determine types and subtypes of circulating influenza virus strains.

Method We conducted surveillance for Influenza Illness or Severe Acute Respiratory Illness at five sites in Kinshasa, for the period of 2009-2011. Oropharyngeal and nasopharyngeal swabs obtained from each patient were collected in cryovials of VTM. RNA was extracted manually by using the QIAmp Viral RNA mini-kit (Qiagen ) and amplified by real time RT-PCR according to CDC protocol.

Results From January 2009 to April 2011, 4156 samples were collected. 3217 were defined as ILI cases and 939 SARI cases. 605 (65%) were laboratory - confirmed positive for influenza. In 2009, ILI was most common in the 15-40 year age group, and SARI was most common in children <5 years of age. In 2010, both ILI and SARI were most common in the <5 year age group. The youngest patient was 4 years of age and the eldest 79 years of age.

In 2009, of 1048 ILI cases, 208 (20%) were positive for influenza. Of 263 SARI cases, 41 (16%) were positive for influenza. Of 249 positive specimens in 2009, 157 (63%) were pandemic influenza (H1N1), 41 (16%) were positive for influenza A(H3N2), 10 (4%) were seasonal influenza A (H1N1), and 18 (7%) were influenza B. In 2010, of 1462 ILI cases, 196 (13%) were positive for influenza. Of 399 SARI cases, 36 (9%) were positive for influenza. Of 2321positive specimens tested in 2010, 11 (5%) were pandemic influenza A (H1N1), 79 (34%) were influenza A (H3N2), and 139 (60%) were influenza B. In the twenty-eight month surveillance period, 38 (7%) were unsubtypable. From January to April of 2011, of 719 ILI cases, 98 (14%) were positive. Of 285 SARI cases, 26 (9%) were positive. Of 124 positive specimen tested, 40 (41%) were pandemic influenza A (H1N1), 71 (72%) were influenza A (H3N1), and 12 (12%) were unsubtypable. Only one (<1%) influenza B was identified.

Conclusion Despite the s success of this sentinel network, the surveillance system needs to be strengthen and expanded. One limitation of the current surveillance is that it is located in Kinshasa. In addition, influenza accounts for 9-20% of SARI and ILI cases, so the surveillance system should test for other respiratory viral aetiologies.


Abstract Title Virological Surveillance of Influenza-Like Illness among Children in Ghana, 2008 – 2010

Authors Joseph H.K. Bonney, Karl C. Kronmann, Christina P. Lindan, Ivy A. Asante, Prince Parbie, James Aboagye, Joseph Amankwah, John Kofi Odoom, Michael Adjabeng, Ndahwouh Talla Nzussouo, Lawson Ahadzie, Robert Vince Barthel, Clair Cornelius, George Amofah, Buhari Oyofo, William K. Ampofo

Background Globally, 20,000 children are hospitalized annually because of influenza. In 2007, Ghana initiated influenza surveillance by routine monitoring of acute respiratory illness to obtain data on circulating strains. We describe influenza surveillance in children < 11 years old who had influenza-like illness (ILI) from January 2008 to December 2010.

Methods Oropharyngeal swabs from paediatric out-patients with ILI attending any of 22 health facilities across the country were submitted to the national influenza centre. We tested swabs for influenza virus using molecular assays, virus isolation and haemagglutination assays.

Results Of the 2,810 swabs, 636 (23%) were positive for influenza virus. The percentage positives for males and females were similar. The proportion of ILI cases positive for influenza increased with age from 11% (31/275) in infants (0-1 years old) to 31% (377/1219) among children 5-10 years old (p<0.001). The majority of cases were influenza A (90%), of which 60% were 2009 pandemic influenza A (H1N1). In all three years, influenza activity was highest during May to July, which corresponds to the rainy season in Ghana.

Conclusions In three years of surveillance for influenza virus in Ghana, we have shown that school age children bear the greatest impact of influenza-associated ILI.


Abstract Title Paucity of complete influenza virus genomes from Sub-Saharan Africa limits full understanding of the virus evolutionally dynamics in the region

Authors Denis K. Byarugaba, Mariette F. Ducatez, Bernard Erima, Edison A. Mworozi, Monica Millard, Hannah Kibuuka, Luswa Lukwago, Josephine Bwogi, Derrick Mimbe, Fred Wabwire-Mangen

Complete influenza virus genomes provide critical and deeper understanding of influenza genetic structure and provide insight into effective control options. However, despite the availability of such data from several developed nations, Sub-Saharan Africa still provides limited complete genomes into the public domain. Most influenza sequencing has focused on the HA1 domain of the hemagglutinin gene, where mutations have the greatest effect on antigenic structure. However, sequencing of the whole influenza virus genome facilitates comparison and understanding of the evolutionary dynamics of circulating viruses and the prediction of potential evolution events that are likely to result in new strains.

It also allows closer examination of the importance of other genes in influenza outbreaks and vaccine selection. Detailed examination of the whole genomes of some recent H3N2 viruses revealed that multiple lineages can co-circulate, persist, and re-assort in epidemiologically significant ways that are not easily discerned by examining the HA genes alone. Some H3N2 isolates could not be distinguished on the basis of their HA genes but could be assigned to different clades on the basis of their seven other gene segments. Therefore, whole genome sequencing allows better monitoring of evolutionary events that can predict the emergence of viruses with pandemic potential and subsequently provides vital data on global viral spread better informing control strategies. In this paper we discuss and compare data on complete influenza virus genomes available from Sub-Saharan Africa.


Abstract Title Establishing Sentinel Influenza Surveillance in Sierra Leone

Authors Ishata N. Conteh1, Senait Kebede2, Christoph Steffen3, Kaat Vandemaele4, Isata Wurie5, Wondimagegnehu Alemu1, Fredson Kuti-George1, Foday Dafae6, Amara Jambai6

Affiliations 1WHO Country Office, Sierra Leone, 2International Health Consultancy, USA, 3Agence de Médecine Préventive (AMP), France, 4Global Program on Influenza, WHO-Geneva, 5Ramsey Medical Laboratory Services, Sierra Leone, 6Ministry of Health and Sanitation, Sierra Leone

Background Acute respiratory infections (ARI) are leading causes of morbidity and mortality in Sierra Leone. Like in most African countries, the contribution of influenza is unknown. The capacity for influenza surveillance in Sierra Leone has been challenged by the lack of resources and trained manpower resulting from a 10-year long civil war that destroyed the country’s health infrastructure. More generally in Africa, the burden of disease of influenza is ill-known. This led to the development of the WHO “Strengthening Influenza Sentinel Surveillance in Africa” (SISA) project and engagement of Agence de Medecine Preventive (AMP) to provide technical support to eight countries in Africa including Sierra Leone.

Methods Situational assessment was performed to determine existing surveillance capacities to capture influenza data, identify sentinel sites using standard protocol and develop a plan of action. The assessment was followed by an implementation phase including the organization of an influenza surveillance system, the training of staff, and direct technical support for activities including data reporting using FluID and FluNet global databases. Based on the WHO protocol for sentinel site selection, four health facilities in Freetown were identified. Patients from inpatient and outpatient departments meeting case definitions for Influenza-like Illness (ILI) and/or Severe Acute Respiratory Infection (SARI) were included in the surveillance scheme. Aggregated and case based data as well as nasal swab were collected in a continuous fashion. Specimens were tested for influenza A and B using real-time RT-PCR at the Institut Pasteur in Dakar, Senegal.

Results From August through November 2011, seven hundred and three (703) ILI cases (13.1% of the total consultations) and 150 SARI cases (5.7% of all hospitalizations) were identified. Specimens were collected from 165 sampled ILI and 131 SARI cases with age ranging from 1 month to 62 years. Laboratory results were available for 121 samples of which 35% (38.9% of the SARI and 42.4% of ILI cases sampled) tested positive. Of the samples that tested positive, 42 (34.7%) were type A (H3N2) and 1 (0.8%) type A (H1N1) pdm09. The frequency of ILI and SARI was highest among children under the age of 2 yrs (75.7% for ILI and 90.2% for SARI), followed by children aged 2-5 years (17.1%for ILI and 5.9% for SARI).

Conclusions Sierra Leone, a post conflict country with limited capacity, has successfully launched influenza sentinel surveillance systems. The newly implemented influenza sentinel surveillance system was effective in identifying patients with influenza viruses. The system, if maintained in the long run, could be effectively used to establish baselines for patterns of circulating influenza strains and determine epidemiological trends that will ultimately guide national control strategies.


Abstract Title A(H1N1)pdm Influenza in a semi-rural area in Madagascar: Could the social patterns explain the spatial distribution?

Authors Hugues Cordel, Arnaud Orelle, Girard Razafitrimo, Soatiana Rajatonirina, Fanjasoa Rakotomanana, Rindra Randremanana, Christophe Rogier, Jean-Michel Héraud, Vincent Richard

Background The new influenza virus A(H1N1)pdm emerged in Mexico in April 2009 before spreading worldwide. Clinical forms range from severe hospitalized forms to asymptomatic ones. The infection and its propagation were described in majority in the northern hemisphere. Household, school and working places are the major hotspot of transmission. In Madagascar, according to the Sentinel surveillance network, the first autochthonous case was reported in October 2009.

Objective The objectives of the study are to define the clinical presentation of a semi-rural community outbreak of influenza and to describe the spatial distribution. We also assess the contacts of the subjects which could explain the spread of the outbreak.

Material/Method A total of 317 blood specimens from individuals living in a semi-rural city of the East of Madagascar were analyzed using Hemagglutinin Inhibition (HI) tests. These individuals were also interviewed and asymptomatic forms were assessed according to the fever event that patients notified during Circulation of A(H1N1)pdm. The subjects were included in a GIS (geographic information system) to give a spatial description of the cases in the study area and to give spatial clustering using the Bernoulli model. The time spent with primary links in hotspots of transmission was evaluated by a survey administrated to the subjects.

Results 317 HI tests were performed. 54 (17%) were positive for Influenza A(H1N1)pdm subtype. Positives HI were the same in the two sexes: 18/104 males and 36/213 females had a positive A(H1N1)pdm serology. Adults from 21 to 60 years old had the highest rate of positivity (28%) although elderly people, more than 61 years old had a lower rate of positivity (16%). Among the positive HI, 18 (33%) subjects declared a fever event during the outbreak of Influenza A(H1N1)pdm showing an important rate of asymptomatic forms.

Conclusion At our knowledge our study allows the first estimation of the proportion of asymptomatic influenza A(H1N1)pdm infections and is one of the rare seroprevalence surveys evaluating the burden of influenza, in a low-income country of the southern hemisphere. With such high proportion of asymptomatic forms, seroprevalence surveys will have to be generalized in future influenza epidemics and pandemics, in order to identify risk factors of influenza infections with. In our semi-rural zone of Madagascar, we showed that adults were more infected by influenza A(H1N1)pdm virus although not for seasonal influenza virus A. School seems to remain an essential place of transmission of influenza and could be a target for public health policies as priority place of vaccination. Contacts should be more analyzed as a factor of spreading for influenza and infectious diseases.


Abstract Title Detection of Respiratory Viruses other than Influenza in Children leaving in a Suburb of Dakar

Authors Mbayame Ndiaye-Niang1, Ndongo Dia1, Massamba Eric1, Fatoumata Diène Sarr2, Ousmane M. Diop1

Affiliations 1Institut Pasteur de Dakar, Medical Virology Unit, 2Institut Pasteur de Dakar, Epidemiology Unit

Background Acute respiratory infections (ARI) are one of the leading causes of child mortality throughout the world, especially in the developing countries. Viruses are recognized as the predominant etiologic agents in ARI. However, in Senegal, few data are available, mainly about classic flu. The objective of this work is to study the circulation of respiratory viruses (other than influenza viruses) in children with ARI leaving in a suburb of Dakar.

Methods From 2008 to 2010, we conducted a laboratory-based surveillance, by collecting respiratory specimens and clinical/demographic data from children up to 15 years consulting for IRA at IPS health structure located in the suburb of Dakar. Children who meet the case definition are included. Virological analyses were undertaken by the national influenza center, Pasteur institute of Dakar by using four multiplex RT-PCR protocols targeting 14 respiratory viruses: Respiratory Syncytial Virus, Human Metapneumovirus, Parainfluenza Viruses, Human Coronaviruses and Human Rhinovirus. Samples were previously tested for influenza detection by Real-time RT-PCR.

Results In total 1132 samples were received from January 2008 to December 2010 at the National Influenza Center and tested for influenza. A subset of 591 samples was screened for the others respiratory viruses. 148 (25 %) were influenza-positive and 42 (7.1 %) were positive for others respiratory viruses (viruses mentioned above). Among positive samples, 10 (1.7%) were Parainfluenza Viruses, 20 (3.4%) were Respiratory Syncytial Virus; 4 (0.7%) were Coronaviruses, 8 (1.3%) were Rhinoviruses. Seventeen cases of co-detection (2.9%) were identified and none Metapneuvirus was detected. Otherwise an molecular characterization of the different groups of viruses is in progress in order to define the phenotypes circulating in the suburbs of Dakar.

Conclusions These results confirm that other respiratory pathogens than influenza may be involved in the etiology of ARI. Among them Respiratory Syncytial Virus and Rhinoviruses seems to be the most common. Their molecular epidemiology and seasonality should be better known for better management of acute respiratory infections who represent the third leading cause of death among children under 5 in Senegal.


Abstract Title Health Workers’ Knowledge and Risk Perception to the 2009 Pandemic Influenza and Vaccine Acceptability: A Case Study of Two Tertiary Health Institutions in Lagos, Nigeria

Authors Ekanem EE1, Ebuehi OM1, Adedokun A2 and Badru A1

Affiliations 1. Department of Community Health & Primary Care, College of Medicine, University of Lagos, Lagos, Nigeria 2. Department of Family Medicine, Lagos State University Teaching Hospital, Ikeja, Lagos, Nigeria

Objectives • Toassesshealthworkers’knowledgeaboutthe2009pandemicInfluenzaandthevaccine • Todeterminetheirriskperceptionsandwillingnesstoreceivethevaccine • Toexaminefactorsinfluencingvaccineacceptability.

Background When the vaccine against the 2009 pandemic influenza H1N1 virus became available, the World Health Organization recommended that priority should be given to most-at risk groups including health workers. 2,880,000 doses of the vaccine was provided to Nigeria. The Federal Ministry of Health developed deployment strategies targeting health workers and essential service workers as priority groups. Studies from a few countries suggested that the acceptance of the vaccine was low. Prior to the vaccination campaign in Nigeria, we undertook a survey to determine health workers’ knowledge about the disease and the vaccine, their perceived risk as well as their willingness to receive the vaccine.

Methods Two hundred and sixty-seven (267) health workers from the two tertiary health facilities (LUTH and LASUTH) in Lagos were interviewed concerning their knowledge, risk perception about the 2009 pandemic influenza (H1N1) and acceptability of its vaccine. Eligible respondents were those who had direct clinical responsibilities. Knowledge about the disease and of the vaccine was evaluated by means of a-thirty item structured questionnaire. Associations between knowledge, risk perception, acceptability and selected independent attributes of respondents were evaluated with the Chi-square test. Significant variables were included in an unconditional logistic regression model (Epi Info 2005) in which willingness and knowledge were the outcomes of interest.

Results Of the 267 health workers only 114 (43.4%) had adequate knowledge about the disease.The disease was perceived as severe by 82.4% of the respondents.Eighty-eight (33.5%) perceived themselves not to be at risk of the infection. Fifty-three (19.9%) expressed unwillingness to receive the vaccine. Of those who expressed unwillingness, the main reason was uncertainly about vaccine safety (51%); 25.5% claimed that they were unlikely to contract the infection and 23% felt that the disease was not serious enough to warrant vaccination. Factors positively associated with willingness to receive the vaccine included: knowledge about the disease (OR 2.4, 95% CI, 2.1-4.8) and household size (OR= 2.1, 95% CI, 1.2- 4.0). Health workers who perceived themselves to be at risk of infection were more willing to receive the vaccine compared to their counterparts (p=0.042) but the association was not statistically significant at the multivariate analysis level.

Conclusion The limited knowledge on the disease and its vaccine may have contributed to the unwillingness of some health workers to receive the vaccine. In future vaccination plans, intensive educational campaign should be embarked upon, focusing on simple, easy to understand and adequate information about the disease, high risk groups and reassurance about vaccine safety.


Abstract Title Analysis of Antigenic Drift in the Neuraminidase (NA) Gene of Pandemic H1N1 Influenza A Virus in Kenya

Authors George Gachara, Samuel Symekher, Lifumo Japheth Magana, Jane Gichogo, Benjamin Opot, Wallace Bulimo

Background In early April 2009, a new influenza A/H1N1 virus emerged among humans in Mexico. The new virus was declared as the first world-wide pandemic of the 21st Century. Genetic analysis have showed that this virus contain a constellation of gene segments from human, avian and swine origins. The neuraminidase (NA) gene of this virus was derived from the Eurasian avian-like swine lineage. It is therefore of importance to understand how this gene has evolved to function optimally in humans.

Objective To describe the evolution by antigenic drift of the NA gene pdH1N1 virus in Kenya

Methods Nasopharyngeal swabs or aspirates in virus transport medium were collected from patients with influenza like illness. pdH1N1 was identified using real-time one step RT-PCR conducted using protocols designed and distributed by WHO/USCDC for detection of influenza A and swine influenza A viruses. Positive samples were then cultured in MDCK cells and later identified by the haemagglutination inhibition test. 80 pdH1N1 isolates representing the period from July 2009 when the first case of the virus in Kenya was identified to January 2011 when the incidence of laboratory confirmed pdH1N1 influenza cases significantly declined. The complete NA gene was amplified using conventional PCR utilizing M13 primers. The resulting amplicons were then directly sequenced and bioinformatics tools used to analyze resulting sequences.

Results The translated NA gene showed very few mutations in the transmembrane and linker region but the catalytic neuraminidase domain harbored certain mutations which have become fixed over the study period. Three dominant mutations V106I, N248D and I329N located in non signature residues were generally fixed in the early part of the pandemic. During the peak of the pandemic, an I396T mutation was observed in most of the isolates but this has not been observed elsewhere. Post translational modification analysis of the NA gene showed potential glycosylation motifs at N50, N58, N63, N68, N88, N146, N235 and N386. All the 8 motifs seem to be conserved in all isolates except N386 which have been lost in a small number of isolates. The residues which interact with sialic acid were generally conserved and no mutations conferring antiviral resistance was noted.

Conclusions The antigenic drift so far observed in the NA gene of pdH1N1 in Kenya suggests a virus that has already evolved to a stable virus. The mutation at position 106 from the avian-like residue valine to the human-like residue isoleucine coupled with N248D and I329N early in the pandemic seem to be the only mutations that enabled this protein function optimally in humans. However, the emergence of the I396T mutation and the loss of the newly acquired potential glycosylation motif N386 need further study to understand their role in the functioning of the Neuraminidase.


Abstract Title Co-morbidity Factors associated with Influenza in Nigeria, November, 2011

Authors Aishatu Bintu Gubio

Objective To analyze Influenza surveillance data from the Northern, Southern, and Western zones in Nigeria to investigate co-morbidity factors associated with influenza in Nigeria. In November 2011.

Background Influenza is viral illness that affects mainly the nose, throat, bronchi and occasionally, the lungs. Influenza viruses have been an under-appreciated contributor to morbidity and mortality in Nigeria. They are a substantial contributor to respiratory disease burden in Nigeria and other developing countries. Nigeria started influenza sentinel surveillance in 2008 to inform disease control and prevention efforts.

Methods We conducted a cross sectional study on secondary data analysis of Influenza surveillance data from January 2009 to December 2010 obtained from Nigeria’s Federal Ministry of Health. Epidemiological data were obtained for suspected ILI and SARI cases defined in accordance with WHO Regional Office for Africa’s guidelines. Laboratory confirmation for presence of influenza viruses was done using real time PCR assays. Standardized case investigation forms used for sample collection were analyzed using Epi-Info software to generate frequency and proportions.

Results Of the 3,017(50.7%) suspected influenza cases reported between January 2009 and December 2010 from all the influenza sites in Nigeria, 611 (20.3%) and 2,406 (79.7%) of the total cases were recorded in 2009 and 2010 respectively. A total of 219 (7.3%) were positive for FluA, FluB. The Northern zone recorded a total of 1908 (AR: 2.6/100,000) suspected cases while the south zone recorded 554 (AR: 1.48/100,000) and the western zone reported 549 (2/100,000) suspected cases. Of the 219 that were positive 2 (0.9%) were health workers, 1 (0.5) had previous history of chronic respiratory tract disease, 2 (0.9%) had previous history of heart disease. A total of 166 (75.8%) of the 219, positive cases occurred in children 5 years and below while 15 (6.8%) occurred in Ages 25years and above. Exposure to poultry was 17 (0.6%) while 11 (0.4) had history of travel All the 3,017 (50.7%) cases had never been vaccinated against influenza.

Conclusions Co-morbidity factors associated with influenza viruses are an important contribution to the burden of respiratory illnesses in Nigeria predominantly affecting children less than 5years and adults 25years and above. Additional years of data are needed to better understand the co-morbidity factors associated epidemiology of influenza viruses in Nigeria.

Key Words Influenza, Surveillance, Co-morbidity, Nigeria


Abstract Title Influenza-Specific CD4+ T-Cell Responses are Impaired in Asymptomatic HIV-Infected African Adults

Authors Kondwani Jambo1; Enoch Sepako1,2; Sarah Glennie1; David Mzinza1; Neil Williams4; Stephen Gordon3; Robert Heyderman1

Affiliations 1Malawi-Liverpool-Wellcome Trust Clinical Research Programme, University of Malawi College of Medicine, Blantyre, Malawi; 2School of Clinical Sciences, University of Liverpool, Daulby Street, L69 3GA, Liverpool, United Kingdom; 3Respiratory Infection Group, Liverpool School of Tropical Medicine, Pembroke place, L3 5QA, Liverpool, United Kingdom; 4Cellular and Molecular Medicine, Medical Sciences Building, University of Bristol, Bristol, United Kingdom.

Background AIDS has been associated with greater seasonal influenza-related morbidity and mortality. Highly-active antiretroviral therapy (HAART) has led to some reduction in influenza-related complications in HIV-infected persons. However, the nature of naturally-acquired T-cell immunity to influenza virus in an African setting, and how this changes with immune reconstitution following HAART is unknown. We measured influenza-specific CD4 T-cell immunity in HIV-infected Malawian adults and then investigated immune reconstitution following HAART.

Methods 46 HIV-uninfected, 53 asymptomatic HIV-infected and 48 HIV-infected adults about to start HAART were recruited at the Queen Elizabeth Central Hospital (QECH), Blantyre, Malawi. We measured Influenza-specific CD4+ T-cell immune responses in PBMCs by CFSE proliferation assay. Results are given as medians with IQR.

Results We found impaired influenza-specific CD4 T-cell immunity in AIDS patients compared to HIV-uninfected adults (0.76%[0.1-3.2] vs 4.78%[1.4-10.1]; p0.05).

Conclusion Our data suggest that asymptomatic HIV-infected adults may also be at risk of influenza-related complications. It also suggests, HAART alone may not circumvent this risk in AIDS patients. This study highlights the need to identify possible interventions early in HIV infection to reduce the risk of influenza-related complications, and also, to conduct surveillance for influenza in these susceptible African populations.


Abstract Title Impact of Sample Quality on the Results of PCR and Virus Isolation in the Network of Influenza Surveillance in Cote d’Ivoire

Authors B. Kouakou1; Coulibaly Daouda2; E. V. Adjogoua1; Ndahwouh Talla Nzussouo3,4; Hervé A. Kadjo1

Affiliations 1Institut Pasteur de Côte d’Ivoire; 2Institut National de l’Hygiène Publique; 3Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA; 4Global Disease Detection and Response Program/US Naval Medical Research Unit-3, (NAMRU-3)

Justification Confirmation of suspected cases of influenza requires the completion of laboratory tests. Several tests can be used, virus isolation and molecular biology tests. The optimization of these diagnostic tests depends on the quality of the samples. The aim of our study was to evaluate the quality of samples received at National Influenza Center (NIC) in Cote d’Ivoire and their impact on the test results.

Methods The analysis of the quality of nasopharyngeal samples transported to the (NIC) as part of sentinel surveillance of influenza from January 2008 to december 2010, focused in part on the respect of the inclusion criteria for the selection of suspected cases of influenza like Illness (ILI) and also the delivery time and temperature of samples upon arrival at the laboratory. Suspected case was defined as any person with a fever greater than or equal to 38 ° C associated with cough plus sore throat. The samples taken should be received no later than 72 hours after their completion at temperatures between 4 ° C and 8 ° C. A real-time PCR was performed systematically on all samples and virus isolation positive cases in PCR.

Results From January 2008 to December 2010, of the 4268 samples received at the NIC, compliance with the case definition was found in 1851 (43.4%) patients, while 1443 (38.8%) samples were received within 72 hours and 684 (16%) received with a temperature upon arrival between 4 ° C and 8 ° C. In total 684 of 4268 samples were considered adequate. PCR was positive in 793 (18.58%) of total samples received whith 338 (49.41%) of the samples adequate and 455 (10.66%) of samples unsuitable. Virus isolation was positive in 121 (15.26%) cases of all PCR positives.

Conclusion This study showed the impact of the quality samples in confirming influenza positive results with molecular biology and virus isolation techniques.


Abstract Title Seasonal Influenza Vaccine Effectiveness in Refugee Children in Kenya, 2010 – 2011: A Retrospective, Case-control Study using Test-negative Controls

Authors Mark A. Katz1, Joshua Wong1, James Ndirangu2, Raymond Nyoka1, Philip Muthoka3, Emma Lebo1, Margaret Nguhi2, Jamal Ahmed1, John Wagacha Burton4, Joshua Mott1, Lilian Waiboci1, Robert Breiman1, Rachel Eidex1

Affiliations 1Kenya Medical Research Institute/Centers for Disease Control-Kenya; 2International Rescue Committee, Kenya; 3Ministry of Public Health and Sanitation, Kenya; 4United Nations High Commission for Refugees, Kenya

Objective To evaluate the effectiveness of seasonal influenza vaccine in preventing influenza-associated respiratory illness in children in a refugee camp in Kenya

Introduction Recent surveillance has shown that influenza is a significant cause of respiratory disease in Africa. However, little is known about the effectiveness of seasonal influenza vaccination in Africa, including among vulnerable populations like refugees.

Methods Influenza surveillance has been ongoing in Kakuma Refugee Camp since 2007. Nasopharyngeal and oropharyngeal specimens are collected from inpatients with severe acute respiratory illness (SARI) and outpatients with influenza-like illness (ILI) and tested for influenza by RT-PCR. During October 2010 – November 2010, we offered two doses of free (donated by Sanofi Pasteur) injectable trivalent 2010 southern hemisphere seasonal influenza vaccine to 5,250 children, 6-24 months old and 36-59 months old residing in the Camp. Because limited quantities of the low dose (0.25mL) vaccine, intended for children < 36 months old, were available, we could not offer vaccine to children 24-36 months old. Patients were asked about vaccination status as part of the routine surveillance questionnaire. We conducted a case-control study to evaluate the effectiveness of the vaccine in preventing laboratory-confirmed influenza associated with ILI and SARI among children 9 months – 59 months old using surveillance data from from Kakuma from December 2010-August 2011. We used generalized linear models with a Bayesian approach to compare the effectiveness of the vaccine stratified by influenza type (influenza A, B, and combined). We calculated the risk ratios between vaccinated and unvaccinated based on posterior summaries.

Results During the evaluation period, specimens from 47/454 (10%) children with respiratory illness (ILI or SARI) were positive for influenza; 27 were influenza A, and 21 were influenza B. Of the children with respiratory illness, 161 (35.5%) were vaccinated. Vaccine effectiveness against laboratory-confirmed influenza associated with respiratory illness was 37.5% [95% Credibility Interval (CI) 27.3,51.5] for any influenza, 59.5% (95% CI 37.9,93.5) for influenza A, and 9.4% (95% CI 5.9,15.0) for influenza B.

Conclusions A trivalent seasonal influenza vaccine was effective in reducing influenza A-associated illness among refugee children in Kenya. In settings where influenza vaccine is not routinely used or available, such as refugee settings, targeted influenza vaccine mass campaigns may be effective for reducing the burden of influenza.


Abstract Title Risk Factors for Introduction and Spread of Avian Influenza in Live Bird Markets in Uganda

Authors Halid Kirunda, Denis K. Byarugaba and Fred Wabwire-Mangen

Objective The study sought to establish risk factors for introduction and spread of influenza viruses in the live poultry trade markets in Uganda.

Background Live bird markets (LBMs) are essential for marketing poultry in many developing countries. But these markets have been linked with many outbreaks of avian influenza and its spread (Cardona et al., 2009). Risk factors for introduction and spread of the highly pathogenic avian influenza in African countries, among others, include places where poultry is traded, (Stevens et al., 2009). Once avian influenza has been introduced into Africa, most of sub-Saharan Africa has the highest likelihood for the spread of the disease (Stevens et al., 2009). Uganda lies along the intra-Africa and the global north-south migratory routes of wild birds, has many water bodies including 33 sites regularly visited by about 20 migratory species including eight, which have been ranked high risk species for spread of avian influenza (Nature Uganda, 2009). In the country live birds and eggs are also sold in over 130 open-air LBMs that are spread across the country.

Methods This cross-sectional study involved 39 LBMs in 29 out of 112 districts in the seven regions of Uganda. Markets used in the study comprised those ranked most risky based on unpublished results of a preliminary study that assessed biosecurity in LBMs in the country. Data were collected using a semi-structured questionnaire. All bird handlers met in a market on the day of visit were interviewed with respondents totaling 424. Consent was sought before being interviewed. All generated data were stored in EpiData and analyzed using STATA statistical programs. Analyses for frequencies and cross tabulation were done by descriptive statistics and significant relationships between independent and dependent variables computed using chi-square (X2) and p-value (significant at <0.05).

Results Results showed a strong association between region and risk factors of poor disposal of poultry carcasses (X2=115.9; p=0.000); not cleaning cages (X2=45.6; p=0.000) and operating within or near major towns (X2=52.2; p=0.000). Up to 76.3%-100.0%; 50.0%-94.0% and 58.0%-100.0% of bird handlers poorly disposed of carcasses, did not regularly clean cages and operated within or near major towns, respectively, in all seven regions. Observed also was an association between background of education and the practice of returning un-sold birds back to their own homes (X2=9.541; p=0.023) with up to 43.7% of handlers of primary compared to 26.2% of secondary education having the practice. Most handlers did not put on protective clothing (98.4%, n=416) and neither regularly cleaned hands (97.4%, n=413) nor operating sites (69.3%, n=294). Yet, most handlers operated in markets congested with people (64.6%, n=274) and near restaurants (50.5%, n=214).

Conclusion Several factors that favour introduction and spread of avian influenza exist in LBMs in Uganda.


Abstract Title Influenza Sentinel Surveillance System in Togo: Trends of Circulating Influenza Strains, June 2010 – May 2011

Authors Essoya D. Landoh1, Nassoury ID1, Banla A2, Koba AK2, Tamekloe T1, Maman I2, Badziklou K2, Pindra YA3, Halatoko W2

Affiliations 1Ministry of Health, Division of Epidemiology, Togo 2Institut National d’Hygiène, Togo 3Bè District Hospital, Togo

Background Type of viruses involved in the occurrence of severe acute respiratory infections (SARI) and influenza-like illness (ILI) had never been described in Togo. In 2009, a sentinel surveillance system for influenza was set up at Bè hospital using the generic protocol by PAHO-CDC.

Objective To describe the strains of influenza that are circulating in Togo from June 2010 to May 2011.

Methods Influenza sentinel surveillance system established at Bè District Hospital in Lomé recruits patients meeting the case definitions of influenza-like illness (fever >38oC associated with sore throat or cough) and severe acute respiratory infections. The first 20 ILI and SARI cases were recruited on each of the first 4 working weekdays. Nasopharyngeal and oropharyngeal swabs were collected and sent to the Institut National d’Hygiène for laboratory confirmation using RNA extraction technique by RT-PCR in real time. Data generated are analyzed using Epi Info version 3.5.1.Chi-square (CI 95%) was used to compare proportion among age groups.

Results From June 2010 to May 2011, 14,400 patients consulted at Bè hospital and 2880 were hospitalised. A total of 300 patients consulted for ILI and two patients for SARI. Samples were taken from 205/302 (68%) patients who met the case definition. Of the 205 samples processed, 64 (32.7%) were positive to influenza. The majority of positive cases 37/64 (57.8%) were reported in 2011. Influenza B 30/64 (46.9%) and Influenza A/H1N1 23/64 (35.9%) were the subtypes most reported. The laboratory was unable to subtype six cases. The age group 0-4 years (42.2%) and 5-9 years (29.7%) were more affected than the remaining age groups (p < 0.001).

Conclusion The ILI and SARI surveillance system showed that influenza viruses are circulating in Togo and will play a significant role in providing data for the description of the influenza seasonality in the country. Strengthen influenza surveillance system by including viral isolation and expanding the model to other regions of the country was recommended.


Abstract Title Prevalence and clinical features of influenza virus infections and co-infections involving influenza and other respiratory viruses in Kenya, 2006 – 2011

Authors Lebo E1; Ochola R2; Otieno N2; Emukule G1; Waiboci L. W.1; Mott J 1, 3; Katz M1, 3

1. Centers for Disease Control and Prevention-Kenya (CDC-K) Nairobi, Kenya 2. Kenya Medical Research Institute /Center for Disease Control and Prevention (CDC/ KEMRI), Nairobi Kenya 3. Influenza Division, CDC-Atlanta

Introduction Influenza and other viral respiratory pathogens contribute substantially to acute respiratory infections and although viral co-infections occur commonly, the clinical significance of these co-infections has not been defined.

Methods In 2006, the Kenya Medical Research Institute/ Centers for Disease Control and Prevention established surveillance for acute respiratory illness in two population-based surveillance sites, Kibera and Lwak; hospital-based surveillance was added in 2009 at Siaya District Hospital in Western Kenya. Nasopharyngeal (NP) and oropharyngeal (OP) swabs, along with clinical information, are collected from outpatients presenting with acute respiratory illness (ARI) or hospitalized severe acute respiratory illness (SARI). NP/OP specimens are tested for 8 respiratory pathogens; Influenza A, Influenza B, Human Metapneumovirus, Adenovirus, Respiratory Syncytial Virus and Parainfluenza 1, 2, 3, using real time Reverse Transcriptase –Polymerase Chain Reaction.

Results Between October 2006 and January 2011, 8,986 respiratory specimens were collected from outpatient ARI cases from Kibera and Lwak. Of these cases, 1,414 (16%) specimens were positive for influenza viruses; of these 459 (33%) were co-infected with another viral respiratory pathogen. Among influenza viral co-infections, the proportion of co-infections was higher in children < 5 years) in the influenza-only inpatients compared to the co-infected patients.

Conclusion Viral co- infections occur commonly in patients with influenza in Kenya, especially among children.


Abstract Title Surveillance de la grippe en RDC

Authors Dr. Lubula Léopold, Dr. D. Wally, Dr. Kabamba Joelle -

Affiliations Point focal grippe Ministère de la santé Publique, Direction de lutte contre la maladie, RDC Superviseur des sites sentinelles, Ecole de Santé Publique CDC/RDC

Introduction A l’avènement de l’Influenza Aviaire en 2003, tous les États du monde redoutait la pandémie. C’est ainsi qu’en RD Congo une surveillance sentinelles avait été mise en œuvre pour appuyer la surveillance de routine qui est engagée dans la détection des infections respiratoires aigües.

Méthode Pour mieux obtenir l’information sur la circulation de la grippe aviaire en particulier et de la grippe en général, quelques structures sanitaires avait été sélectionnées pour jouer le rôle de sites sentinelles. Ce qui a permis d’assurer le prélèvement et l’envoi des échantillons au laboratoire national de référence (INRB). Les autres données des infections respiratoires et autres pathologies similaires à la grippe ont été recueillies par le système de routine à travers les structures sanitaires du pays.

Résultats La proportion de cas de grippe par rapport aux infections respiratoires captées par le système sentinelle est de 34,07% don’t 26,83% sont des ILI (syndrome semblable à la grippe), 7,75% sont de SARI (infections respiratoires aigües) et 65,4% sont des infections respiratoires atypiques. Le système de routine, quant à lui a enregistré 50,19% de cas de grippe parmi les infections respiratoires; ce qui représente 4,60% de la morbidité proportionnelle en RDC en 2010. Il faut signaler que, les données en rapport avec les facteurs de risque (profession, âge, sexe …) n’ont pas été pris en compte ici car n’étant pas repris sur nos outils de surveillance.

Conclusion Au de ces résultats, la surveillance de la grippe est sensible car elle a permis de capter les cas suspect de grippe; néanmoins vu l’étendu de notre pays et la diversité de son écosystème, il est souhaitable qu’on étende le nombre de sites à l’Est du pays parallèlement au système de routine pour nous permettre d’avoir une vue d’ensemble sur la circulation de virus grippal en RDC.


Abstract Title Molecular Characterization of Human Influenza B Viruses circulating in Kenya during the Period 2008 – 2009

Authors Janet Majanja, Wallace Bulimo, Rachel Achilla, Meshack Wadegu, Silvanos Mukunzi, Josephat Mwangi, Julia Wangui, Finnley Osuna, Janet Nyambura, Benjamin Opot and Eyako K. Wurapa

Background Although Influenza B does not show antigenic shifts resulting in pandemics, genetic variations through insertions, deletions and substitutions among different lineages are common resulting in epidemics. Recent circulating Influenza B viruses are subdivided into two genetic lineages, namely B/Victoria/2/87 and B/Yamagata/16/88. The National Influenza Centre (NIC) in Nairobi was set up as part of the global Influenza surveillance for early detection of pandemics, to monitor the viruses for drug resistance, and to detect antigenic changes in Influenza viruses.

Objective To analyze the HA1 domain of the hemagglutinin (HA) gene of Influenza B viruses isolated in Kenya in 2008 and 2009 in comparison to the vaccine strains.

Methods Nasopharyngeal swabs specimen were collected from consenting patients meeting the WHO Influenza like illness case definition and transported to the NIC. Screening for Influenza A and B viruses was done using real time RT-PCR. Samples positive for Influenza were isolated in MDCK cell line and HAI performed with reference antiserum in accordance with CDC protocols. The HA gene of the positive isolates was amplified by RT-PCR and the resulting amplicons sequenced. Bioinformatics tools were used for phylogenetic analysis.

Results A total of 100 isolates were analyzed from 2008 while 35 isolates were analyzed from 2009. Phylogenetic analysis showed that the isolates from the two years fell into two distinct lineages. The 2008 isolates clustered in the B/Yamagata/16/88 lineage while the 2009 isolates clustered in the B/Victoria/2/87 lineage. Comparison of the amino acid (aa) sequences of the HA1 region of the Kenyan strains with the respective vaccine strains of the same period revealed multiple changes in amino acids. Compared to the vaccine strain for that year (B/Florida/4/2006), all the 2008 isolates showed S150I, N165I, and D196N aa substitutions which are located in the major epitopes of the Influenza B virus. In addition, they showed additional aa substitutions at K88R and S229D. The 2008 isolates showed 99.1-100% amino acid sequence identity with each other. In comparison to the vaccine strain for 2009, (B/Brisbane/60/2008) molecular characterization of the 2009 Influenza B isolates showed one major aa substitution V225I in 22 of the 35 isolates. This residue is located in a part of the antigenic site of influenza B virus HA surrounding the receptor-binding site. 4 other aa substitutions occurred randomly among the isolates. The 2009 isolates showed 99.4-100% amino acid sequence identity with each other.

Conclusion Phylogenetic analysis of the viruses displayed displacement of the B/Yamagata/16/88 lineage by the B/Victoria/2/87 lineage in succeeding years. This observation together with the antigenic variations observed in the HA1 region of the Influenza B virus underlie the importance of continued surveillance in detection of viral antigenic drifts and selection of appropriate virus components for influenza vaccines.


Abstract Title Seasonality and Burden of Influenza among Children and Adults Presenting to Queen Elizabeth Central Hospital with Influenza-like Illness or Severe Acute Respiratory Illness—Blantyre, Malawi, January – September 2011

Authors Shikha Garg1, Dean Everett2,3, Miguel SanJoaquin2,4, Suzanne Anderson2, Jane Mallewa2, Camilla Rothe5, Thembi Katangwe6, Mavis Menyere2, David Lalloo4, Adam L. Cohen1, Marc-Alain Widdowson1, Robert S. Heyderman2,4,

Affiliations 1Influenza Division, CDC, Atlanta, Georgia, USA; 2Malawi-Liverpool-Wellcome Trust Clinical Research Programme, College of Medicine, Blantyre, Malawi; 3University of Liverpool, Liverpool, UK; 4Liverpool School of Tropical Medicine, UK; 5Adult Medicine Department, College of Medicine, Blantyre, Malawi; 6Pediatrics Department, College of Medicine, Blantyre, Malawi

Introduction Little is known about the burden of influenza in Malawi, a country with high prevalence of HIV, malaria, and tuberculosis. We conducted surveillance to determine the seasonality of influenza and the proportion of acute respiratory illness due to influenza virus infection in Malawi.

Methods Beginning January, 2011, the first 100 children (>3 months and < 15 years) and 100 adults (≥15 years) to present weekdays to Queen Elizabeth Central Hospital in Blantyre, with fever >37.5°C and respiratory symptoms were screened for influenza–like illness (ILI) and severe acute respiratory illness (SARI). ILI was defined as fever and ≥2 of the following: cough, sore throat, rhinorrhea, myalgia, or diarrhea. For children <5 years, SARI was defined as fever and evidence of lower respiratory tract disease. For persons > 5 years, SARI was defined as fever, cough or sore throat, and shortness of breath. Up to 10 children and 10 adults meeting ILI or SARI criteria per day had nasopharyngeal swabs collected for influenza testing by polymerase chain reaction and finger sticks for malaria rapid test. Patients with SARI also had HIV rapid tests. Patients were interviewed to collect data on demographics and underlying conditions.

Results From January 1, 2011 to September 30, 2011, 990 ILI and 416 SARI patients were enrolled. Children with SARI [43/148 (29%)] and adults with SARI [93/239 (39%)] were more likely to test influenza positive than children with ILI [74/473 (16%)] and adults with ILI [48/335 (14%)] (children p<0.01; adults p<0.01). Influenza viruses were first detected in January and circulated during all months except September, with the highest prevalence in March [33/93 (38%)] and the lowest in September [0/74 (0%)]. Pandemic influenza A (pH1N1) viruses predominated in January/February [(77%) 24/31 positive specimens] and influenza A (H3N2) viruses predominated in April/May [(48%) 49/102]. Among 388 children with epidemiologic data, the median age with ILI was 2.3 years (range 3 months-14 years) and with SARI was 3.3 years (range: 6 months-14 years). Among 504 adults with epidemiologic data, the median age with ILI was 29 years (range: 15-69 years) and with SARI was 33 years (range: 16-67 years)]. Among the 504 adults, 124 (25%) had HIV infection by self-report or rapid test, 32 (6%) had a positive malaria test, and 28 (6%) reported tuberculosis infection. Among 256 adults with epidemiologic and laboratory data, a positive influenza test was not associated with HIV (p=0.30), malaria (p 0.99), or TB (p=0.29) infection.

Conclusions Influenza viruses circulated throughout most of the surveillance period in Blantyre and contributed substantially to the burden of acute respiratory illness among children and adults seeking medical care. Additional year-round surveillance is needed to further describe the seasonality and burden of influenza in Malawi.


Abstract Title Influenza Virological Surveillance in Tanzania between January – October 2011

Authors Matonya M, Mwafulango A, Mwakapeje E, Mponela M, Mmbaga V, Mwalongo V, Mosha F, Massambu C, Mmbuji P

Background Influenza surveillance and laboratory capacity were established in Tanzania in 2007 supported by a cooperative agreement between the Ministry of Health and Social Welfare of Tanzania and the Centers for Disease Control and Prevention (CDC). Under this agreement, a National Influenza Laboratory (NIL) was established at the National Health Laboratory Quality Assurance and Training Centre (NHLQATC) and six sentinel sites county wide. We assessed the progress of the surveillance system by analyzing the virological samples submitted to the NIL from the sentinel sites between January 2011 and October 2011 with the aim of documenting the common influenza strains in the country.

Methods At sentinel sites, nosalpharyngial or oropharyngeal (NP/ OP) swabs were collected daily from two patients at outpatient departments meeting standard case definitions for influenza like illness and all inpatients with severe acute respiratory infection. The swabs were placed into a vial containing viral transport medium and stored at 2 – 80C before shipping to the NIL within 72 hours. At the NIL the samples were aliquoted and kept at -860C until processed. Influenza typing and sub typing was done using the CDC real time reverse transcriptase PCR protocol for detection and characterization of influenza viruses. A subset of positive samples was sent to World Health Organization Collaborating Center (WHOCC) at CDC Atlanta for further testing.

Results A total of 1606 specimens were tested between January -October 2011. Out of these, 162 specimens (10.1%) were positive for influenza A and B, with influenza A being the dominant type among the positives 121/162 (74.7%). Influenza B accounted for 41/162 (25.3%). Sub-typing of the influenza A positive samples revealed that 44/121 (36.4%) were pandemic H1N1, 72/121 (59.5%) H3 and 5/121 (4.1%) samples have not yet been sub typed. Out of positive samples, 120 samples were sent to WHOCC CDC Atlanta for characterization. Out of 120 samples, 63 were characterized and the results revealed that 50 (79.4%) were Influenza A and 17/63 (20.6%) were influenza B (similar to B/Brisbane/60/2008). Out of Influenza A positives, 33/50 (66.0%) were pandemic H1N1 (similar to A/California/07/2009) and 17/50 (34.0%) were H3 (similar to A/Perth/16/2009- like H3N2 virus).

Conclusion The influenza viruses which have been circulating in 2011 in Tanzania are the same strains which WHO has recommended to be included in the northern hemisphere 2010/2011 influenza vaccine. However, influenza surveillance is yet to define the burden of the disease in Tanzania.


Abstract Title Epidemiology of Influenza in Zambia post Influenza A,H1N1 pandemic 2009

Authors Mazyanga Liwewe1, A Theo2, P Simusika2, I Ndumba1, E Chentulo2, M Kapina3, C Malama4, P Songolo1, O Babaniyi1, Mwaka Monze2

Affiliations 1World Health Organization; 2University Teaching Hospital – Virology Laboratory; 3Ministy of Health - Zambia; 4Centres for Diseases Control and Prevention - Zambia

Background On 10 August 2010, WHO Director-General Dr. Margaret Chan announced that the H1N1 influenza virus has moved into the post-pandemic period, citing that localized outbreaks of various magnitudes are likely to continue. In Zambia as is seen globally, the levels and patterns of H1N1 transmission in the declared post pandemic period differ significantly from what was observed during the pandemic. Out-of-season outbreaks are no longer being reported in Zambia. In fact, since the declaration of a post pandemic period was announced, Zambia has recorded only 2 cases of Influenza A, H1N1 pandemic 2009.

Methodology Zambian public health authorities has in place a surveillance system for detecting suspected Influenza cases including Influenza A,H1N1 Pandemic 2009 and seasonal flu. Samples collected from suspected cases are analyzed primarily by Real time Polymerase Chain Reaction (RT-PCR).

Results 464 suspected flu cases were investigated under the Influenza Sentinel surveillance program from August 2010 to September 2011. Out of the 87 positive cases, 2 (2.3%) were Influenza A, H1N1 pandemic, 2 (2.3%) A, H3N2, 8 (9.2%) Influenza A not Sub typed and 69 (79.3%) Influenza B. In 2009, out of the 112 laboratory confirmed Influenza cases the following were the subtype frequencies: 86 cases (68%) AH1N1pandemic; 22 cases (20%) AH1N1 seasonal; 1 (2%) AH3N2; 9 (7%) A Not Sub typed and 4 (3%) FluB. In 2010, out of the 64 laboratory confirmed Influenza cases the following were the subtype frequencies: 10 cases (16%) AH1N1pandemic; 1 case (1%) AH1N1 seasonal; 12 (19%) AH3N2; 9 (14%) A Not Sub typed and 32 (50%) FluB. In 2011 as at 30th September, out of the 64 laboratory confirmed Influenza cases the following were the subtype frequencies: 2 cases (2.7%) AH1N1pandemic; 0 cases (0%) AH1N1 seasonal; 2 (2.7%) AH3N2; 8 (10.9%) A Not Sub typed and 61 (83.6%) FluB.

Conclusion Zambia in the post pandemic period has seen a shift in the pattern of influenza infections presenting from mostly Influenza type A in 2009 to Influenza type B in 2010 and 2011. As anticipated by the teams in WHO reviewing the status of Influenza A, H1N1 pandemic worldwide, the pandemic is of the past in Zambia with only 2 cases having been picked through the surveillance system.


Abstract Title Human Parainfluenza Viruses Infections in Children, Kenya (2007 – 2011)

Authors Keneth Mitei, Wallace Bulimo, Rachel Achilla, Janet Majanja, Meshack Wadegu, Silvanos Mukunzi, Josephat Mwangi, Julia Wangui, Benjamin Opot, Finnley Osuna, James Njiri and Eyako K. Wurapa

Background Human parainfluenza viruses (HPIVs) are common causes of respiratory tract disease in infants and young children. Four HPIVs serotypes are currently recognized. Each of the four HPIVs has different clinical and epidemiologic features. The most distinctive clinical feature of HPIV-1 and HPIV-2 is croup (i.e., laryngotracheobronchitis or swelling around the vocal chords and other parts of the upper and middle airway); HPIV-1 is the leading cause of croup in children, whereas HPIV-2 is less frequently detected. HPIV-3 is more often associated with bronchiolitis (swelling of the small airways leading to the lungs) and pneumonia. HPIV-4 is detected infrequently, and is less likely to cause severe disease. In May 2007 through and existing influenza surveillance network, the Kenyan National Influenza center started screening for Parainfluenza Viruses. The Influenza surveillance network is made up of 8 sentinel sites spread throughout the country.

Objective The objective of this study was to evaluate the occurrence of HPIV in children under the age of 5 years in Kenya.

Method Nasopharyngeal swab specimens were collected from consenting patients ≥ 2 months old presenting with fever (≥ 38°C) accompanied by cough and/or sore throat reported within 72 hours of onset of symptoms. Specimens were transported to the Kenyan NIC where they were inoculated into LLC-MK2 cell line. After observing cells for Cytopathic effect, samples were analyzed by direct immunofluorescence assay (IFA) performed using the Respiratory Panel I Viral Screening and Identification kit (Chemicon International, Inc.), following the manufacturer’s instructions, for detecting antigens of HPIV-1, 2 and 3.

Results A total of 15,540 samples of nasopharyngeal swabs were collected from July 2006 -October 2011. Respiratory pathogens were detected in 3, 432 cases representing 22.1% of all samples; of these, 801 (23.3%) were HPIV. HPIV- 3 was the most frequent detected type among HPIV-positive cases accounting for 361 (45.0%) cases, HPIV-1 and HPIV-2 were detected in 296 (37.0%) cases and 144 (18.0%) cases respectively. Analyses of co-infection pairs showed that HPIV and FLUAV are the most common paired viruses with HPIV3 having the highest number; 28 cases followed by HPIV1 with a total of total number of 9 cases. There were only 2 co-infections with HPIV and pH1N1; one with HPIV- 1 and the other with HPIV2 both occurring in the year 2010. Overall, 30 cases were positive for human parainfluenza 1, 2 &3.

Conclusions Continued surveillance of non-influenza respiratory viruses provides useful information that aids in public health interventions and treatment of viral respiratory infections. This study calls for a further need for close analysis of HPIV pairing with other viruses that cause acute respiratory infections. Knowledge of HPIV’s seasonality would also be very vital.


Abstract Title Pandemic Influenza H1N1 in Pigs Raised in Small Holder Farms in Kenya, 2010

Authors Munyua P1, Junghae M1, Halliday J2, Ogola E3, Mwasi L3, Breiman RF1, Mott J1,4, Katz MA1, 4, Cardona C5, Njenga MK1

Affiliations 1US Centers for Disease Control and Prevention-Kenya (CDC-K); 2College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK; 3Kenya Medical Research Institute/CDC-K; 4NCRID, US Centers for Disease Control and Prevention, Atlanta GA, USA; 5College of Veterinary Medicine, University of Minnesota, USA

Background Since the emergence of the 2009 pandemic influenza A H1N1 (pH1N1) virus in 2009, and its subsequent global spread in humans, the virus has been detected in multiple animal species. Our objective was to define the prevalence of influenza A viruses in pigs taken for slaughter in a pig slaughterhouse located in Nairobi, and determine if the pH1N1 virus that was introduced into the human population in Kenya in July of 2009 had spread to pigs by May 2010.

Methods The study was conducted among pigs brought to the slaughterhouse during May 4-17, 2010. Pigs arrived in groups and a maximum of two pigs from each group were randomly selected and blood, nasal and rectal swabs collected immediately post-mortem. A standardized questionnaire was administered to the trader to collect data on pig numbers at the farms from which the sampled pigs came. Swabs were tested for influenza A by rt RT-PCR, and sera tested for anti-influenza A nucleoprotein antibodies by ELISA. All ELISA-positive sera were tested by hemagglutination inhibition (HI) for antibodies to human influenza A strains pH1N1, seasonal H1N1 and H3N2 using the 2009/2010 WHO influenza diagnostic kit following standard protocols.

Results Data were collected from 203 pigs from 178 groups. The median number of pigs in each group was 1 (range 1-33). Only 38/178 groups had data on the number of pigs at the farms they came from; of these, the median number of pigs at the farm was 90 (range 2-1000). Thirty (14.9%) of the sera were positive for influenza A antibodies. The seropositive pigs were drawn from 29 (16.3%) groups. On HI assay, 25 (83.3%) of the sera were reactive to the pH1N1 antigens and one (3.3%) was reactive to both pH1N1 and seasonal H1N1 antigens. None of the sera were reactive to the H3N2 antigens. In total, 3 (1.5%) nasal and 3 (1.5%) rectal swabs from six pigs were positive for influenza A. Virus culture and subtyping of the six influenza A positive swabs is pending.

Conclusions We report possible circulation of pH1N1 among pigs raised in small holder farms across Kenya, though we cannot rule out serologic cross reaction with antibodies to other SIV strains. Pigs play an important role in the evolution of influenza strains and continued surveillance in pigs, and in humans, may be of value for identifying the emergence of novel influenza strains.


Abstract Title Surveillance of Influenza and Influenza like Illness in Humans in Uganda

Authors E. A. Mworozi1, D. K. Byarugaba2, B. Erima3, J. Bwogi4, L. Luswa5, D. Mimbe3, M. Milland3, H. Kibuuka3, R. Sonko3, C. Ikomera3, F. Wabwire –Mangen6

Affiliations 1Mulago National Referral Hospital, Kampala, Uganda; 2Faculty of Veterinary Medicine, Makerere University, Kampala, Uganda; 3Makerere University Walter Reed Project, Kampala, Uganda; 4Uganda Virus Research Institute, Entebbe, Uganda; 5Surveilance Division, Ministry of Health, Kampala, Uganda; 6School of Public Health, Makerere University, Kampala, Uganda

Background Following the outbreaks of the highly pathogenic influenza virus subtype H5N1 in 2006 in many parts of the world, and later the Pandemic Influenza A(H1NI) in 2009, Makerere University Walter Reed Project (MUWRP) together with Ministry of Health, the National Task Force on Avian influenza (AI) and other stakeholders undertook surveillance for Influenza like illnesses (ILIs) in human population in Uganda in order to detect potential pandemic influenza threats and control them.

Objective To conduct surveillance of influenza and influenza-like illnesses in human population in Uganda in order todetect circulating influenza strains and map the human populations at risk.

Methods From 1st 0ctober 2008 to date MUWRP has been carrying out surveillance for influenza and influenza like illness among patients attending out patient clinics at 5 of the Sentinal sites ie Mulago National Referral Hospital, Jinja & Gulu Regional Referral Hospitals and Kayunga & Bugiri District Hospitals. Patients aged 6 months or older presenting with fever (temperature > 38O Celsius) combined with a cough and/or a cold and/or a sore-throat within 72 hrs before presenting to hospital were enrolled in the study after obtaining informed consent (and assent for children aged 8 – 17 years). Demographic, social, travel, work and exposure history to birds and/or animals was collected, followed by a physical examination. A throat and and/ or Nasopharyngeal swab was collected in viral transport medium and shipped to the BSL2 Influenza Research Laboratory at the Uganda Virus Research Institute in Entebbe Uganda for virus isolation and typing using RT-PCR for flu A and flu B respectively.

Results A total of 3547 participants were enrolled in the study of whom 1797 (50.7%) were females. By age, 2875 (81.1%) and 307 (8.7% ) were Chidren Under 5yrs and 6 -17 respectively. The majority, 3070 of the 3547 (86.6%) tested negative on RT-PCR screening for Flu A & B, while 368 (10.4%) patients tested positive for Flu A, and 102/3547 (2.9%) tested positive for Flu B. On subtyping for Flu A, 5 (1.9%) were H1,84 (32.6%) were H3 and 39 (2.1%) had co-infections of H3 and HINI was present in 90 (34.9%) and H3N2 in 53 (20.5%) specimens, while 23 (8.9%) were untypable. Subtyping for Flu B is still ongoing. By Gender females contributed 130/258 (50.4%) subtypes of Flu A while by age children under five and those aged 6-17 yrs contributed 179/255 ( 70.2%) and42 (16.5%) respectively.

Conclusion Influenza virus was not commonly isolated from patients presenting with influenza / influenza like illnesses (ILIs) at participating outpatient clinics particulary among adults which calls for further investigations to determine other potential pathogens. Influenza A virus H1N1 followed H3N2 were the main virus subtypes being isolated.


Abstract Title Current and Future Plans for Enhancing Influenza Laboratory Capacity in Africa by WHO and Partners

Authors Dhamari Naidoo, Terry Besselaar, Wenqing Zhang

Since the establishment of the WHO Global Influenza Surveillance and Response System (GISRS) in 1952, the network has seen a tremendous growth in the number of countries actively participating in influenza virus surveillance. As of 2011, the network comprises 136 National Influenza Centres (NICs) in 106 WHO member states, six WHO Collaborating Centres for Influenza and four Essential Regulatory laboratories. These laboratories play important but different roles in surveillance and response to influenza epidemics and pandemics. In a region spanning 46 countries where HIV/Aids, malaria and TB are the leading causes of morbidity and mortality, the implementation of influenza surveillance has been challenging. However, since the re-emergence of highly pathogenic influenza A(H5N1) in 2003, many partners have supported WHO to develop and strengthen laboratory-based influenza surveillance in Africa.

In a collaborative project with USAID, CDC and WHO AFRO regional office, an assessment was performed to determine the current laboratory capacities of NICs and influenza reference laboratories in the WHO AFRO region. The key areas targeted were molecular testing using real time PCR and virus isolation capacity. Twenty nine countries were identified with PCR testing capacity with capabilities ranging from fully functional to partially functional. Eight countries have expressed an interest to implement virus isolation techniques and capacity building has begun in 4 laboratories. Four countries have been identified with existing capacity as potential candidates for NIC status designation. Four NICs have been proposed for consideration as regional labs and their role in the region will be strengthened to support neighbouring countries without NICs or influenza surveillance systems. In a region where no WHO Collaborating Centre exists, and with only 12 NICs in 11 WHO member states, it is hoped that the establishment of regional laboratories and additional NICs will enhance laboratory based surveillance to detect and monitor the emergence and spread of influenza viruses. Through the continued support of partners, this collaboration will assist WHO GISRS in broadening its capacities in resource scare countries.


Abstract Title Viral Etiology of Influenza-Like Illnesses in Cameroon, January to December 2009

Authors Richard Njouom, Elsie Laban Yekwa, Pierre Cappy, Astrid Vabret, Pascal Boisier and Dominique Rousset

Background No information is available on the viral etiology of upper respiratory tract infections in Cameroon.

Methods We prospectively enrolled Influenza-Like Illness (ILI) outpatients presenting at 14 sentinel clinics located across the country from January to December 2009. The specimens were tested using real time and multiplex RT-PCR methods for the detection of 15 RNA respiratory viruses.

Results We detected at least one respiratory virus in 365/561 (65.1%) specimens. Overall Influenza virus (IFV) (28.2%) was the most common detected virus, followed by human rhinovirus (HRV) (17.8%), parainfluenza viruses (PIV 1-4) (7.5%), enterovirus (EV) (5.9%), respiratory syncytial virus (RSV) (5.7%), human coronaviruses (HCOV) -OC43, -229E, -NL63 and -HKU1 (5.3%), and human metapneumovirus (HMPV) (5.0%). RSV (26/31, 83.9%), PIVs (30/39, 76.9%), and HRV (64/99, 64.6%) were most common in children < 5 years of age. Coinfections were found in 53/365 (14.5%) positive specimens and most (71.7%) were in children < 5 years of age. While IFV, EV, RSV and HMPV had a defined period of circulation the other viruses were detected throughout the year.

Conclusions We found that respiratory viruses play an important role in the etiology of ILI in Cameroon, particularly in children < 5 years of age.


Abstract Title Virologic Surveillance of Influenza Viruses in Rwanda, 2008 – 2011

Authors Richard C. M. Nkunda1, Alice Kabanda1, Joseph Rukelibuga2, Enatha Mukantwali1, Marie A. Muhimpundu1, Thierry Nyatanyi1, Pratima Raghunathan2, Odette Mukabayire1

Affiliations 1Rwanda Biomedical Centre – Institute of HIV/AIDS and Diseases Prevention and Control 2Centers for Disease Control and Prevention – Rwanda

Background In response to the threat of Avian Influenza, many countries established surveillance systems to monitor the trend of the disease. In July 2008, Rwanda established a sentinel surveillance system for Influenza. The sentinel sites comprise two referral and four district hospitals. Patients with syndromes of influenza infection are identified and tested for the presence of the virus. The objective of our study was to identify and characterize the influenza virus strains circulating in the country.

Methods We identified patients presenting at the sentinel sites with Influenza like illness (ILI) and severe-acute respiratory illness (SARI) from the period from July 2008 to September 2011. We collected nasopharyngeal and oropharyngeal specimens from each patient and tested using RT-PCR for Avian Influenza (H5N1), human seasonal Influenza (A/H1N1, A/H3N2 and B), and A (H1N1) pdm09 Influenza. We entered the data in Ms Excel and analyzed for the distribution of the positivity of the various strains for the study period.

Results In all, 4,976 patients were tested out of which 732 (15%) were positive for influenza virus. Among those who were positive, 665 (91%) had Influenza type A and 67 (9%) had type B. Out of the 665 type A, 530 (80%) were subtype A (H1N1) pdm09, 115 (17%) subtype A/H3 and 20 (3%) subtype A/H1. The distribution of Influenza virus strains overtime showed that Influenza A/H1 predominated in 2008; Influenza A/H3 predominated in the first semester of 2009 until the outbreak of A (H1N1) pdm09 occurred in the October 2009. However, A/H3 and Influenza B co-circulated with the A (H1N1) pdm09. In 2010, A (H1N1) pdm09 remained predominant in the first semester and later A/H3 became predominant until to date (2011) with co-circulation of Influenza B. The highest proportion of Influenza positivity in Rwanda was realized in 2009 and 2010 due to the pandemic outbreak of Influenza A (H1N1) pdm09. The general positivity decreased from 15% to 6% after the pandemic whereas the number of specimen collected and tested increased from 62 in 2008 to 1,464 as of September 2011.

Conclusion The virologic surveillance of influenza during the last 3 years in Rwanda reveals circulation of seasonal A/H1 and A/H3, B and A (H1N1) pdm09. Increase in specimen collection and testing due to intensified surveillance was not proportional to the increase in Influenza positivity. This has prompted a need for evaluation of the surveillance system to determine the sensitivity of the case definition and also improve on the laboratory testing capacity to detect other respiratory pathogens.

Keywords Influenza, Sentinel, Virologic surveillance, RT-PCR, Rwanda


Abstract Title About the Seasonality of Influenza in Kinshasa, DRCongo in 2009 – 2011

Authors E. Nkwembe1, S. Karhemere1, F. Bankoshi1, P. babakazo2, B. Kebela3, E. Okito2, JJ. Muyembe1

Affiliations 1Laboratoire National Grippe, Institut National de Recherche Biomédicale (INRB); 2Ecole de Santé publique, Kinshasa; 3Direction de la lutte contre les maladies (Ministère de la santé).

Background Contrary to the northern hemisphere, the epidemiology and seasonality of influenza are not well understood in Central African countries. Since 2007, five sentinel sites were selected in Kinshasa, the capital city of DRC, to determine the seasonality of circulating influenza viruses and to detect any new emerging strains.

Methods Epidemiologic findings and throat swabs for laboratory testing were collected from patients with Influenza –Like Illness (ILI) or Severe Acute Respiratory Infections (SARI). Viral RNA was manually extracted from clinical samples by QIAmp viral RNA mini kit “QIAGEN”, and amplified by real time RT-PCR, according to the CDC method.

Results From January 2009 to October 2011, 5966 samples were collected from 4444 patients with ILI and 1490 with SARI. 32 patients were not specified. 516 (8, 6%) samples were positives for influenza A and 192 (3, 2%) for influenza B. Of these influenza A, 225 were pandemic H1N1, 243 were H3N2, 10 were seasonal H1N1 and 36 unsubtypable. Co-infections by pandemic H1N1 and seasonal H3N2 occurred in 3 patients. Kinshasa with its 6 millions inhabitants has two seasons, the dry season from May to September and the rainy season from October to April. Pandemic influenza A (H1N1) was the predominant subtype from August to December 2009 with the peak in October 2009.Apart from this period, the data showed influenza activity during at least one peak each year from January to March, April or May. During the three year period (2009–2011), there were three peaks of influenza A (H3N2) activity, in 2009 (from January to February and August to November), 2010 (January to May) and 2011 (from January –July), although this may have been affected by the peaks of pandemic influenza A (H1N1) from September–December 2009 and March-July 2010; and from January and February 2011. One peak of H1N1 seasonal activity was observed from January to February 2009. The peak of Influenza B activity was observed from January to March 2009, March to July 2010 and June to October 2011.

Conclusion Major influenza activities were seen during the rain season in Kinshasa.Pandemic influenza A (H1N1), seasonal influenza types A (H3N2) and type B co-circulated during this period of time.


Abstract Title Viral Etiologies of Acute Respiratory Infections among Inpatients and Outpatients in Rural Western Kenya, August 01, 2009 – July 31, 2011

Authors Rachel A. Ochola1, Emma Lebo1, Sammy Khagayi2, Reuben Onkoba2, Lilian Waiboci1, Phillip Muthoka3, Danny Feikin2, 4, Frank Odhiambo2, Kayla Laserson2, Deron Burton2, Josh Mott1, Mark A. Katz1

Affiliations 1Influenza Program, Global Disease Detection Division, CDC-Kenya; 2Centers for Global Health Research, KEMRI, Kenya; 3Ministry of Public Health and Sanitation, Division of Disease Surveillance and Response, Kenya; 4John Hopkins Bloomberg School of Public Health and Centers for Disease Control and Prevention, USA

Objectives To ascertain viral etiologies of acute respiratory infections in both out- and hospitalized patients in a rural community in Kenya.

Background Acute respiratory infections (ARI) are one of the leading causes of morbidity and mortality in the developing world. The epidemiology and burden of ARI in rural Kenya is not well understood.

Methods The study was carried out in Karemo Division of Siaya District, rural Western Kenya, an area under continual health and demographic surveillance since August 01, 2009, by the Kenya Medical Research Institute/ Centers for Disease Control Collaborative Program (KEMRI/CDC). During a 2-year period (August 01, 2009 - July 31, 2011), we collected nasopharyngeal (NP) and oropharyngeal (OP) specimens along with demographic and clinical information from inpatients with severe respiratory infection (SRI) and outpatients with influenza-like illness (ILI) at two health facilities, Siaya District hospital (SDH) and Tin’gwan’gi Health Clinic (THC) respectively, in western Kenya. We defined ILI as cough or sore throat and temperature ≥ 38oC. We defined hospitalized SRI according to the WHO Integrated Management of Childhood Illness classification of pneumonia or severe pneumonia in hospitalized children 2mo- 5 years; and a temperature ≥ 38oC and cough or shortness of breath or difficulty in breathing in hospitalized patients > 5 years. We tested samples for influenza (Flu) A and B, respiratory syncytial virus (RSV), parainfluenzae (PIV) - 1, -2 and -3, adenovirus (AV), human metapneumovirus (HMPV) by real time reverse transcriptase polymerase chain reaction (qPCR).

Results From the 4,024 inpatients admitted, 2,437 (60.6%) met the hospitalized SRI case definition, 1,956 (80.3%) had swabs collected; 2055 (51.1%) were male and the mean age was 62.2 (SD, 135.3) months. From the 5,553 outpatients visits, 1,214 (21%) met the ILI case definition, 1,147 (94.5%) had swabs collected; 2,770 (49.9%) were male and the mean age was 43.5 (47.4) months. One or more respiratory viruses were identified in 898 (36.9%) samples from SRI patients, and 608 (50.1%) specimens from outpatients. In hospitalized SRI patients, AV (15%), PIV-3 (9%), RSV (8%), Flu A (5%), and HMPV (5%) were the most common. In outpatients, AV (20%), Flu A (10%), RSV (9%), PIV3 (9%), and HMPV (9%) were commonly detected. Of the hospitalized SRI patients, one (1/138 (0.7%)) and five (5/204 (2.5%)) deaths were recorded among influenza and RSV patients, respectively.

Conclusion In western Kenya, viruses were identified in nearly 40% and 50% of inpatient and outpatient visits associated with SRI and ILI, respectively. These findings are similar to previous studies in Kenya and other countries, and thus underscore the potential importance of vaccine and other interventions in reducing the ARI disease burden.


Abstract Title Virological Patterns of Influenza in Nigeria, March 2009- September 2011

Authors Onyiah A. P., Biya D., Shilo P. A., Nwakamma A. N., Adedeji A. A.

Affiliations Federal Ministry of Health, Abuja, Nigeria National Influenza Reference Laboratory (NIRL)

Objectives To determine the spectrum and seasonal pattern of influenza viruses among suspected influenza cases in Nigeria.

Background National Influenza Sentinel Surveillance (NISS) Nigeria was instituted by the Federal Ministry of Health in a bid to understand the epidemiology of influenza infection in Nigeria and provide information for public health decision-making. The surveillance system is comprised of four sentinel sites which are spread across four of the six geo-political zones in the country. Weekly virological as well as epidemiological reports are sent to World Health Organisation (WHO) and other stakeholders. The seasonality of Influenza and the prevalent Influenza subtype had not been studied prior to the introduction of NISS in Nigeria.

Methods Four (4) cases of Influenza-Like Illness (ILI) are recruited per day for the first four days of the week from the General Outpatient Department (GOPD) of each sentinel hospital. All Severe Acute Respiratory Infection (SARI) cases are recruited from the in-patient wards of the sentinel hospitals. The case definition for ILI are patients with temperature above 38°C and cough or sore throat. SARI case definition for patients above 5 years are patients with temperature above 38°C, cough or sore throat, difficulty in breathing or shortness of breath, and requiring hospitalization. SARI cases in children below 5 years are recruited using Integrated Management of Childhood Illness (IMCI) case definition for pneumonia. Epidemiological data and specimen are collected from all cases recruited and delivered by courier to the National Influenza Reference Laboratory within 4 days of collection where they are tested for influenza using real time Reverse-Transcriptase Polymerase Chain Reaction (RT-rtPCR). Data from March 2009 to September 2011 was analysed using epi info 3.5.1 software.

Results Altogether, 5635 Cases were recruited and 5544 (98.4%) specimens tested between March 2009 and September 2011. Of the total specimens tested, 448 (8.1%) tested positive for influenza. Of the influenza positive specimens, 303 (67.6%) were positive for influenza A and 145 (32.4%) were positive for influenza B. Influenza subtypes A/2009 H1N1, A/H1, A/H3, and A/H5 account for 49.8%, 5.3%, 36.6%, and 0.0% of all Influenza A positive specimens. Influenza activity is highest in weeks 8 to 22 of 2009, weeks 51 of 2009- week10 of 2010, and weeks 49 of 2010 to 9 of 2011. Influenza positivity was highest in children within the age range of 5 and17 (8.7%) and lowest in adults above 65 years (5.1%).

Conclusions Influenza A/2009 H1N1 is the predominant influenza A subtype circulating in Nigeria during the reporting period. Influenza positivity in Nigeria appears to be higher at the end of each year and the beginning of subsequent year and lowest around the middle of the year. Influenza was recorded more in children. The Influenza surveillance system should be sustained.


Abstract Title Divergent Evolution of Genes in Recent Influenza A (H3N2) Viruses Isolated in Kenya

Authors Benjamin Opot, Finley Osuna, Meshack Wadegu, Rachel Achilla, Janet Majanja, Eyako Wurapa and Wallace Bulimo

Background Understanding the evolution of influenza A viruses in humans is important for surveillance and vaccine strain selection. We performed a Phylogenetic analysis of 129 samples of human H3N2 influenza A viruses collected between 2006 and 2010 from our 8 sites across Kenya. While virulence of influenza virus is polygenic, the hemagglutinin (HA) protein particularly the globular HA1 domain is important in receptor binding, membrane fusion and harbors antigenic determinants against the virus. Objective To describe the evolution of HA1 protein of the H3N2 influenza A virus in Kenya from 2006 to 2010.

Methods Nasopharyngeal samples from patients meeting the WHO ILI case definition were collected between 2006 and 2010 from across Kenya. The detection of H3N2 virus was carried out using real-time RT-PCR. The positive samples were then cultured in MDCK cells and confirmed using the HAI assay. 129 isolates from this period were selected for sequencing and PCR to amplify the HA1 portion of the HA gene was performed and the nucleotide sequences of the resulting amplicons sequenced. A suite of bioinformatics tools was used for gene analysis.

Results Analysis of amino acid substitution of the HA1 protein of the 129 isolates showed substitutions located at various glycosylation sites. A/Perth 16/2009 vaccine strain for the 2010 season had a N144K amino acid (aa) substitution whereas 21 Kenyan isolates collected in 2008 showed a N144S substitution at site A. The vaccine strain at the time A/Brisbane 10/2007 did not have this substitution. An S45N aa substitution at site C was observed in all the 2010 isolates and majority of the 2008 isolates. A/Wisconsin 67/2005 vaccine strain for 2007 showed an N122D aa substitution at site B/A. This substitution has been seen in only one Kenyan strains which had an N122S.

Conclusions Our results show that A/Brisbane 10/2007 did not have the substitution observed in some of the 2008 isolates but this change soon disappeared and has not been seen since. Continued surveillance is important since H3N2 influenza strains continue to evolve and vaccine composition is determined by these changes.


Abstract Title Do Kenyan Parents Want Their Children Vaccinated Against Influenza? Parental Attitudes towards Childhood Influenza Vaccination Prior to and Following an Influenza Vaccination Campaign, Kenya, 2010 – 2011

Authors Prisca A. Oria1, Joshua M. Wong3, Deborah Caselton3, Nancy A. Otieno1, Emmaculate Lebo3, Gideon Emukule3, Philip M. Muthoka2, David Mutonga2, Joshua A. Mott3, Robert F. Breiman3, Mark A. Katz3

Affiliations 1Kenya Medical Research Institute/Centers for Disease Control and Prevention, Nairobi, Kenya; 2Ministry of Public Health and Sanitation, Nairobi, Kenya; 3Centers for Disease Control and Prevention, Nairobi, Kenya

Background Influenza vaccine is rarely used in Kenya, and little is known about attitudes towards the vaccine. In 2010, Kenya Medical Research Institute/Centers for Disease Control began a three-year observational seasonal influenza vaccine effectiveness study in children in two population-based infectious disease surveillance (PBIDS) communities: Kibera, an informal settlement in Nairobi; and Lwak, a rural area in western Kenya.

Objective To examine parents’ opinions about childhood seasonal influenza vaccination and potential knowledge and attitudinal factors that might influence such opinions, and to identify motivators and barriers that influence vaccine uptake.

Methods In 2010, free influenza vaccine was offered to children 6 months–10 years old enrolled in the two PBIDS communities with a combined total population of about 55,000 people. The vaccine campaign was preceded by an awareness campaign. We conducted focus group discussions with parents of children of enrollment age in the two sites prior to and following the vaccination campaign.

Results We conducted 4 group discussions prior to the vaccine campaign and 12 afterwards, with a total of 111 parents. Pre-vaccination, no parent had heard of the seasonal influenza vaccine. Most parents said low temperatures, dust, and smoke caused influenza, and said they preferred homemade remedies rather than hospital treatment for influenza. However, many parents were willing to have their children vaccinated provided they received more information about the safety and effectiveness of influenza vaccine. Post-vaccination, all parents knew about influenza vaccine. Out of 18,652 eligible children, 5,817 (31.2%) were fully vaccinated, 2,073 (11.1%) partially vaccinated and 10,762 (57.7%) non-vaccinated. Most parents whose children were not vaccinated said the reason their children did not get vaccinated was that they were away during the vaccination period. In pre- and post-vaccination group discussions, some parents who did not plan to and/or did not vaccinate their children said they believed influenza was not severe enough to warrant vaccination and that it was normal to occasionally suffer from influenza.

Conclusion With awareness campaigns, some parents, previously unaware of influenza vaccine, were willing to have their children receive a free influenza vaccine. If seasonal influenza vaccine were to be introduced more broadly in Kenya, effective health messaging focusing on vaccine effectiveness, safety, and the potential severity of influenza could increase vaccine acceptance.


Abstract Title Human Influenza Surveillance in Cameroon: Differences in Symptoms and Seasonality by Subtype

Authors Saylors KE, Ortiz N, Papworth EM, Tamoufe U, Djoko CF, Wurapa EK, Sanchez JL, Fair JN, Wolfe ND

Objective 1. Describe the different symptoms associated with Influenzas A and B in study participants who tested positive for influenza in Cameroon. 2. Discuss the seasonality of influenza subtypes in Cameroon.

Background Between January 2010 and August of 2011 in Cameroon, surveillance was conducted among patients presenting to care facilities with influenza-like illness (ILI) in order to detect and characterize circulating human influenza viruses in the country. Study participants included 2,490 patients of all ages presenting with ILI at one of 37 clinics, hospitals, and infirmaries in 3 regions of Cameroon (Center, South and East).

Methods Patients two months or older presenting with ILI within 72 hours of enrollment were eligible for study inclusion. Once enrolled, each participant provided either a nasopharyngeal or throat swab that was screened by real-time PCR (RT-PCR) for influenza viruses prior to virus isolation and further characterization. Additionally, a data collection instrument was used to collect demographic information and to record the signs and symptoms that patients reported. Epidemiological data was analyzed using STATA 11.

Results A total of 15.4% of samples tested positive for influenza. Influenza B was the most common subtype constituting 8.8% of samples tested; 6.6% of samples subtyped as Influenza A. From among the A subtypes, 4.9% were identified as H1N1 and 1.7% identified as H3N2. 86.4% of influenza positive samples collected between March – September 2010 were identified as Influenza B. Between November 2010 – January 2011, H1N1 accounted for the majority of influenza positive samples collected each month with an 85% average for the 3-month period. 64% of influenza positives for September and October of 2010 were H3N2. Among participants, patients with H3N2 reported 24.6% more acute symptoms as compared to H1N1 patients and 54.8% more symptoms than Influenza B patients. An analysis of the data stratified by five-year age ranges revealed that over half of participants in the study were under the age of five. Further research is necessary to determine if the population is comprised of a young population or if parents of younger children are more likely to seek care for ILI and are therefore disproportionately represented.

Conclusion Our study points to seasonal trends of influenza by subtype in Cameroon with Influenza B peaking between the months of March and September, while Influenza A accounts for most cases of flu between September and January. Continued surveillance is necessary to determine if this same trend is observed annually. Surveillance should be expanded to include more regions of Cameroon.


Abstract Title Viral Etiology of Severe Acute Respiratory Infection in Madagascar

Authors Norosoa Razanajatovo, Arnaud Orelle, Soatina Rajatonirina, Rila Ratovoson, Perlinot Herindrainy, Zo Andrianirina Zafitsara, Rakotovao Domohina, Richard Vincent and Jean-Michel Heraud

Background Acute lower respiratory infection causes 1.2 to 2.2 millions of death in children worldwide. Forty two percent of this mortality occurred only in developing countries. The incidence of pneumonia which is the most severe case is estimated to be 0.29 by infant by year. In Madagascar, the viral etiology of influenza-like illness (ILI) is well established. However, no data exist concerning the severe acute respiratory infection (SARI) caused by respiratory viruses and its contribution to co-infection.

Objective Our study aimed to describe the relative frequency of respiratory viruses in hospitalized patients presenting SARI and compare genetically viral strains associated to SARI and those associated to ILI.

Methods From November 2010 to November 2011, we collect samples from patients that were hospitalized in two sites and responding to the SARI case definition. We analyzed samples using an in-house real-time RT-PCR multiplex which detected 14 respiratory viruses. Viral etiology was studied and isolates were genetically characterized and compared to strains from the ILI study. We reported here the results from one year study. Results: From November 2010 to November 2011, we analyzed 237 SARI cases which 76% were positive for respiratory viruses. Influenza A (32%), RSV (25%) and rhinovirus (19%) were the main viruses detected. Co-infection occurred in 30% of infected patients. Children less than 5 years were the most infected compared to patients more than 5 years (75% vs 25%). Genetic analysis highlights the diversity of circulating genotypes and serotypes during the study period and shows multiple viral introductions. Some genotypes from two viruses, RSV and human metapneumovirus were found more frequently in SARI cases than ILI cases.

Conclusion Our study is the first study in Madagascar that aimed to describe viral etiology of SARI cases. During our first year study period, we showed that influenza accounted for the main cause of hospitalization for SARI patient mainly in children under 5 years. Preliminary results might indicate that virulence of some viruses could be linked to a specific genotype/serotype. More work is needed to better characterize relationship between virulence and antigenic diversity and to estimate burden of SARI within population and especially in children. Our result could help policy maker to identify vaccine that could reduce morbidity of SARI among children.


Abstract Title Multiple and Single Infections of Influenza, RSV and Human Bocavirus during the Post Pandemic Period

Authors Samwel Lifumo Symekher, George Gachara, Carol Gikera, Jane Gichogu, Moses Rotich, Musa Ng’ayo, and Japhet Magana

Introduction Acute respiratory infections (ARI) are leading causes of morbidity and mortality in children. Viruses have been recognized as predominant causative agents of ARI in them. Molecular testing has increased detection of pathogens.

Objective To identify influenza, respiratory syncytial virus (RSV) and human bocavirus (HBoV) using molecular methods from patients recruited from an influenza sentinel surveillance in Kenya.

Methods Oropharyngeal swabs from consenting patients with influenza like illness were collected, placed into cryovials with virus transport medium, and transported at +40C to the ARI-Unit, in Center for Virus Research, KEMRI. RNA and DNA were extracted from the samples. Influenza real time PCR was performed according to WHO protocols. Conventional PCR for RSV targeting the nucleocapsid and HBoV targeting the NS1 gene were carried out using established protocols. The PCR products were observed in 2% agarose gel. Proportions of RSV positive and HBoV samples were sequenced using the big dye technique.

Results 297 samples were collected from the study sites. The most detected virus was RSV (n=140; 47.1%), followed by influenza viruses (n=66; 22.2%), and then HBoV (n=28; 9.4%). Of the influenza viruses detected, 64 (97%) were influenza A and 2 (3%) were influenza B. There were a total of 184 (61.95%) patients that had viruses detected in them. 133 patients infected by a single agent, 47 patients infected by two agents, and 4 patients infected by three agents. The sequence analysis of this study’s RSV strains indicate clustering together of this study’s isolates. For HBoV, the strains showed the clustering together with HBoV prototype strains ST1 and ST2 and other strains from Genbank.

Conclusions 234 viruses were identified from the patients recruited. Multiple infections were seen in 51 patients. Majority of this study’s RSV clustered together on a different branch separate from other RSV indicating variability, while the HBoV detected clustered together with other HBoV, indicating conservation.


Abstract Title Virological Surveillance of Influenza-like Illness in Burkina Faso: Preliminary Results, 2010 – 2011

Authors Z. Tarnagda, Arsene Ouedraogo, T. Kagone, A. Cisse, D. Valea, H. Zampa, A. Sanon, F. Drabo, Y. Ndjakani, L. Sangare, and JB Ouedraogo

Background Influenza is thought to be a neglected disease in Burkina Faso. Since the emergence of a new influenza A(H1N1)pdm09 virus in North America in 2009 and its international spread, many countries, including Burkina Faso started sentinel surveillance of influenza-like illness (ILI) for the first time. The aim of this study is to describe and characterize influenza viruses circulating in Burkina Faso in 2010-2011 season.

Methods Oro-pharyngeal swabs from outpatients (5 years ≤ age ≥ 65 years) in two sentinel sites in Bobo-Dioulasso were collected according to the national protocol and WHO case definition for ILI:[fever≥38ºC, AND cough and/or sore throat (in the absence of a known cause other than influenza)] from July 2010 to June 2011. Influenza cases were detected by real time RT-PCR in an ABI machine 7500 Fast at the National Influenza Reference Laboratory of Burkina Faso using the CDC primers and protocol for influenza detection.

Results A total of 348 oro-pharyngeal swabs were collected from outpatients whose age average was 14 years (95% CI:14.53-11.42). We detected 6.8% (24/348) cases of influenza viruses. Sixteen (66.7%) cases were influenza A viruses and 8 (33.3%) cases were influenza B viruses. After subtyping of influenza A cases, 14 cases were confirmed to be A(H1N1)pdm09 and two cases were seasonal A/H3N2. The distribution of cases by sex was not statistically significant (chi square = 0.74, p = 0.194).The majority of influenza cases,96% occurred in patients which age ranged5 to 34 years. Te period of high detection of influenza virus was from November to February corresponding to the cold season (temperature less than 25°C).

Conclusion This study confirms the circulation of influenza viruses in Burkina Faso. Therefore, it is important to continue and improve the virological and epidemiological surveillances in order to determine the trends and the seasonality of influenza in the country.


Abstract Title Vaccination Campaign against 2009 Pandemic Influenza A (H1N1) in Côte d’Ivoire in September 2010

Authors Y Traoré1, D Coulibaly1, D Cherif1, A K. N’gattia1, Ndahwouh Talla Nzussouo2,3, E KN N’guessan1, D K. Ekra1, S N. Dagnan1.

Affiliations 1National Institute of Public Hygiene, Abidjan, Côte d’Ivoire; 2Influenza Division, U.S. Centers for Disease Control and Prevention, Influenza Division, Atlanta, GA; 3Global Disease Detection and Response Program/US Naval Medical Research Unit No. 3, (NAMRU-3)

Background Côte d’Ivoire has recorded 36 cumulative cases of pandemic influenza A (H1N1) in 2009 with zero death. One of the key measures to fight against this pandemic was the vaccination of 10% of the total population at high risk. Thus, a vaccination campaign was carried out to protect people against the disease. The objective of this study is to describe the vaccination campaign.

Methods The campaign was conducted in 83 health districts from the 2nd to the 8th of September 2010. The priority target groups were made up of health workers, children aged from 6 to 59 months, pregnant women, patients with chronic conditions and critical staff of the Government and strategic areas (Water, Electricity company, customs, security forces). The vaccination strategy was fixed in urban areas and mobile in rural areas.

Results In total 2,186,203 people were vaccinated, a vaccine coverage of 104.3%. At Nassian and Anyama the maximum and minimum vaccination coverage rates were obtained respectively with 157.3% and 83.6%. However 33% of subjects aged from 9 months to 4 years, 11% of the 5 to 14 years and 56% of 15 years and above presented adverse events following immunizations (AEFI). These AEFI were due to post-vaccination reactions (66.7%) and, coincidences (33.3%) in patients with a history of asthma and hypertension. No case of accidental exposure to blood was recorded.

Conclusion Given that the circulation of pandemic influenza in Cote d’Ivoire (and in the West Africa) was out of synchrony with other parts of the world, this campaign though conducted in September 2010 might have helped to prevent a high transmission of the 2009 pandemic influenza.

Keywords Pandemic Influenza A (H1N1) - Preventive vaccination - Cote d’Ivoire


Abstract Title Developing Respiratory and Emerging Infectious Disease Biosurveillance Activities in Resource-Limited Settings

Authors Cockrill JA, Tsai AY, Burke RL, Perdue CL, Vest KG, Lewis S, Blazes DL, Sanchez JL

Objectives Originally established by Presidential Directive NSTC-7 in 1997, the Department of Defense (DoD) Global Emerging Infections Surveillance and Response System (GEIS) was expanded in 2006 and subsequently incorporated as a Division of the Armed Forces Health Surveillance Center (AFHSC) in 2008. The goal of the AFHSC’s respiratory pathogen surveillance program is to maintain awareness and monitor respiratory disease activity worldwide with the objective of protecting the health of the US military. As part of these efforts, we pursue establishment and sustainment of biosurveillance activities that detect and discover emerging infectious diseases (EID) in resource-limited settings, contributing to global health, and early detection and response to reportable diseases among local populations in compliance with WHO’s International Health Regulations (2005). The key to the success of early disease detection is to ensure that biosurveillance technologies are host country appropriate and sustainable, as well as compatible with other existing technologies. To this end, AFHSC-GEIS has partnered with the Johns Hopkins University Applied Physics Laboratory to develop two biosurveillance systems, the Suite for Automated Global bioSurveillance (SAGES) and the Respiratory Disease Dashboard (RDD).

Results AFHSC-GEIS partners that utilize SAGES are located in Peru, Cambodia, Philippines and Thailand. SAGES is also being implemented in Cameroon, Djibouti, and Nicaragua and considered for implementation in East Africa in coordination with local civilian and military health officials. As an example, outbreaks of meningitis and influenza A/H1N1 have been detected using SAGES in refugee camps along the Northern Thai-Myanmar border during the fall of 2010. Additionally, our Philippine partners reported recently that SAGES systems detected outbreaks an average of 5 days earlier than the previous system used by the Philippine National Epidemiology Center. Lastly, the Respiratory Disease Dashboard is currently being beta-tested by the US Army Medical Research Unit-Kenya (USAMRU-K) and will be available for utilization by a broader audience in early 2012.

Conclusion These broad-based, disease surveillance platforms developed by the AFHSC-GEIS will provide partner countries with additional tools which support IHR (2005) implementation and reporting requirements, including the early detection of EIDs and other public health events of international concern.


Abstract Title Molecular Antiviral Susceptibility Testing of Influenza A Virus Isolates obtained in Kenya in the Year 2008 – 2009

Authors Meshack Wadegu, Wallace D. Bulimo, Rachel A. Achilla, Janet Majanja, Silvanos Mukunzi, Finnley Osuna, James Njiri, Benjamin Opot, David C. Schnabel, Eyako K. Wurapa

Introduction Antivirals play an important role in the treatment and prevention of severe influenza infections. Amantidine and remantidine are matrix 2 (M2) protein inhibitors of influenza A virus while oseltamivir and zanamivir are neuraminidase (NA) inhibitors of influenza A and B viruses. The M2 protein mediates influx of protons through the transmembrane domain causing dissociation of the viral matrix and ribonucleoprotein (RNP) during virus entry into the cell. Binding of M2 inhibitors to the transmembrane domain of the M2 protein inhibits viral genome uncoating and subsequent RNP import into the nucleus. NA catalyzes the removal of terminal sialic acid residues from viral and cellular glycoconjugates by cleaving off the terminal sialic acids on the glycosylated HA during virus budding to facilitate virus release. In addition NA helps virus spread through the circulation by further removing sialic acids from the cell surface. The NA inhibitors interfere with the release of progeny influenza virus from infected host cells, a process that prevents infection of new host cells and thereby halting the spread of infection in the respiratory tract. Mutations in M2 and NA proteins underpin these resistances at the molecular level. H274Y (H275 in N2 numbering) change in the NA protein alters drug binding activity and results in Oseltamivir resistance. S31N substitution in the M2 domain is the major determinant of antiviral resistance to M2 inhibitors. This study investigated genetic characteristics of NA and M2 gene of seasonal influenza A virus isolated in Kenya in 2008-2009 in relation to antiviral resistance.

Method Nasopharyngeal specimen from outpatients of ages greater than or equal to two months were screened by reverse transcriptase real time PCR (RRT-PCR) using subtype specific primers. Positive specimens were inoculated onto MDCK monolayers. RNA extraction and amplification of M and NA genes was carried out on influenza positive cultures. Nucleotide sequencing of the amplified gene segments was done and sequences deposited in Gene Bank

Results In the study period, the M and NA genes of 12 influenza A (H1N1), 48 pandemic H1N1 and 36 influenza A (H3N2) were sequenced. 58% of influenza A (H1N1) specimens depicted Oseltamivir resistant marker H275Y but all were sensitive to adamantanes. All pandemic H1N1 and H3N2 strains showed resistance to adamantanes through possession of S31N substitution in the M2 protein. All H3N2 strains were sensitive to oseltamivir. These findings conform to the global picture regarding influenza antiviral activity. Antiviral resistance remains a global concern. Genotypic data obtained in this study demonstrate antiviral resistance in seasonal influenza A viruses isolated in Kenya in 2008-2009 despite lack of widespread antiviral use.

Conclusion Our results emphasize the unpredictable nature of influenza viruses hence need for continued surveillance and monitoring of drug resistance patterns globally.


Abstract Title Influenza Surveillance in Kenya, 2008 – 2011: A Low Likelihood of Successful Subtyping and Virus Isolation for Influenza Positive Specimens with High Cycle Threshold (CT) Values

Authors *Waiboci L.W.1, Arunga G.2, Mayieka L.M.2, Kikwai G.2, Wakhule L.2, Shigoli M.T.2, Junghae M.1, Mott J., Katz M.A1, and Njenga K.1

1US Centers for Disease Control and Prevention-Kenya, Nairobi, Kenya 2Kenya Medical Research Institute/ US Centers for Disease Control and Prevention-Kenya Nairobi, Kenya *Corresponding Author: Lilian W. Waiboci, CDC Kenya

Background We conducted retrospective data analyses to determine the relationship between influenza initial testing results and the ability to subtype and/or isolate influenza viruses in subsequent assays for specimens received by the KEMRI/CDC laboratory from June 2008 to May 2011.

Methods Nasopharyngeal and oropharyngeal specimens from patients with acute respiratory illness were tested for influenza A and influenza B by real time RT-PCR and results recorded as cycle threshold (CT) values. Influenza A positive specimens were subtyped for H1, H3, and H5 and beginning June 2009 for influenza A(H1N1)pdm09 (pH1). Virus isolation was attempted for a proportion of the positives. Binary regression model was used to determine the relationship between CT values and days since illness onset with subtyping and virus isolation results. CT 30 < 35 was used as a reference.

Results 18,675 were tested for influenza of which 2152 (11.5%) were influenza positive; 1649 (8.8%) were influenza A and 503 (2.6%) were influenza B positive. 42 (2.2%) specimens were positive for both influenza A and B. Of 1500 influenza A positives subtyped, 1024 (68.3%) subtyped as H1, H3 or pH1 of which 962/1024 (94%) specimens had CT < 35. Specimens with CT < 25 were 11.7 more likely to subtype than the reference [OR 11.7 (5.8 – 23.8); P < 0.001]. Specimens with CT 25 < 30 were 6.4 times more likely to subtype [OR 6.4 (3.1 -13.7); P <0.001] while specimens with CT 35 < 40 were 0.6 times less likely to subtype when compared to the reference [OR 0.06 (0.04 – 0.1); P < 0.001].

Influenza A was isolated from 475/601 (79%) specimens of which 466 (98.1%) had CT < 35. Influenza A was 4.8 times more likely to be isolated from specimens with CT < 25 and 3.3 more likely to be isolated from specimens with CT 25 < 30 when compared to the reference (P < 0.001). There was a 0.33 less likelihood of isolating influenza A from specimens with CT ≥ 35 when compared to the reference (P < 0.05). Influenza B was isolated from 46/79 (58.2%) specimens all with CT < 35. Specimens collected >3 days after symptoms onset were 0.57 times less likely to be culture positive that specimens collected 0 - 3 days after symptoms onset [OR 0.57 (0.38 – 0.84); P= 0.005].

Discussion We found that influenza subtyping and virus isolation were likely to produce positive results for specimens with CT < 35. In laboratories with limited resources, subtyping influenza A samples and culture of influenza A and B specimens with CT values < 35 may be more cost-effective than attempting to subtype and culture all influenza positive specimens.

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