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Current State of Infectious Current State of Infectious Diseases in Southern AfricaDiseases in Southern Africa
Diana DickinsonDiana Dickinson
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
OverviewOverview
HIV epidemic) HIV epidemic) already dealt with, just a few personalalready dealt with, just a few personal
TB ) TB ) insightsinsights
Pneumococcus in detailPneumococcus in detailOther regional problemsOther regional problems– MalariaMalaria– Hepatitis BHepatitis B– Herpes SimplexHerpes Simplex– Cervical cancer associated with HPVCervical cancer associated with HPV– KS associated with HHSV8KS associated with HHSV8
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Challenges of coping with the increases Challenges of coping with the increases and changing pattern of diseaseand changing pattern of disease
How modellers fit in at every stageHow modellers fit in at every stage– Planning Planning – Changing policy.Changing policy.– Evaluating…Evaluating…
A global view of HIV infection38.6 million people [33.4‒46.0 million] living with HIV, 2005
2.4
HIV prevalence (%) in adults in Africa, 2005
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
People living with HIV……….38.6 millionPeople living with HIV……….38.6 million– Children 2.3Children 2.3
New HIV infections in 2005… 4.1 millionNew HIV infections in 2005… 4.1 million– Children .54Children .54
Deaths due to AIDS in 2005.. 2.8 millionDeaths due to AIDS in 2005.. 2.8 million– Children .38Children .38– NB 1/3 of all HIV deaths are in Southern NB 1/3 of all HIV deaths are in Southern
AfricaAfrica
Global HIV epidemic, 1990‒2005* HIV epidemic in sub-Saharan Africa, 1985‒2005*
Number of people living with HIV
% HIV prevalence, adult (15-49)
% HIV prevalence, adult (15‒49)
Number of peopleliving with HIV (millions)
0
10
20
30
40
50
1990 1995 2000 2005
0.0
1.0
2.0
3.0
4.0
5.0
1985 1990 1995 2000 2005
0
5
10
15
20
25
30
0.0
2.5
5.0
7.5
12.5
15.0
% HIV prevalence, adult (15‒49)
Number of peopleliving with HIV (millions)
Estimated number of people living with HIV and adult HIV prevalence
This bar indicates the range around the estimate
*Even though the HIV prevalence rates have stabilized in sub-Saharan Africa, the actual number of people infected continues to grow because of population growth. Applying the same prevalence rate to a growing population will result in increasing numbers of people living with HIV.
10.0
2.2
Impact of AIDS on life expectancy in five African countries, 1970–2010
Life expectancy at birth (years)
Source: United Nations Population Division (2004). World Population Prospects: The 2004 Revision, database.
Botswana
South Africa
Swaziland
Zambia
Zimbabwe
1970–1975 1975–1980
1980–19851985–1990
1990–19951995–2000
2000–20052005–2010
70
65
60
55
50
45
40
35
30
25
20
4.1
People in sub-Saharan Africa on antiretroviral treatment as percentage of those in need, 2002–2005
20022003
2004
2005
7.2Source: WHO/UNAIDS (2005). Progress on global access to HIV antiretroviral therapy: An update on “3 by 5.”
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Age-specific prevalence of HIV in pregnant Age-specific prevalence of HIV in pregnant women, Botswana Sentinel Survey 2005 women, Botswana Sentinel Survey 2005 2003 22.8 38.6 49.7 45.9 2003 22.8 38.6 49.7 45.9
41.5 34.4 41.5 34.4
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
So what influenced Botswana to be the trend setters???So what influenced Botswana to be the trend setters???Obviously the foresight and wisdom of Botswana’s Obviously the foresight and wisdom of Botswana’s leaders, but aided by…leaders, but aided by…
Brian Gazzard, Lisbon IAS 1999Brian Gazzard, Lisbon IAS 1999-projection of reduction of costs when HIV is treated-projection of reduction of costs when HIV is treated
The The Durban AIDS ConferenceDurban AIDS Conference with Jeffrey with Jeffrey Sach’s projection on how NO developing country could Sach’s projection on how NO developing country could afford NOT to treat HIVafford NOT to treat HIV
Projected population graph with AIDS uncheckedProjected population graph with AIDS uncheckedLifetime risk of acquiring HIV of a 15 year old boyLifetime risk of acquiring HIV of a 15 year old boy
Projected population structure with and Projected population structure with and without the AIDS epidemic, Botswana, 2020without the AIDS epidemic, Botswana, 2020
80757065605550454035302520151050
020406080100120140 0 20 40 60 80 100 120 140
Males Females Deficits due to AIDS
Projected population structure in 2020
Population (thousands)
Ag
e in
yea
rs
Source: US Census Bureau, World Population Profile 2000
Lifetime risk of AIDS death for 15-year-old boys, Lifetime risk of AIDS death for 15-year-old boys, assuming unchanged or halved risk of becoming assuming unchanged or halved risk of becoming
infected with HIV, selected countriesinfected with HIV, selected countries
Source: Zaba B, 2000 (unpublished data)
Current adult HIV prevalence rate
Burkina Faso
Cambodia
Côte d’Ivoire
Kenya
South AfricaZambia
Zimbabwe
Botswana
Burkina FasoCambodia
Côte d’Ivoire
Kenya
South AfricaZambia
Zimbabwe
Botswana
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0% 5% 10% 15% 20% 25% 30% 35% 40%
Ris
k o
f d
yin
g o
f A
IDS
current level of risk maintained
risk halved over next 15 years
Anthony Harries Malawi, Ministry of HAnthony Harries Malawi, Ministry of Healthealth
TB (TB (CROI 2006) CROI 2006)
20032003
9,000,000 new cases9,000,000 new cases
4,000,000 smear positive4,000,000 smear positive
2,000,000 deaths2,000,000 deaths
Global TB incidence growing at 1% per yearGlobal TB incidence growing at 1% per year
Risk of TB 5-15% per year HIV + (50x HIV-)Risk of TB 5-15% per year HIV + (50x HIV-)
09/2006 TB Unit Ministry of Health Bot09/2006 TB Unit Ministry of Health Botswanaswana
0
100
200
300
400
500
600
700
Year
TB
Ca
se
Ra
te (
pe
r 1
00
,00
0)
0
5
10
15
20
25
30
35
40
45
HIV
se
rop
rev
ale
nc
e (%
)Reported TB Case Rate Botswana, 1975–2004Reported TB Case Rate Botswana, 1975–2004
and HIV Prevalence Antenatal Women, 1992-2005 and HIV Prevalence Antenatal Women, 1992-2005
TB
HIV
Malawi illustrates this-- note Malawi illustrates this-- note increasing smear negative cases increasing smear negative cases
30% treatment success and 60% mortality30% treatment success and 60% mortality
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
30-40% of all HIV deaths in Africa are due to 30-40% of all HIV deaths in Africa are due to TB usually diagnosed postmortemTB usually diagnosed postmortem
Lucas 1993 Cote d’IvoireLucas 1993 Cote d’Ivoire– 40% of HIV wasted patients who died had TB40% of HIV wasted patients who died had TB
Lewis 2005 MalawiLewis 2005 Malawi– 10% of HIV patients with severe anemia had 10% of HIV patients with severe anemia had
disseminated TB diagnosed by bone marrow disseminated TB diagnosed by bone marrow C/S C/S
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Malawi- 1999Malawi- 1999– 2979 Health workers died- 50% TB2979 Health workers died- 50% TB
- 40% AIDS- 40% AIDS– 105 TB control officers died105 TB control officers died
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Outcomes of TB in MalawiOutcomes of TB in Malawi
HIV +ve only 20% still alive 2 years after HIV +ve only 20% still alive 2 years after diagnosis (No treatment for HIV then)diagnosis (No treatment for HIV then)
HIV neg 50% only still alive at 7 yrsHIV neg 50% only still alive at 7 yrs
11-12% of TB notifications 11-12% of TB notifications recurrences/relapse- strong HIV recurrences/relapse- strong HIV associationassociation
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Outcomes of Isoniazid Prophylaxis (IPT) on Outcomes of Isoniazid Prophylaxis (IPT) on Incidence of TBIncidence of TB
IPT Reduces TB risk 40% IPT Reduces TB risk 40% (Wilkinson, BMJ 1998)(Wilkinson, BMJ 1998)
IPT Reduces risk of recurrence 50-80% IPT Reduces risk of recurrence 50-80% (Churchyard (Churchyard AIDS 2003, Fitzgerald Lancet 2000)AIDS 2003, Fitzgerald Lancet 2000)
HAART reduces TB risk but NOT back to normalHAART reduces TB risk but NOT back to normalIf patient has NO HAART If patient has NO HAART
9.7 risk of TB per 100 pt yrs9.7 risk of TB per 100 pt yrs If patient on HAARTIf patient on HAART
2.4 TB cases /100 pt yrs- 2.4 TB cases /100 pt yrs- Badri Lancet 2001 Badri Lancet 2001
continues reducing to 1% by 5 yrs continues reducing to 1% by 5 yrs Lawn Lawn AIDS 2005AIDS 2005
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Deaths due to TBDeaths due to TB
60% of TB deaths in 160% of TB deaths in 1stst 2 months 2 months
Early HAART after 2 weeks reduces Early HAART after 2 weeks reduces deathsdeaths
However Increased IRIS with possible However Increased IRIS with possible deaths with early HAART in first 3mdeaths with early HAART in first 3m
A balance has to be struckA balance has to be struck
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
What about other respiratory What about other respiratory diseases?diseases?
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Pneumococcal invasive illness has Pneumococcal invasive illness has escalated in our region…escalated in our region…
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Keith Klugman CROI 2006Keith Klugman CROI 2006
Changing Patterns of Pneumococcal Changing Patterns of Pneumococcal Infection in Southern AfricaInfection in Southern Africa
Generally Increasing prevalence of invasive Generally Increasing prevalence of invasive pneumococcal illness in developing countries. In RSA it pneumococcal illness in developing countries. In RSA it seems to have replaced Haemophilus Influenza in LRTIsseems to have replaced Haemophilus Influenza in LRTIs– Now 74% vs 12.9% Hib- reverse ratioNow 74% vs 12.9% Hib- reverse ratio
Increased prevalence of Paediatric (invasive) serotypes Increased prevalence of Paediatric (invasive) serotypes in HIVin HIV++ patients patientsIncreased mortality-65% with meningitis Malawi Increased mortality-65% with meningitis Malawi
-20% with pneumonia -20% with pneumoniaIncreased symptoms and signs with HIV+ patientsIncreased symptoms and signs with HIV+ patients– Pleurisy, haemoptysis, diarrhoea, meningitis,Pleurisy, haemoptysis, diarrhoea, meningitis,
Degree of risk CD4 driven Degree of risk CD4 driven – average CD4 in patients who died was 110 vs 170 in survivorsaverage CD4 in patients who died was 110 vs 170 in survivors
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Pneumococcal pneumonia is a disease of the very young and very old giving a U shaped curve in Western countries
Percentage of distribution of deaths by age in southern Africa, 1985–1990 and 2000–2005
0–4 5–19 20–29 30–39 40–49 50–59 60+
40
35
30
25
20
15
10
5
0
1985-1990 2000-2005
Percentage of total deaths
Age-groups:
Source: Population Division of the Department of Economic and Social Affairs of the United Nations Secretariat (2005). World Population Prospects: The 2004 Revision. Highlights. New York: United Nations. 4.2
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Note, modellers!Note, modellers!
Risks now have changed-Risks now have changed-– HIV+HIV+ (Lost immunity to paediatric strains) (Lost immunity to paediatric strains)– Young womenYoung women– Small child in homeSmall child in home– Health workerHealth worker– Abuse of drugs,Abuse of drugs,– smoking or alcoholsmoking or alcohol
Antibiotic resistance and severity of illness Antibiotic resistance and severity of illness increase with HIVincrease with HIV
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Morbidity reduced with HAARTMorbidity reduced with HAART– Spain, rate of invasive pneumococcal disease Spain, rate of invasive pneumococcal disease
dropped from 24.1/1000 in 1985 to 2/1000 dropped from 24.1/1000 in 1985 to 2/1000 (We have yet to see those results in Southern (We have yet to see those results in Southern Africa)Africa)
– However still increased risk X 30 to 35xHowever still increased risk X 30 to 35x
Mahdi et al CID 2005, 40,1511-18 Mahdi et al CID 2005, 40,1511-18
Pneumococcal vaccinePneumococcal vaccine
Normal paediatric pneumococcal vaccine Normal paediatric pneumococcal vaccine reduces prevalence of paediatric reduces prevalence of paediatric serotypes and greatly reduces riskserotypes and greatly reduces risk
However other less virulent strains replace However other less virulent strains replace themthem
Note- NOT the 23 valent vaccine- seemed Note- NOT the 23 valent vaccine- seemed to increase morbidity in Rakai- ? Due to to increase morbidity in Rakai- ? Due to severe immunocompromisation?severe immunocompromisation?
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Burden of disease in adults reduced by Burden of disease in adults reduced by vaccination of children (USA)vaccination of children (USA)
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
MalariaMalaria
LaurenceSlutsker Kenya Med Res StatioLaurenceSlutsker Kenya Med Res Station, Kisumu CROI 2006n, Kisumu CROI 2006
MalariaMalaria
Clinical Manifestations vary depending if occurs in stable or Clinical Manifestations vary depending if occurs in stable or unstable transmission areasunstable transmission areas– UnstableUnstable
acute febrile disease, cerebral malaria and death;acute febrile disease, cerebral malaria and death; still birth and abortion in pregnant womenstill birth and abortion in pregnant women
– StableStable Children chronic recurrent infections with anemia and growth retardationChildren chronic recurrent infections with anemia and growth retardationAdults acquired immunity, asymptomatic,Adults acquired immunity, asymptomatic, Pregnant women, increased foetal growth retardation and increased infant Pregnant women, increased foetal growth retardation and increased infant mortalitymortality
Severity in adults and children invariably aggravated by HIV, Severity in adults and children invariably aggravated by HIV, especially in unstable areas; with increased risk of Intensive care especially in unstable areas; with increased risk of Intensive care and death (and death (Cohen CID 2005, Grimwald Ped Inf Disease 2003) Cohen CID 2005, Grimwald Ped Inf Disease 2003)
Infants in stable areas get more frequent and severe anaemiaInfants in stable areas get more frequent and severe anaemia (van (van Eijke,AJTMH,2002)Eijke,AJTMH,2002)
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Cotrimoxazole ProphylaxisCotrimoxazole Prophylaxis
Ugandan cohort Ugandan cohort Lancet 2004Lancet 2004 70% reduction of 70% reduction of morbidity rate of severe malariamorbidity rate of severe malaria
Mali 97% efficacy to prevent infection in Mali 97% efficacy to prevent infection in HIV neg childrenHIV neg children
Abidjan Abidjan (Anglaret Lancet 1999)(Anglaret Lancet 1999) 5-6% reduction of 5-6% reduction of morbiditymorbidity
W Kenya- decreases in level of W Kenya- decreases in level of parasitaemiaparasitaemia
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Effect of HIV on malariaEffect of HIV on malaria
3 million excess cases3 million excess cases5% increase of malaria deaths(65,000)5% increase of malaria deaths(65,000) Increases parasitaemia with increasing Increases parasitaemia with increasing immunosuppression, reduced clearance abilityimmunosuppression, reduced clearance abilityUnder 5 yrs of age, 1.7 fold increase in clinical Under 5 yrs of age, 1.7 fold increase in clinical diseasediseaseMax impact in unstable transmission areasMax impact in unstable transmission areas– Botswana, Namibia, Zimbabwe. South AfricaBotswana, Namibia, Zimbabwe. South Africa– Incidence increased 28% (14-40.7%)Incidence increased 28% (14-40.7%)– Deaths increased 114% (37-188%)Deaths increased 114% (37-188%)
– Emergent Infectious Diseases 2005Emergent Infectious Diseases 2005
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Effect of Malaria on HIVEffect of Malaria on HIV
Reversible increase viral load (2 fold in Reversible increase viral load (2 fold in pregnancy)pregnancy)Malawi- increased neonatal mortality Malawi- increased neonatal mortality (AIDS (AIDS
1999)1999)
Possible reduction in CD4Possible reduction in CD4
No evidence of mother to child No evidence of mother to child transmission increasetransmission increase
Jean Nachega Jean Nachega
Hepatitis BHepatitis B
Worldwide huge burdenWorldwide huge burden– 2 billion people infected2 billion people infected– 400 million chronic infection400 million chronic infection– 500,000 to 1 million deaths annually500,000 to 1 million deaths annually
Chronic hepatitisChronic hepatitis
CirrhosisCirrhosis
Hepatocellular carcinomaHepatocellular carcinoma
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Subsaharan AfricaSubsaharan Africa
Horizontal transmission (Infected older siblings)Horizontal transmission (Infected older siblings)Acquired mainly between 6 months and 5 yrs Acquired mainly between 6 months and 5 yrs Some sexual transmission Some sexual transmission – Most exposed to HBV as children before HIV Most exposed to HBV as children before HIV
exposureexposure
Some perinatal transmission (+ or- HIV)Some perinatal transmission (+ or- HIV)Coinfection with HIV may result inCoinfection with HIV may result in– Reactivation of infection in silent chronic carriersReactivation of infection in silent chronic carriers– New HBV infection as protective immunity lost with New HBV infection as protective immunity lost with
HIVHIV
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
HOWEVERHOWEVER– Botswana our own stats show 40% incidence Botswana our own stats show 40% incidence
of exposure but <1% hepB sAG positiveof exposure but <1% hepB sAG positiveIncreased risk of Haart related hepatotoxicity Increased risk of Haart related hepatotoxicity Increased liver related mortality Increased liver related mortality IDCC no longer screens for this as numbers are so IDCC no longer screens for this as numbers are so small there is no impact on disease management small there is no impact on disease management
– South Africa 2 studies concurSouth Africa 2 studies concur 41-43.3% evidence of previous or current infection 41-43.3% evidence of previous or current infection Liver International 2005;25:201-213Liver International 2005;25:201-213
AIDS Read 2004;14(3):122-137AIDS Read 2004;14(3):122-137
Robert Newton Univ of York UKRobert Newton Univ of York UK
Kaposi SarcomaKaposi Sarcoma
HHSV8 associatedHHSV8 associated– Men more common in WestMen more common in West– Similar prevalence of HHSv8 in M and F in sub saharan AfricaSimilar prevalence of HHSv8 in M and F in sub saharan Africa
Incidence risen in Zimbabwe fromIncidence risen in Zimbabwe from– 2.3/100,000 in males and 0.3/100,000 in females pre HIV2.3/100,000 in males and 0.3/100,000 in females pre HIV– Now 48/100,000 and 18/100,000 in 2001Now 48/100,000 and 18/100,000 in 2001
Incidence risen in Uganda by 20 or 30 times in the last 2 Incidence risen in Uganda by 20 or 30 times in the last 2 decades, 81% HIV+decades, 81% HIV+Incidence increased in South Africa by 2 (??)Incidence increased in South Africa by 2 (??)Women seem to have more aggressive and symptomatic Women seem to have more aggressive and symptomatic disease ?due to increased cytokines. Maybe biological disease ?due to increased cytokines. Maybe biological difference?difference?
Meditz U ZimbabweMeditz U Zimbabwe
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Cervical CancerCervical Cancer
Associated with oncogenic Human Papilloma VirusAssociated with oncogenic Human Papilloma VirusIncreases in Africa across all age groupsIncreases in Africa across all age groups– Uganda, increases predate HIV epidemicUganda, increases predate HIV epidemic
An international Collaboration on HIV and Ca Cervix showed 1.88 An international Collaboration on HIV and Ca Cervix showed 1.88 increased incidence and no change with HAARTincreased incidence and no change with HAARTHIV-infected women more likely than HIV-negative women to be HIV-infected women more likely than HIV-negative women to be coinfected with HPV coinfected with HPV 1
– (58% vs 24%; (58% vs 24%; P P < .01)< .01)HIV infected women more likely to have multiple strains of HPV HIV infected women more likely to have multiple strains of HPV (clearance of HPV affected)(clearance of HPV affected)HIV-infected women more likely to have high-risk HPV infection HIV-infected women more likely to have high-risk HPV infection 1
– (23% vs 14%; (23% vs 14%; P P < .01)< .01)
1 Duerr A, Paramsothy P, Jamieson DJ, et al. 1 Duerr A, Paramsothy P, Jamieson DJ, et al. Effect of HIV infection on atypical squamous cells of undetermined significance. Clin Effect of HIV infection on atypical squamous cells of undetermined significance. Clin Infect Dis. 2006;42:855-861.Infect Dis. 2006;42:855-861.
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Genital HerpesGenital Herpes
Herpes Simplex 2 responsible for Herpes Simplex 2 responsible for recurrent outbreaks of genital herpesrecurrent outbreaks of genital herpesIncreases HIV shedding in HIV+ patientsIncreases HIV shedding in HIV+ patientsIncreases infectiousness of HIV+ and theIncreases infectiousness of HIV+ and the
likelihood of infection in HIV- patient likelihood of infection in HIV- patient exposed to HIV (upregulates mucosal exposed to HIV (upregulates mucosal immune activity)immune activity)HIV increases severity of lesions and HIV increases severity of lesions and durationduration
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Other infectious diseases with Other infectious diseases with differencesdifferences
ToxoplasmosisToxoplasmosis– COMMON opportunistic Infection in the westCOMMON opportunistic Infection in the west– <1% among our HIV patients<1% among our HIV patients
CytomegalovirusCytomegalovirus– Causes devastating disease in very immune Causes devastating disease in very immune
compromised people, may result in blindnesscompromised people, may result in blindness– 50-65% previous exposure in the west50-65% previous exposure in the west– 99.5% Botswana99.5% Botswana
CryptococcusCryptococcus– Very common in our settingVery common in our setting
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Diarrhoea in HIV+ patientsDiarrhoea in HIV+ patients
CryptosporidiumCryptosporidium
MicrosporidiumMicrosporidium
Isospora BelliIsospora Belli
Salmonella, recurrent- not easily clearedSalmonella, recurrent- not easily cleared
As well as all the usual causes of diarrhoeaAs well as all the usual causes of diarrhoea
Botswana has recently had a country wide epidemic of Botswana has recently had a country wide epidemic of Cryptosporidium and enteropathogenic E ColiCryptosporidium and enteropathogenic E Coli
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Where does all this lead to? Where does all this lead to? Where do modellers come in??Where do modellers come in??
We need to be able to INFLUENCE We need to be able to INFLUENCE POLICY- you can help us therePOLICY- you can help us there
We need to be able toWe need to be able to– predict the changing faces of the different predict the changing faces of the different
diseasesdiseases– Evaluate different prevention strategies Evaluate different prevention strategies – Evaluate different treatment interventionsEvaluate different treatment interventions– PrioritisePrioritise
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
We need you forWe need you for
Programme PlanningProgramme Planning– Costs of prevention and testingCosts of prevention and testing– Costs of treatment, both of HIV but other diseasesCosts of treatment, both of HIV but other diseases– Costs of laboratory tests, diagnostic and monitoringCosts of laboratory tests, diagnostic and monitoring– Human resource management, number of health Human resource management, number of health
workers required in different situationsworkers required in different situations– Education of Health Care Workers, costs and Education of Health Care Workers, costs and
personnel neededpersonnel needed– Social programmes necessarySocial programmes necessary
Orphan care, educationOrphan care, educationFeeding programmesFeeding programmes
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
And for the fun things?And for the fun things?
Modelling even paints fitness landscapes Modelling even paints fitness landscapes of individual HIV viruses and enables of individual HIV viruses and enables prediction of resistance mutation patternsprediction of resistance mutation patterns
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
I don’t know what we could do without you! I don’t know what we could do without you! We would be struggling at an individual We would be struggling at an individual level to make an impactlevel to make an impact
You paint the bigger pictureYou paint the bigger picture
With you we can crack this epidemic, you With you we can crack this epidemic, you have already shown the way!have already shown the way!
09/2006 Facing the Challenges of Infecti09/2006 Facing the Challenges of Infectious Diseases in Africa- the Role of Mathous Diseases in Africa- the Role of Mathematical Modellingematical Modelling
Thank You for listeningThank You for listening
Thankyou also to Florence Doualla BellThankyou also to Florence Doualla Bell– Who enabled you not to sit through 90 Who enabled you not to sit through 90
minutes today!!minutes today!!
Sala SintleSala Sintle