A brief introduction to infectious disease epidemiologyinfeksius.com/wp-content/uploads/2017/01/ID_Kuliah-2.pdfA brief introduction to infectious disease epidemiology Mata Kuliah:

A brief introduction to infectious disease epidemiology

Mata Kuliah:Model Matematika Penyakit Infeksi

Panji Fortuna Hadisoemarto, dr, MPH28/9/2015

Outline

• Why study infectious diseases?

• Classification of infectious diseases

• Characteristics of infectious diseases

• Measures of infectious disease transmission

Panji Hadisoemarto, 2015 2

“Most of the infectious diseases have now yielded up their secrets. Many illnesses have been exterminated; others have been brought under control.” (H. Siegerist in 1931)

(Image: Wikipedia)



The plague

• The Justinian plague– 541 AD

– 100 million deaths

• “The Black Death”– 1334

– 30-60% of Europe

• The modern plague– 1860

– 10 million


The quarantine

The trentino law (1377):

(1) that citizens or visitors from plague-endemic areas would not be admitted into Ragusa until they had first remained in isolation for 1 month;

(2) that no person from Ragusa was permitted go to the isolation area, under penalty of remaining there for 30 days;

(3) that persons not assigned by the Great Council to care for those being quarantined were not permitted to bring food to isolated persons, under penalty of remaining with them for 1 month; and

(4) that whoever did not observe these regulations would be fined and subjected to isolation for 1 month.


Smallpox

• Ramses V (c. 1100 BC)

– Reigned for 5 years

– Died in his 30s

– Possible cause of death: Smallpox


Variolation


London cholera outbreak

“The year 1853 saw outbreaks in Newcastle and Gateshead as well as in London, where a total of 10,675 people died of the disease. In the 1854 London epidemic the worst-hit areas at first were Southwark and Lambeth. Soho suffered only a few, seemingly isolated, cases in late August. Then, on the night of the 31st, what Dr Snow later called "the most terrible outbreak of cholera which ever occurred in the kingdom" broke out.

It was as violent as it was sudden. During the next three days, 127 people living in or around Broad Street died. Few families, rich or poor, were spared the loss of at least one member. Within a week, three-quarters of the residents had fled from their homes, leaving their shops shuttered, their houses locked and the streets deserted. Only those who could not afford to leave remained there. It was like the Great Plague all over again.

By 10 September, the number of fatal attacks had reached 500 and the death rate of the St Anne's, Berwick Street and Golden Square subdivisions of the parish had risen to 12.8 per cent --more than double that for the rest of London.“

Summers, Judith. Soho -- A History of London's Most Colourful Neighborhood, Bloomsbury, London, 1989


London cholera outbreak

Snow’s map Broad street pump


(Kass. JID. 1971)


(Armstrong, et al. JAMA. 1999)Panji Hadisoemarto, 2015 12

http://vizhub.healthdata.org/gbd-compare/


http://vizhub.healthdata.org/gbd-compare/

Classifications of ID

• Clinical classification– Diarrheal diseases: secretory, invasive

– Respiratory diseases: upper, lower

– Etc.

• Microbiologic classification– Bacterial: gram +/-

– Viral: DNA/RNA virus

– Parasitic

– Etc.


• Transmission routes classification

– Contact: direct/indirect

– Food-/water-borne

– Airborne

– Vector-borne

– Perinatal

• Reservoir types classification

– Human/animals/soil/water


• For modeling purpose (Anderson&May)

– Micro-parasites: virus, bacteria, protozoa

– Macro-parasites: helmints


Characteristics of ID

• Infectivity: ability to cause infection

• Pathogenicity: ability to cause illness

• Virulence: ability to produce severe illness

• Immunogenicity: ability to induce an immune response

– Complete vs. partial

– Neutralizing vs. non-neutralizing

– Lifelong vs. temporary


Natural history of ID

• Incubation period: exposure to onset of symptoms

• Latent period: exposure to becoming infectious

• Serial interval/generation time: onset of symptoms case 1 to onset of symptoms case 2


Non-infectiveLatent period Infectious period

Incubation period Symptomatic period Non-diseased

Infection

Non-infectiveLatent period Infectious period

Incubation period Symptomatic period Non-diseased

Infection

Serial interval

Case 1

Case 2


Infectious Disease Mean Incubation period Mean Latent period Mean Infectious period

Measles 10 7 7

Mumps 19 15 6

Pertussis 8 22 8

Rubella 18 9 11

Diptheria 3 15 3

Chicken pox 15 10 11

Hepatitis B 50 14 20

Poliomyelitis 9 2 2

Influenza 2 2 3

Smallpox 12 9 2

Scarlet fever 2 1 18

Source: Professor Megan Murray’s lecture slide


(Nelson & Williams. 2014. p26)


Measures of ID transmission

• Prevalence: proportion of population infected at a given time (%)

• Incidence: new cases among population at risk during a time period (person-time-1), such that

Prevalence = Incidence x Duration

• Attack rate: proportion of cases among all susceptible

• Secondary attack rate: proportion of infected among all susceptibles in contact with a primary case


• Reproductive number: average number of successful transmission per infectious person

• Basic reproductive number (R0): reproductive number if case is introduced in a completely susceptible population

• Net/effective reproductive number (Rn or Re): reproductive number in partially immune population


t t+1 t+2

R0=4


R0 and immunization

Re is always smaller than R0, such that

Re = R0 x s,

where s is proportion of susceptible.

If,

R > 1 epidemic

R = 1 endemic

R < 1 disease dies out, then


The critical threshold of proportion susceptible:

s = 1/R0

Hence, proportion to immunize:

HIT = 1 – s

= 1 – 1/R0

= R0 – 1 R0


Disease

Measles

Diphteria

Smallpox

HIV

SARS

Influenza0

0.2

0.4

0.6

0.8

1

0 5 10P

rop

ort

ion

to

imm

un

ize

Basic reproductive number

R0

12 – 18

6 – 7

5 – 7

2 – 5

2 – 5

2 – 3


Documents

A brief introduction to infectious disease epidemiologyinfeksius.com/wp-content/uploads/2017/01/ID_Kuliah-2.pdfA brief introduction to infectious disease epidemiology Mata Kuliah: