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Infectious Disease Epidemiology
EPIET Introductory Course, 2006Lazareto, Menorca
Prepared by: Mike Catchpole, Johan Giesecke, John Edmunds, Bernadette Gergonne
Epidemiology: Why Bother?
Human disease does not occur at random
Epidemiology leads to the identification of causal and preventive factors in human disease
-1500 -1000 -500 0 500 1000 1500
Respiratory infections
Hepatitis
Meningitis
Childhood cluster*
Diarrhoeal disease
HIV
STDs (excluding HIV)
Tuberculosis
Thousands of DALYS lost
Women Men
Burden of disease in adult men and women, Established Market
Economies: 1990
Source: World Bank
*Pertussis, polio, measles and tetanus
Epidemiology: basic concepts
The study of the distribution and determinants of disease frequency in (human) populations
• Frequency • Distribution• Determinants
What is special about infectious disease epidemiology?
Specific concepts
Attack rate, immunity, vector, transmission, carrier, subclinical disease, serial interval, index case, source, exposure, reservoir, incubation period, colonization, generations, susceptible, non-specific immunity, clone, resistance, repeat episodes …
But why do we need these concepts?
Infectious disease: the unique factor
Infectious diseases can be spread from human to human
(or animal to human)
Chain of Transmission
Portal of exit
Portal of entry
Agent
Susceptible Host
Mode of transmission
ReservoirPerson to person transmission
Chain of transmission
Reservoir
Human
Person with symptomatic illness
Carriers:
Asymptomatic
Incubating
Convalescent
Chronic
Animal: zoonosis
Environmental: soil, plant, water
Chain of transmission
Direct
Direct contact
Secretions, Blood, Faeces/urine
Droplet spread
Indirect
Food/water
Aerosol
Animal vectors
Fomites
Medical devices and treatments
Mode of Transmission
Chain of transmission
Human/animal
Respiratory tract
Genito-Urinary tract
Faeces
Saliva
Skin (exanthema, cuts, needles, blood-sucking arthropods)
Conjunctival secretions
Placenta
Environmental
Cooling towers
Portal of exit
Respiratory tract
Mouth (faecal-oral transmission)
Skin
Mucous membranes
Blood
Portal of entry
Chain of transmission
Level of disease occurence
Sporadic level: occasional cases occurring at irregular intervals
Endemic level: persistent occurrence with a low to moderate level
Hyperendemic level: persistently high level of occurrence
Epidemic or outbreak: occurrence clearly in excess of the expected level for a given time period
Pandemic: epidemic spread over several countries or continents, affecting a large number of people
What causes incidence to increase?
Portal of exit
Portal of entry
Agent
Susceptible Host
Mode of transmission
Reservoir
Why does an epidemic occur ?
Agent and host in adequate number
Recent increase in amount of the agent
Recent increase in infectivity / virulence of the agent
Recent introduction of the agent
Enhanced mode of transmission
Increase of host exposure
Change in the susceptibility of the host response to the agent
Introduction through new portals of entry
Host
Agent Environment
Factors influencing disease transmission
Agent
Host
Environment
• Age
• Sex
• Genotype
• Behaviour
• Nutritional status
• Health status
• Infectivity
• Pathogenicity
• Virulence
• Immunogenicity
• Antigenic stability
• Survival
• Weather
• Housing
• Geography
• Occupational setting
• Air quality
• Food
Factors influencing disease transmission
Infectious Disease Epidemiology: five major differences
1. A case can also be an exposure
2. Sub-clinical infections influence epidemiology
3. Contact patterns play major role
4. Immunity
5. There is sometimes a need for urgency
1. Case = exposure
Unique to infectious disease epidemiology.
Usually, the sets of exposures and outcomes are completely apart e.g. smoking and cancer.
The average number of cases an infectious individual will generate
Dependent on 4 factors:
1) The number of contacts made (c)
2) The probability of infection given contact (p)
3) The duration of infectiousness (D)
4) The proportion of contacts who are susceptible (S)
The basic reproduction number, R0
Useful summary statistic
Definition: the average number of secondary cases a typical infectious individual will cause in a completely susceptible population
Measure of the intrinsic potential for an infectious agent to spread
The basic reproduction number, R0
If everyone is susceptible then the average number of secondary infections generated by a single infectious individual is given by:
R0 = p x c x D
Can be estimated if we know p, c, & D, or from proportion susceptible, outbreaks in susceptible populations, the average age at infection (and many other ways)
R0, threshold for invasion
If R0 < 1 then infection cannot invade a population
implications: infection control mechanisms unnecessary (therefore not cost-effective)
If R0 > 1 then (on average) the pathogen will invade that population
implications: control measure necessary to prevent (delay) an epidemic
After invasion: the effective reproduction number, R(t)
As pathogen invades, the number of susceptibles declines through recovery (or death)
Eventually, insufficient susceptibles to maintain chains of transmission
On average each infectious person infects < 1 other, epidemic dies out
Initial invasion, R(t) = R0
Peak of epidemic R(t) = 1
Changes to R(t), over an epidemic
0
200
400
600
800
1000
1200
0 0,05 0,1 0,15 0,2
time
nu
mb
er
Susceptible
Incident cases
Recovered
R=R0
R>1
R=1
R<1
Determinants of STI incidence
R0 = p c D
p Risk of transmission
c Rate of sexual partner change
D Duration of infectivity
STI Control Strategies
R0 = p c D
p condoms, acyclovir, zidovudine
c health education, negotiating skills
D case ascertainment (screening,partner notification), treatment, compliance, health seeking
behaviour, accessibility of services
Cases of Gonorrhoea and Genital Herpes seen in STI clinics in England, 1971-1999
0
20000
40000
60000
80000
Year
Num
ber
of C
ases
Genital Herpes
Gonorrhoea
Determinants of STD incidence
cT = 1 pD
cT Critical threshold for maintenance
pRisk of transmission
D Duration of infectivity
Sexual partners in last 12 months*
0
0,05
0,1
0,15
0,2
0,25
0,3
0,35
0,4
0 1 2 3 4 5
Number of partners
Pro
port
ion
of p
opul
atio
n
* UK National Study of Sexual Attitudes and Lifestyles
Sexual partners in last 12 months
0
0,05
0,1
0,15
0,2
0,25
0,3
0,35
0,4
0 1 2 3 4 5
Number of partners
Pro
port
ion
of p
opu
latio
n cHerpes cGC
2. Subclinical infections
R0 = p x c x D
A case can be a case without being recognised as a case.
– What do we mean by ´asymptomatic´? – How do recognise these?– What level of infectious risk do they pose?
Asymptomatic Infections
Genital Chlamydia trachomatis infection- 50-70% infected women asymptomatic
Poliomyelitis- 90% asymptomatic or non-specific fever
HIV- majority asymptomatic or non-specific symptoms pre-AIDS
SARS-CoV- ??
Rates of genital chlamydial infection in the general population, UK 2000
0
0,5
1
1,5
2
2,5
3
3,5
18-24 25-34 35-44 All
Age group
Pre
va
len
ce
Men
Women
Adj OR 0.58 (0.18-1.85)Adj OR 0.43 (0.13-1.39)
Adj OR 1.37 (0.47-4.00)Adj OR 0.90 (0.36-2.29)
0
1
2
3
4
5
16-17 18-19 20-24 25-29 30-34 35-39 40-44Age group
Pre
vale
nc
e
Men
Women
Source: Natsal 2000
Undiagnosed HIV Infection Among Men Who Have Sex With Men, STI Clinic Attendees, London 2003
0%
20%
40%
60%
80%
100%
All MSM MSM with STI
Undiagnosed HIVinfectionAnonymously testedfor HIV
3. Contact patterns
R0 = p x c x D
Do all cases contribute equally to the spread of disease?
How can we identify and control 'super spreaders'?
SARS, Inner Mongolia
Meng 157
Tongs
Vis 283 Vis 242 Pt 168 Rel 164 Rel 160 Rel 161 Rel 165 HCW 241
Acq 285 Acq 88 HCW 78 Vis 284 Rel 243 HCW 100 HCW 245
Acq 176 Vis 238 Rel 98 Rel 75 Rel 259 Rel 85
Thoracic Hospital
HCW 183 HCW 175 HCW 84 HCW 267 HCW 141 HCW 137
Inner Mongolia Hospital
HCW 250 HCW 255
abr-21 abr-24
abr-12abr-12
abr-25
abr-16 abr-25 abr-13abr-12
abr-24
abr-16abr-19abr-11
abr-21
abr-03
abr-18
abr-18
abr-29 abr-30
abr-02abr-01
abr-07
mar-30 mar-31
abr-11abr-16
mar-19
mar-26 mar-27 mar-30
Small world
How big probability that there is a sexual chain between two random people?
'Six degrees of separation'
Do people choose sexual partner at random?
If not, how does this affect epidemiology?
Reported new sexual partners from outside the UK in the past 5 years, by gender and age-group
0
5
10
15
20
25
16-24 25-34 35-44 All agegroups
Age Group
Per
cen
tag
e
Men
Women
Source: Natsal 2000
4. Immunity
R0 = p x c x D
– Can we measure it?
– How can we change it (positively or negatively)?
– Can we predict the consequences of changing immunity?
Vaccination coverage required for elimination
0%
20%
40%
60%
80%
100%
0 2 4 6 8 10 12 14 16 18 20
Basic reproduction number, Ro
Critic
al pro
portio
n, Pc
Pc = 1-1/Ro
rubella measles
Consequences of Changing Immunity
Not always what you might intuitively expect
Proportion of pregnant women susceptible to rubella
Athens, 1975-91
0%
10%
20%
30%
40%
1971-75 1980-81 1984-89 1990-91
Year
% s
usc
epti
ble
Infant vaccination introduced 1975
data from Panagiotopoulos et al, BMJ, 1999
Age distribution of outpatient rubella cases, Athens
0%
10%
20%
30%
40%
0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40+
Age group
Pro
po
rtio
n o
f ca
ses
1986 (n=113)
1993 (n=326)
from Panagiotopoulos et al, BMJ, 1999
Rubella and CRS in Greece, 1993
0
500
1000
1500
2000
2500
3000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Month
Ru
bel
la N
oti
fica
tio
ns
0
1
2
3
4
5
6
7
8
CR
S c
ases
CRS cases
Rubella notifications
5. A need for urgency
R0 = p x c x D
What EPIET is very much about…
Five major differences
1. A case can also be an exposure
2. Sub-clinical infections influence epidemiology
3. Contact patterns play major role
4. Immunity
5. There is sometimes a need for urgency
If you enjoyed this…
Further reading:
McNeill, WH. Plagues and Peoples
Diamond J. Guns, Germs, and Steel: The fates of human societies.
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