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Kermack &
McKendrick
Epidemic Threshold
Theorem
- BY
SMRUTI MOKAL
MSC. BIOSTATISTICS AND DEMOGRAPHY
IIPS, MUMBAI.
SOURCES
 A generalization of the Kermack and McKendrick deterministic
epidemic model- Capasso and Serio, mathematical
biosciences 1978.
 Wolfram Mathworld
 The mathematics of infectious diseases – Lenka Bubniakova
Some History…
 McKendrick was a physician commissioned by the English
Army to India.
 McKendrick became involved with in the study of epidemic
diseases using mathematical models through the direct
encouragement of Sir Ronald Ross who was also a physician.
 His simple epidemic model was published in a joint paper with
Kermack (Kermack and McKendrick, 1927).
 It involved the study of the transmission dynamics of a
communicable disease that provide permanent immunity
after recovery.
 Their model was used to study single epizootic outbreaks.
 Their mathematical work led to the first widely recognized
threshold theorem in epidemiology.
 It was proposed to explain the rapid rise and fall in the
number of infected patients observed in epidemics such as
the plague (London 1665-1666, Bombay 1906) and cholera
(London 1865).
The Kermack-McKendrick model is an SIR Model for the number
of people infected with a contagious illness in a closed
population over time.
Assumptions
 The population size is fixed (i.e., no births, deaths due to
disease, or deaths by natural causes).
 Incubation period of the infectious agent is instantaneous.
 Duration of infectivity is same as length of the disease
 A completely homogeneous population with no age, spatial,
or social structure.
This simple model is formulated for a population of N being divided into
three dis-joint subpopulation– the susceptible class S, the infective Class I
and the Removed class R.
The model consists of a system of ordinary differential equations-
𝑑𝑆
𝑑𝑡
= -βSI …(1)
𝑑𝑅
𝑑𝑡
= γI …(2)
But since N= S+I+R,
𝑑𝑆
𝑑𝑡
+
𝑑𝑅
𝑑𝑡
+
𝑑𝐼
𝑑𝑡
= 0
Therefore,
𝑑𝐼
𝑑𝑡
= βSI – γI …(3)
β is the infection rate
γ is the recovery rate
The key value governing these equations is the so called
epidemiological threshold,
R0 = βS/γ
The quantity R0 defined above is referred to as the basic
reproduction number of the SIR model, accounting for the
average number of new infections that a single infectious
individual can cause during the infection life time.
(i) When R0 = βS/γ <1, there is no outbreak of the disease in the
sense that the population of the infectious class decreases
monotonically to 0.
(ii) When R0 = βS/γ >1, there will be a single outbreak of the
disease in the sense that firstly increases monotonically
to a maximum value, and after that, decreases monotonically to
0.
 From the summary of the model, we know that the disease
dynamics of this model is very clear: the disease either dies
out quickly without causing new infectious, or experiences a
single outbreak before dying out.
 This model does not include demographic structure and is
suitable for describing those diseases that suddenly develop
in a community and then disappear without infecting the
entire community.
THANK YOU

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kermack &amp; mc kendrick epidemic threshold theorem

  • 1. Kermack & McKendrick Epidemic Threshold Theorem - BY SMRUTI MOKAL MSC. BIOSTATISTICS AND DEMOGRAPHY IIPS, MUMBAI.
  • 2. SOURCES  A generalization of the Kermack and McKendrick deterministic epidemic model- Capasso and Serio, mathematical biosciences 1978.  Wolfram Mathworld  The mathematics of infectious diseases – Lenka Bubniakova
  • 3. Some History…  McKendrick was a physician commissioned by the English Army to India.  McKendrick became involved with in the study of epidemic diseases using mathematical models through the direct encouragement of Sir Ronald Ross who was also a physician.  His simple epidemic model was published in a joint paper with Kermack (Kermack and McKendrick, 1927).
  • 4.  It involved the study of the transmission dynamics of a communicable disease that provide permanent immunity after recovery.  Their model was used to study single epizootic outbreaks.  Their mathematical work led to the first widely recognized threshold theorem in epidemiology.  It was proposed to explain the rapid rise and fall in the number of infected patients observed in epidemics such as the plague (London 1665-1666, Bombay 1906) and cholera (London 1865).
  • 5. The Kermack-McKendrick model is an SIR Model for the number of people infected with a contagious illness in a closed population over time.
  • 6. Assumptions  The population size is fixed (i.e., no births, deaths due to disease, or deaths by natural causes).  Incubation period of the infectious agent is instantaneous.  Duration of infectivity is same as length of the disease  A completely homogeneous population with no age, spatial, or social structure.
  • 7. This simple model is formulated for a population of N being divided into three dis-joint subpopulation– the susceptible class S, the infective Class I and the Removed class R. The model consists of a system of ordinary differential equations- 𝑑𝑆 𝑑𝑡 = -βSI …(1) 𝑑𝑅 𝑑𝑡 = γI …(2) But since N= S+I+R, 𝑑𝑆 𝑑𝑡 + 𝑑𝑅 𝑑𝑡 + 𝑑𝐼 𝑑𝑡 = 0 Therefore, 𝑑𝐼 𝑑𝑡 = βSI – γI …(3) β is the infection rate γ is the recovery rate
  • 8. The key value governing these equations is the so called epidemiological threshold, R0 = βS/γ The quantity R0 defined above is referred to as the basic reproduction number of the SIR model, accounting for the average number of new infections that a single infectious individual can cause during the infection life time.
  • 9. (i) When R0 = βS/γ <1, there is no outbreak of the disease in the sense that the population of the infectious class decreases monotonically to 0. (ii) When R0 = βS/γ >1, there will be a single outbreak of the disease in the sense that firstly increases monotonically to a maximum value, and after that, decreases monotonically to 0.
  • 10.  From the summary of the model, we know that the disease dynamics of this model is very clear: the disease either dies out quickly without causing new infectious, or experiences a single outbreak before dying out.  This model does not include demographic structure and is suitable for describing those diseases that suddenly develop in a community and then disappear without infecting the entire community.
  • 11.
  • 12.