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Kermack–McKendrick theory

Kermack–McKendrick theory is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Kermack–McKendrick theory rather than just read about it. In short: Kermack–McKendrick theory is a hypothesis that predicts the number and distribution of cases of an immunizing infectious disease over time as it is transmitted through a population based on characteristics of infectivity and recovery, under a strong-mixing assumption. Building on the research of Ronald Ross and Hilda Hudson, A.

Key takeaways

  • Kermack–McKendrick theory belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Kermack–McKendrick theory to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Kermack–McKendrick theory from memory before moving on to harder problems.

Reference excerpt

Kermack–McKendrick theory is a hypothesis that predicts the number and distribution of cases of an immunizing infectious disease over time as it is transmitted through a population based on characteristics of infectivity and recovery, under a strong-mixing assumption. Building on the research of Ronald Ross and Hilda Hudson, A. G. McKendrick and W. O. Kermack published their theory in a set of three articles from 1927, 1932, and 1933. Kermack–McKendrick theory is one of the sources of the SIR model and other related compartmental models. This theory was the first to explicitly account for the dependence of infection characteristics and transmissibility on the age of infection. Because of their seminal importance to the field of theoretical epidemiology, these articles were republished in the Bulletin of Mathematical Biology in 1991.

Epidemic model (1927) In its initial form, Kermack–McKendrick theory is a partial differential-equation model that structures the infected population in terms of age-of-infection, while using simple compartments for people who are susceptible (S), infected (I), and recovered/removed (R). Specified initial conditions would change over time according to

d S d t = − λ S , {\displaystyle {\frac {dS}{dt}}=-\lambda S,}

∂ i ∂ t + ∂ i ∂ a = δ ( a ) λ S − γ ( a ) i , {\displaystyle {\frac {\partial i}{\partial t}}+{\frac {\partial i}{\partial a}}=\delta (a)\lambda S-\gamma (a)i,}

I ( t ) = ∫ 0 ∞ i ( a , t ) d a , {\displaystyle I(t)=\int _{0}^{\infty }i(a,t)\,da,}

d R d t = ∫ 0 ∞ γ ( a ) i ( a , t ) d a , {\displaystyle {\frac {dR}{dt}}=\int _{0}^{\infty }\gamma (a)i(a,t)\,da,}

where δ ( a ) {\displaystyle \delta (a)} is a Dirac delta-function and the infection pressure

λ = ∫ 0 ∞ β ( a ) i ( a , t ) d a . {\displaystyle \lambda =\int _{0}^{\infty }\beta (a)i(a,t)\,da.}

This formulation is equivalent to defining the incidence of infection i ( t , 0 ) = λ S {\displaystyle i(t,0)=\lambda S} . Only in the special case when the removal rate γ ( a ) {\displaystyle \gamma (a)} and the transmission rate β ( a ) {\displaystyle \beta (a)} are constant for all ages can the epidemic dynamics be expressed in terms of the prevalence I ( t ) {\displaystyle I(t)} , leading to the standard compartmental SIR model. This model only accounts for infection and removal events, which are sufficient to describe a simple epidemic, including the threshold condition necessary for an epidemic to start, but can not explain endemic disease transmission or recurring epidemics.

Endemic disease (1932, 1933) In their subsequent articles, Kermack and McKendrick extended their theory to allow for birth, migration, and death, as well as imperfect immunity. In modern notation, their model can be represented as

d S d t = b 0 + b S S + b I I + b R R − λ S − m S S , {\displaystyle {\frac {dS}{dt}}=b_{0}+b_{S}S+b_{I}I+b_{R}R-\lambda S-m_{S}S,}

∂ i ∂ t + ∂ i ∂ a = δ ( a ) λ ( S + σ R ) − γ ( a ) i − μ ( a ) i − m i ( a ) i , {\displaystyle {\frac {\partial i}{\partial t}}+{\frac {\partial i}{\partial a}}=\delta (a)\lambda (S+\sigma R)-\gamma (a)i-\mu (a)i-m_{i}(a)i,}

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Kermack–McKendrick theory

Start with the simplest possible case. Write down what Kermack–McKendrick theory claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Kermack–McKendrick theory before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Kermack–McKendrick theory ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Kermack–McKendrick theory

In research
Kermack–McKendrick theory appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Kermack–McKendrick theory in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Kermack–McKendrick theory is common in secondary-school and first-year university syllabi. It links to neighbouring topics Differential equations, Epidemiology, Mathematics in medicine, so understanding it makes those chapters shorter.
In everyday life
Look for Kermack–McKendrick theory outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Kermack–McKendrick theory in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Kermack–McKendrick theory means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Kermack–McKendrick theory out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Kermack–McKendrick theory in simple terms?

Kermack–McKendrick theory is a hypothesis that predicts the number and distribution of cases of an immunizing infectious disease over time as it is transmitted through a population based on characteristics of infectivity and recovery, under a strong-mixing assumption. Building on the research of Ro…

Why does Kermack–McKendrick theory matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Kermack–McKendrick theory?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Kermack–McKendrick theory.

Tags

  • Differential equations
  • Epidemiology
  • Mathematics in medicine

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