Subsection 11.2.1 Epidemics, The SIR Model
The SIR Model is a fairly simple model that is frequently used to understand the spread of an infectious disease through a population. As with any mathematical model, it is over–simplified but, just like
IVP (11.1), it provides a foundation which can be tweaked as needed for better predictions.
We will assume that every member the population falls into one of three categories: (S)usceptible, (I)nfected, or (R)ecovered. We assume that any population member who has recovered from the disease is immune to it, and those that have not are susceptible to infection.
We let
\begin{align*}
S\amp =S(t)=\text{ The fraction of the population
susceptible to infection.}\\
I\amp =I(t)=\text{ The fraction of the population
currently infected.}\\
R\amp =R(t)=\text{ The fraction of the population no longer
susceptible to infection. }
\end{align*}
Note that \(R(t)\) includes those victims who have died.
Drill 11.2.1.
Assuming that no members are entering or leaving the population (by births, deaths from other diseases, or migration), explain why
\begin{equation*}
S+I+R=1.
\end{equation*}
Since the disease spreads by contact between a susceptible and an infected individual, we will assume that the number of susceptible population members is decreasing (you cannot get the disease twice) and the rate of decrease is proportional to the number of susceptible and the number of infected currently present. This says that
\begin{equation*}
\dfdx{S}{t}=-aSI
\end{equation*}
for some positive constant, \(a\text{.}\) The constant \(a\) is called the transmission rate. (Why?)
Drill 11.2.2.
Explain how we know that \(\dfdx{S}{t}\) must be negative.
Since the only way to become immune is to recover from the disease, we also assume that the rate of change of \(R\) is proportional to the number of infected individuals present. This means that
\begin{equation*}
\dfdx{R}{t}=bI
\end{equation*}
for some positive constant \(b\text{.}\) The constant \(b\) is called the recovery rate. (Why?)
Problem 11.2.3.
(a)
Explain how we know that \(\dfdx{R}{t}\) must be positive.
(b)
Show that
\begin{equation*}
\dfdx{I}{t}=(aS-b)I.
\end{equation*}
(c)
Use the information in part (b) to show that the number of infected is increasing when \(S\gt
\frac{b}{a}\) and decreasing when \(S\lt
\frac{b}{a}.\)
(d)
Show that
\begin{equation*}
\dfdxn{I}{t}{2}=a^2I\left[S^2-\left(\frac{2b}{a}+I\right)S+\left(\frac{b}{a}\right)^2\right]
\end{equation*}
and use this to show that \(\dfdxn{I}{t}{2}\lt 0\) when
\begin{equation*}
\frac{b}{a}+\left(\frac{I}{2}-\sqrt{\left(\frac{I}{2}\right)^2+\frac{bI}{a}}\right)\lt S\lt \frac{b}{a}+\left(\frac{I}{2}+\sqrt{\left(\frac{I}{2}\right)^2+\frac{bI}{a}}\right)
\end{equation*}
and is positive otherwise.
Putting this together we see that the number of infected is increasing and accelerating when
\begin{equation*}
\frac{b}{a}+\left(\frac{I}{2}+\sqrt{\left( \frac{I}{2}\right)^2+\frac{bI}{a}}\right)\lt S\lt 1
\end{equation*}
and increasing, but slowing down, when
\begin{equation*}
\frac{b}{a}\lt S\lt \frac{b}{a}+\left(\frac{I}{2}+\sqrt{\left(\frac{I}{2}\right)^2+\frac{bI}{a}}\right).
\end{equation*}
When \(S\lt \frac{b}{a}\) it is decreasing.