SIR model: swine flu

From JSXGraph Wiki

The SIR model (see also Epidemiology: The SIR model) tries to predict influenza epidemics. Here, we try to model the spreading of the H1N1 virus, aka swine flu.

  • According to the CDC Centers of Disease Control and Prevention: "Adults shed influenza virus from the day before symptoms begin through 5-10 days after illness onset. However, the amount of virus shed, and presumably infectivity, decreases rapidly by 3-5 days after onset in an experimental human infection model." So, here we set [math]\displaystyle{ \gamma=1/7=0.1428 }[/math] as the recovery rate. This means, on average an infected person sheds the virus for 7 days.
  • In Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1) the authors estimate the reproduction rate [math]\displaystyle{ R_0 }[/math] of the virus to be about [math]\displaystyle{ 2 }[/math]. For the SIR model this means: the reproduction rate [math]\displaystyle{ R_0 }[/math] for influenza is equal to the infection rate of the strain ([math]\displaystyle{ \beta }[/math]) multiplied by the duration of the infectious period ([math]\displaystyle{ 1/\gamma }[/math]), i.e.
[math]\displaystyle{ \beta = R_0\cdot \gamma }[/math]. Therefore, we set [math]\displaystyle{ \beta = 2\cdot 1/7 = 0.2857. }[/math] For the 1918–1919 pandemic [math]\displaystyle{ R_0 }[/math] is estimated to be between 2 and 3, whereas for the seasonal flu the range for [math]\displaystyle{ R_0 }[/math] is 0.9 to 2.1.
  • In [1] the mortality is estimated to be approximately 0.4 per cent.
  • We run the simulation for a population of 1 million people, where 1 person is infected initially, i.e. [math]\displaystyle{ s=1E{-6} }[/math]. Thus, S(0) = 1, I(0) = 1.E-6, R(0) = 0.

The lines in the JSXGraph-simulation below have the following meaning:

* Blue: Rate of susceptible population
* Red: Rate of infected population
* Green: Rate of recovered population

External links

The underlying JavaScript code

<form><input type="button" value="clear and run a simulation of 200 days" onClick="clearturtle();run()">
<input type="button" value="stop" onClick="stop()">
<input type="button" value="continue" onClick="goOn()"></form>
var brd = JXG.JSXGraph.initBoard('jxgbox', {boundingbox: [-6.66, 1.2, 226.66, -0.8], axis:true});
var S = brd.create('turtle',[],{strokeColor:'blue',strokeWidth:3});
var I = brd.create('turtle',[],{strokeColor:'red',strokeWidth:3});
var R = brd.create('turtle',[],{strokeColor:'green',strokeWidth:3});
var s = brd.create('slider', [[0,-0.3], [60,-0.3],[0,1E-6,1]], {name:'s'});
var beta = brd.create('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'&beta;'});
var gamma = brd.create('slider', [[0,-0.5], [60,-0.5],[0,0.1428,0.5]], {name:'&gamma;'});
var mort = brd.create('slider', [[0,-0.6], [60,-0.6],[0,0.4,10.0]], {name:'% mortality'});
brd.create('text', [90,-0.3, "initially infected population rate"]);
brd.create('text', [90,-0.4, function(){ return "&beta;: infection rate, R<sub>0</sub>="+(beta.Value()/gamma.Value()).toFixed(2);}]);
brd.create('text', [90,-0.5, function(){ return "&gamma;: recovery rate = 1/(days of infection), days of infection= "+(1/gamma.Value()).toFixed(1);}]);
var t = 0; // global
brd.create('text', [100,-0.2, 
        function() {return "Day "+t+
                           ": infected="+(1000000*I.Y()).toFixed(1)+
                           " recovered="+(1000000*R.Y()).toFixed(1)+
                           " dead="+(1000000*R.Y()*mort.Value()*0.01).toFixed(0);}]);
function clearturtle() {
function run() {
  delta = 1; // global
  t = 0;  // global
function turtleMove(turtle,dx,dy) {
function loop() {
  var dS = -beta.Value()*S.Y()*I.Y();
  var dR = gamma.Value()*I.Y();
  var dI = -(dS+dR);
  t += delta;
  if (t<200.0) {
    active = setTimeout(loop,10);
function stop() {
  if (active) clearTimeout(active);
  active = null;
function goOn() {
   if (t>0) {
     if (active==null) {
       active = setTimeout(loop,10);
   } else {