SIR model: swine flu: Difference between revisions
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The SIR model | The SIR model (see also [[Epidemiology: The SIR model]]) tries to predict influenza epidemics. Here, we try to model the spreading of the swine flu. | ||
* According to the [http://www.cdc.gov/ 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>\gamma=1/7=0.1428</math> as the recovery rate. This means, on average an infected person sheds the virus for 7 days. | * According to the [http://www.cdc.gov/ 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>\gamma=1/7=0.1428</math> as the recovery rate. This means, on average an infected person sheds the virus for 7 days. | ||
* In [http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2715422 Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)] the authors estimate the reproduction rate <math>R_0</math> of the virus to be about <math>2</math>. For the SIR model this means: the reproduction rate <math>R_0</math> for influenza is equal to the infection rate of the strain (<math>\beta</math>) multiplied by the duration of the infectious period (<math>1/\gamma</math>), i.e. | * In [http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2715422 Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)] the authors estimate the reproduction rate <math>R_0</math> of the virus to be about <math>2</math>. For the SIR model this means: the reproduction rate <math>R_0</math> for influenza is equal to the infection rate of the strain (<math>\beta</math>) multiplied by the duration of the infectious period (<math>1/\gamma</math>), i.e. | ||
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</jsxgraph> | </jsxgraph> | ||
===External links=== | |||
* [http://www.cdc.gov/flu/professionals/acip/clinical.htm Clinical Signs and Symptoms of Influenza] | |||
* [http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2715422 Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)] | |||
* [http://www.newscientist.com/article/dn17109-first-analysis-of-swine-flu-spread-supports-pandemic-plan.html First analysis of swine flu spread supports pandemic plan] | |||
===The underlying JavaScript code=== | |||
<source lang="xml"> | |||
<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> | |||
</html> | |||
<jsxgraph width="700" height="500"> | |||
var brd = JXG.JSXGraph.initBoard('jxgbox', {originX: 20, originY: 300, unitX: 3, unitY: 250, axis:true}); | |||
var S = brd.createElement('turtle',[],{strokeColor:'blue',strokeWidth:3}); | |||
var I = brd.createElement('turtle',[],{strokeColor:'red',strokeWidth:3}); | |||
var R = brd.createElement('turtle',[],{strokeColor:'green',strokeWidth:3}); | |||
var s = brd.createElement('slider', [[0,-0.3], [60,-0.3],[0,1E-6,1]], {name:'s'}); | |||
brd.createElement('text', [120,-0.3, "initially infected population rate"]); | |||
var beta = brd.createElement('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'β'}); | |||
brd.createElement('text', [90,-0.4, "β: infection rate"]); | |||
var gamma = brd.createElement('slider', [[0,-0.5], [60,-0.5],[0,0.1428,1]], {name:'γ'}); | |||
brd.createElement('text', [90,-0.5, "γ: recovery rate = 1/(days of infection)"]); | |||
var t = 0; // global | |||
brd.createElement('text', [90,-0.2, | |||
function() {return "Day "+t+": infected="+brd.round(1000000*I.Y(),1)+" recovered="+brd.round(1000000*R.Y(),1);}]); | |||
S.hideTurtle(); | |||
I.hideTurtle(); | |||
R.hideTurtle(); | |||
function clearturtle() { | |||
S.cs(); | |||
I.cs(); | |||
R.cs(); | |||
S.hideTurtle(); | |||
I.hideTurtle(); | |||
R.hideTurtle(); | |||
} | |||
function run() { | |||
S.setPos(0,1.0-s.Value()); | |||
R.setPos(0,0); | |||
I.setPos(0,s.Value()); | |||
delta = 1; // global | |||
t = 0; // global | |||
loop(); | |||
} | |||
function turtleMove(turtle,dx,dy) { | |||
turtle.moveTo([dx+turtle.X(),dy+turtle.Y()]); | |||
} | |||
function loop() { | |||
var dS = -beta.Value()*S.Y()*I.Y(); | |||
var dR = gamma.Value()*I.Y(); | |||
var dI = -(dS+dR); | |||
turtleMove(S,delta,dS); | |||
turtleMove(R,delta,dR); | |||
turtleMove(I,delta,dI); | |||
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 { | |||
run(); | |||
} | |||
} | |||
</jsxgraph> | |||
</source> | |||
[[Category:Examples]] | |||
[[Category:Turtle graphics]] |
Revision as of 11:37, 10 August 2009
The SIR model (see also Epidemiology: The SIR model) tries to predict influenza epidemics. Here, we try to model the spreading of the 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 the :[math]\displaystyle{ \beta = 2\cdot 1/7 = 0.2857 }[/math]
- 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
- Clinical Signs and Symptoms of Influenza
- Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)
- First analysis of swine flu spread supports pandemic plan
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>
</html>
<jsxgraph width="700" height="500">
var brd = JXG.JSXGraph.initBoard('jxgbox', {originX: 20, originY: 300, unitX: 3, unitY: 250, axis:true});
var S = brd.createElement('turtle',[],{strokeColor:'blue',strokeWidth:3});
var I = brd.createElement('turtle',[],{strokeColor:'red',strokeWidth:3});
var R = brd.createElement('turtle',[],{strokeColor:'green',strokeWidth:3});
var s = brd.createElement('slider', [[0,-0.3], [60,-0.3],[0,1E-6,1]], {name:'s'});
brd.createElement('text', [120,-0.3, "initially infected population rate"]);
var beta = brd.createElement('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'β'});
brd.createElement('text', [90,-0.4, "β: infection rate"]);
var gamma = brd.createElement('slider', [[0,-0.5], [60,-0.5],[0,0.1428,1]], {name:'γ'});
brd.createElement('text', [90,-0.5, "γ: recovery rate = 1/(days of infection)"]);
var t = 0; // global
brd.createElement('text', [90,-0.2,
function() {return "Day "+t+": infected="+brd.round(1000000*I.Y(),1)+" recovered="+brd.round(1000000*R.Y(),1);}]);
S.hideTurtle();
I.hideTurtle();
R.hideTurtle();
function clearturtle() {
S.cs();
I.cs();
R.cs();
S.hideTurtle();
I.hideTurtle();
R.hideTurtle();
}
function run() {
S.setPos(0,1.0-s.Value());
R.setPos(0,0);
I.setPos(0,s.Value());
delta = 1; // global
t = 0; // global
loop();
}
function turtleMove(turtle,dx,dy) {
turtle.moveTo([dx+turtle.X(),dy+turtle.Y()]);
}
function loop() {
var dS = -beta.Value()*S.Y()*I.Y();
var dR = gamma.Value()*I.Y();
var dI = -(dS+dR);
turtleMove(S,delta,dS);
turtleMove(R,delta,dR);
turtleMove(I,delta,dI);
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 {
run();
}
}
</jsxgraph>