SIR model: swine flu - Revision history

Michael at 12:46, 8 June 2011

2011-06-08T12:46:41Z

Michael at 12:45, 8 June 2011

2011-06-08T12:45:37Z

← Older revision		Revision as of 12:45, 8 June 2011
Line 15:		Line 15:
	<input type="button" value="continue" onClick="goOn()"></form>		<input type="button" value="continue" onClick="goOn()"></form>
	</html>		</html>

	<jsxgraph width="700" height="500">		<jsxgraph width="700" height="500">
	var brd = JXG.JSXGraph.initBoard('jxgbox', {~~originX~~: 20, ~~originY: 300~~, ~~unitX: 3~~, ~~unitY: 250~~, axis:true});		var brd = JXG.JSXGraph.initBoard('jxgbox', { boundingbox: [-6.66, 1.2, 226.66, -0.8], axis:true});

	var S = brd.createElement('turtle',[],{strokeColor:'blue',strokeWidth:3});		var S = brd.createElement('turtle',[],{strokeColor:'blue',strokeWidth:3});
Line 108:		Line 109:
	<input type="button" value="continue" onClick="goOn()"></form>		<input type="button" value="continue" onClick="goOn()"></form>
	</html>		</html>
	<~~jsxgraph width~~="~~700" height="500~~">		</source>
	var brd = JXG.JSXGraph.initBoard('jxgbox', {~~originX~~: 20, ~~originY: 300~~, ~~unitX: 3~~, ~~unitY: 250~~, axis:true});
			<source lang="javascript">
			var brd = JXG.JSXGraph.initBoard('jxgbox', {boundingbox: [-6.66, 1.2, 226.66, -0.8], axis:true});

	var S = brd.createElement('turtle',[],{strokeColor:'blue',strokeWidth:3});		var S = brd.createElement('turtle',[],{strokeColor:'blue',strokeWidth:3});
Line 186:		Line 189:

	}		}
	~~</jsxgraph>~~
	</source>		</source>

	[[Category:Examples]]		[[Category:Examples]]
	[[Category:Turtle Graphics]]		[[Category:Turtle Graphics]]

Bianca at 12:36, 26 June 2010

2010-06-26T12:36:15Z

New page

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 [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.
:<math>\beta = R_0\cdot \gamma</math>. Therefore, we set <math>\beta = 2\cdot 1/7 = 0.2857.</math> For the 1918–1919 pandemic <math>R_0</math> is estimated to be between 2 and 3, whereas for the seasonal flu the range for <math>R_0</math> is 0.9 to 2.1.
* In [http://www.newscientist.com/article/dn17109-first-analysis-of-swine-flu-spread-supports-pandemic-plan.html] 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>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:
* <span style="color:Blue">Blue: Rate of susceptible population</span>
* <span style="color:red">Red: Rate of infected population</span>
* <span style="color:green">Green: Rate of recovered population
<html>
<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'});
var beta = brd.createElement('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'β'});
var gamma = brd.createElement('slider', [[0,-0.5], [60,-0.5],[0,0.1428,0.5]], {name:'γ'});
var mort = brd.createElement('slider', [[0,-0.6], [60,-0.6],[0,0.4,10.0]], {name:'% mortality'});
brd.createElement('text', [90,-0.3, "initially infected population rate"]);
brd.createElement('text', [90,-0.4, function(){ return "β: infection rate, R<sub>0</sub>="+(beta.Value()/gamma.Value()).toFixed(2);}]);
brd.createElement('text', [90,-0.5, function(){ return "γ: recovery rate = 1/(days of infection), days of infection= "+(1/gamma.Value()).toFixed(1);}]);

var t = 0; // global

brd.createElement('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);}]);

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>

===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]
* [http://jsxgraph.org JSXGraph Homepage]

===The underlying JavaScript code===
<source lang="xml">
<html>
<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'});
var beta = brd.createElement('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'β'});
var gamma = brd.createElement('slider', [[0,-0.5], [60,-0.5],[0,0.1428,0.5]], {name:'γ'});
var mort = brd.createElement('slider', [[0,-0.6], [60,-0.6],[0,0.4,10.0]], {name:'% mortality'});
brd.createElement('text', [90,-0.3, "initially infected population rate"]);
brd.createElement('text', [90,-0.4, function(){ return "β: infection rate, R<sub>0</sub>="+(beta.Value()/gamma.Value()).toFixed(2);}]);
brd.createElement('text', [90,-0.5, function(){ return "γ: recovery rate = 1/(days of infection), days of infection= "+(1/gamma.Value()).toFixed(1);}]);

var t = 0; // global

brd.createElement('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);}]);

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]]

A WASSERMANN at 12:34, 10 August 2009

2009-08-10T12:34:11Z

← Older revision		Revision as of 12:34, 10 August 2009
Line 1:		Line 1:
	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.		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 [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.

A WASSERMANN at 12:29, 10 August 2009

2009-08-10T12:29:04Z

← Older revision		Revision as of 12:29, 10 August 2009
Line 4:		Line 4:
	:<math>\beta = R_0\cdot \gamma</math>. Therefore, we set <math>\beta = 2\cdot 1/7 = 0.2857.</math> For the 1918–1919 pandemic <math>R_0</math> is estimated to be between 2 and 3, whereas for the seasonal flu the range for <math>R_0</math> is 0.9 to 2.1.		:<math>\beta = R_0\cdot \gamma</math>. Therefore, we set <math>\beta = 2\cdot 1/7 = 0.2857.</math> For the 1918–1919 pandemic <math>R_0</math> is estimated to be between 2 and 3, whereas for the seasonal flu the range for <math>R_0</math> is 0.9 to 2.1.
	* In [http://www.newscientist.com/article/dn17109-first-analysis-of-swine-flu-spread-supports-pandemic-plan.html] the mortality is estimated to be approximately 0.4 per cent.		* In [http://www.newscientist.com/article/dn17109-first-analysis-of-swine-flu-spread-supports-pandemic-plan.html] 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>s=1E{-6}</math>.		* We run the simulation for a population of 1 million people, where 1 person is infected initially, i.e. <math>s=1E{-6}</math>. Thus, S(0) = 1, I(0) = 1.E-6, R(0) = 0.
	Thus, S(0) = 1, I(0) = 1.E-6, R(0) = 0.

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

A WASSERMANN at 12:28, 10 August 2009

2009-08-10T12:28:48Z

← Older revision		Revision as of 12:28, 10 August 2009
Line 3:		Line 3:
	* 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.
	:<math>\beta = R_0\cdot \gamma</math>. Therefore, we set <math>\beta = 2\cdot 1/7 = 0.2857.</math> For the 1918–1919 pandemic <math>R_0</math> is estimated to be between 2 and 3, whereas for the seasonal flu the range for <math>R_0</math> is 0.9 to 2.1.		:<math>\beta = R_0\cdot \gamma</math>. Therefore, we set <math>\beta = 2\cdot 1/7 = 0.2857.</math> For the 1918–1919 pandemic <math>R_0</math> is estimated to be between 2 and 3, whereas for the seasonal flu the range for <math>R_0</math> is 0.9 to 2.1.
			* In [http://www.newscientist.com/article/dn17109-first-analysis-of-swine-flu-spread-supports-pandemic-plan.html] 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>s=1E{-6}</math>.		* We run the simulation for a population of 1 million people, where 1 person is infected initially, i.e. <math>s=1E{-6}</math>.
	Thus S(0) = 1, I(0) = 1.E-6, R(0) = 0.		Thus, S(0) = 1, I(0) = 1.E-6, R(0) = 0.

	~~In [http://www.newscientist.com/article/dn17109-first-analysis-of-swine-flu-spread-supports-pandemic-plan.html] the mortality is estimated to be approximately 0.4 per cent.~~
	The lines in the JSXGraph-simulation below have the following meaning:		The lines in the JSXGraph-simulation below have the following meaning:
	* <span style="color:Blue">Blue: Rate of susceptible population</span>		* <span style="color:Blue">Blue: Rate of susceptible population</span>

A WASSERMANN at 12:28, 10 August 2009

2009-08-10T12:28:01Z

← Older revision		Revision as of 12:28, 10 August 2009
Line 5:		Line 5:
	* We run the simulation for a population of 1 million people, where 1 person is infected initially, i.e. <math>s=1E{-6}</math>.		* We run the simulation for a population of 1 million people, where 1 person is infected initially, i.e. <math>s=1E{-6}</math>.
	Thus S(0) = 1, I(0) = 1.E-6, R(0) = 0.		Thus S(0) = 1, I(0) = 1.E-6, R(0) = 0.

	In [http://www.newscientist.com/article/dn17109-first-analysis-of-swine-flu-spread-supports-pandemic-plan.html] the mortality is estimated to be approximately 0.4 per cent.		In [http://www.newscientist.com/article/dn17109-first-analysis-of-swine-flu-spread-supports-pandemic-plan.html] the mortality is estimated to be approximately 0.4 per cent.
	The lines in the JSXGraph-simulation below have the following meaning:		The lines in the JSXGraph-simulation below have the following meaning:

A WASSERMANN at 12:25, 10 August 2009

2009-08-10T12:25:06Z

A WASSERMANN at 12:23, 10 August 2009

2009-08-10T12:23:51Z

← Older revision		Revision as of 12:23, 10 August 2009
Line 24:		Line 24:
	var s = brd.createElement('slider', [[0,-0.3], [60,-0.3],[0,1E-6,1]], {name:'s'});		var s = brd.createElement('slider', [[0,-0.3], [60,-0.3],[0,1E-6,1]], {name:'s'});
	var beta = brd.createElement('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'β'});		var beta = brd.createElement('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'β'});
	var gamma = brd.createElement('slider', [[0,-0.5], [60,-0.5],[0,0.1428,1]], {name:'γ'});		var gamma = brd.createElement('slider', [[0,-0.5], [60,-0.5],[0,0.1428,0.5]], {name:'γ'});
	var mort = brd.createElement('slider', [[0,-0.6], [60,-0.6],[0,0.4,10.0]], {name:'% mortality'});		var mort = brd.createElement('slider', [[0,-0.6], [60,-0.6],[0,0.4,10.0]], {name:'% mortality'});
	brd.createElement('text', [90,-0.3, "initially infected population rate"]);		brd.createElement('text', [90,-0.3, "initially infected population rate"]);

A WASSERMANN at 12:23, 10 August 2009

2009-08-10T12:23:11Z

← Older revision		Revision as of 12:23, 10 August 2009
Line 28:		Line 28:
	brd.createElement('text', [90,-0.3, "initially infected population rate"]);		brd.createElement('text', [90,-0.3, "initially infected population rate"]);
	brd.createElement('text', [90,-0.4, function(){ return "β: infection rate, R<sub>0</sub>="+(beta.Value()/gamma.Value()).toFixed(2);}]);		brd.createElement('text', [90,-0.4, function(){ return "β: infection rate, R<sub>0</sub>="+(beta.Value()/gamma.Value()).toFixed(2);}]);
	brd.createElement('text', [90,-0.5, "γ: recovery rate = 1/(days of infection)"]);		brd.createElement('text', [90,-0.5, function(){ return "γ: recovery rate = 1/(days of infection), days of infection= "+(1/gamma.Value()).toFixed(1);}]);

	var t = 0; // global		var t = 0; // global

← Older revision		Revision as of 12:46, 8 June 2011
Line 19:		Line 19:
	var brd = JXG.JSXGraph.initBoard('jxgbox', { boundingbox: [-6.66, 1.2, 226.66, -0.8], axis:true});		var brd = JXG.JSXGraph.initBoard('jxgbox', { boundingbox: [-6.66, 1.2, 226.66, -0.8], axis:true});

	var S = brd.~~createElement~~('turtle',[],{strokeColor:'blue',strokeWidth:3});		var S = brd.create('turtle',[],{strokeColor:'blue',strokeWidth:3});
	var I = brd.~~createElement~~('turtle',[],{strokeColor:'red',strokeWidth:3});		var I = brd.create('turtle',[],{strokeColor:'red',strokeWidth:3});
	var R = brd.~~createElement~~('turtle',[],{strokeColor:'green',strokeWidth:3});		var R = brd.create('turtle',[],{strokeColor:'green',strokeWidth:3});

	var s = brd.~~createElement~~('slider', [[0,-0.3], [60,-0.3],[0,1E-6,1]], {name:'s'});		var s = brd.create('slider', [[0,-0.3], [60,-0.3],[0,1E-6,1]], {name:'s'});
	var beta = brd.~~createElement~~('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'β'});		var beta = brd.create('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'β'});
	var gamma = brd.~~createElement~~('slider', [[0,-0.5], [60,-0.5],[0,0.1428,0.5]], {name:'γ'});		var gamma = brd.create('slider', [[0,-0.5], [60,-0.5],[0,0.1428,0.5]], {name:'γ'});
	var mort = brd.~~createElement~~('slider', [[0,-0.6], [60,-0.6],[0,0.4,10.0]], {name:'% mortality'});		var mort = brd.create('slider', [[0,-0.6], [60,-0.6],[0,0.4,10.0]], {name:'% mortality'});
	brd.~~createElement~~('text', [90,-0.3, "initially infected population rate"]);		brd.create('text', [90,-0.3, "initially infected population rate"]);
	brd.~~createElement~~('text', [90,-0.4, function(){ return "β: infection rate, R<sub>0</sub>="+(beta.Value()/gamma.Value()).toFixed(2);}]);		brd.create('text', [90,-0.4, function(){ return "β: infection rate, R<sub>0</sub>="+(beta.Value()/gamma.Value()).toFixed(2);}]);
	brd.~~createElement~~('text', [90,-0.5, function(){ return "γ: recovery rate = 1/(days of infection), days of infection= "+(1/gamma.Value()).toFixed(1);}]);		brd.create('text', [90,-0.5, function(){ return "γ: recovery rate = 1/(days of infection), days of infection= "+(1/gamma.Value()).toFixed(1);}]);

	var t = 0; // global		var t = 0; // global

	brd.~~createElement~~('text', [100,-0.2,		brd.create('text', [100,-0.2,
	function() {return "Day "+t+		function() {return "Day "+t+
	": infected="+(1000000*I.Y()).toFixed(1)+		": infected="+(1000000*I.Y()).toFixed(1)+
Line 114:		Line 114:
	var brd = JXG.JSXGraph.initBoard('jxgbox', {boundingbox: [-6.66, 1.2, 226.66, -0.8], axis:true});		var brd = JXG.JSXGraph.initBoard('jxgbox', {boundingbox: [-6.66, 1.2, 226.66, -0.8], axis:true});

	var S = brd.~~createElement~~('turtle',[],{strokeColor:'blue',strokeWidth:3});		var S = brd.create('turtle',[],{strokeColor:'blue',strokeWidth:3});
	var I = brd.~~createElement~~('turtle',[],{strokeColor:'red',strokeWidth:3});		var I = brd.create('turtle',[],{strokeColor:'red',strokeWidth:3});
	var R = brd.~~createElement~~('turtle',[],{strokeColor:'green',strokeWidth:3});		var R = brd.create('turtle',[],{strokeColor:'green',strokeWidth:3});

	var s = brd.~~createElement~~('slider', [[0,-0.3], [60,-0.3],[0,1E-6,1]], {name:'s'});		var s = brd.create('slider', [[0,-0.3], [60,-0.3],[0,1E-6,1]], {name:'s'});
	var beta = brd.~~createElement~~('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'β'});		var beta = brd.create('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'β'});
	var gamma = brd.~~createElement~~('slider', [[0,-0.5], [60,-0.5],[0,0.1428,0.5]], {name:'γ'});		var gamma = brd.create('slider', [[0,-0.5], [60,-0.5],[0,0.1428,0.5]], {name:'γ'});
	var mort = brd.~~createElement~~('slider', [[0,-0.6], [60,-0.6],[0,0.4,10.0]], {name:'% mortality'});		var mort = brd.create('slider', [[0,-0.6], [60,-0.6],[0,0.4,10.0]], {name:'% mortality'});
	brd.~~createElement~~('text', [90,-0.3, "initially infected population rate"]);		brd.create('text', [90,-0.3, "initially infected population rate"]);
	brd.~~createElement~~('text', [90,-0.4, function(){ return "β: infection rate, R<sub>0</sub>="+(beta.Value()/gamma.Value()).toFixed(2);}]);		brd.create('text', [90,-0.4, function(){ return "β: infection rate, R<sub>0</sub>="+(beta.Value()/gamma.Value()).toFixed(2);}]);
	brd.~~createElement~~('text', [90,-0.5, function(){ return "γ: recovery rate = 1/(days of infection), days of infection= "+(1/gamma.Value()).toFixed(1);}]);		brd.create('text', [90,-0.5, function(){ return "γ: recovery rate = 1/(days of infection), days of infection= "+(1/gamma.Value()).toFixed(1);}]);

	var t = 0; // global		var t = 0; // global

	brd.~~createElement~~('text', [100,-0.2,		brd.create('text', [100,-0.2,
	function() {return "Day "+t+		function() {return "Day "+t+
	": infected="+(1000000*I.Y()).toFixed(1)+		": infected="+(1000000*I.Y()).toFixed(1)+

← Older revision		Revision as of 12:25, 10 August 2009
Line 99:		Line 99:
	* [http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2715422 Modeling influenza epidemics and pandemics: insights into the future of swine flu (H1N1)]		* [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]		* [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]
			* [http://jsxgraph.org JSXGraph Homepage]

	===The underlying JavaScript code===		===The underlying JavaScript code===
Line 116:		Line 117:
	var s = brd.createElement('slider', [[0,-0.3], [60,-0.3],[0,1E-6,1]], {name:'s'});		var s = brd.createElement('slider', [[0,-0.3], [60,-0.3],[0,1E-6,1]], {name:'s'});
	var beta = brd.createElement('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'β'});		var beta = brd.createElement('slider', [[0,-0.4], [60,-0.4],[0,0.2857,1]], {name:'β'});
	var gamma = brd.createElement('slider', [[0,-0.5], [60,-0.5],[0,0.1428,1]], {name:'γ'});		var gamma = brd.createElement('slider', [[0,-0.5], [60,-0.5],[0,0.1428,0.5]], {name:'γ'});
	var mort = brd.createElement('slider', [[0,-0.6], [60,-0.6],[0,0.4,10.0]], {name:'% mortality'});		var mort = brd.createElement('slider', [[0,-0.6], [60,-0.6],[0,0.4,10.0]], {name:'% mortality'});
	brd.createElement('text', [90,-0.3, "initially infected population rate"]);		brd.createElement('text', [90,-0.3, "initially infected population rate"]);
	brd.createElement('text', [90,-0.4, function(){ return "β: infection rate, R<sub>0</sub>="+(beta.Value()/gamma.Value()).toFixed(2);}]);		brd.createElement('text', [90,-0.4, function(){ return "β: infection rate, R<sub>0</sub>="+(beta.Value()/gamma.Value()).toFixed(2);}]);
	brd.createElement('text', [90,-0.5, "γ: recovery rate = 1/(days of infection)"]);		brd.createElement('text', [90,-0.5, function(){ return "γ: recovery rate = 1/(days of infection), days of infection= "+(1/gamma.Value()).toFixed(1);}]);

	var t = 0; // global		var t = 0; // global