Just notice that this email was stuck due to the image attached was
too large, and notice the new post by Claus with the SEIR model from
Matlab, perhaps Scilabers could make the model more realistic together.
CL
============ Forwarded message ============
From: Chin Luh Tan <chinluh....@bytecode-asia.com
<mailto:chinluh....@bytecode-asia.com>>
To: "Users mailing list for Scilab"<users@lists.scilab.org
<mailto:users@lists.scilab.org>>
Date: Thu, 30 Apr 2020 00:03:46 +0800
Subject: Re: [Scilab-users] Corona modelling
============ Forwarded message ============
Hi,
I just modified Stephane's nice GUI to make it able to load the
real world data from internet so that we could overlapped the data
to the SIR model to study the effect of locked-down, and the
meaning of the coefficients.
From some reading from the internet, the "Susceptible" population
is kind of like difficult to determined, and some suggested to use
"current cases" as "optimum model" assuming the condition is
recovering. As or the "optional model", the "total population" is
being used.
While "beta" is the transmission coefficient, "gamma" the recovery
factor, can anyone explained more details, perhaps in layman term,
how to relate these parameters to one country condition, such as
the relationship between gamma with the number of days (what days
is it referring to), beta "actual meaning" in layman term, and
perhaps link with some "technical term" the newspaper always seen
on papers?
I attached the GUI, which will load 3 sets of data from Johns
Hopkins Github,
(https://github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_time_series
<https://antispam.utc.fr/proxy/2/c3RlcGhhbmUubW90dGVsZXRAdXRjLmZy/github.com/CSSEGISandData/COVID-19/tree/master/csse_covid_19_data/csse_covid_19_time_series>)
which could be download using following 3 lines directly from the
Scilab:
--> fn =
getURL('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv
<https://antispam.utc.fr/proxy/2/c3RlcGhhbmUubW90dGVsZXRAdXRjLmZy/raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv>')
--> fn =
getURL('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv
<https://antispam.utc.fr/proxy/2/c3RlcGhhbmUubW90dGVsZXRAdXRjLmZy/raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv>')
--> fn =
getURL('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_recovered_global.csv
<https://antispam.utc.fr/proxy/2/c3RlcGhhbmUubW90dGVsZXRAdXRjLmZy/raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_recovered_global.csv>')
and run the GUI as attached.
rgds,
CL
---- On Mon, 30 Mar 2020 14:13:40 +0800 *Stéphane Mottelet
<stephane.motte...@utc.fr <mailto:stephane.motte...@utc.fr>>*
wrote ----
Hello Heinz,
Here is an interactive version (made for my children last
week...) :
/// Confinement COVID-19 !/
/// Stephane MOTTELET, UTC/
/// Tue Mar 24 08:55:03 CET 2020/
/// /
function *dydt*=_sir_(*t*, *y*, *bet*, *gam*, *N*)
*dydt*=[-*bet*/*N***y*(1)**y*(2)
*bet*/*N***y*(1)**y*(2)-*gam***y*(2)
*gam***y*(2)];
endfunction
function _draw_(*bet*, *gam*)
t=0:1:360;
N=6e7;
if exists("gcbo") && is_handle_valid(gcbo)
sb = gcbo;
if sb.tag=="beta"
*bet*=sb.value;
*gam*=findobj("gamma").value
else
*gam*=sb.value;
*bet*=findobj("beta").value
end
y=ode('stiff',[N-1;1;0],0,t,list(_sir_,*bet*,*gam*,N));
curves = findobj("curves");
curves.children(1).data(:,2)=y(3,:);
curves.children(2).data(:,2)=y(2,:);
curves.children(3).data(:,2)=y(1,:);
else
y=ode('stiff',[N-1;1;0],0,t,list(_sir_,*bet*,*gam*,N));
scf(0)
clf
plot(t,y)
gce().tag="curves";
gce().children.thickness=2;
legend("Susceptible","Infected","Recovered",-1)
sb1 = uicontrol("style","slider",...
"units","normalized",...
"Position", [0.85,0.2,0.05,0.48],...
"BackgroundColor", [1,1,1],...
"Callback_Type",12,...
"sliderstep",[1/1000,1/10],...
"min",0.15,"max",0.3,"value",*bet*,...
"Callback","draw","tag","beta");
uicontrol("style","text",...
"string","$\beta$",...
"units","normalized",...
"Position", [0.85,0.125,0.05,0.08],...
"BackgroundColor", [1,1,1],...
"HorizontalAlignment","center");
sb1 = uicontrol("style","slider",...
"units","normalized",...
"Position", [0.90,0.2,0.05,0.48],...
"BackgroundColor", [1,1,1],...
"Callback_Type",12,...
"sliderstep",[1/1000,1/10],...
"min",0,"max",1/15,"value",*gam*,...
"Callback","draw","tag","gamma");
uicontrol("style","text",...
"string","$\gamma$",...
"units","normalized",...
"Position", [0.9,0.125,0.05,0.08],...
"BackgroundColor", [1,1,1],...
"HorizontalAlignment","center");
end
end
clf
_draw_(0.3,1/15)
Le 30/03/2020 à 02:14, Heinz Nabielek a écrit :
Colleagues:
is there an straightforward Scilab approach for solving the three
coupled nonlinear differential equations of first order given by the Standard
Model of Epidemics?
S= number Susceptible: S'=-aSI
I= number Infected: I'=aSI - bI
R= number Recovered: R'=bI
whereby 'a' is the transmission coefficient, 'b' the recovery
factor (after Reed-Frost 1928).
Initial values for S, I, R are available.
Thank you
Heinz
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--
Stéphane Mottelet
Ingénieur de recherche
EA 4297 Transformations Intégrées de la Matière Renouvelable
Département Génie des Procédés Industriels
Sorbonne Universités - Université de Technologie de Compiègne
CS 60319, 60203 Compiègne cedex
Tel : +33(0)344234688
http://www.utc.fr/~mottelet
<https://antispam.utc.fr/proxy/1/c3RlcGhhbmUubW90dGVsZXRAdXRjLmZy/www.utc.fr/~mottelet>
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