Re: [Scilab-users] Corona modelling

Le 20/05/2020 à 17:40, Chin Luh Tan a écrit : I can confirm this, this also happened in Scilab 6.1 Windows 10, however, it runs smooth in Scilab 6.0.2 same machine. Thanks. The issue is now reported here: http://bugzilla.scilab.org/show_bug.cgi?id=11852#c9 Samuel

Re: [Scilab-users] Corona modelling

I can confirm this, this also happened in Scilab 6.1 Windows 10, however, it runs smooth in Scilab 6.0.2 same machine.  rgds, CL On Wed, 20 May 2020 21:50:04 +0800 Samuel Gougeon wrote Hello, Thank you Stéphane for this nice example of applied GUI. The screenshot of

Re: [Scilab-users] Corona modelling

dream. So this is is a bad example. De : users De la part de Samuel Gougeon Envoyé : mercredi 20 mai 2020 15:50 À : users@lists.scilab.org Objet : Re: [Scilab-users] Corona modelling Hello, Thank you Stéphane for this nice example of applied GUI. The screenshot of the Xcos model from

Re: [Scilab-users] Corona modelling

Hello, Thank you Stéphane for this nice example of applied GUI. The screenshot of the Xcos model from Hervé is also quite stimulating. About the GUI run on Scilab 6.1.0, i have noticed that the Scilab filebrowser is blinking when using any of both sliders, as if it was updated/redisplayed for

Re: [Scilab-users] Corona modelling

And how does it compare with Johns Hopkins? Heinz > On 07.05.2020, at 13:49, hdf wrote: > > and here are the results, with parameters given: > Sent from the Scilab users - Mailing Lists Archives mailing list archive at > Nabble.com. > ___ > users

Re: [Scilab-users] Corona modelling

Hello Heinz, Before comparing with John Hopkins' data and try to identify the different parameters I wanted to 'improve' the model. I have read several interesting articles on the web. One of them , written by David

Re: [Scilab-users] Corona modelling

and here are the results, with parameters given: -- Sent from:

Re: [Scilab-users] Corona modelling

Hello,My contribution, I've done it with Xcos: where you can play with other parameters like a limited immunization (delta), deaths (Mu) etc ...I'm thinking to modelize the healthcare system showing the number of

Re: [Scilab-users] Corona modelling

As there have already been some cases where persons have been infected twice, you would have to take into account that only a finite percentage of infected people become immune and that this immunity might also only last some finite time. Another thought experiment would be to randomly test some

Re: [Scilab-users] Corona modelling

> On 30.03.2020, at 20:37, Tim Wescott wrote: > > Someone was tagging "R" as "removed", which works if it's the aggregate > of "live and no longer contagious" and "dead". > > Actually assessing the proportion of R depends on the local health > system, and, to some extent, the size of the peak

Re: [Scilab-users] Corona modelling

Someone was tagging "R" as "removed", which works if it's the aggregate of "live and no longer contagious" and "dead". Actually assessing the proportion of R depends on the local health system, and, to some extent, the size of the peak -- the main reason we're quarantining is to bring the peak

Re: [Scilab-users] Corona modelling

R = recovered = people who can not infect others anymore...this includes the dead people... (or not?) there are some nice introducton videos at YouTube about thiseven showing the mentioned model... numberphile: https://www.youtube.com/watch?v=k6nLfCbAzgo 3brown1blue:

Re: [Scilab-users] Corona modelling

It is generally assumed that 1% of the infected will die. But that would not be part of the modelling, depends mainly on local health services. Heinz > On 30.03.2020, at 16:12, Vesela Pasheva wrote: > > Hello colleagues, > > I would like to know whether the variable D of dead persons could

Re: [Scilab-users] Corona modelling

nfected 'I'. Regards, Rafael -Original Message- From: users On Behalf Of Vesela Pasheva Sent: Monday, March 30, 2020 5:13 PM To: Users mailing list for Scilab Subject: Re: [Scilab-users] Corona modelling Hello colleagues, I would like to know whether the variable D of dead persons could be

Re: [Scilab-users] Corona modelling

Hello colleagues, I would like to know whether the variable D of dead persons could be included in the model considered. Up till now the model considers the variables S - susceptible, I - infected and R - recovered. Where do the Dead persons D go. Of course i such case the system will be of

Re: [Scilab-users] Corona modelling

> On 30.03.2020, at 08:13, Stéphane Mottelet 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 Great many thanks: o The SIR model is great and

Re: [Scilab-users] Corona modelling

Merci Stéphane, for the very interesting code and Heinz for the reference to the math behind the epidemy “curve”, or one of its models. From: users On Behalf Of Stéphane Mottelet Sent: Monday, March 30, 2020 9:14 AM To: users@lists.scilab.org Subject: Re: [Scilab-users] Corona modelling

Re: [Scilab-users] Corona modelling

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)];

Re: [Scilab-users] Corona modelling

This will be a straightforward application of the ODE solver. Type "help ode" for more detail. You'll make a function that takes the vector x = [S; I; R] as an argument and returns [S'; I'; R']. Then you'll call that function with some starting x and let it play out. You can speed up

[Scilab-users] Corona modelling

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: