SETM

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Simple Epidemic Transmision Models
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View the Project on GitHub rvalla/SETM




12 Sep 2020

Simulate to learn

There is nothing I like more than to learn new things. It makes me feel active and awake. When I say new things I am talking about really new things. I have never paid attention to epidemic transmission dynamics but in 2020 I had reasons to do it. While monitoring the Dengue outbreak in Argentina first cases of COVID-19 were confirmed.

Immediately newspapers got full of news and hundreds of experts start talking about what to do and what not to do. They did it as, in the world, all were disconnected. Economists were talking about saving the economy and epidemiologists like it was possible to stay at home during 60 days. I changed my information sources very fast of course. Today is possible to make contact with a lot of people instantly so I started following on twitter
those who helped me to stay tuned and make sense about a lot of problems around the COVID-19 pandemic.
But the future does not exist. And when things are so dynamic and reactions of governments and people interact with a virus, you never know what to expect.

So I complemented my reading about SARS-CoV-2, COVID-19 and different contingency measures with a computational model which allowed me to question myself about the outbreak and the effects of different social responses in its evolution. I learnt a lot about the problem and I was surprised sometimes by the results.

Charts to read the results easily are saved after each simulation automatically. I worked a lot in them.

I said I enjoy to learn new things so I coded the software in Python. A programming language I had not used a lot. The main goal was always to make a model which serves to study a dynamic problem so I designed it in a way which allows me to make a lot of changes. The firsts runs could only simulate mobility reductions of the population in certain period of time. Now it is possible to simulate things as the social response to the outbreak (changing how much careful the population is) or isolation of closed contacts of confirmed cases.

Since today I will try to write a more complete and clear documentation for curious people like me who wants to run simulations or analyse the results without needing to study the code. Perhaps they find out something that until now has eluded me.




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