Simulated and reported number of deaths in the U.S. as of March 31. Note that in the logarithmic plot, the deviations between the model and the reported cases at small values of deaths look larger than at larger numbers. The smaller graph shows the same data in a logarithmic scale for the y-axis. Image courtesy of COMSOL.
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April 27, 2020
COMSOL has posted an interesting blog (written by Ed Fontes) that leverages mathematical models and multiphysics software to simluate the spread and fatality rate of COVID-19 in three different geographies and with different approaches to social distancing.
In the article, COMSOL compares simulations with reported data from Hubei, Sweden, and the United States.
While there are limits to what these particular models can predict, they do provide an interesting view into the dynamics of the spread of the disease. According to Fontes:
“The models also give an intuition of how important it is to reduce the reproduction number of COVID-19 by keeping social distance and avoiding unnecessary social interaction, to reduce the peak of infected patients in intensive care and to reduce the total impact of the epidemic.”
You can read the blog here, and download the model and app files here.
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