Abstract
We have studied the dynamic evolution of the Covid-19 pandemic in Argentina. The marked heterogeneity in population density and the very extensive geography of the country becomes a challenge itself. Standard compartment models fail when they are implemented in the Argentina case. We extended a previous successful model to describe the geographical spread of the AH1N1 influenza epidemic of 2009 in two essential ways: we added a stochastic local mobility mechanism, and we introduced a new compartment in order to take into account the isolation of infected asymptomatic detected people. Two fundamental parameters drive the dynamics: the time elapsed between contagious and isolation of infected individuals (alpha) and the ratio of people isolated over the total infected ones (p). The evolution is more sensitive to the p-parameter. The model not only reproduces the real data but also predicts the second wave before the former vanishes. This effect is intrinsic of extensive countries with heterogeneous population density and interconnection.The model presented has proven to be a reliable predictor of the effects of public policies as, for instance, the unavoidable vaccination campaigns starting at present in the world an particularly in Argentina.
Highlights
We have studied the dynamic evolution of the Covid-19 pandemic in Argentina
The total population inside of each parcel was assigned from the data provided by the National Geographic Institute of Argentina (IGN)
In this work we have proposed a novel model to study the influence of geographical and sociological conditions on the spread of the virus SARS-CoV2, causing the COVID-19 pandemic in Argentina
Summary
We have studied the dynamic evolution of the Covid-19 pandemic in Argentina. The marked heterogeneity in population density and the very extensive geography of the country becomes a challenge itself. Several models have been proposed to include the actual geographic spread using real data or time-dependent parameters to simulate people’s m obility[13,14,15,16,17,18,19,20].
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