[Evaluation of interventions during the COVID-19 pandemic: development of a model based on subpopulations with different contact rates].

Although multiple attempts have been made to mathematically model the current epidemic of SARS-CoV-2, the causative agent of coronavirus disease 2019 (COVID-19), few models have been conceived as accessible interactive tools for users from various backgrounds. The goal of this study was to develop a model that took into account the heterogeneity in contact rates within the population and to implement it in an accessible application allowing to estimate the impact of possible interventions based on available information. An extended version of the Susceptible-Exposed-Infected-Resistant (SEIR) model, named SEIR-HL, was developed, assuming a population divided into two subpopulations, with different contact rates. Additionally, a formula for the calculation of the basic reproduction number (R(0)) for a population divided into n subpopulations was proposed, where the contact rates for each subpopulation can be distinguished according to contact type or context. The predictions made by SEIR-HL were compared to those of SEIR, showing that the heterogeneity in contact rates can dramatically affect the dynamics of simulations, even when run from the same initial conditions and with the same parameters. SEIR-HL was used to predict the effect on the epidemic evolution of the displacement of individuals from high-contact positions to low-contact positions. Lastly, by way of example, SEIR-HL was applied to the analysis of the SARS-CoV-2 epidemic in Argentina and an example of the application of the R(0) formula was also developed. Both the SEIR-HL model and an R(0) calculator were computerized and made available to the community.