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Revista argentina de microbiología
versión impresa ISSN 0325-7541versión On-line ISSN 1851-7617
Resumen
MORANDO, Nicolás et al. Evaluation of interventions during the COVID-19 pandemic: development of a modelbased on subpopulations with different contact rates. Rev. argent. microbiol. [online]. 2022, vol.54, n.2, pp.91-100. ISSN 0325-7541.
Although multiple attempts have been made to mathematically model the currentepidemic of SARS-CoV-2, the causative agent of coronavirus disease 2019 (COVID-19), fewmodels 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 incontact rates within the population and to implement it in an accessible application allowingto estimate the impact of possible interventions based on available information. An extendedversion of the Susceptible-Exposed-Infected-Resistant (SEIR) model, named SEIR-HL, was deve-loped, assuming a population divided into two subpopulations, with different contact rates.Additionally, a formula for the calculation of the basic reproduction number (R0) for a popula-tion divided into n subpopulations was proposed, where the contact rates for each subpopulationcan be distinguished according to contact type or context. The predictions made by SEIR-HLwere compared to those of SEIR, showing that the heterogeneity in contact rates can drama-tically affect the dynamics of simulations, even when run from the same initial conditions andwith the same parameters. SEIR-HL was used to predict the effect on the epidemic evolution ofthe displacement of individuals from high-contact positions to low-contact positions. Lastly, byway of example, SEIR-HL was applied to the analysis of the SARS-CoV-2 epidemic in Argentinaand an example of the application of the R0formula was also developed. Both the SEIR-HLmodel and an R0calculator were computerized and made available to the community.
Palabras clave : COVID-19; SARS-CoV-2; SEIR; Argentina; Basic reproductionnumber; Model.