Non-pharmaceutical interventions (NPIs) have played a crucial role in controlling the spread of COVID-19. Nevertheless, NPI efficacy varies enormously between and within countries, mainly because of population and behavioral heterogeneity. In this work, we adapted a multi-group SEIRA model to study the spreading dynamics of COVID-19 in Chile, representing geographically separated regions of the country by different groups. We use national mobilization statistics to estimate the connectivity between regions and data from governmental repositories to obtain COVID-19 spreading and death rates in each region. We then assessed the effectiveness of different NPIs by studying the temporal evolution of the reproduction number . Analysing data-driven and model-based estimates of , we found a strong coupling of different regions, highlighting the necessity of organized and coordinated actions to control the spread of SARS-CoV-2. Finally, we evaluated different scenarios to forecast the evolution of COVID-19 in the most densely populated regions, finding that the early lifting of restriction probably will lead to novel outbreaks.
Keywords: COVID-19; Chile; Epidemiological model; Inverse problems; Reproduction number; SARS-CoV-2; SEIRD model.
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