On the heterogeneous spread of COVID-19 in Chile

TL;DR

This study models COVID-19 spread in Chile using a multi-group SEIRA approach, revealing regional coupling and emphasizing the importance of coordinated NPIs to prevent outbreaks upon lifting restrictions.

Contribution

It adapts a multi-group SEIRA model to Chilean regions, incorporating mobility and regional data to analyze COVID-19 dynamics and NPI effectiveness.

Findings

Strong regional coupling necessitates coordinated interventions.

Early lifting of restrictions risks new outbreaks.

Model forecasts highlight importance of sustained NPIs.

Abstract

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 behavioural 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 Rt. Analyzing data-driven and model-based estimates of Rt, 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.