O impacto das intervenções não farmacêuticas governamentais durante o primeiro surto pandêmico de SARS-CoV-2: um estudo de modelagem computacional baseado em agentes na cidade de Natal

Abstract

The first wave of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic hit almost all cities in Brazil in early 2020 and lasted for several months. Despite the effort of local state and municipal governments, an inhomogeneous nationwide response resulted in a death toll among the highest recorded globally. To evaluate the impact of the nonpharmaceutical governmental interventions applied by different cities - such as the closure of schools and business in general - in the evolution and epidemic spread of SARS-CoV-2, we constructed a full-sized agentbased epidemiological model adjusted to the singularities of single cities. The model incorporates detailed demographic information, mobility networks segregated by economic segments, and restricting bills enacted during the pandemic period. As a case study, we analyzed how the City of Natal - a midsized state capital - reacted to the pandemic. Although our results indicate that the governmental response was suboptimal (the restrictive mobility acts saved many lives), our simulations showed that the suspension of school activities was essential to avoid a high number of deaths (the increase would be around 514.65%). The effective closing of Work activities would decrease the number of deaths by approximately 70.52% and religious activities by 11.19%. The absence of intervention would result in a catastrophic scenario of 6779 deaths, this number corresponds to about 0.91% of the Natal city population. The simulations show that a compartmental analysis of the alternative scenarios can inform policymakers about the most impactful measures for further surges of the pandemic and support future decisions as the pandemic progresses.