Assessing the nationwide impact of COVID-19 mitigation policies on the transmission rate of SARS-CoV-2 in Brazil

Abstract

COVID-19 is now identified in almost all countries in the world, with poorer regions being particularly more disadvantaged to efficiently mitigate the impacts of the pandemic. In the absence of efficient therapeutics or large-scale vaccination, control strategies are currently based on non-pharmaceutical interventions, comprising changes in population behavior and governmental interventions, among which the prohibition of mass gatherings, closure of non-essential establishments, quarantine and movement restrictions. In this work we analyzed the effects of 707 governmental interventions published up to May 22, 2020, and population adherence thereof, on the dynamics of COVID-19 cases across all 27 Brazilian states, with emphasis on state capitals and remaining inland cities. A generalized SEIR (Susceptible, Exposed, Infected and Removed) model with a time-varying transmission rate (TR), that considers transmission by asymptomatic individuals, is presented. We analyze the effect of both the extent of enforced measures across Brazilian states and population movement on the changes in the TR and effective reproduction number. The social mobility reduction index, a measure of population movement, together with the stringency index, adapted to incorporate the degree of restrictions imposed by governmental regulations, were used in conjunction to quantify and compare the effects of varying degrees of policy strictness across Brazilian states. Our results show that population adherence to social distance recommendations plays an important role for the effectiveness of interventions and represents a major challenge to the control of COVID-19 in low- and middle-income countries.

A snapshot of a pandemic: The interplay between social isolation and COVID-19 dynamics in Brazil

“…Nevertheless, the pandemic spread has been frequently modeled by dynamical systems (deterministic or stochastic models), 7 , 8 , 9 , 10 , 11 , 12 which usually have as a control parameter some measure of amplification/attenuation of the disease infection rate due to different transmission scenarios of varying human contact. 13 Human contact is indirectly measured through indices of human density, mobility, isolation, and social distancing. 13 , 14 , 15 , 16 While in theory this is well accepted and provides insights on possible outcomes of the pandemic, it is usually very difficult to quantify the effects of non-pharmaceutical interventions on infection rates, 17 , 18 , 19 so most studies use ad hoc tuning parameters.…”

“… 13 Human contact is indirectly measured through indices of human density, mobility, isolation, and social distancing. 13 , 14 , 15 , 16 While in theory this is well accepted and provides insights on possible outcomes of the pandemic, it is usually very difficult to quantify the effects of non-pharmaceutical interventions on infection rates, 17 , 18 , 19 so most studies use ad hoc tuning parameters. 8 , 9 , 10 , 11 , 12 , 20 , 21 , 22 , 23 Hence, it is important to properly understand the relationship between disease spread and human mobility data in order to better model an epidemic.…”

“…This was followed by the implementation of nationwide non-pharmaceutical measures, including physical distancing, social isolation, quarantine, compulsory notification, and mask use. 13 , 26 Due to a lack of national coordination, the pandemic was mostly fought by the 27 states and 5,568 municipalities who took diverse, heterogeneous, and mainly non-coordinated decisions by government officials at the federal, state, and municipal levels. This led to both success and failure stories and to distinct efficacy of non-pharmaceutical measures in slowing the rate of transmission across the country, which outlines the importance of taking into account the socioeconomic, geographic, and demographic backgrounds of a region when implementing such measures.…”

“…This led to both success and failure stories and to distinct efficacy of non-pharmaceutical measures in slowing the rate of transmission across the country, which outlines the importance of taking into account the socioeconomic, geographic, and demographic backgrounds of a region when implementing such measures. 13 , 27 …”

“…The task of measuring the efficacy of these non-pharmaceutical interventions is especially hard in countries such as Brazil, due to its great heterogeneity. 13 , 28 , 29 Brazil is divided into five disparate regions, shown in Figure 1 . The South and Southeast regions concentrate more than half of the population, have the most developed infrastructure, are home to the wealthiest states and financial centers, offer better-paying jobs, and have better socioeconomic indexes.…”