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.

Keywords: Brazil; COVID-19; Mathematical modeling; Non-pharmaceutical interventions; Public policies; Transmission rate.

Graphical abstract

Fig. 1

(A) A timeline of events associated with the spread of SARS-CoV-2 across the 27 Brazilian states. The dates of first registered cases are shown (red dots), followed by the moment that community transmission was declared in each state (blue dots). The dates when the TR were observed to change (${\beta }_0\to {\beta }_1$ and, when applicable, ${\beta }_1\to {\beta }_2$, are shown as triangles). The orange segments indicate the interval between the initial NPIs enforced by states and the first observed peak in stringency. Dates refer to the year 2020. (B) Estimates of $R_0$ (and corresponding 95% confidence intervals) for each state, their capitals and remaining inland cities. Data for the Federal District (DF), the smallest Brazilian federal unit and the only one that has no municipalities, is only shown at the state-level.

Fig. 2

Evolution of the governmental measures adopted for each Brazilian state with respect to COVID-19 death incidence. The figure shows the variation of the stringency index over time for each state relative to the number of confirmed death per 100,000 inhabitants The number of confirmed deaths per 100,000 population is shown in logarithmic scale on the $x$-axis.

Fig. 3

Illustrative examples of a general pattern observed for the behavior of stringency measures over time in Brazil. Upper panels show COVID-19 incidence and bottom panels exhibit the social mobility reduction and the stringency indexes over time for (a) Santa Catarina (increase-and-decrease, ID), (b) São Paulo (increase-and-steady, IS) and (c) Amapá (increase-and-increase, II). The social mobility index is considered separately for capitals, inland cities and the whole state. Plots for the remaining Brazilian states are shown in Supplementary Figure 2 and 3. The average reduction in the SMRI according to the stringency pattern for all states is shown in panel d. For each category, the median is shown as a solid horizontal bar.

Fig. 4

Impact of measures and popular adherence on the effective reproduction number in each Brazilian state. The plot depicts the decrease of the average of ${\mathcal{R}}_t$ before and after the first TR change.