Abstract
The first case of COVID-19 in South America occurred in Brazil on February 25, 2020. By July 20, 2020, there were 2,118,646 confirmed cases and 80,120 confirmed deaths. To assist with the development of preventive measures and targeted interventions to combat the pandemic in Brazil, we present a geographic study to detect “active” and “emerging” space–time clusters of COVID-19. We document the relationship between relative risk of COVID-19 and mortality, inequality, socioeconomic vulnerability variables. We used the prospective space–time scan statistic to detect daily COVID-19 clusters and examine the relative risk between February 25–June 7, 2020, and February 25–July 20, 2020, in 5570 Brazilian municipalities. We apply a Generalized Linear Model (GLM) to assess whether mortality rate, GINI index, and social inequality are predictors for the relative risk of each cluster. We detected 7 “active” clusters in the first time period, being one in the north, two in the northeast, two in the southeast, one in the south, and one in the capital of Brazil. In the second period, we found 9 clusters with RR > 1 located in all Brazilian regions. The results obtained through the GLM showed that there is a significant positive correlation between the predictor variables in relation to the relative risk of COVID-19. Given the presence of spatial autocorrelation in the GLM residuals, a spatial lag model was conducted that revealed that spatial effects, and both GINI index and mortality rate were strong predictors in the increase in COVID-19 relative risk in Brazil. Our research can be utilized to improve COVID-19 response and planning in all Brazilian states. The results from this study are particularly salient to public health, as they can guide targeted intervention measures, lowering the magnitude and spread of COVID-19. They can also improve resource allocation such as tests and vaccines (when available) by informing key public health officials about the highest risk areas of COVID-19.
Highlights
Over the past 18 years, zoonotic coronavirus transmissions have been a global health concern
There were two epidemics: SARS-CoV in 2003 in China, which spread across 30 countries in six continents and resulted in 8098 cases and 774 deaths (9.5%), while the second being Middle East Syndrome Coronavirus (MERS-CoV), which started in the Kingdom of Saudi Arabia in 2012 and spread throughout 27 countries with 2494 laboratory-confirmed cases and 858 related deaths (Al-Tawfiq et al 2014; WHO 2019; Aly et al 2017)
To reduce uncertainty by identifying the municipalities that are the highest risk locations in a cluster, we report the relative risk of each areal unit belonging to a space–time cluster, which can provide additional evidence for targeted interventions
Summary
Over the past 18 years, zoonotic coronavirus transmissions have been a global health concern. By June 7, 2020, there were 691,758 confirmed cases and 36,455 confirmed deaths in Brazil, with a mortality rate of 5.3%. By July 20th, the figures increased to 2,118,646 cases and 80,120 deaths with a mortality rate of 3.8% (Brazil 2020). It is generally acknowledged that the highest proportion of deaths by COVID-19 occur among the elderly; those with the most severe disease were most likely having a history of hypertension, respiratory disease, and cardiovascular disease (Jordan et al 2020; Du et al 2020). Promislow (2020) reported that COVID-19 mortality rates tended to increase exponentially with age, while males tended to have a higher risk of dying across all ages The risk of death among young adults is smaller than that of older adults, e.g., at most 0.1%–0.2% (Jordan et al 2020; Kobayashi et al 2020); severe outcomes and deaths have been reported among children (Deyà-Martínez et al 2020; Jones et al 2020). Promislow (2020) reported that COVID-19 mortality rates tended to increase exponentially with age, while males tended to have a higher risk of dying across all ages
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
