Spatiotemporal dynamics and risk estimates of COVID-19 epidemic in Minas Gerais State: analysis of an expanding process

Abstract

COVID-19 is an infectious disease caused by the recently discovered coronavirus SARS-Cov-2. The disease became pandemic affecting many countries globally, including Brazil. Considering the expansion process and particularities during the initial stages of the epidemic, we aimed to analyze the spatial and spatiotemporal patterns of COVID-19 occurrence and to identify priority risk areas in Minas Gerais State, Southeast Brazil. An ecological study was performed considering all data from human cases of COVID-19 confirmed from the epidemiological week (EW) 11 (March 08, 2020) to EW 26 (June 27, 2020). Crude and smoothed incidence rates were used to analyze the distribution of disease patterns based on global and local indicators of spatial association and space-time risk assessment. Positive spatial autocorrelation and spatial dependence were found. Our results suggest that the metropolitan region of the State capital Belo Horizonte (MRBH) and Vale do Rio Doce mesoregions, as major epidemic foci in the beginning of the expansion process, have had important influence on the dispersion of SARS-CoV-2 in Minas Gerais State. Triangulo Mineiro/Alto Paranaiba region presented the highest risk of infection. In addition, six statistically significant spatiotemporal clusters were identified in the State, three at high risk and three at low risk. Our findings contribute to a greater understanding of the space-time disease dynamic and discuss strategies for identification of priority areas for COVID-19 surveillance and control.

Influence of Population Size, the Human Development Index and the Gross Domestic Product on Mortality by COVID-19 in the Southeast Region of Brazil

“…Minas Gerais had the lowest mortality rate among all the states, and a lower lethality rate than São Paulo and Rio de Janeiro. Minas Gerais adopted strict measures to control the spread of the virus, particularly in the capital, where commercial establishments were closed between March and August 2020 [ 23 ]. The incidence coefficient in the capital was lower than it was in other smaller cities in this state during the period.…”

Logistics Workers Are a Key Factor for SARS-CoV-2 Spread in Brazilian Small Towns: Case-Control Study

“…Considering our findings, one factor that probably explains why Town 2 had a seroprevalence almost four times higher than Town 1 is the fact that the population of Town 2 had a significantly higher proportion of logistics workers (Table 1). Another factor is that the study was done in Town 2 later than in Town 1, but this time gap alone likely does not explain the difference between the two towns because data from nearby cities indicate that seroprevalence in the area was stable and did not even double during this interval [5,21]. Apart from that, it should be observed that both towns have similar economies, are close to each other within the same state, and were taking the same lockdown measures in accordance with guidelines from their State Health Department.…”

Spatiotemporal analysis of the morbidity of global Omicron from November 2021 to February 2022

“…Urbanization and transit mediums, especially rail and aviation, were positively correlated with higher incidence of infections 7 . These scholars not only explored the abovementioned countries and regions, they also analyzed three cities in the United States, Minas Gerais State in southeastern Brazil, and Italy in Europe 8–10 …”

“…7 These scholars not only explored the abovementioned countries and regions, they also analyzed three cities in the United States, Minas Gerais State in southeastern Brazil, and Italy in Europe. [8][9][10] VOC has become a public health threat worldwide; its pathogenic characteristics and the epidemic have caused a public health burden. This study aimed to investigate the global spatiotemporal characteristics and relative influencing factors of the novel Omicron variant of SARS-CoV-2.…”