ANALYSIS OF THE TIME-SPATIAL DIFFUSION OF COVID-19 IN TWO BRAZILIAN STATES
Coronavirus (COVID-19); Socioeconomic, Demographic and environmental factors; Geographically Weighted Regression (GWR); Dynamic Systems; Behavioral epidemiological model.
The SARS-CoV-2 pandemic had impactful effects on the world's poverty level, as discussed in the vast literature, as well as, affected regions with more vulnerable populations, both socially and in terms of health and sanitary conditions. It is in this context that this study's main focus is to examine the flow of the spread of the COVID-19 infection to the states of Rio Grande do Norte and Amazonas. Thus, using data from the Secretariat of Public Health (SESAP) of the state of Rio Grande do Norte and from the IBGE – 2010 Census, we analyzed the incidence of COVID-19 for the period of the SE49 epidemiological week (11/23/2020 to 11/29/2020). It is about of exploratory cross-sectional research, whose empirical foundation is to analyze a local spatial model to model the incidence of COVID-19 in the 167 municipalities of potiguar and its main determinants. From a methodological point of view, we describe the presence of spatial autocorrelation and cluster formation, using Exploratory Spatial Data Analysis (AEDE). It was observed the presence of spatial heterogeneity for the incidence of COVID-19 in the municipalities of the state, which allows adjusting a Geographically Weighted Regression (GWR) model for the identification indicators of social vulnerability for a local analysis. From the results perspective, it is demonstrated that the coefficients of the study variables showed patterns of associations with socioeconomic, demographic and environmental factors. Already for the study of the extensive transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the state of Amazonas, we used data from MonitoraCovid-19/Fiocruz and the Amazonas Health Surveillance Foundation (FVS-AM) from march 9, 2020 to april 25, 2021. From a methodological point of view, we used a descriptive ecological study, using continuous dynamic simulation modeling through dynamical systems, with an emphasis on the behavioral, susceptible, infected, recovered, and dead (SIRD) epidemiological model. This analysis procedure aims to estimate alternative scenarios, based on the social distancing measures imposed by the state government of Amazonas, at the population level, to predict deaths and cases by COVID-19.