Background Identified in December 2019 in the city of Wuhan, China, the outbreak of COVID-19 spread throughout the world and its impacts affect different populations differently, where countries with high levels of social and economic inequality such as Brazil gain prominence, for understanding of the vulnerability factors associated with the disease. Given this scenario, in the absence of a vaccine or safe and effective antiviral treatment for COVID-19, nonpharmacological measures are essential for prevention and control of the disease. However, many of these measures are not feasible for millions of individuals who live in territories with increased social vulnerability. The study aims to analyze the spatial distribution of COVID-19 incidence in Brazil’s municipalities (counties) and investigate its association with sociodemographic determinants to better understand the social context and the epidemic’s spread in the country. Methods This is an analytical ecological study using data from various sources. The study period was February 25 to September 26, 2020. Data analysis used global regression models: ordinary least squares (OLS), spatial autoregressive model (SAR), and conditional autoregressive model (CAR) and the local regression model called multiscale geographically weighted regression (MGWR). Findings The higher the GINI index, the higher the incidence of the disease at the municipal level. Likewise, the higher the nurse ratio per 1,000 inhabitants in the municipalities, the higher the COVID-19 incidence. Meanwhile, the proportional mortality ratio was inversely associated with incidence of the disease. Discussion Social inequality increased the risk of COVID-19 in the municipalities. Better social development of the municipalities was associated with lower risk of the disease. Greater access to health services improved the diagnosis and notification of the disease and was associated with more cases in the municipalities. Despite universal susceptibility to COVID-19, populations with increased social vulnerability were more exposed to risk of the illness.

No abstract

Objective: to analyze the association between the occurrence of new tuberculosis cases and the Adapted Living Condition Index, and to describe the spatial distribution in an endemic municipality. Method: this is an analytical and ecological study that was developed from new cases in residents of an endemic municipality in the North Region of Brazil. The data were obtained from the Notifiable Diseases Information System and from the 2010 Demographic Census. The Adapted Living Conditions Index was obtained by factor analysis and its association with the occurrence of the disease was analyzed by means of the chi-square test. The type I error was set at 0.05. Kernel estimation was used to describe the density of tuberculosis in each census sector. Results: the incidence coefficient was 97.5/100,000 inhabitants. The data showed a statistically significant association between the number of cases and socioeconomic class, with the fact that belonging to the highest economic class reduces the chance of the disease occurring. The thematic maps showed that tuberculosis was distributed in a heterogeneous way with a concentration in the Southern region of the municipality. Conclusion: tuberculosis, associated with precarious living conditions, reinforces the importance of discussion on social determinants in the health-disease process to subsidize equitable health actions in risk areas, upon a context of vulnerability.

No abstract

Objective: Correlate the cases of multidrug-resistant tuberculosis and its spatial patterns with the type of notification and sociodemographic variables. Method: Ecological study carried out in the municipality of Belém, with 77 cases of multidrug-resistant tuberculosis registered in the Special Treatment Information System for Tuberculosis, between 2012 and 2016. For analysis, the data was debugged followed by geo-referencing in ArcGis 10.3 and Terra View 4.2.2. To relate the cases with the type of notification, the BioEstat 5.4 software was used, with a significance level of 95%. Results: Of the total, 40 (52%) were new cases; 27 (35%), relapses; and ten (13%) were re-enrolled after leaving. Multidrug-resistant tuberculosis was randomly distributed and related to income, household, territorial cluster and water supply. There was a concentration of cases in two administrative districts, corresponding to 28.5% and 27.3% of the total, with a median Sociodemographic Index. Conclusion: Behavior of multidrug-resistant tuberculosis influenced by sociodemographic indicators.