Spatiotemporal trends of Chagas disease-related mortality in the Northeast of Brazil, 2007-2017.

Chagas disease (CD) is a neglected disease and endemic in Brazil. In the Brazilian Northeast Region, it affects millions of people. Therefore, it is necessary to identify the spatiotemporal trends of CD mortality in the Northeast of Brazil. This ecological study was designed, in which the unit of analysis was the municipality of the Brazilian northeast. The data source was the Information System of Mortality. It was calculated relative risk from socioeconomic characteristics. Mortality rates were smoothed by the Local Empirical Bayes method. Spatial dependency was analysed by the Global and Local Moran Index. Scan spatial statistics were also used. A total of 11 287 deaths by CD were notified in the study. An expressive parcel of this number was observed among 70-year-olds or more (n = 4381; 38.8%), no schooling (n = 4381; 38.8%), mixed-race (n = 4381; 62.3%), male (n = 6875; 60.9%). It was observed positive spatial autocorrelation, mostly in municipalities of the state of Bahia, Piauí (with high-high clusters), and Maranhão (with low-low clusters). The spatial scan statistics has presented a risk of mortality in 24 purely spatial clusters (P < 0.05). The study has identified the spatial pattern of CD mortality mostly in Bahia and Piauí, highlighting priority areas in planning and control strategies of the health services.

Mortality and survival of COVID-19.

This study aims to identify the risk factors associated with mortality and survival of COVID-19 cases in a state of the Brazilian Northeast. It is a historical cohort with a secondary database of 2070 people that presented flu-like symptoms, sought health assistance in the state and tested positive to COVID-19 until 14 April 2020, only moderate and severe cases were hospitalised. The main outcome was death as a binary variable (yes/no). It also investigated the main factors related to mortality and survival of the disease. Time since the beginning of symptoms until death/end of the survey (14 April 2020) was the time variable of this study. Mortality was analysed by robust Poisson regression, and survival by Kaplan-Meier and Cox regression. From the 2070 people that tested positive to COVID-19, 131 (6.3%) died and 1939 (93.7%) survived, the overall survival probability was 87.7% from the 24th day of infection. Mortality was enhanced by the variables: elderly (HR 3.6; 95% CI 2.3-5.8; P < 0.001), neurological diseases (HR 3.9; 95% CI 1.9-7.8; P < 0.001), pneumopathies (HR 2.6; 95% CI 1.4-4.7; P < 0.001) and cardiovascular diseases (HR 8.9; 95% CI 5.4-14.5; P < 0.001). In conclusion, mortality by COVID-19 in Ceará is similar to countries with a large number of cases of the disease, although deaths occur later. Elderly people and comorbidities presented a greater risk of death.