Temporal trends and spatial and spatiotemporal distribution of schistosomiasis mansoni in northeast Brazil between 2005 and 2016.

BACKGROUND: Schistosoma mansoni is a parasitic disease of great magnitude for Brazilian public health. We aimed to analyse the temporal trend and spatial and spatiotemporal distribution of positivity rates for schistosomiasis mansoni in northeast Brazil. METHODS: This is a descriptive study with an ecological approach, carried out between 2005 and 2016. We calculated the positivity rate for the disease and then performed a segmented trend analysis (Joinpoint). For spatial analysis, we smoothed the positivity rates using the local empirical Bayesian method. We checked for spatial autocorrelation using Moran's global and local. Subsequently, we performed Kulldorff's space time sweep analysis. RESULTS: In the period under review, 7 745 650 tests were performed in the northeast, of which 577 793 were positive for Schistosoma mansoni. In the historical series of positivities, it is noted that the highest rates were in Sergipe, Alagoas and Pernambuco. The states of Alagoas and Sergipe showed higher positivity in relation to the average positivity of the northeast and of Brazil. The spatial analysis maps identify clusters of high risk of schistosomiasis cases, mainly in coastal municipalities. There was also stability in positivity rates in some states and the maintenance of endemic areas. CONCLUSIONS: Thus effective public health policies are needed in health education in order to reduce schistosomiasis positivity and improve the health conditions of the northeastern population.

Corrigendum: Impact of the COVID-19 pandemic on the diagnosis of tuberculosis in Brazil: Is the WHO end TB strategy at risk?

[This corrects the article DOI: 10.3389/fphar.2022.891711.].

Basic and associated causes of schistosomiasis-related mortality in Brazil: A population-based study and a 20-year time series of a disease still neglected.

BACKGROUND: Schistosomiasis is a persistent public health problem in Brazil. Regardless advances in diagnosis and mass treatment, schistosomiasis has a severe impact on morbimortality in the country and remains a neglected tropical disease. Herein, we assessed the basic and associated causes of schistosomiasis-related deaths and the temporal and spatial patterns of mortality from the disease in Brazil between 1999 and 2018. METHODS: We conducted an ecological and time series study. The segmented log-linear regression model was applied to assess time trends, considering all deaths recorded in the category B65/ICD-10. Additionally, we elaborated maps of mortality rates from schistosomiasis in Brazil. RESULTS: A total of 4168 schistosomiasis-related deaths were recorded in Brazil in this period, as an associated cause. Time trend analysis revealed an increase in the average age of deaths from schistosomiasis (annual percentage change (APC) = 0.84), and stable trend in Brazil (APC = 0.31). Concerning schistosomiasis-related deaths, we observed disorders related to the digestive system, liver diseases, septicemias, and chronic diseases. Surprisingly, there were deaths caused by non-endemic Schistosoma species in Brazil. Also, municipalities from non-endemic areas in Brazil presented schistosomiasis-related deaths. CONCLUSION: Altogether, our analyses demonstrated that schistosomiasis remains a significant cause of death in Brazil, and it is increasing in some areas, especially in the Northeast region. Additionally, women and the elderly showed a stable time trend of deaths. Thereby, it urgently requires improvements in the control programs strategies, in the sense of an effective reduction in cases and deaths from the disease in Brazil.

Spatiotemporal Pattern of COVID-19-Related Mortality during the First Year of the Pandemic in Brazil: A Population-based Study in a Region of High Social Vulnerability.

Currently, the world is facing a severe pandemic caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although the WHO has recommended preventive measures to limit its spread, Brazil has neglected most of these recommendations, and consequently, our country has the second largest number of deaths from COVID-19 worldwide. In addition, recent studies have shown the relationship between socioeconomic inequalities and the risk of severe COVID-19 infection. Herein, we aimed to assess the spatiotemporal distribution of mortality and lethality rates of COVID-19 in a region of high social vulnerability in Brazil (Northeast region) during the first year of the pandemic. A segmented log-linear regression model was applied to assess temporal trends of mortality and case fatality rate (CFR) and according to the social vulnerability index (SVI). The Local Empirical Bayesian Estimator and Global Moran Index were used for spatial analysis. We conducted a retrospective space-time scan to map clusters at high risk of death from COVID-19. A total of 66,358 COVID-19-related deaths were reported during this period. The mortality rate was 116.2/100,000 inhabitants, and the CFR was 2.3%. Nevertheless, CFR was > 7.5% in 27 municipalities (1.5%). We observed an increasing trend of deaths in this region (AMCP = 18.2; P = 0.001). Also, increasing trends were observed in municipalities with high (N = 859) and very high SVI (N = 587). We identified two significant spatiotemporal clusters of deaths by COVID-19 in this Brazilian region (P = 0.001), and most high-risk municipalities were on the coastal strip of the region. Taken together, our analyses demonstrate that the pandemic has been responsible for several deaths in Northeast Brazil, with clusters at high risk of mortality mainly in municipalities on the coastline and those with high SVI.

Population-based, spatiotemporal modeling of social risk factors and mortality from schistosomiasis in Brazil between 1999 and 2018.

Schistosomiasis remains a significant public health concern in Brazil. To identify areas at, and social determinants of health (SDH) associated with, high-risk for schistosomiasis-related mortality from Brazil, we conducted a spatial and spatiotemporal modeling assessing all deaths confirmed in Brazil between 1999 and 2018. We used the segmented log-linear regression model to assess temporal trends, and the local empirical Bayesian estimator, the Global and Local Moran Index for spatial analysis. A total of 12,251 schistosomiasis-related deaths were reported in this period. Within the Mortality Information System (SIM) of the Brazilian Ministry of Health, the states of Alagoas (AL), Pernambuco (PE) and Sergipe (SE) recording the highest mortality rates: 2.21, 1.92 and 0.80 deaths/100,000 inhabitants, respectively. Analyses revealed an increase in the mean age of schistosomiasis-related deaths over the time assessed (APC = 0.9; p-value<0.05). Spatial analysis identified a concentration of municipalities presenting high risk of schistosomiasis-related mortality along the coastline of PE and AL. Similarly, we identified the formation of high space-time clusters in municipalities in the states of PE, AL, SE, Bahia, and Minas Gerais. Finally, mortality rates showed a significant correlation with 96.96% of SDH indices. The data reveal additional important changes in schistosomiasis-related deaths in Brazil between 1999 and 2018, such as a slow reduction among males (unlike females that displayed no change). Regardless, our analyses indicates that schistosomiasis continues to have the greatest detrimental impact in poor regions of Brazil and suggest the need for enhancement of current control measures to accelerate progress.