Basic sanitation: a new indicator for the spread of COVID-19?

BACKGROUND: Basic sanitation could be a potential indicator of the spread of coronavirus disease-2019 (COVID-19) and, in this context, space-time patterns are important tools with which to elucidate the spread of disease and identify risk factors. The aim of this study was to assess a possible association between basic sanitation indices and COVID-19 rates in all the 5570 municipalities of Brazil and its spatial distribution. METHODS: Data of COVID-19 cases registered in Brazil from 28 February until 31 May 2020 and independent variables associated with basic sanitation were included. RESULTS: High incidence rates were significantly associated with precarious water service index (0-25% coverage) and offstandard faecal coliforms index for tap water (5-50% and 75-100% of samples tested). A significant association between high mortality rates and sewage collection (0-25% coverage)/treatment (25-50% coverage) indices was also verified. In addition, clusters with significant spatial autocorrelation were identified mainly in the North and Northeast regions for mortality and incidence rates (high-high risk areas) and for offstandard faecal coliforms index. Those regions are considered the poorest in Brazil, presenting with low incomes, human agglomerations, as well as a poor basic sanitation system, which also hinder the implementation of COVID-19-preventative measures. CONCLUSIONS: A precarious basic sanitation infrastructure could potentially be associated with the high transmission of severe acute respiratory syndrome coronavirus-2 in Brazil.

Space-time risk cluster of visceral leishmaniasis in Brazilian endemic region with high social vulnerability: An ecological time series study.

BACKGROUND: Despite visceral leishmaniasis (VL) being epidemic in most Brazilian regions, the Northeast region is responsible for the highest morbidity and mortality outcomes within the country. OBJECTIVE: To analyse the spatiotemporal dynamics of VL cases to identify the temporal trends and high-risk areas for VL transmission, as well as the association of the disease with social vulnerability in Brazilian Northeast. METHODS: We carried out an ecological time series study employing spatial analysis techniques using all VL confirmed cases of 1,794 municipalities of Brazilian Northeast between the years 2000 to 2017. The Social Vulnerability Index (SVI) was used to represent the social vulnerability. Incidence rates were standardized and smoothed by the Local Empirical Bayesian Method. Time trends were examined through segmented linear regression. Spatiotemporal analysis consisted of uni- and bivariate Global and Local Moran indexes and space-time scan statistics. RESULTS: Incidence rate remained stable and ranged from 4.84 to 3.52 cases/100,000 inhabitants. There was higher case prevalence between males (62.71%), children and adolescents (63.27%), non-white (69.75%) and urban residents (62.58%). Increasing trends of new cases were observed among adult male subjects (≥ 40 years old) and urban residents. Importantly, VL incidence showed a direct spatial dependence. Spatial and space-time clusters were identified in sertão and meio-norte sub-regions, overlapping with high social vulnerability areas. CONCLUSIONS: VL is a persistent health issue in Brazilian Northeast and associated with social vulnerability. Space-time clustering of VL cases in socially vulnerable municipalities demands intersectoral public policies of surveillance and control, with focus on reducing inequalities and improving living conditions for regional inhabitants.

Spatiotemporal clustering, social inequities and the risk of leptospirosis in an endemic area of Brazil: a retrospective spatial modelling.

BACKGROUND: Leptospirosis is an endemic disease in Brazil of social and economic relevance related to behavioural and socioenvironmental factors. This study aimed to analyse the spatiotemporal distribution of the incidence of leptospirosis and its association with social determinants in health in a state of northeastern Brazil. METHODS: An ecological study of temporal series with techniques of spatial analysis using secondary data of the cases of leptospirosis notified in the Information System of Notifiable Diseases of the state of Sergipe (2008-2017) was conducted. The analysis of temporal trends was performed using Poisson regression. Spatial analyses were performed using the Moran index, the local empirical Bayesian model, scan statistics and spatial regression. RESULTS: The incidence rate decreased from 3.66 to 1.44 cases per 100 000 inhabitants in 2008 and 2017, respectively. Leptospirosis was associated with social inequities, mostly affecting males aged 20-49 y living in urban areas. The space-time scan indicated the formation of a risk cluster in municipalities in the metropolitan region of the state. CONCLUSIONS: The data indicated the persistence of leptospirosis transmission, maintaining a pattern of high endemicity in some municipalities associated with social inequities. The study showed the temporal and spatial dynamics of the disease to better target specific actions for prevention and control.

Analysis of the relationship between life expectancy and social determinants in a north-eastern region of Brazil, 2010-2017.

The process of population aging is a worldwide reality becoming a global public health challenge. Although population aging is especially noticeable in more developed regions, there has also been a significant advance in the quantity of elderly people in areas with unfavourable socioeconomic indicators, and a rapid growth in countries with a low level of economic development. This article presents an analysis based on spatial autocorrelation of the relationship between life expectancy and social determinants in a north-eastern region of Brazil. An ecological study was conducted using the secondary data of social, demographic, and health indicators of elderly people collected in the Brazilian Demographic Census of the 75 municipalities of the state of Sergipe. Spatial autocorrelation was evaluated using the Moran global index and the local indicators of space association. Multiple linear regression models were used to identify the relationship between life expectancy and social determinants. The South-eastern region of the state presented clusters with all indicators pointing to acceptable lifestyles, whereas the municipalities of the north-western and far-eastern regions were characterized by values demonstrating precarious living conditions. The high dependency ratio, illiteracy rate, and unemployment rate among elderly people had a negative impact on life expectancy. The evidence confirms that there is an autocorrelation between social determinants and life expectancy, indicating that the worse the social, economic, and health indicators are, the lower the life expectancy. This finding indicates the need to redirect public policies and formulate strategies aimed at reducing social and health inequalities.

Trend and spatial analysis of prostate cancer mortality in the state of Sergipe, Brazil.

This is an ecological study with exploratory analysis of spatial and temporal data based on mortality data with respect to prostate cancer obtained from the Mortality Information System concerning residents of the state of Sergipe, Brazil between 2000 and 2015. The analysis of temporal trends was performed using the Joinpoint Regression Program through Poisson regression. Spatial analysis was performed using the empirical Bayesian model, Kernel analysis, Global Moran and Local indices. There were 1,986 deaths due to prostate cancer, most of which occurring after 60 years of age. An increasing, non-constant but significant trend in mortality rates was noted. The kernel density estimator showed hotspot densities of the highest rates of prostate cancer mortality in the north-eastern and central regions of the state. High-risk clusters were identified for prostate cancer mortality (I = 0.55, P<0.01). There was an increase in prostate cancer mortality rates and a heterogeneous geographic distribution of risk areas, with high-risk priority areas identified in certain regions of the state. These priority areas include the municipalities located in the Northeast (Amparo do São Francisco, Aquidabã, Canhoba, Cedro de São João and Telha), the West (Frei Paulo and Pedra Mole) and the south-western region of the state (Poço Verde and Simão Dias).

Spatial analysis of the prevalence of schistosomiasis in an endemic coastal area in north-eastern Brazil.

Due to contact and misuse of water drainage channels, schistosomiasis has spread and become a constant concern in northeastern Brazil. The aim of this study was to monitor human cases of Schistosomiasis mansoni and the breeding areas of the snail intermediate host Biomphalaria glabrata through spatial analysis in a community named Invasão do Canal do Guaxinim, located in Barra dos Coqueiros City in an endemic coastal part of the state of Sergipe, Brazil. This research was performed as a cross-sectional epidemiological study conducted with parasitological and malacological surveys. To verify the spatial analysis, a two-year spatial point pattern analysis was performed by means of Kernel intensity estimation using TerraView software 4.2.2. A schistosomiasis prevalence reduction from 8.1% (2013) to 4.9% (2014) was observed but mild infection prevailed in adolescents and/or young adults during the two-year study. In malacological research, 387 specimens of snails of the genus B. glabrata were collected and all were negative with regard to schistosomiasis. Spatial analysis showed a strong, spatial trend of increased transmission risk areas north and south of the community, both in 2013 and 2014. In Invasão do Canal do Guaxinim itself, the increased risk was only seen in the northern part. When combined, the human and the malacological spatial analyses constituted an important methodological approach for monitoring and controlling this parasitic disease.