Spatial analysis for the identification of risk areas for schistosomiasis mansoni in the State of Sergipe, Brazil, 2005-2014

Abstract

Introduction: Schistosomiasis is a parasitic infectious disease with a worldwide prevalence. The objective of this work is to identify risk areas for schistosomiasis mansoni transmission in the State of Sergipe, Brazil, during the period from 2005 to 2014. Methods: We conducted an epidemiological study with secondary data from the Information System Control Program of Schistosomiasis [Sistema de Informação do Programa de Controle da Esquistossomose (SISPCE)]. Temporal trends were analyzed to obtain the annual percentage change (APC) in the rates of annual prevalence. In addition to the description of general indicators of the disease, the spatial analysis was descriptive, by means of the estimator of intensity kernel, and showed spatial dependence by indicators of global Moran (I) and Local Index of Spatial Association (LISA). Thematic maps of spatial distribution were made, identifying priority intervention areas in need of healthcare. Results: There were 78,663 cases of schistosomiasis, with an average of 8.7% positivity recorded; 79.8% of the cases were treated, and Sergipe showed a decreasing positive trend (APC: -2.78). There was the presence of spatial autocorrelation and a significant global Moran index (I = 0.19; p-value = 0.03). We identified clusters of highrisk areas, mainly located in the northeast and southcentral of the state, which each had equally high infection rates. Conclusions: There was a decreasing positive trend of schistosomiasis in Sergipe. Spatial analysis identified the geographic distribution of risk and allowed the definition of priority areas for the maintenance and intensification of control interventions.

Clinical and epidemiological indicators and spatial analysis of leprosy cases in patients under 15 years old in an endemic area of Northeast Brazil: an ecological and time series study

“…It has a population of 2 068 017 inhabitants and an area of 21 910 354 km², equivalent to 0.26% of the national territory. The median population per county was 27 573.56 in 2015 16. Population data were obtained from the IBGE (Brazilian Institute of Geography and Statistics), based on population estimates for the intercensus years (2002–2015).…”

“…The point distribution was transformed into a smoothed surface and presented as a continuous map, representing different levels of case intensity. The amount of smoothing, that is, the width of the radius of influence was defined as 3000 m, since this value generated an adequate representation of the distribution of the leprosy cases in the municipalities, minimising the overlapping bias or the occurrence of subdistribution patterns smoothed 16 21…”

Retrocesso do Programa de Controle da Esquistossomose no estado de maior prevalência da doença no Brasil

“…correlação negativa estatisticamente significante entre o percentual de adesão de municípios ao PCE e o percentual de pacientes com alta carga parasitária (rs = -0,7139; p = 0,0203) e também entre o número de exames realizados anualmente e o percentual de pacientes com alta carga parasitária (rs = -0,7091; p = 0,0216 25 . Dado relevante é que essa redução de adesão ao PCE coincide com a emergência -ou agravamento -de outras epidemias no estado, como dengue, chikungunya, zika, dentre outras, sugerindo possível desvio da atenção dos órgãos de saúde pública 26,27,28,29,30,31 . Em decorrência do menor número de municípios endêmicos realizando atividades do Programa, o número de exames realizados diminuiu, apresentando tendência de queda de aproximadamente 9,6% por ano, o que assinala provável subnotificação de casos.…”

Diversity of Biomphalaria spp. freshwater snails and associated mollusks in areas with schistosomiasis risk, using molecular and spatial analysis tools

“…Spatial analysis techniques are being used systematically to analyze distribution patterns of snail species in the genera Bulinus and Biomphalaria which colonize specific regions of Africa (Simoonga et al 2009;Moser et al, 2014). In Brazil, geographic information systems (GIS) have been utilized in studies correlating the distribution patterns of snails which are intermediate hosts of S. mansoni in areas where schistosomiasis is highly endemic, including Bahia (Bavia et al 1999, Cardim et al 2011), Pernambuco (Almeida et al 2003Gomes et al 2012), Minas Gerais (Guimarães et al 2009, Fonseca et al 2014, and Sergipe (Barboza et al 2012, Santos et al 2016.…”