Spatial and spatiotemporal dynamics of visceral leishmaniasis in an endemic North-eastern region of Brazil

Abstract

Visceral Leishmaniasis (VL) is a neglected disease with increasing incidence in Brazil, particularly in the North-eastern. The aim of this study was to analyze the spatial and spatiotemporal dynamics of VL in an endemic region of North-eastern Brazil, between 2009 and 2017. Using spatial analysis techniques, an ecological and time series study was made regarding VL cases in Sergipe filed as notifiable disease events. With data from the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística, IBGE), a digital population and cartographic baseline was established. Segmented linear regression was used to examine the temporal trends. The statistical analysis methods of Global and Local Moran’ I, local Bayesian empirical methodology and spatial-temporal scanning were used to produce thematic maps. High instances were found among adults, males, urban residents, non-Whites and persons with low levels of education. A decrease in the recovery rate and an increase in the proportion of urban cases and lethality was found. A heterogeneous VL distribution with spatiotemporal agglomeration on the seaside of the state was seen in Sergipe. To better manage the disease, new research is encouraged together with development of public health strategies. Further, improving health care networks, especially primary care, is suggested as this approach has a key role in health promotion, prevention and monitoring of the most prevalent diseases.

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Published
2021-01-11
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Original Articles
Keywords:
Epidemiology, morbidity and mortality indicators, visceral leishmaniasis, spatial analysis, serial temporal studies, Brazil.
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How to Cite
Almeida, Ândria S., Ribeiro, C. J. N., Carlini, C. C., Santos, R. S., dos Santos, A. D., Tavares, D. S., de Araújo, K. C. G. M., Moura, T. R. de, & Santos, P. L. dos. (2021). Spatial and spatiotemporal dynamics of visceral leishmaniasis in an endemic North-eastern region of Brazil. Geospatial Health, 15(2). https://doi.org/10.4081/gh.2020.885