Spatial-temporal risk clusters, social vulnerability, and identification of priority areas for surveillance and control of cutaneous leishmaniasis in Maranhão, Brazil: an ecological study

Cutaneous leishmaniasis (CL) is a neglected disease widely distributed in Maranhão, Brazil and presents a significant public health problem. However, its transmission dynamics and determining factors are not clearly understood. In this context, geospatial technologies help interpret the process. Thi...

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Veröffentlicht in:Journal of medical entomology 2024-03, Vol.61 (2), p.481-490
Hauptverfasser: Oliveira, Romário de Sousa, Andrade Pimentel, Karen Brayner, Ribeiro da Silva, Rosa Cristina, Guimarães-e-Silva, Antonia Suely, Soares Moura, Maria Edileuza, Soares Pinheiro, Valéria Cristina
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container_title Journal of medical entomology
container_volume 61
creator Oliveira, Romário de Sousa
Andrade Pimentel, Karen Brayner
Ribeiro da Silva, Rosa Cristina
Guimarães-e-Silva, Antonia Suely
Soares Moura, Maria Edileuza
Soares Pinheiro, Valéria Cristina
description Cutaneous leishmaniasis (CL) is a neglected disease widely distributed in Maranhão, Brazil and presents a significant public health problem. However, its transmission dynamics and determining factors are not clearly understood. In this context, geospatial technologies help interpret the process. This study, then, characterized the space–time dynamics and the influence of social vulnerability on CL in an endemic area in Northeast Brazil. This is an ecological study about new cases of CL in Maranhão, from 2007 to 2020, obtained directly from the Notifiable Diseases Information System. The incidence rate was smoothed using a spatial empirical Bayesian method. Subsequently, global and local Moran statistics and their association with social vulnerability indicators were determined. Disease distribution was not random but grouped in space and time. All Social Vulnerability Index domains were positively correlated with the CL incidence. A likely cluster was detected in western Maranhão (P < 0.001), which encompassed 18 municipalities, from January 2007 to December 2013, with a high relative risk (5.06). The research findings suggest that planning public health actions and allocating resources should be prioritized in these areas to help effectively reduce the incidence of the disease.
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However, its transmission dynamics and determining factors are not clearly understood. In this context, geospatial technologies help interpret the process. This study, then, characterized the space–time dynamics and the influence of social vulnerability on CL in an endemic area in Northeast Brazil. This is an ecological study about new cases of CL in Maranhão, from 2007 to 2020, obtained directly from the Notifiable Diseases Information System. The incidence rate was smoothed using a spatial empirical Bayesian method. Subsequently, global and local Moran statistics and their association with social vulnerability indicators were determined. Disease distribution was not random but grouped in space and time. All Social Vulnerability Index domains were positively correlated with the CL incidence. A likely cluster was detected in western Maranhão (P &lt; 0.001), which encompassed 18 municipalities, from January 2007 to December 2013, with a high relative risk (5.06). 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subjects Animals
Bayes Theorem
Bayesian analysis
Brazil - epidemiology
Cities
Cutaneous leishmaniasis
Ecological studies
endemic diseases
epidemiology
Incidence
Leishmaniasis, Cutaneous - epidemiology
neglected diseases
Parasitic diseases
Public health
Social Vulnerability
Vector-borne diseases
VECTOR-BORNE DISEASES, SURVEILLANCE, PREVENTION
title Spatial-temporal risk clusters, social vulnerability, and identification of priority areas for surveillance and control of cutaneous leishmaniasis in Maranhão, Brazil: an ecological study
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