Forecasting temporal dynamics of cutaneous leishmaniasis in Northeast Brazil.

INTRODUCTION:Cutaneous leishmaniasis (CL) is a vector-borne disease of increasing importance in northeastern Brazil. It is known that sandflies, which spread the causative parasites, have weather-dependent population dynamics. Routinely-gathered weather data may be useful for anticipating disease ri...

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Bibliographic Details
Published in:PLoS Neglected Tropical Diseases
Main Authors: Joseph A Lewnard, Lara Jirmanus, Nivison Nery Júnior, Paulo R Machado, Marshall J Glesby, Albert I Ko, Edgar M Carvalho, Albert Schriefer, Daniel M Weinberger
Format: Article in Journal/Newspaper
Language:English
Published: Public Library of Science (PLoS) 2014
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Online Access:https://doi.org/10.1371/journal.pntd.0003283
https://doaj.org/article/1fd2f48acebc4274a786b7b5a46e5d26
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Summary:INTRODUCTION:Cutaneous leishmaniasis (CL) is a vector-borne disease of increasing importance in northeastern Brazil. It is known that sandflies, which spread the causative parasites, have weather-dependent population dynamics. Routinely-gathered weather data may be useful for anticipating disease risk and planning interventions. METHODOLOGY/PRINCIPAL FINDINGS:We fit time series models using meteorological covariates to predict CL cases in a rural region of Bahía, Brazil from 1994 to 2004. We used the models to forecast CL cases for the period 2005 to 2008. Models accounting for meteorological predictors reduced mean squared error in one, two, and three month-ahead forecasts by up to 16% relative to forecasts from a null model accounting only for temporal autocorrelation. SIGNIFICANCE:These outcomes suggest CL risk in northeastern Brazil might be partially dependent on weather. Responses to forecasted CL epidemics may include bolstering clinical capacity and disease surveillance in at-risk areas. Ecological mechanisms by which weather influences CL risk merit future research attention as public health intervention targets.