Revisiting area risk classification of visceral leishmaniasis in Brazil

Gustavo Machado, Julio Alvarez, Haakon Christopher Bakka, Andres Perez, Lucas Edel Donato, Francisco Edilson de Ferreira Lima Júnior, Renato Vieira Alves, Victor Javier Del Rio Vilas

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8 Scopus citations


BACKGROUND:Visceral leishmaniasis (VL) is a neglected tropical disease of public health relevance in Brazil. To prioritize disease control measures, the Secretaria de Vigilância em Saúde of Brazil's Ministry of Health (SVS/MH) uses retrospective human case counts from VL surveillance data to inform a municipality-based risk classification. In this study, we compared the underlying VL risk, using a spatiotemporal explicit Bayesian hierarchical model (BHM), with the risk classification currently in use by the Brazil's Ministry of Health. We aim to assess how well the current risk classes capture the underlying VL risk as modelled by the BHM. METHODS:Annual counts of human VL cases and the population at risk for all Brazil's 5564 municipalities between 2004 and 2014 were used to fit a relative risk BHM. We then computed the predicted counts and exceedence risk for each municipality and classified them into four categories to allow comparison with the four risk categories by the SVS/MH. RESULTS:Municipalities identified as high-risk by the model partially agreed with the current risk classification by the SVS/MH. Our results suggest that counts of VL cases may suffice as general indicators of the underlying risk, but can underestimate risks, especially in areas with intense transmission. CONCLUSION:According to our BHM the SVS/MH risk classification underestimated the risk in several municipalities with moderate to intense VL transmission. Newly identified high-risk areas should be further evaluated to identify potential risk factors and assess the needs for additional surveillance and mitigation efforts.
Original languageEnglish (US)
JournalBMC Infectious Diseases
Issue number1
StatePublished - Jan 3 2019

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: Acknowledgements: We would like to thank Serviço de Vigilância em Saúde, Ministério da Saúde (SVS-MOH), Brasília, Brazil. Funding: This study was funded by the Academic Health Center Faculty Research Development Grant Program (FRD #16.36) and CVM-Department of Population Health and Pathobiology- North Carolina State University, Grant/Award Number: Startup fund. The funder had no role in the collation of the data, development of the conceptual framework, analysis of data, interpretation of data, writing of the manuscript, or the decision to submit the paper for publication.


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