Revisiting area risk classification of visceral leishmaniasis in Brazil
Artículo de investigación publicado en BMC Infectious Diseases
3 de enero de 2019
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.
Keywords: Visceral leishmaniasis, Brazil, Disease mapping, Bayesian, Risk classification
Machado G., Alvarez J., Bakka HC., Perez AM., Donato LE., de Ferreira Lima FE., Vieria-Alves R. y del Rio Vilas VJ.
 | Department of Population Health and Pathobiology. College of Veterinary Medicine. North Carolina State University (NCSU). |
 | Servicio de Zoonosis Emergentes, de Baja Prevalencia y Agresivos Biológicos (NED). Centro de Vigilancia Sanitaria Veterinaria (VISAVET). Universidad Complutense (UCM). |
| Departamento de Sanidad Animal. Facultad de Veterinaria. Universidad Complutense (UCM). |
 | CEMSE Division. King Abdullah University of Science and Technology. |
 | Department of Veterinary Population Medicine. College of Veterinary Medicine. University of Minnesota (UMM). |
 | Secretaria de Vigilância em Saúde. Ministério da Saúde. Governo do Brasil. |
 | School of Veterinary Medicine. Faculty of Health and Medical Sciences. University of Surrey. |
