02530nas a2200289   4500000000100000008004100001653003900042653003200081653002400113653001300137653001100150653002000161100001400181700001400195700001300209700001200222700001400234700002900248700001300277700002100290245007700311856007900388300000600467490000700473520174600480022001402226       2019                            d10aNeglected tropical diseases (NTDs)10aVisceral leishmaniasis (VL)10aRisk classification10aBayesian10aBrazil10aDisease mapping1 aMachado G1 aAlvarez J1 aBakka HC1 aPerez A1 aDonato LE1 aFerreira Lima Júnior FE1 aAlves RV1 aDel Rio Vilas VJ00aRevisiting area risk classification of visceral leishmaniasis in Brazil.  uhttps://bmcinfectdis.biomedcentral.com/track/pdf/10.1186/s12879-018-3564-0  a20 v193 a<p><strong>BACKGROUND: </strong>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.</p>

<p><strong>METHODS: </strong>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.</p>

<p><strong>RESULTS: </strong>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.</p>

<p><strong>CONCLUSION: </strong>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.</p>
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