Dimitrios-Alexios Karagiannis-Voules|Ronaldo Guilherme Carvalho Scholte|Luiz Henrique Guimarães|Jürg Utzinger|Penelope Vounatsou
Bayesian Geostatistical Modeling of Leishmaniasis Incidence in Brazil
University of Basel|Swiss Tropical and Public Health Institute|University of Basel|Swiss Tropical and Public Health Institute|Fundação Oswaldo Cruz|Complexo Hospitalar Universitário Professor Edgard Santos|Universidade Federal da Bahia|University of Basel|Swiss Tropical and Public Health Institute|University of Basel|Swiss Tropical and Public Health Institute
background leishmaniasis endemic 98 countries estimated 350 million people risk approximately 2 million cases annually brazil one severely affected countries methodology applied bayesian geostatistical negative binomial models analyze reported incidence data cutaneous visceral leishmaniasis brazil covering 10year period 20012010 particular emphasis placed spatial temporal patterns models fitted using integrated nested laplace approximations perform fast approximate bayesian inference bayesian variable selection employed determine important climatic environmental socioeconomic predictors cutaneous visceral leishmaniasis principal findings types leishmaniasis precipitation socioeconomic proxies identified important risk factors predicted number cases 2010 30189 standard deviation sd 7676 cutaneous leishmaniasis 4889 sd 288 visceral leishmaniasis risk maps predicted highest numbers infected people states minas gerais par visceral cutaneous leishmaniasis respectively conclusionssignificance spatially explicit highresolution incidence maps identified priority areas leishmaniasis control efforts targeted ultimate goal reduce disease incidence