Bayesian geostatistical modeling of leishmaniasis incidence in Brazil.

ABSTRACT:

Background

Leishmaniasis is endemic in 98 countries with an estimated 350 million people at risk and approximately 2 million cases annually. Brazil is one of the most severely affected countries.

Methodology

We applied Bayesian geostatistical negative binomial models to analyze reported incidence data of cutaneous and visceral leishmaniasis in Brazil covering a 10-year period (2001-2010). Particular emphasis was placed on spatial and temporal patterns. The models were fitted using integrated nested Laplace approximations to perform fast approximate Bayesian inference. Bayesian variable selection was employed to determine the most important climatic, environmental, and socioeconomic predictors of cutaneous and visceral leishmaniasis.

Principal findings

For both types o

SUBMITTER: Karagiannis-Voules DA 

PROVIDER: S-EPMC3649962 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature