title: Forecasting temporal dynamics of cutaneous leishmaniasis in Northeast Brazil.
abstract: BACKGROUND
  Cutaneous leishmaniasis (CL) is a vector-borne disease of increasing importance in northeastern Brazil. It is known that sandflies, which spread the causative parasites, have weather-dependent population dynamics. Routinely-gathered weather data may be useful for anticipating disease risk and planning interventions.
  
  
  RESULTS
  We fit time series models using meteorological covariates to predict CL cases in a rural region of Bahía, Brazil from 1994 to 2004. We used the models to forecast CL cases for the period 2005 to 2008. Models accounting for meteorological predictors reduced mean squared error in one, two, and three month-ahead forecasts by up to 16% relative to forecasts from a null model accounting only for temporal autocorrelation.
  
  
  CONCLUSIONS
  These outcomes suggest CL risk in northeastern Brazil might be partially dependent on weather. Responses to forecasted CL epidemics may include bolstering clinical capacity and disease surveillance in at-risk areas. Ecological mechanisms by which weather influences CL risk merit future research attention as public health intervention targets.
authors.affiliation: Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America.
authors.forename: Joseph A
authors.initials: JA
authors.lastname: Lewnard
authors.affiliation: Serviço de Imunologia, Hospital Universitário Prof. Edgard Santos, Universidade Federal da Bahía, Salvador, Brazil; Center for Women's Health and Gender Biology, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
authors.forename: Lara
authors.initials: L
authors.lastname: Jirmanus
authors.affiliation: Centro de Pesquisas Gonçalo Moniz, Fundação Oswaldo Cruz, Ministério da Saúde, Salvador, Brazil.
authors.forename: Nivison Nery
authors.initials: NN
authors.lastname: Júnior
authors.affiliation: Serviço de Imunologia, Hospital Universitário Prof. Edgard Santos, Universidade Federal da Bahía, Salvador, Brazil.
authors.forename: Paulo R
authors.initials: PR
authors.lastname: Machado
authors.affiliation: Division of Infectious Diseases, Weill Cornell Medical College, New York, New York, United States of America.
authors.forename: Marshall J
authors.initials: MJ
authors.lastname: Glesby
authors.affiliation: Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America; Centro de Pesquisas Gonçalo Moniz, Fundação Oswaldo Cruz, Ministério da Saúde, Salvador, Brazil.
authors.forename: Albert I
authors.initials: AI
authors.lastname: Ko
authors.affiliation: Serviço de Imunologia, Hospital Universitário Prof. Edgard Santos, Universidade Federal da Bahía, Salvador, Brazil.
authors.forename: Edgar M
authors.initials: EM
authors.lastname: Carvalho
authors.affiliation: Serviço de Imunologia, Hospital Universitário Prof. Edgard Santos, Universidade Federal da Bahía, Salvador, Brazil.
authors.forename: Albert
authors.initials: A
authors.lastname: Schriefer
authors.affiliation: Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America.
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Weinberger
mesh_terms: D000818:Animals; D001938:Brazil / Q000453:epidemiology; D004463:Ecology; D006801:Humans; D016773:Leishmaniasis, Cutaneous / Q000453:epidemiology* / Q000635:transmission; D015233:Models, Statistical; D011157:Population Dynamics; D011576:Psychodidae; D011634:Public Health; D014887:Weather