title: Application of spatio-temporal scan statistics for the detection of areas with increased risk for American visceral leishmaniasis in the state of Bahia, Brazil.
abstract: Mirroring the global increase of registered cases of American visceral leishmaniasis (AVL), this infection has become a growing public health problem in Brazil during the last several years. As the traditional approach to control employed by the governmental health agencies has failed to reduce the incidence and epidemic outbreaks of this illness, we propose a re-evaluation of the national strategy of intervention and monitoring. Our thinking is based on a series of spatio-temporal scan statistics of the west-central region of the state of Bahia covering the 11-year period from 1994 to 2004. By analyzing the situation, spatially and temporally, we show that the disease is a not only a growing focal threat but that it is also appearing in the form of endemic clusters in the cities. The areas where the disease has been found have been classified according to the degree of risk of infection for humans and canines. The overall objective of this study was to identify areas of increased risk of AVL, including its seasonality, and to suggest ways and means to improve the detection of the disease. The findings presented here should not only be of interest for the efforts to control AVL in the study area but also be useful for developing control strategies in other endemic regions of Brazil.
authors.affiliation: School of Veterinary Medicine, Federal University of Bahia, Salvador, Brazil. ddmtc@msn.com
authors.forename: Deborah D M T
authors.initials: DD
authors.lastname: Carneiro
authors.forename: Maria E
authors.initials: ME
authors.lastname: Bavia
authors.forename: Washington J S F
authors.initials: WJ
authors.lastname: Rocha
authors.forename: Antônio C Q
authors.initials: AC
authors.lastname: Tavares
authors.forename: Luciana L
authors.initials: LL
authors.lastname: Cardim
authors.forename: Biruk
authors.initials: B
authors.lastname: Alemayehu
mesh_terms: D000818:Animals; D001938:Brazil / Q000453:epidemiology; D003710:Demography; D019353:Endemic Diseases; D005260:Female; D005843:Geography / Q000706:statistics & numerical data; D006801:Humans; D007893:Leishmania donovani; D007898:Leishmaniasis, Visceral / Q000453:epidemiology* / Q000517:prevention & control; D008297:Male; D018570:Risk Assessment