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Multilevel modelling of the incidence of visceral leishmaniasis in Teresina, Brazil

  • G. L. WERNECK (a1) (a2), C. H. N. COSTA (a3), A. M. WALKER (a4), J. R. DAVID (a1), M. WAND (a5) and J. H. MAGUIRE (a1)
  • DOI:
  • Published online: 01 July 2006

Epidemics of visceral leishmaniasis (VL) in major Brazilian cities are new phenomena since 1980. As determinants of transmission in urban settings probably operate at different geographic scales, and information is not available for each scale, a multilevel approach was used to examine the effect of canine infection and environmental and socio-economic factors on the spatial variability of incidence rates of VL in the city of Teresina. Details on an outbreak of greater than 1200 cases of VL in Teresina during 1993–1996 were available at two hierarchical levels: census tracts (socio-economic characteristics, incidence rates of human VL) and districts, which encompass census tracts (prevalence of canine infection). Remotely sensed data obtained by satellite generated environmental information at both levels. Data from census tracts and districts were analysed simultaneously by multilevel modelling. Poor socio-economic conditions and increased vegetation were associated with a high incidence of human VL. Increasing prevalence of canine infection also predicted a high incidence of human VL, as did high prevalence of canine infection before and during the epidemic. Poor socio-economic conditions had an amplifying effect on the association between canine infection and the incidence of human VL. Focusing interventions on areas with characteristics identified by multilevel analysis could be a cost-effective strategy for controlling VL. Because risk factors for infectious diseases operate simultaneously at several levels and ecological data usually are available at different geographical scales, multilevel modelling is a valuable tool for epidemiological investigation of disease transmission.

Corresponding author
Instituto de Medicina Social/IMS, Departamento de Epidemiologia, Universidade do Estado do Rio de Janeiro (UERJ), Rua São Francisco Xavier 524, 70 andar, Bloco D, Maracanã, Rio de Janeiro, RJ, Brazil 20559-900. (Email:
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Epidemiology & Infection
  • ISSN: 0950-2688
  • EISSN: 1469-4409
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