International Journal of Epidemiology, Vol 28, 982-989, Copyright © 1999 by International Epidemiological Association
GL Machado-Coelho, R Assuncao, W Mayrink and WT Caiaffa
BACKGROUND: American cutaneous leishmaniasis (ACL) is endemic in many rural
areas of Brazil where different transmission patterns of the disease have
been described. This ecological study was carried out in a municipality
located in Southeast Brazil and aimed to investigate the space-temporal
patterns of the disease and environmental risk factors from 1966 to 1996.
METHODS: Incident ACL cases were defined by clinical diagnosis, confirmed
by a positive skin test and/or parasitological examination. Age-adjusted
morbidity rate of ACL was calculated by year for this municipality and
their different census enumeration districts. The homogeneity chi2 test,
Moran and empirical Bayes index and Knox procedure were employed for
testing the significance of clusters in time, space and in time-space,
respectively. A Poisson regression model was used to identify environmental
factors related to rate variability. RESULTS: A total of 1712 new ACL cases
were reported with a yearly incidence rate of 48/100000 inhabitants. Higher
incidence rates were detected in 1968, 1974, and 1988 (100, 160, and 190
cases/100000, respectively) with evidence of spatial clustering from 1986
to 1993. Significant space-time clustering with epidemic peaks followed by
low incidence in subsequent periods was observed. The incidence rates of
ACL were independently associated with rural areas; areas lacking sanitary
installations and with higher proportion of exposed garbage (P < 0.01).
CONCLUSIONS: This study suggests that ACL rates vary across space and time.
Rural areas and some environmental factors could explain part of this
variation. Environmental modifications in the vicinity of households over
time and accumulation of susceptible individuals are discussed as possible
factors responsible for variability.
ARTICLES
American cutaneous leishmaniasis in Southeast Brazil: space-time clustering
Department of Pharmacy, Federal University of Ouro Preto, Minas Gerais, Brazil. gmcoelho@ef.ufop.br
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