Background: The physical characteristics of the environment influence the composition, distribution and behavior of the vectors and mammalian hosts involved in the transmission of visceral leishmaniasis (VL), thereby affecting the epidemiology of the disease. In Brazil, urbanization of human VL is a recent phenomenon and represents an issue of particular concern to local health authorities. The present study aimed to establish the degree of spatial dependency between canine and human VL in the municipality of Divinópolis, Minas Gerais, Brazil, and to identify priority risk areas in which stricter control measures should be implemented.
Methods: The selected canine population comprised 3,652 dogs distributed within 11 strata and 1,247 urban blocks. Serum samples were collected between March 2013 and February 2014. Serodiagnosis of dogs was performed using the enzyme-linked immunosorbent assay and the indirect fluorescent-antibody test. The blocks sampled for canine VL and the addresses of the 16 confirmed cases of human VL notified in Divinópolis during the period 2007-2013 were georeferenced. Spatial analysis of the data was performed using Kernel density estimation, Ripley's bivariate K-function and directional distribution methods.
Results: The overall prevalence of seropositive animals was 4.63% (range 3.95-5.31) (n =169) and varied in different strata between 0.9 (range 0.0-1.91) and 8.73% (range 5.65-11.81). A positive spatial dependency was detected between human and canine VL in which the occurrence of human cases of the disease tended to concentrate in locations that were close to areas with a higher incidence of canine VL. The priority risk area could be clearly distinguished from Kernel density estimation and standard deviational ellipse plots in which the human VL ellipse was totally enclosed within the canine VL ellipse.
Conclusions: The results presented herein will enable the Municipal Health Office of Divinópolis to devise a more effective management plan for human VL in which specific strategies would be applied to areas presenting different levels of risk. This spatial evaluation of leishmaniasis model could be applied in other urban areas of Brazil.