High seroprevalence and peripheral spatial distribution of visceral leishmaniasis among domestic dogs in an emerging urban focus in Central Brazil: a cross-sectional study

Abstract

The Brazilian municipality of Rondonópolis is an emerging urban focus of intense transmission of visceral leishmaniasis (VL), where few investigations have addressed canine reservoirs. This study assessed the seroprevalence and spatial distribution of canine visceral leishmaniasis (CVL) in the urban area of Rondonópolis. A CVL serosurvey was conducted between October 2016 and February 2017 using an immunochromatographic rapid test and enzyme-linked immunosorbent assay. Domestic dogs were sampled from 25 heterogeneous regions previously defined by the Spatial ‘K’luster Analysis by Tree Edge Removal algorithm, which considered the socioeconomic and environmental features from the last demographic census. The CVL spatial distribution was analyzed by kernel density estimation (KDE) and spatial scan statistic. All the  autochthonous human VL cases reported between 2014 and 2016 were georeferenced. Of the 600 dogs tested, 115 were seropositive in both tests. The overall CVL prevalence was 19.2% (95%CI: 16.1–22.3%), which varied widely among the evaluated regions (0.0–35.1%). Almost 25% of the sampled households (n = 405) had at least one infected dog. KDE demonstrated that positive CVL households were concentrated in the peripheral areas of the city. Spatial scan statistics detected a spatial cluster with significantly low CVL prevalence in the central region (relative risk = 0.37; p = 0.04), where only one human VL case was reported. Thus, we demonstrated a high prevalence of CVL in domestic dogs from diverse socioeconomic and environmental urban contexts in Rondonópolis. The CVL cases were peripherally distributed and occurred more frequently in areas that had reported human VL.

Keywords:

• Visceral leishmaniasis
• Leishmania infantum
• dogs
• seroprevalence
• spatial analysis
• epidemiology
• disease control
• Brazil

Acknowledgments

The authors are grateful to the Municipal Health Department of Rondonópolis, especially the Environmental Surveillance Division (Zoonosis Control Center) and Epidemiological Surveillance Sector, for their cooperation, dedication, and support in data collection, as well as for providing the digital georeferenced database of neighborhoods.