Interaction between environmental and socioeconomic determinants for cutaneous leishmaniasis risk in Latin America

• Published in: Revista Panamericana de Salud Pública
• Main Authors: Ana Nilce. S. Maia-Elkhoury, Daniel Magalhães Lima, Oscar Daniel Salomón, Lia Puppim Buzanovsky, Martha Idalí Saboyá-Díaz, Samantha Y.O.B. Valadas, Manuel J. Sanchez-Vazquez
• Format: Article in Journal/Newspaper
• Language: English; Spanish; Portuguese
• Published: Pan American Health Organization 2021
• Subjects: cutaneous leishmaniasis; cluster analysis; latin america; Medicine; R; Arctic medicine. Tropical medicine; RC955-962; Public aspects of medicine; RA1-1270; Arctic
• Online Access: https://doi.org/10.26633/RPSP.2021.83; https://doaj.org/article/d1b54ffe8364439889299afd68804f7f

Objective. Determine and characterize potential risk areas for the occurrence of cutaneous leishmaniasis (CL) in Latin America (LA). Method. Ecological observational study with observation units defined by municipalities with CL transmission between 2014-2018. Environmental and socioeconomic variables available for at least 85% of the municipalities were used, combined in a single database, utilizing the R software. The principal component analysis methodology was combined with a hierarchical cluster analysis to group clusters of municipalities based on their similarity. The V-test was estimated to define the positive or negative association of the variables with the clusters and separation by natural breaks was used to determine which ones contributed the most to each cluster. Information on cases was also incorporated in the analyses to attribute CL risk for each cluster. Results. This study included 4,951 municipalities with CL transmission (36.5% of the total in LA) and seven clusters were defined by their association with 18 environmental and socioeconomic variables. The historical risk of CL is positively associated with the Amazonian, Andean and Savannah clusters in a decreasingly manner; and negatively associated with the Forest evergreen, Forest/crop and Forest/populated clusters. The Agricultural cluster did not reveal any association with the CL cases. Conclusions. The study made it possible to identify and characterize the CL risk by clusters of municipalities and to recognize the epidemiological distribution pattern of transmission, which provides managers with better information for intersectoral interventions to control CL.