Spatial dynamics and socioeconomic factors correlated with American cutaneous leishmaniasis in Pernambuco, Brazil from 2008 to 2017

• Autor(a) principal: Gonçalves,Andréa Flávia Luckwü de Santana
• Data de Publicação: 2020
• Outros Autores: Lima,Suzanne Santos de, Silva,Amanda Priscila de Santana Cabral, Barbosa,Celivane Cavalcanti
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista da Sociedade Brasileira de Medicina Tropical
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822020000100317
• topic: Neglected diseases; Cutaneous leishmaniasis; Public health surveillance; Spatial analysis

Abstract INTRODUCTION: American cutaneous leishmaniasis (ACL) is a public health problem and has been associated with country’s territory. We aimed to analyze the spatial dynamics and socioeconomic factors correlated to the incidence of ACL in Pernambuco, Brazil from 2008 to 2017. METHODS: A cross-sectional, ecological study was conducted in the Brazilian municipalities. Patient data were obtained from the Health Hazard Notification System (SINAN); indicators and incidence for the total period and for quinquennium were obtained. Socioeconomic factors were analyzed to evaluate the association between the incidence of ACL and presence of bathroom and running water, garbage collection availability, inadequate water supply, sanitation, rural population, per capita income, and vulnerability to poverty. Spatial analysis considered the gross incidence; the Bayesian local empirical method and Moran spatial autocorrelation index were applied using Terra View and QGIS. RESULTS: The incidence of ACL reduced (0.29/100,000 inhabitants per year). Individuals with ACL were young adults (30.3%), men (60.2%), brown skinned (62.9%), rural residents (70.6%), and less educated (46.7%); had autochthonous transmission (78.8%); developed the cutaneous form (97.2%); had evolution to cure (82.7%); and were diagnosed using the clinical epidemiological criterion (70.5%). ACL occurred in the large part of the state and showed heterogeneous distribution, with persistence of two high priority intervention clusters covering Health Regions I, II, III, IV, and XII. CONCLUSIONS: Spatial analysis and epidemiological indicators complement each other. The combination of these methods can improve the understanding on ACL occurrence, which will help subsidize planning and enhance the quality and effectiveness of healthcare interventions.