Determining the spatial distribution of environmental and socio-economic suitability for human leptospirosis in the face of limited epidemiological data  

作　　者：Maximiliano A.Cristaldi Thibault Catry Aurea Pottier Vincent Herbreteau Emmanuel Roux Paulina Jacob M.Andrea Previtali 

机构地区：[1]Department of Natural Sciences,College of Humanities and Sciences,National University of Litoral,Santa Fe,Argentina [2]不详

出　　处：《Infectious Diseases of Poverty》2022年第4期99-100,共2页贫困所致传染病（英文）

摘　　要：Background:Leptospirosis is among the leading zoonotic causes of morbidity and mortality worldwide.Knowledge about spatial patterns of diseases and their underlying processes have the potential to guide intervention efforts.However,leptospirosis is often an underreported and misdiagnosed disease and consequently,spatial patterns of the disease remain unclear.In the absence of accurate epidemiological data in the urban agglomeration of Santa Fe,we used a knowledge-based index and cluster analysis to identify spatial patterns of environmental and socioeconomic suitability for the disease and potential underlying processes that shape them.Methods:We geocoded human leptospirosis cases derived from the Argentinian surveillance system during the period 2010 to 2019.Environmental and socioeconomic databases were obtained from satelite images and publicly available platforms on the web.Two sets of human leptospirosis determinants were considered according to the level of their support by the literature and expert knowledge.We used the Zonation algorithm to build a knowledge-based index and a clustering approach to identify distinct potential sets of determinants.Spatial similarity and correlations between index,clusters,and incidence rates were evaluated.Results:We were able to geocode 56.36%of the human leptospirosis cases reported in the national epidemiological database.The knowledge-based index showed the suitability for human leptospirosis in the UA Santa Fe increased from downtown areas of the largest cities towards peri-urban and suburban areas.Cluster analysis revealed downtown areas were characterized by higher levels of socioeconomic conditions.Peri-urban and suburban areas encompassed two clusters which differed in terms of environmental determinants.The highest incidence rates overlapped areas with the highest suitability scores,the strength of association was low though(CSc r=0.21,P<0.001 and ESc r=0.19,P<0.001).Conclusions:We present a method to analyze the environmental and socioeconomic suitability for hu

关 键 词：Spatial epidemiology Underreported misdiagnosed diseases Environmental conditions Socioeconomic groups Knowledge-based index Cluster analysis 

分 类 号：R181[医药卫生—流行病学]