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dc.contributor.author
Cristaldi, Maximiliano Ariel  
dc.contributor.author
Thibault, Catry  
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Pottier, Auréa  
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Herbreteau, Vincent  
dc.contributor.author
Roux, Emmanuel  
dc.contributor.author
Jacob, Paulina  
dc.contributor.author
Previtali, Maria Andrea  
dc.date.available
2023-09-29T11:01:17Z  
dc.date.issued
2022-08  
dc.identifier.citation
Cristaldi, Maximiliano Ariel; Thibault, Catry; Pottier, Auréa; Herbreteau, Vincent; Roux, Emmanuel; et al.; Determining the spatial distribution of environmental and socio-economic suitability for human leptospirosis in the face of limited epidemiological data; BioMed Central; Infectious Diseases of Poverty; 11; 1; 8-2022; 1-19  
dc.identifier.issn
2049-9957  
dc.identifier.uri
http://hdl.handle.net/11336/213531  
dc.description.abstract
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 satellite 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 human leptospirosis based on literature and expert knowledge. The methodology can be thought as an evolutive and perfectible scheme as more studies are performed in the area and novel information regarding determinants of the disease become available. Our approach can be a valuable tool for decision-makers since it can serve as a baseline to plan intervention measures.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
BioMed Central  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by/2.5/ar/  
dc.subject
CLUSTER ANALYSIS  
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ENVIRONMENTAL CONDITIONS  
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KNOWLEDGE-BASED INDEX  
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SOCIOECONOMIC GROUPS  
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SPATIAL EPIDEMIOLOGY  
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UNDERREPORTED MISDIAGNOSED DISEASES  
dc.subject.classification
Enfermedades Infecciosas  
dc.subject.classification
Ciencias de la Salud  
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CIENCIAS MÉDICAS Y DE LA SALUD  
dc.title
Determining the spatial distribution of environmental and socio-economic suitability for human leptospirosis in the face of limited epidemiological data  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2023-07-07T22:14:04Z  
dc.identifier.eissn
2049-9957  
dc.journal.volume
11  
dc.journal.number
1  
dc.journal.pagination
1-19  
dc.journal.pais
Reino Unido  
dc.description.fil
Fil: Cristaldi, Maximiliano Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; Argentina  
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Fil: Thibault, Catry. Université Montpellier II; Francia  
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Fil: Pottier, Auréa. Centre National de la Recherche Scientifique. Institut de Recherche pour le Développement; Francia  
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Fil: Herbreteau, Vincent. Centre National de la Recherche Scientifique. Institut de Recherche pour le Développement; Francia  
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Fil: Roux, Emmanuel. Centre National de la Recherche Scientifique. Institut de Recherche pour le Développement; Francia  
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Fil: Jacob, Paulina. Dirección Nacional de Instituto de Investigación. Administración Nacional de Laboratorios e Instituto de Salud "Dr. C. G. Malbran". Instituto Nacional de Enfermedades Respiratorias; Argentina  
dc.description.fil
Fil: Previtali, Maria Andrea. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina  
dc.journal.title
Infectious Diseases of Poverty  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1186/s40249-022-01010-x