Evidence map›Paper›PMID 35927739›Full record

ArticleInfectious diseases of poverty2022

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

Maximiliano A Cristaldi, Thibault Catry, Auréa Pottier, Vincent Herbreteau, Emmanuel Roux, Paulina Jacob, M Andrea Previtali

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Article in Infectious diseases of poverty, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

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5citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Maximiliano A CristaldiDepartment of Natural Sciences, College of Humanities and Sciences, National University of Litoral, Santa Fe, Argentina. maximilianocristaldi@yahoo.com.ar.
Thibault CatryESPACE-DEV, French National Research Institute for Sustainable Development (IRD), University of Montpellier, University of French West Indies, University of French Guiana, University of La Reunion, Montpellier, France.
Auréa PottierESPACE-DEV, French National Research Institute for Sustainable Development (IRD), University of Montpellier, University of French West Indies, University of French Guiana, University of La Reunion, Montpellier, France.
Vincent HerbreteauESPACE-DEV, French National Research Institute for Sustainable Development (IRD), University of Montpellier, University of French West Indies, University of French Guiana, University of La Reunion, Montpellier, France.
Emmanuel RouxESPACE-DEV, French National Research Institute for Sustainable Development (IRD), University of Montpellier, University of French West Indies, University of French Guiana, University of La Reunion, Montpellier, France.
Paulina JacobNational Institute of Respiratory Diseases (INER) "Dr. E. Coni"/National Administration of Health Institutes (ANLIS "Dr. C.G. Malbrán"), Santa Fe, Argentina.
M Andrea PrevitaliDepartment of Natural Sciences, College of Humanities and Sciences, National University of Litoral, Santa Fe, Argentina. andrea.previtali@gmail.com.ORCID http://orcid.org/0000-0002-8205-3872

Funding

Agencia Nacional de Promoción de la Investigación, el Desarrollo Tecnológico y la Innovación PICT 2017-4280Universidad Nacional del Litoral CAI+D orientado
6 · The paper itself

Abstract

backgroundLeptospirosis 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.

methodsWe 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.

resultsWe 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).

conclusionsWe 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.

Indexed as

LeptospirosisCitiesCluster AnalysisHumansIncidenceRisk FactorsSocioeconomic FactorsCluster analysisEnvironmental conditionsKnowledge-based indexSocioeconomic groupsSpatial epidemiologyUnderreported misdiagnosed diseases

Identifiers

PMID35927739
PMCPMC9351081

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.