{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T17:16:23Z","timestamp":1790010983719,"version":"4.0.1"},"reference-count":28,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2014,10,10]],"date-time":"2014-10-10T00:00:00Z","timestamp":1412899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Leptospirosis displays a great diversity of routes of exposure, reservoirs, etiologic agents, and clinical symptoms. It occurs almost worldwide but its pattern of transmission varies depending where it happens. Climate change may increase the number of cases, especially in developing countries, like Brazil. Spatial analysis studies of leptospirosis have highlighted the importance of socioeconomic and environmental context. Hence, the choice of the geographical scale and unit of analysis used in the studies is pivotal, because it restricts the indicators available for the analysis and may bias the results. In this study, we evaluated which environmental and socioeconomic factors, typically used to characterize the risks of leptospirosis transmission, are more relevant at different geographical scales (i.e., regional, municipal, and local). Geographic Information Systems were used for data analysis. Correlations between leptospirosis incidence and several socioeconomic and environmental indicators were calculated at different geographical scales. At the regional scale, the strongest correlations were observed between leptospirosis incidence and the amount of people living in slums, or the percent of the area densely urbanized. At the municipal scale, there were no significant correlations. At the local level, the percent of the area prone to flooding best correlated with leptospirosis incidence.<\/jats:p>","DOI":"10.3390\/ijerph111010366","type":"journal-article","created":{"date-parts":[[2014,10,10]],"date-time":"2014-10-10T10:24:07Z","timestamp":1412936647000},"page":"10366-10383","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":43,"title":["Geographical Scale Effects on the Analysis of  Leptospirosis Determinants"],"prefix":"10.3390","volume":"11","author":[{"given":"Renata","family":"Gracie","sequence":"first","affiliation":[{"name":"FIOCRUZ, ICICT\/LIS, N\u00facleo de Geoprocessamento, Avenida Brasil, 4365 Pavilh\u00e3o Haity Moussatch\u00e9, sala 231, Rio de Janeiro 21045-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christovam","family":"Barcellos","sequence":"additional","affiliation":[{"name":"FIOCRUZ, ICICT\/LIS, N\u00facleo de Geoprocessamento, Avenida Brasil, 4365 Pavilh\u00e3o Hai ty Moussatch\u00e9, sala 231- Manguinhos, Rio de Janeiro 21045-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M\u00f4nica","family":"Magalh\u00e3es","sequence":"additional","affiliation":[{"name":"FIOCRUZ, ICICT\/LIS, N\u00facleo de Geoprocessamento, Avenida Brasil, 4365 Pavilh\u00e3o Hai ty Moussatch\u00e9, sala 231- Manguinhos, Rio de Janeiro 21045-900, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Reinaldo","family":"Souza-Santos","sequence":"additional","affiliation":[{"name":"FIOCRUZ, ENSP\/DENSP, Rua Leopoldo Bulh\u00f5es, 1480 ENSP, sala 607\u2014Manguinhos, Rio de Janeiro, ENSP 21041-210, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paulo","family":"Barrocas","sequence":"additional","affiliation":[{"name":"FIOCRUZ, ENSP\/DSSA, Rua Leopoldo Bulh\u00f5es, 1480 ENSP, sala 521\u2014Manguinhos, Rio de Janeiro 21041-210, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2014,10,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Vinetz, J.M. 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