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Entomological indicators associated with other biotic and abiotic parameters can assertively characterize the spatiotemporal trends related to dengue transmission risk. However, the unpredictability of the non-linear nature of the data, as well as the uncertainty and subjectivity inherent in biological data are often neglected in conventional models.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>As an alternative for analyzing dengue-related data, we devised a fuzzy-logic approach to test ensembles of these indicators across categories, which align with the concept of degrees of truth to characterize the success of dengue transmission by <jats:italic>Aedes aegypti<\/jats:italic> mosquitoes in an endemic city in Brazil. We used locally gathered entomological, demographic, environmental and epidemiological data as input sources using freely available data on digital platforms. The outcome variable, risk of transmission, was aggregated into three categories: low, medium, and high. Spatial data was georeferenced and the defuzzified values were interpolated to create a map, translating our findings to local public health managers and decision-makers to direct further vector control interventions.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The classification of low, medium, and high transmission risk areas followed a seasonal trend expected for dengue occurrence in the region. The fuzzy approach captured the 2020 outbreak, when only 14.06% of the areas were classified as low risk. The classification of transmission risk based on the fuzzy system revealed effective in predicting an increase in dengue transmission, since more than 75% of high-risk areas had an increase in dengue incidence within the following 15 days.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>Our study demonstrated the ability of fuzzy logic to characterize the city\u2019s spatiotemporal heterogeneity in relation to areas at high risk of dengue transmission, suggesting it can be considered as part of an integrated surveillance system to support timely decision-making.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12889-024-19942-4","type":"journal-article","created":{"date-parts":[[2024,9,27]],"date-time":"2024-09-27T11:02:41Z","timestamp":1727434961000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["The fuzzy system ensembles entomological, epidemiological, demographic and environmental data to unravel the dengue transmission risk in an endemic city"],"prefix":"10.1186","volume":"24","author":[{"given":"Andr\u00e9","family":"de Souza Leandro","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Felipe","family":"de Oliveira","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Renata Defante","family":"Lopes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"A\u00e7ucena Veleh","family":"Rivas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caroline Amaral","family":"Martins","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isaac","family":"Silva","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel A. 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Therefore, all medical staff working in the 48161 public health units and 4466 private hospitals distributed across the country must report disease occurrence. By corollary, the original data collection does not require IRB approval. The work presented herein uses only secondary data. The Ministry of Health Legislation (Law 66, from December 10th, 2004) establishes the procedures and responsibilities relating to the technical-scientific dissemination of data and information from the Health Surveillance Secretariat - SVS\/MS. Since the co-authors ASL, RDL, and IS are civil servants as public health managers of the city of Foz do Igua\u00e7u, among their professional routine duties is access and analyze disease occurrence within the city. Thus, permission to access secondary data regarding disease occurrence for surveillance purposes is granted to those co-authors. Therefore, considering both Federal and Local legislations, there is no need to request consent to participate.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"2587"}}