دورية أكاديمية
أعرض في EDS

Data-driven computational intelligence applied to dengue outbreak forecasting: a case study at the scale of the city of Natal, RN-Brazil.

التفاصيل البيبلوغرافية
العنوان: Data-driven computational intelligence applied to dengue outbreak forecasting: a case study at the scale of the city of Natal, RN-Brazil.
المؤلفون: Sanchez-Gendriz I; Laboratory for Technological Innovation in Health (LAIS), Hospital Universitário Onofre Lopes, Federal University of Rio Grande Do Norte (UFRN), Natal, Rio Grande do Norte, Brazil. ignaciogendriz@gmail.com.; Department of Computer Engineering and Automation, UFRN, Natal, Rio Grande do Norte, Brazil. ignaciogendriz@gmail.com., de Souza GF; Advanced Nucleus of Technological Innovation (NAVI), Federal Institute of Rio Grande Do Norte (IFRN), Natal, Rio Grande do Norte, Brazil., de Andrade IGM; Laboratory for Technological Innovation in Health (LAIS), Hospital Universitário Onofre Lopes, Federal University of Rio Grande Do Norte (UFRN), Natal, Rio Grande do Norte, Brazil., Neto ADD; Department of Computer Engineering and Automation, UFRN, Natal, Rio Grande do Norte, Brazil., de Medeiros Tavares A; Municipal Health Department, Zoonoses Control Center, Natal, Rio Grande do Norte, Brazil., Barros DMS; Laboratory for Technological Innovation in Health (LAIS), Hospital Universitário Onofre Lopes, Federal University of Rio Grande Do Norte (UFRN), Natal, Rio Grande do Norte, Brazil., de Morais AHF; Advanced Nucleus of Technological Innovation (NAVI), Federal Institute of Rio Grande Do Norte (IFRN), Natal, Rio Grande do Norte, Brazil., Galvão-Lima LJ; Laboratory for Technological Innovation in Health (LAIS), Hospital Universitário Onofre Lopes, Federal University of Rio Grande Do Norte (UFRN), Natal, Rio Grande do Norte, Brazil., de Medeiros Valentim RA; Laboratory for Technological Innovation in Health (LAIS), Hospital Universitário Onofre Lopes, Federal University of Rio Grande Do Norte (UFRN), Natal, Rio Grande do Norte, Brazil.
المصدر: Scientific reports [Sci Rep] 2022 Apr 21; Vol. 12 (1), pp. 6550. Date of Electronic Publication: 2022 Apr 21.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
أسماء مطبوعة: Original Publication: London : Nature Publishing Group, copyright 2011-
مواضيع طبية MeSH: Aedes* , Dengue*/epidemiology, Animals ; Artificial Intelligence ; Brazil/epidemiology ; Humans ; Mosquito Vectors
مستخلص: Dengue is recognized as a health problem that causes significant socioeconomic impacts throughout the world, affecting millions of people each year. A commonly used method for monitoring the dengue vector is to count the eggs that Aedes aegypti mosquitoes have laid in spatially distributed ovitraps. Given this approach, the present study uses a database collected from 397 ovitraps allocated across the city of Natal, RN-Brazil. The Egg Density Index for each neighborhood was computed weekly, over four complete years (from 2016 to 2019), and simultaneously analyzed with the dengue case incidence. Our results illustrate that the incidence of dengue is related to the socioeconomic level of the neighborhoods in the city of Natal. A deep learning algorithm was used to predict future dengue case incidence, either based on the previous weeks of dengue incidence or the number of eggs present in the ovitraps. The analysis reveals that ovitrap data allows earlier prediction (four to six weeks) compared to dengue incidence itself (one week). Therefore, the results validate that the quantification of Aedes aegypti eggs can be valuable for the early planning of public health interventions.
(© 2022. The Author(s).)
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تواريخ الأحداث: Date Created: 20220422 Date Completed: 20220425 Latest Revision: 20220716
رمز التحديث: 20221213
مُعرف محوري في PubMed: PMC9023501
DOI: 10.1038/s41598-022-10512-5
PMID: 35449179
قاعدة البيانات: MEDLINE
الوصف
تدمد:2045-2322
DOI:10.1038/s41598-022-10512-5