Multiplicative Mixed-Effects Modelling of Dengue Incidence: An Analysis of the 2019 Outbreak in the Dominican Republic

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dc.contributor.authorFreitas, Adelaideen
dc.contributor.authorRodrigues, Helena Sofiaen
dc.contributor.authorMartins, Natáliaen
dc.contributor.authorIutis, Adelaen
dc.contributor.authorRobert, Michael A.en
dc.contributor.authorHerrera, Demianen
dc.contributor.authorColomé-Hidalgo, Manuelen
dc.coverage.countryDominican Republicen
dc.date.accessioned2023-02-10T14:45:28Zen
dc.date.available2023-02-10T14:45:28Zen
dc.date.issued2023-02-01en
dc.date.updated2023-02-10T14:28:43Zen
dc.description.abstractDengue is a vector-borne disease that is endemic to several countries, including the Dominican Republic, which has experienced dengue outbreaks for over four decades. With outbreaks growing in incidence in recent years, it is becoming increasingly important to develop better tools to understand drivers of dengue transmission. Such tools are critical for providing timely information to assist healthcare authorities in preparing human, material, and medical resources for outbreaks. Here, we investigate associations between meteorological variables and dengue transmission in the Dominican Republic in 2019, the year in which the country’s largest outbreak to date ocurred. We apply generalized linear mixed modelling with gamma family and log link to model the weekly dengue incidence rate. Because correlations in lags between climate variables and dengue cases exhibited different behaviour among provinces, a backward-type selection method was executed to find a final model with lags in the explanatory variables. We find that in the best models, meteorological conditions such as temperature and rainfall have an impact with a delay of 2–5 weeks in the development of an outbreak, ensuring breeding conditions for mosquitoes.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationFreitas, A.; Rodrigues, H.S.; Martins, N.; Iutis, A.; Robert, M.A.; Herrera, D.; Colomé-Hidalgo, M. Multiplicative Mixed-Effects Modelling of Dengue Incidence: An Analysis of the 2019 Outbreak in the Dominican Republic. Axioms 2023, 12, 150.en
dc.identifier.doihttps://doi.org/10.3390/axioms12020150en
dc.identifier.urihttp://hdl.handle.net/10919/113780en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectdengueen
dc.subjectDominican Republicen
dc.subjectclimate variablesen
dc.subjectlagsen
dc.subjectgeneralized linear mixed modelsen
dc.titleMultiplicative Mixed-Effects Modelling of Dengue Incidence: An Analysis of the 2019 Outbreak in the Dominican Republicen
dc.title.serialAxiomsen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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Journal Articles, Multidisciplinary Digital Publishing Institute (MDPI)
Scholarly Works, Center for Emerging, Zoonotic, and Arthropod-borne Pathogens (CeZAP)
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