دورية أكاديمية
Joint spatial modeling of the risks of co-circulating mosquito-borne diseases in Ceará, Brazil.
| العنوان: | Joint spatial modeling of the risks of co-circulating mosquito-borne diseases in Ceará, Brazil. |
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| المؤلفون: | Pavani J; Department of Statistics, Pontificia Universidad Católica de Chile, Santiago, Chile. Electronic address: jlpavani@mat.uc.cl., Bastos LS; Scientific Computing Program, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil., Moraga P; Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. |
| المصدر: | Spatial and spatio-temporal epidemiology [Spat Spatiotemporal Epidemiol] 2023 Nov; Vol. 47, pp. 100616. Date of Electronic Publication: 2023 Aug 25. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Country of Publication: Netherlands NLM ID: 101516571 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1877-5853 (Electronic) Linking ISSN: 18775845 NLM ISO Abbreviation: Spat Spatiotemporal Epidemiol Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: Amsterdam : Elsevier, 2009- |
| مواضيع طبية MeSH: | Chikungunya Fever*/epidemiology , Dengue*/epidemiology , Zika Virus Infection*/epidemiology, Animals ; Humans ; Brazil/epidemiology ; Bayes Theorem |
| مستخلص: | Mosquito-borne diseases such as dengue and chikungunya have been co-circulating in the Americas, causing great damage to the population. In 2021, for instance, almost 1.5 million cases were reported on the continent, being Brazil the responsible for most of them. Even though they are transmitted by the same mosquito, it remains unclear whether there exists a relationship between both diseases. In this paper, we model the geographic distributions of dengue and chikungunya over the years 2016 to 2021 in the Brazilian state of Ceará. We use a Bayesian hierarchical spatial model for the joint analysis of two arboviruses that includes spatial covariates as well as specific and shared spatial effects that take into account the potential autocorrelation between the two diseases. Our findings allow us to identify areas with high risk of one or both diseases. Only 7% of the areas present high relative risk for both diseases, which suggests a competition between viruses. This study advances the understanding of the geographic patterns and the identification of risk factors of dengue and chikungunya being able to help health decision-making. Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2023 Elsevier Ltd. All rights reserved.) |
| فهرسة مساهمة: | Keywords: Bayesian inference; Chikungunya fever; Dengue fever; Disease mapping; INLA; Spatial modeling |
| تواريخ الأحداث: | Date Created: 20231202 Date Completed: 20231204 Latest Revision: 20240119 |
| رمز التحديث: | 20240119 |
| DOI: | 10.1016/j.sste.2023.100616 |
| PMID: | 38042535 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 1877-5853 |
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| DOI: | 10.1016/j.sste.2023.100616 |