The ecological determinants of severe dengue: A Bayesian inferential model

Esther Annan, Moeen Hamid Bukhari, Jesus Trevino, Zahra Shakeri Hossein Abad, Jailos Lubinda, Eduardo A. B. da Silva, Ubydul Haque

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Low socioeconomic status (SES), high temperature, and increasing rainfall patterns are associated with increased dengue case counts. However, the effect of climatic variables on individual dengue virus (DENV) serotypes and the extent to which serotype count affects the rate of severe dengue in Mexico have not been studied before. A principal components analysis was used to determine the poverty indices across Mexico. Conditional autoregressive Bayesian models were used to determine the effect of poverty and climatic variables on the rate of serotype distribution and severe dengue in Mexico. A unit increase in poverty increased the rate of DENV-1, DENV-2, DENV-3, and DENV-4 by 8.4%, 5%, 16%, and 13.8% respectively. An increase in one case attributable to DENV-1, DENV-2, DENV-3, and DENV-4 was independently associated with an increase in the rate of severe dengue by 0.02%, 0.1%, 0.03%, and 5.8% respectively. Hotspots of all DENV serotypes and severe dengue are found mostly in parts of the Northeastern, Center west, and Southeastern regions of Mexico. The association between climatic parameters predominant in the Southeast region and severe dengue leaves several states in this region at an increased risk of a higher number of severe dengue cases. Our study's results may guide policies that help allocate public health resources to the most vulnerable municipalities in Mexico.
Original languageEnglish
Article number101986
Number of pages8
JournalEcological Informatics
Volume74
Early online dateJan 2023
DOIs
Publication statusPublished - May 2023

Fingerprint

Dive into the research topics of 'The ecological determinants of severe dengue: A Bayesian inferential model'. Together they form a unique fingerprint.

Cite this