Bayesian spatial modeling of COVID-19 case-fatality rate inequalities
DOI
https://doi.org/10.1016/j.sste.2022.100494
Document Type
Article
Publication Date
6-1-2022
Publication Title
Spatial and Spatio-temporal Epidemiology
Abstract
The ongoing outbreak of COVID-19 challenges the health systems and epidemiological responses of all countries worldwide. Although preventive measures have been globally considered, the spatial heterogeneity of its effectiveness is evident, underscoring global health inequalities. Using Bayesian-based Markov chain Monte Carlo simulations, we identify the spatial association of socioeconomic factors and the risk for dying from COVID-19 in Colombia. We confirm that from March 16 to October 04, 2020, the COVID-19 case-fatality rate and the multidimensional poverty index have a heterogeneous spatial distribution. Spatial analysis reveals that the risk of dying from COVID-19 increases in regions with a higher proportion of poor people with dwelling (RR 1.74 95%CI = 1.54–9.75), educational (RR 1.69 95%CI = 1.36–5.94), childhood/youth (RR 1.35 95%CI = 1.08–4.03), and health (RR 1.16 95%CI = 1.06–2.04) deprivations. These findings evidence the vulnerability of most disadvantaged members of society to dying in a pandemic and assist the spatial planning of preventive strategies focused on vulnerable communities.
Volume
41
ISSN
18775845
Recommended Citation
Polo, Gina; Soler-Tovar, Diego; Villamil Jimenez, Luis Carlos; Benavides-Ortiz, Efraín; and Mera Acosta, Carlos, "Bayesian spatial modeling of COVID-19 case-fatality rate inequalities" (2022). Scopus Unisalle. 749.
https://ciencia.lasalle.edu.co/scopus_unisalle/749
PubMed ID
35691638
Identifier
85127365151 (Scopus)