Demographic and socioeconomic determinants of COVID-19 across Oman - A geospatial modelling approach

Autor: Khalifa M. Al Kindi, Adhra Al-Mawali, Amira Akharusi, Duhai Alshukaili, Noura Alnasiri, Talal Al-Awadhi, Yassine Charabi, Ahmed M. El Kenawy
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Geospatial Health, Vol 16, Iss 1 (2021)
Druh dokumentu: article
ISSN: 1827-1987
1970-7096
DOI: 10.4081/gh.2021.985
Popis: Local, bivariate relationships between coronavirus 2019 (COVID-19) infection rates and a set of demographic and socioeconomic variables were explored at the district level in Oman. To limit multicollinearity a principal component analysis was conducted, the results of which showed that three components together could explain 65% of the total variance that were therefore subjected to further study. Comparison of a generalized linear model (GLM) and geographically weighted regression (GWR) indicated an improvement in model performance using GWR (goodness of fit=93%) compared to GLM (goodness of fit=86%). The local coefficient of determination (R2) showed a significant influence of specific demographic and socioeconomic factors on COVID-19, including percentages of Omani and non-Omani population at various age levels; spatial interaction; population density; number of hospital beds; total number of households; purchasing power; and purchasing power per km2. No direct correlation between COVID- 19 rates and health facilities distribution or tobacco usage. This study suggests that Poisson regression using GWR and GLM can address unobserved spatial non-stationary relationships. Findings of this study can promote current understanding of the demographic and socioeconomic variables impacting the spatial patterns of COVID-19 in Oman, allowing local and national authorities to adopt more appropriate strategies to cope with this pandemic in the future and also to allocate more effective prevention resources.
Databáze: Directory of Open Access Journals
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