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

Autor:	Al Kindi KM; Geography Department, College of Arts and Social Sciences, Sultan Qaboos University, Muscat. alkindi.km@yahoo.com., Al-Mawali A; Director/Centre of Studies and Research, Ministry of Health, Muscat. adhra.almawali@gmail.com., Akharusi A; Physiology Department, College of Medicine and Health Sciences, Sultan Qaboos University, Muscat. akharusi@squ.edu.om., Alshukaili D; University of Technology and Applied Sciences, Nizwa. duhai.alshukaili@nct.edu.om., Alnasiri N; Geography Department, College of Arts and Social Sciences, Sultan Qaboos University, Muscat, Oman; Center for Environmental Studies and Research, Muscat. noura@squ.edu.om., Al-Awadhi T; Geography Department, College of Arts and Social Sciences, Sultan Qaboos University, Muscat. alawadhi@squ.edu.om., Charabi Y; Geography Department, College of Arts and Social Sciences, Sultan Qaboos University, Muscat, Oman; Center for Environmental Studies and Research, Muscat. yassine@squ.edu.om., El Kenawy AM; Geography Department, College of Arts and Social Sciences, Sultan Qaboos University, Muscat, Oman; Department of Geography, Mansoura University, Mansoura. akenawy@squ.edu.om.
Jazyk:	angličtina
Zdroj:	Geospatial health [Geospat Health] 2021 May 14; Vol. 16 (1). Date of Electronic Publication: 2021 May 14.
DOI:	10.4081/gh.2021.985
Abstrakt:	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:	MEDLINE
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