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Geospatial Health 2021; volume 16:985 Demographic and socioeconomic determinants of COVID-19 across Oman - A geospatial modelling approach Khalifa M. Al Kindi,1 Adhra Al-Mawali,2 Amira Akharusi,3 Duhai Alshukaili,4 Noura Alnasiri,1,5 Talal Al-Awadhi,1 Yassine Charabi,1,5 Ahmed M. El Kenawy1,6 1Geography Department, College of Arts & Social Sciences, Sultan Qaboos University, Muscat, Oman; 2Director/Centre of Studies & Research, Ministry of Health, Muscat, Sultanate of Oman; 3Physiology Department, College of Medicine & Health Sciences, Sultan Qaboos University, Muscat, Oman; 4University of Technology & Applied Sciences, Nizwa, Oman; 5Center for Environmental Studies & Research, Muscat, Oman; 6Department of Geography, Mansoura University, Mansoura, Egypt (GLM) and geographically weighted regression (GWR) indicated Abstract an improvement in model performance using GWR (goodness of fit=93%) compared to GLM (goodness of fit=86%). The local Local, bivariate relationships between coronavirus 2019 2 (COVID-19) infection rates and a set of demographic and socioe- coefficient of determination (R ) showed a significant influence of specific demographic and socioeconomic factors on COVID-19, conomic variables were explored at the district level in Oman. To including percentages of Omani and non-Omani population at var- limit multicollinearity a principal component analysis was con- ious age levels; spatial onlyinteraction; population density; number of ducted, the results of which showed that three components togeth- hospital beds; total number of households; purchasing power; and er could explain 65% of the total variance that were therefore sub- purchasing power per km2. No direct correlation between COVID- jected to further study. Comparison of a generalized linear model 19 rates and health facilities distribution or tobacco usage.
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