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

• Main Authors: Khalifa M. Al Kindi, Adhra Al-Mawali, Amira Akharusi, Duhai Alshukaili, Noura Alnasiri, Talal Al-Awadhi, Yassine Charabi, Ahmed M. El Kenawy
• Format: Article
• Language: English
• Published: PAGEPress Publications 2021-05-01
• Series: Geospatial Health
• Subjects: COVID-19; geographically weighted regression; generalized linear model; geographical information systems; Oman; socioeconomic determinants.
• Online Access: https://geospatialhealth.net/index.php/gh/article/view/985
• ISSN: 1827-1987; 1970-7096

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.