TY - JOUR AU - Al Kindi, Khalifa M. AU - Al-Mawali, Adhra AU - Akharusi, Amira AU - Alshukaili, Duhai AU - Alnasiri, Noura AU - Al-Awadhi, Talal AU - Charabi, Yassine AU - El Kenawy, Ahmed M. PY - 2021/05/14 Y2 - 2024/03/28 TI - Demographic and socioeconomic determinants of COVID-19 across Oman - A geospatial modelling approach JF - Geospatial Health JA - Geospat Health VL - 16 IS - 1 SE - Original Articles DO - 10.4081/gh.2021.985 UR - https://www.geospatialhealth.net/gh/article/view/985 SP - AB - <p>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 (R<sup>2</sup>) 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 km<sup>2</sup>. 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.</p> ER -