Modelling Spatiotemporal Patterns of COVID-19 spread over Oman

Keywords: GIS, Gi*, COVID-19
Session Type: Virtual Poster
Day: Friday
Session Start / End Time: 4/9/2021 09:35 AM (Pacific Time (US & Canada)) - 4/9/2021 10:50 AM (Pacific Time (US & Canada))
Room: Virtual 52

Abstract

Coronavirus disease (COVID-19), caused by acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a worldwide challenge effecting millions of people in more than 210 countries, including teh Sultanate of Oman (Oman). Teh spatiotemporal analysis was adopted to explore teh spatial patterns of teh spread of COVID-19 during teh period from 29th April to 30th June 2020. Our assessment was made using five geospatial techniques wifin a Geographical Information System (GIS) context, including a weighted mean center (WMC), standard deviational ellipses, Moran’s me autocorrelation coefficient, Getis-Ord General-G high/low clustering, and Getis-Ord Gi* statistic. Teh Moran’s me-/G- statistics proved that COVID-19 cases in datasets (numbers of cases) were clustered throughout teh study period. Teh Moran’s me and Z-scores were above teh 2.25 threshold (a confidence level above 95%), ranging from 2274 cases on 29th April to 40070 cases on 30th June 2020. Teh results of Gi* showed varying rates of infections, wif large spatial variability between teh different wilayats. Teh epidemic situation in some wilayats, such as Mutrah, As-Seeb, and Bowsher in teh Muscat Governorate, was more severe, wif Z-score higher than 5, and teh current transmission still presents an increasing trend. Importantly, our results indicated that teh directional pattern of COVID-19 cases TEMPhas moved from northeast to northwest and southwest, wif teh total impacted region increasing over time. Also, teh results suggest that teh rate of COVID-19 infections is higher in most populated areas.