Geographic information system-based spatio-temporal detection and mapping of COVID–19 hot/cold spots in Oman

Infected COVID-19 patients, especially after March 11, 2020, grew drastically in Oman. Hence, a variety of measures were issued to restrict all social gatherings, commercial activities, and mandating preventative health practices. This study aimed to i) understand distribution patterns and impact of decisions and responses at the spread of confirmed cases; ii) highlight and verify most concentrated regions with infections; and iii) overview spatial changes of cases overtime. The analysis was carried out using inverse–distance-weighted interpolation and hotspot (Getis–Ord GI*) techniques. Results showed a substantial relationship between spatial structure of COVID–19 and population distribution and density. COVID–19 has increased by 11.5% weekly in the capital, which were locked down since April 2020. However, after health quarantine was lifted on May 29, 2020, weekly cases surged in the capital. Al-Batinah-North and Dhofar recorded an increase of 32.1% and 30.5%, respectively, after restrictions had eased. The analysis illustrated that spread of COVID–19 was shifting from Northeast to Southeast and later shifted back to the Northeast of the country at the end of year 2022. This study is beneficial for pertinent organizations to perform detailed studies for developing and monitoring disease systems and dominating relevant factors.

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Publication Details

Journal
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
Published
2024-08-09
DOI
https://doi.org/10.11591/ijece.v14i5.pp5779-5801
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
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article

Geographic information system-based spatio-temporal detection and mapping of COVID–19 hot/cold spots in Oman

Yaseen Al-Mulla, Taif B. Al-Badi, Krishna Parimi, Ahsan Ali et al.
International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering
COVID-19 epidemiological studies
article

Geographic information system-based spatio-temporal detection and mapping of COVID–19 hot/cold spots in Oman

Yaseen Al-Mulla, Taif B. Al-Badi, Krishna Parimi, Ahsan Ali, Mohammed Al–Muqaimi, Anusha Chowdary
article en

Abstract

Infected COVID-19 patients, especially after March 11, 2020, grew drastically in Oman. Hence, a variety of measures were issued to restrict all social gatherings, commercial activities, and mandating preventative health practices. This study aimed to i) understand distribution patterns and impact of decisions and responses at the spread of confirmed cases; ii) highlight and verify most concentrated regions with infections; and iii) overview spatial changes of cases overtime. The analysis was carried out using inverse–distance-weighted interpolation and hotspot (Getis–Ord GI*) techniques. Results showed a substantial relationship between spatial structure of COVID–19 and population distribution and density. COVID–19 has increased by 11.5% weekly in the capital, which were locked down since April 2020. However, after health quarantine was lifted on May 29, 2020, weekly cases surged in the capital. Al-Batinah-North and Dhofar recorded an increase of 32.1% and 30.5%, respectively, after restrictions had eased. The analysis illustrated that spread of COVID–19 was shifting from Northeast to Southeast and later shifted back to the Northeast of the country at the end of year 2022. This study is beneficial for pertinent organizations to perform detailed studies for developing and monitoring disease systems and dominating relevant factors.

International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer EngineeringVol. 14(5)
Sultan Qaboos University (OM)
Partnerships for the goals
Openalex Percentile: Top 86%
COVID-19 epidemiological studies
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