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Modelling the impact of non-pharmaceutical interventions on the spread of COVID-19 in Saudi Arabia
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Althobaity, Yehya and Tildesley, Michael J. (2023) Modelling the impact of non-pharmaceutical interventions on the spread of COVID-19 in Saudi Arabia. Scientific Reports, 13 (1). 843. doi:10.1038/s41598-022-26468-5 ISSN 2045-2322.
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Official URL: https://doi.org/10.1038/s41598-022-26468-5
Abstract
Countries around the world have implemented a series of interventions to contain the pandemic of coronavirus disease (COVID-19), and significant lessons can be drawn from the study of the full transmission dynamics of the disease caused by—severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)—in the Eastern, Madinah, Makkah, and Riyadh regions of Saudi Arabia, where robust non-pharmaceutical interventions effectively suppressed the local outbreak of this disease. On the basis of 333732 laboratory-confirmed cases, we used mathematical modelling to reconstruct the complete spectrum dynamics of COVID-19 in Saudi Arabia between 2 March and 25 September 2020 over 5 periods characterised by events and interventions. Our model account for asymptomatic and presymptomatic infectiousness, time-varying ascertainable infection rate, and transmission rates. Our results indicate that non-pharmaceutical interventions were effective in containing the epidemic, with reproduction numbers decreasing on average to 0.29 (0.19–0.66) in the Eastern, Madinah, Makkah, and Riyadh region. The chance of resurgence after the lifting of all interventions after 30 consecutive days with no symptomatic cases is also examined and emphasizes the danger presented by largely hidden infections while switching control strategies. These findings have major significance for evaluating methods for maintaining monitoring and interventions to eventually reduce outbreaks of COVID-19 in Saudi Arabia in the future.
| Item Type: | Journal Article | |||||||||
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| Subjects: | R Medicine > RA Public aspects of medicine | |||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) | |||||||||
| SWORD Depositor: | Library Publications Router | |||||||||
| Library of Congress Subject Headings (LCSH): | COVID-19 (Disease) , COVID-19 (Disease) -- Transmission -- Saudi Arabia -- Prevention -- Mathematical models | |||||||||
| Journal or Publication Title: | Scientific Reports | |||||||||
| Publisher: | Nature Publishing Group UK | |||||||||
| ISSN: | 2045-2322 | |||||||||
| Official Date: | 16 January 2023 | |||||||||
| Dates: |
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| Volume: | 13 | |||||||||
| Number: | 1 | |||||||||
| Article Number: | 843 | |||||||||
| DOI: | 10.1038/s41598-022-26468-5 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Open Access (Creative Commons) | |||||||||
| Date of first compliant deposit: | 18 January 2023 | |||||||||
| Date of first compliant Open Access: | 18 January 2023 | |||||||||
| RIOXX Funder/Project Grant: |
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