Leveraging an epidemic–economic mathematical model to assess human responses to COVID-19 policies and disease progression
Abstract It is imperative that resources are channelled towards programs that are efficient and cost effective in combating the spread of COVID-19, the disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This study proposed and analyzed control strategies for that pur...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-39723-0 |
| _version_ | 1797453136140435456 |
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| author | Wisdom S. Avusuglo Nicola Bragazzi Ali Asgary James Orbinski Jianhong Wu Jude Dzevela Kong |
| author_facet | Wisdom S. Avusuglo Nicola Bragazzi Ali Asgary James Orbinski Jianhong Wu Jude Dzevela Kong |
| author_sort | Wisdom S. Avusuglo |
| collection | DOAJ |
| description | Abstract It is imperative that resources are channelled towards programs that are efficient and cost effective in combating the spread of COVID-19, the disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This study proposed and analyzed control strategies for that purpose. We developed a mathematical disease model within an optimal control framework that allows us to investigate the best approach for curbing COVID-19 epidemic. We address the following research question: what is the role of community compliance as a measure for COVID-19 control? Analyzing the impact of community compliance of recommended guidelines by health authorities—examples, social distancing, face mask use, and sanitizing—coupled with efforts by health authorities in areas of vaccine provision and effective quarantine—showed that the best intervention in addition to implementing vaccination programs and effective quarantine measures, is the active incorporation of individuals’ collective behaviours, and that resources should also be directed towards community campaigns on the importance of face mask use, social distancing, and frequent sanitizing, and any other collective activities. We also demonstrated that collective behavioral response of individuals influences the disease dynamics; implying that recommended health policy should be contextualized. |
| first_indexed | 2024-03-09T15:18:33Z |
| format | Article |
| id | doaj.art-7267d7752e624412acaa43a38eb08030 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T15:18:33Z |
| publishDate | 2023-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-7267d7752e624412acaa43a38eb080302023-11-26T12:56:22ZengNature PortfolioScientific Reports2045-23222023-08-0113111710.1038/s41598-023-39723-0Leveraging an epidemic–economic mathematical model to assess human responses to COVID-19 policies and disease progressionWisdom S. Avusuglo0Nicola Bragazzi1Ali Asgary2James Orbinski3Jianhong Wu4Jude Dzevela Kong5Africa-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Laboratory for Industrial and Applied Mathematics, York UniversityAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Laboratory for Industrial and Applied Mathematics, York UniversityAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), The Advanced Disaster, Emergency and Rapid Response Program, York UniversityAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), The Dahdaleh Institute for Global Health Research, York UniversityAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Laboratory for Industrial and Applied Mathematics, York UniversityAfrica-Canada Artificial Intelligence and Data Innovation Consortium (ACADIC), Laboratory for Industrial and Applied Mathematics, York UniversityAbstract It is imperative that resources are channelled towards programs that are efficient and cost effective in combating the spread of COVID-19, the disease caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This study proposed and analyzed control strategies for that purpose. We developed a mathematical disease model within an optimal control framework that allows us to investigate the best approach for curbing COVID-19 epidemic. We address the following research question: what is the role of community compliance as a measure for COVID-19 control? Analyzing the impact of community compliance of recommended guidelines by health authorities—examples, social distancing, face mask use, and sanitizing—coupled with efforts by health authorities in areas of vaccine provision and effective quarantine—showed that the best intervention in addition to implementing vaccination programs and effective quarantine measures, is the active incorporation of individuals’ collective behaviours, and that resources should also be directed towards community campaigns on the importance of face mask use, social distancing, and frequent sanitizing, and any other collective activities. We also demonstrated that collective behavioral response of individuals influences the disease dynamics; implying that recommended health policy should be contextualized.https://doi.org/10.1038/s41598-023-39723-0 |
| spellingShingle | Wisdom S. Avusuglo Nicola Bragazzi Ali Asgary James Orbinski Jianhong Wu Jude Dzevela Kong Leveraging an epidemic–economic mathematical model to assess human responses to COVID-19 policies and disease progression Scientific Reports |
| title | Leveraging an epidemic–economic mathematical model to assess human responses to COVID-19 policies and disease progression |
| title_full | Leveraging an epidemic–economic mathematical model to assess human responses to COVID-19 policies and disease progression |
| title_fullStr | Leveraging an epidemic–economic mathematical model to assess human responses to COVID-19 policies and disease progression |
| title_full_unstemmed | Leveraging an epidemic–economic mathematical model to assess human responses to COVID-19 policies and disease progression |
| title_short | Leveraging an epidemic–economic mathematical model to assess human responses to COVID-19 policies and disease progression |
| title_sort | leveraging an epidemic economic mathematical model to assess human responses to covid 19 policies and disease progression |
| url | https://doi.org/10.1038/s41598-023-39723-0 |
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