Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic
Since the recent introduction of several viable vaccines for SARS-CoV-2, vaccination uptake has become the key factor that will determine our success in containing the COVID-19 pandemic. We argue that game theory and social network models should be used to guide decisions pertaining to vaccination p...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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The Royal Society
2021-06-01
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| Series: | Royal Society Open Science |
| Subjects: | |
| Online Access: | https://royalsocietypublishing.org/doi/10.1098/rsos.210429 |
| _version_ | 1819014581316485120 |
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| author | Mahendra Piraveenan Shailendra Sawleshwarkar Michael Walsh Iryna Zablotska Samit Bhattacharyya Habib Hassan Farooqui Tarun Bhatnagar Anup Karan Manoj Murhekar Sanjay Zodpey K. S. Mallikarjuna Rao Philippa Pattison Albert Zomaya Matjaz Perc |
| author_facet | Mahendra Piraveenan Shailendra Sawleshwarkar Michael Walsh Iryna Zablotska Samit Bhattacharyya Habib Hassan Farooqui Tarun Bhatnagar Anup Karan Manoj Murhekar Sanjay Zodpey K. S. Mallikarjuna Rao Philippa Pattison Albert Zomaya Matjaz Perc |
| author_sort | Mahendra Piraveenan |
| collection | DOAJ |
| description | Since the recent introduction of several viable vaccines for SARS-CoV-2, vaccination uptake has become the key factor that will determine our success in containing the COVID-19 pandemic. We argue that game theory and social network models should be used to guide decisions pertaining to vaccination programmes for the best possible results. In the months following the introduction of vaccines, their availability and the human resources needed to run the vaccination programmes have been scarce in many countries. Vaccine hesitancy is also being encountered from some sections of the general public. We emphasize that decision-making under uncertainty and imperfect information, and with only conditionally optimal outcomes, is a unique forte of established game-theoretic modelling. Therefore, we can use this approach to obtain the best framework for modelling and simulating vaccination prioritization and uptake that will be readily available to inform important policy decisions for the optimal control of the COVID-19 pandemic. |
| first_indexed | 2024-12-21T02:18:07Z |
| format | Article |
| id | doaj.art-37225de84bc940a9a18b5a6441bf6c6e |
| institution | Directory Open Access Journal |
| issn | 2054-5703 |
| language | English |
| last_indexed | 2024-12-21T02:18:07Z |
| publishDate | 2021-06-01 |
| publisher | The Royal Society |
| record_format | Article |
| series | Royal Society Open Science |
| spelling | doaj.art-37225de84bc940a9a18b5a6441bf6c6e2022-12-21T19:19:13ZengThe Royal SocietyRoyal Society Open Science2054-57032021-06-018610.1098/rsos.210429Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemicMahendra Piraveenan0Shailendra Sawleshwarkar1Michael Walsh2Iryna Zablotska3Samit Bhattacharyya4Habib Hassan Farooqui5Tarun Bhatnagar6Anup Karan7Manoj Murhekar8Sanjay Zodpey9K. S. Mallikarjuna Rao10Philippa Pattison11Albert Zomaya12Matjaz Perc13Complex Systems Research Group, Faculty of Engineering, University of Sydney, New South Wales 2006, AustraliaWestmead Clinical School, Faculty of Medicine and Health, University of Sydney, New South Wales 2006, AustraliaSchool of Public Health, Faculty of Medicine and Health, University of Sydney, New South Wales 2006, AustraliaWestmead Clinical School, Faculty of Medicine and Health, University of Sydney, New South Wales 2006, AustraliaDepartment of Mathematics, School of Natural Sciences, Shiv Nadar University, Uttar Pradesh, IndiaPublic Health Foundation of India, Delhi, IndiaICMR-National Institute of Epidemiology, Chennai, IndiaPublic Health Foundation of India, Delhi, IndiaICMR-National Institute of Epidemiology, Chennai, IndiaPublic Health Foundation of India, Delhi, IndiaIndustrial Engineering and Operations Research, Indian Institute of Technology Bombay, Mumbai, IndiaOffice of the Deputy Vice-Chancellor, University of Sydney, New South Wales 2006, AustraliaSchool of Computer Science, Faculty of Engineering, University of Sydney, New South Wales 2006, AustraliaFaculty of Natural Sciences and Mathematics, University of Maribor, Maribor, SloveniaSince the recent introduction of several viable vaccines for SARS-CoV-2, vaccination uptake has become the key factor that will determine our success in containing the COVID-19 pandemic. We argue that game theory and social network models should be used to guide decisions pertaining to vaccination programmes for the best possible results. In the months following the introduction of vaccines, their availability and the human resources needed to run the vaccination programmes have been scarce in many countries. Vaccine hesitancy is also being encountered from some sections of the general public. We emphasize that decision-making under uncertainty and imperfect information, and with only conditionally optimal outcomes, is a unique forte of established game-theoretic modelling. Therefore, we can use this approach to obtain the best framework for modelling and simulating vaccination prioritization and uptake that will be readily available to inform important policy decisions for the optimal control of the COVID-19 pandemic.https://royalsocietypublishing.org/doi/10.1098/rsos.210429vaccinationevolutionary game theorycooperationsocial dilemma |
| spellingShingle | Mahendra Piraveenan Shailendra Sawleshwarkar Michael Walsh Iryna Zablotska Samit Bhattacharyya Habib Hassan Farooqui Tarun Bhatnagar Anup Karan Manoj Murhekar Sanjay Zodpey K. S. Mallikarjuna Rao Philippa Pattison Albert Zomaya Matjaz Perc Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic Royal Society Open Science vaccination evolutionary game theory cooperation social dilemma |
| title | Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic |
| title_full | Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic |
| title_fullStr | Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic |
| title_full_unstemmed | Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic |
| title_short | Optimal governance and implementation of vaccination programmes to contain the COVID-19 pandemic |
| title_sort | optimal governance and implementation of vaccination programmes to contain the covid 19 pandemic |
| topic | vaccination evolutionary game theory cooperation social dilemma |
| url | https://royalsocietypublishing.org/doi/10.1098/rsos.210429 |
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