Scenario Analysis of Vaccine Supply for COVID-19 in Japan Using Mathematical Models of Infectious Diseases
AbstractVaccines suppress the increased spread of infectious diseases or the number of severe cases. Considerable research and development yielded several vaccines against coronavirus disease 2019 (COVID-19). To contain the disease, governments have run vaccination campaigns and implemented restrict...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Journal of Chemical Engineering of Japan |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/00219592.2024.2313318 |
| _version_ | 1797299877430951936 |
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| author | Junu Kim Kensaku Matsunami Yusuke Ichida Kozue Okamura Sara Badr Hirokazu Sugiyama |
| author_facet | Junu Kim Kensaku Matsunami Yusuke Ichida Kozue Okamura Sara Badr Hirokazu Sugiyama |
| author_sort | Junu Kim |
| collection | DOAJ |
| description | AbstractVaccines suppress the increased spread of infectious diseases or the number of severe cases. Considerable research and development yielded several vaccines against coronavirus disease 2019 (COVID-19). To contain the disease, governments have run vaccination campaigns and implemented restrictions depending on vaccination status. Ensuring the stability of vaccine supply with increased and/or seasonal demand has thus become critical. However, determination of the required vaccine supply is difficult due to variations in virus mutations, their impacts on the disease, and vaccine efficacy. In this work, we developed a mathematical model to consider the effect of vaccination on the infection numbers, taking COVID-19 as a case study. We have conducted a sensitivity analysis to identify the key variables affecting the required vaccine supply. We have conducted a scenario analysis to assess the impact of changes in vaccine supply parameters on the number of severe cases in Japan. Production of different products at dual-use facilities has been suggested to tackle the variability in vaccine demand. The analysis provided insights into the feasibility and adequate timing for product-switch at dual-use facilities. The proposed method can be applied to other infectious diseases and can be expanded to support various aspects for decision-making for policy building. |
| first_indexed | 2024-03-07T22:58:02Z |
| format | Article |
| id | doaj.art-34dda64ade314802a9febc1a0ed9c6c2 |
| institution | Directory Open Access Journal |
| issn | 0021-9592 1881-1299 |
| language | English |
| last_indexed | 2024-03-07T22:58:02Z |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Journal of Chemical Engineering of Japan |
| spelling | doaj.art-34dda64ade314802a9febc1a0ed9c6c22024-02-22T18:34:19ZengTaylor & Francis GroupJournal of Chemical Engineering of Japan0021-95921881-12992024-12-0157110.1080/00219592.2024.2313318Scenario Analysis of Vaccine Supply for COVID-19 in Japan Using Mathematical Models of Infectious DiseasesJunu Kim0Kensaku Matsunami1Yusuke Ichida2Kozue Okamura3Sara Badr4Hirokazu Sugiyama5Department of Chemical System Engineering, The University of Tokyo, Hongo, Bunkyo-ku, Tokyo, JapanDepartment of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg, Ghent, BelgiumDepartment of Chemical System Engineering, The University of Tokyo, Hongo, Bunkyo-ku, Tokyo, JapanDepartment of Chemical System Engineering, The University of Tokyo, Hongo, Bunkyo-ku, Tokyo, JapanDepartment of Chemical System Engineering, The University of Tokyo, Hongo, Bunkyo-ku, Tokyo, JapanDepartment of Chemical System Engineering, The University of Tokyo, Hongo, Bunkyo-ku, Tokyo, JapanAbstractVaccines suppress the increased spread of infectious diseases or the number of severe cases. Considerable research and development yielded several vaccines against coronavirus disease 2019 (COVID-19). To contain the disease, governments have run vaccination campaigns and implemented restrictions depending on vaccination status. Ensuring the stability of vaccine supply with increased and/or seasonal demand has thus become critical. However, determination of the required vaccine supply is difficult due to variations in virus mutations, their impacts on the disease, and vaccine efficacy. In this work, we developed a mathematical model to consider the effect of vaccination on the infection numbers, taking COVID-19 as a case study. We have conducted a sensitivity analysis to identify the key variables affecting the required vaccine supply. We have conducted a scenario analysis to assess the impact of changes in vaccine supply parameters on the number of severe cases in Japan. Production of different products at dual-use facilities has been suggested to tackle the variability in vaccine demand. The analysis provided insights into the feasibility and adequate timing for product-switch at dual-use facilities. The proposed method can be applied to other infectious diseases and can be expanded to support various aspects for decision-making for policy building.https://www.tandfonline.com/doi/10.1080/00219592.2024.2313318PandemicSEIR modelMachine learningDual-use facilityPolicy making |
| spellingShingle | Junu Kim Kensaku Matsunami Yusuke Ichida Kozue Okamura Sara Badr Hirokazu Sugiyama Scenario Analysis of Vaccine Supply for COVID-19 in Japan Using Mathematical Models of Infectious Diseases Journal of Chemical Engineering of Japan Pandemic SEIR model Machine learning Dual-use facility Policy making |
| title | Scenario Analysis of Vaccine Supply for COVID-19 in Japan Using Mathematical Models of Infectious Diseases |
| title_full | Scenario Analysis of Vaccine Supply for COVID-19 in Japan Using Mathematical Models of Infectious Diseases |
| title_fullStr | Scenario Analysis of Vaccine Supply for COVID-19 in Japan Using Mathematical Models of Infectious Diseases |
| title_full_unstemmed | Scenario Analysis of Vaccine Supply for COVID-19 in Japan Using Mathematical Models of Infectious Diseases |
| title_short | Scenario Analysis of Vaccine Supply for COVID-19 in Japan Using Mathematical Models of Infectious Diseases |
| title_sort | scenario analysis of vaccine supply for covid 19 in japan using mathematical models of infectious diseases |
| topic | Pandemic SEIR model Machine learning Dual-use facility Policy making |
| url | https://www.tandfonline.com/doi/10.1080/00219592.2024.2313318 |
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