How can age-based vaccine allocation strategies be optimized? A multi-objective optimization framework
Human life is deeply influenced by infectious diseases. A vaccine, when available, is one of the most effective ways of controlling the spread of an epidemic. However, vaccine shortage and uncertain vaccine effectiveness in the early stage of vaccine production make vaccine allocation a critical iss...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2022.934891/full |
| _version_ | 1798036843601592320 |
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| author | Hao Wu Kaibo Wang Lei Xu |
| author_facet | Hao Wu Kaibo Wang Lei Xu |
| author_sort | Hao Wu |
| collection | DOAJ |
| description | Human life is deeply influenced by infectious diseases. A vaccine, when available, is one of the most effective ways of controlling the spread of an epidemic. However, vaccine shortage and uncertain vaccine effectiveness in the early stage of vaccine production make vaccine allocation a critical issue. To tackle this issue, we propose a multi-objective framework to optimize the vaccine allocation strategy among different age groups during an epidemic under vaccine shortage in this study. Minimizing total disease onsets and total severe cases are the two objectives of this vaccine allocation optimization problem, and the multistage feature of vaccine allocation are considered in the framework. An improved Strength Pareto Evolutionary Algorithm (SPEA2) is used to solve the optimization problem. To evaluate the two objectives under different strategies, a deterministic age-stratified extended SEIR model is developed. In the proposed framework, different combinations of vaccine effectiveness and vaccine production capacity are investigated, and it is identified that for COVID-19 the optimal strategy is highly related to vaccine-related parameters. When the vaccine effectiveness is low, allocating most of vaccines to 0–19 age group or 65+ age group is a better choice under a low production capacity, while allocating most of vaccines to 20–49 age group or 50–64 age group is a better choice under a relatively high production capacity. When the vaccine effectiveness is high, a better strategy is to allocate vaccines to 65+ age group under a low production capacity, while to allocate vaccines to 20–49 age group under a relatively high production capacity. |
| first_indexed | 2024-04-11T21:18:33Z |
| format | Article |
| id | doaj.art-4a90aafe711e4857a9ea4a2808e3947b |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-04-11T21:18:33Z |
| publishDate | 2022-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-4a90aafe711e4857a9ea4a2808e3947b2022-12-22T04:02:43ZengFrontiers Media S.A.Frontiers in Public Health2296-25652022-09-011010.3389/fpubh.2022.934891934891How can age-based vaccine allocation strategies be optimized? A multi-objective optimization frameworkHao Wu0Kaibo Wang1Lei Xu2Department of Industrial Engineering, Tsinghua University, Beijing, ChinaVanke School of Public Health, Tsinghua University, Beijing, ChinaVanke School of Public Health, Tsinghua University, Beijing, ChinaHuman life is deeply influenced by infectious diseases. A vaccine, when available, is one of the most effective ways of controlling the spread of an epidemic. However, vaccine shortage and uncertain vaccine effectiveness in the early stage of vaccine production make vaccine allocation a critical issue. To tackle this issue, we propose a multi-objective framework to optimize the vaccine allocation strategy among different age groups during an epidemic under vaccine shortage in this study. Minimizing total disease onsets and total severe cases are the two objectives of this vaccine allocation optimization problem, and the multistage feature of vaccine allocation are considered in the framework. An improved Strength Pareto Evolutionary Algorithm (SPEA2) is used to solve the optimization problem. To evaluate the two objectives under different strategies, a deterministic age-stratified extended SEIR model is developed. In the proposed framework, different combinations of vaccine effectiveness and vaccine production capacity are investigated, and it is identified that for COVID-19 the optimal strategy is highly related to vaccine-related parameters. When the vaccine effectiveness is low, allocating most of vaccines to 0–19 age group or 65+ age group is a better choice under a low production capacity, while allocating most of vaccines to 20–49 age group or 50–64 age group is a better choice under a relatively high production capacity. When the vaccine effectiveness is high, a better strategy is to allocate vaccines to 65+ age group under a low production capacity, while to allocate vaccines to 20–49 age group under a relatively high production capacity.https://www.frontiersin.org/articles/10.3389/fpubh.2022.934891/fullinfectious diseaseSEIR modelmulti-objective (MO) optimizationvaccine allocationimproved Strength Pareto Evolutionary Algorithm (SPEA2) |
| spellingShingle | Hao Wu Kaibo Wang Lei Xu How can age-based vaccine allocation strategies be optimized? A multi-objective optimization framework Frontiers in Public Health infectious disease SEIR model multi-objective (MO) optimization vaccine allocation improved Strength Pareto Evolutionary Algorithm (SPEA2) |
| title | How can age-based vaccine allocation strategies be optimized? A multi-objective optimization framework |
| title_full | How can age-based vaccine allocation strategies be optimized? A multi-objective optimization framework |
| title_fullStr | How can age-based vaccine allocation strategies be optimized? A multi-objective optimization framework |
| title_full_unstemmed | How can age-based vaccine allocation strategies be optimized? A multi-objective optimization framework |
| title_short | How can age-based vaccine allocation strategies be optimized? A multi-objective optimization framework |
| title_sort | how can age based vaccine allocation strategies be optimized a multi objective optimization framework |
| topic | infectious disease SEIR model multi-objective (MO) optimization vaccine allocation improved Strength Pareto Evolutionary Algorithm (SPEA2) |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2022.934891/full |
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