Optimizing Covid-19 vaccine allocation considering the target population
Bibliographic Data
| ID | 22074778 |
|---|---|
| Authors | Zongliang Wen (Xuzhou Medical College), Tingyu Yue (Xuzhou Medical College), Wei Chen (0000-0002-9419-148X, Xuzhou Medical College), Guanhua Jiang (Xuzhou Medical College), Bin Hu (0000-0002-1852-9952, Xuzhou Medical College, corresponding author) |
| Year | 2023 |
| Volume | 10 |
| Pages | 1015133-1015133 |
| Publication date | 2023-01-06 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2022.1015133 |
| PMID | 36684954 |
| OpenAlex | W4313598952 |
| Language | EN |
| Citations received | 1 |
| References cited | 32 |
Vaccine allocation strategy for COVID-19 is an emerging and important issue that affects the efficiency and control of virus spread. In order to improve the fairness and efficiency of vaccine distribution, this paper studies the optimization of vaccine distribution under the condition of limited number of vaccines. We pay attention to the target population before distributing vaccines, including attitude toward the vaccination, priority groups for vaccination, and vaccination priority policy. Furthermore, we consider inventory and budget indexes to maximize the precise scheduling of vaccine resources. A mixed-integer programming model is developed for vaccine distribution considering the target population from the viewpoint of fairness and efficiency. Finally, a case study is provided to verify the model and provide insights for vaccine distribution
Environmental health · Integer programming · Mathematical optimization · Population · Vaccination · Computer Science · COVID-19 epidemiological studies · Mathematics · Medicine · SARS-CoV-2 and COVID-19 Research · Vaccine Coverage and Hesitancy · Virology
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| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |