Scroggins Stephen, Goodson Justin, Afroze Tasnova, Shacham Enbal
Taylor Geospatial Institute, College for Public Health and Social Justice, Saint Louis University, St. Louis, MO 63103, USA.
Department of Operations and IT Management, Chaifetz School of Business, Saint Louis University, St. Louis, MO 63103, USA.
Vaccines (Basel). 2022 Dec 28;11(1):64. doi: 10.3390/vaccines11010064.
Early distribution of COVID-19 vaccines was largely driven by population size and did not account for COVID-19 prevalence nor location characteristics. In this study, we applied an optimization framework to identify distribution strategies that would have lowered COVID-19 related morbidity and mortality. During the first half of 2021 in the state of Missouri, optimized vaccine allocation would have decreased case incidence by 8% with 5926 fewer COVID-19 cases, 106 fewer deaths, and 4.5 million dollars in healthcare cost saved. As COVID-19 variants continue to be identified, and the likelihood of future pandemics remains high, application of resource optimization should be a priority for policy makers.
新冠疫苗的早期分配很大程度上是由人口规模驱动的，没有考虑新冠疫情的流行情况和地理位置特征。在本研究中，我们应用了一个优化框架来确定能够降低与新冠相关的发病率和死亡率的分配策略。在2021年上半年的密苏里州，优化后的疫苗分配本可使病例发病率降低8%，减少5926例新冠病例、106例死亡，并节省450万美元的医疗成本。随着新冠病毒变异株不断被发现，未来大流行的可能性仍然很高，资源优化的应用应成为政策制定者的首要任务。
