Abstract
AbstractOur study utilizes network science to examine how uneven vaccine distribution affects mass vaccination strategies in the United States. Using mobility network data and epidemiological models, we find that distributing a fixed quantity of additional vaccines across Census Block Groups (CBGs) can vary case count reductions by up to 200%. This highlights the impact of vaccination heterogeneity in mobility networks on epidemic outcomes. Our efficient algorithm identifies optimal vaccine distribution for maximum case reduction. Simulations show a possible 9.5% decrease in case numbers with just a 1% increase in the national vaccination rate if vaccines are optimally distributed. This result surpasses those from other vaccine distribution models. Our findings underline the need for policymakers to understand the interaction between vaccination patterns and mobility networks, suggesting that grasping geographical vaccine uptake variations could be as crucial as raising the overall vaccination rate.
Publisher
Springer Science and Business Media LLC
Subject
General Physics and Astronomy
Reference41 articles.
1. Wagner, C. E. et al. Vaccine nationalism and the dynamics and control of sars-cov-2. Science (2021).
2. Goldstein, J. R., Cassidy, T. & Wachter, K. W. Vaccinating the oldest against covid-19 saves both the most lives and most years of life. Proc. Natl Acad. Sci. USA 118, 1–3 (2021).
3. Arce, J. S. S. et al. Covid-19 vaccine acceptance and hesitancy in low and middle income countries, and implications for messaging. Nat. Med. 27, 1385–1394 (2021).
4. Hou, X. et al. Intracounty modeling of covid-19 infection with human mobility: Assessing spatial heterogeneity with business traffic, age, and race. Proc. Natl Acad. Sci. USA 118, e2020524118 (2021).
5. Matrajt, L., Eaton, J., Leung, T. & Brown, E. R. Vaccine optimization for covid-19: Who to vaccinate first? Sci. Adv. 7, eabf1374 (2021).
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献