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The optimal allocation of Covid-19 vaccines

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  • Babus, Ana
  • Das, Sanmay
  • Lee, SangMok

Abstract

We develop a simple model of vaccine prioritization for a potential pandemic. We illustrate how the model applies to the case of Covid-19, using an early 2020 primitive estimate of occupation-based exposure risks and age-based infection fatality rates. Even based on primitive estimates the vaccine distribution strongly emphasizes age-based mortality risk rather than occupation-based exposure risk. Among others, our result suggests that 50-year-old food-processing workers and 60-year-old financial advisors should have been equally prioritized. We also find that the priorities minimally change when certain populations’ exposure risks are altered by targeted stay-at-home orders or call-up of essential workers.

Suggested Citation

  • Babus, Ana & Das, Sanmay & Lee, SangMok, 2023. "The optimal allocation of Covid-19 vaccines," Economics Letters, Elsevier, vol. 224(C).
    • Handle: RePEc:eee:ecolet:v:224:y:2023:i:c:s0165176523000332
    DOI: 10.1016/j.econlet.2023.111008
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    Cited by:

    1. Liang Guo & Wendy Xu, 2023. "“We Are the World”: When More Equality Improves Efficiency and Antipandemic Consumptions Are Intervened," Marketing Science, INFORMS, vol. 42(2), pages 214-232, March.
    2. González-Parra, Gilberto & Villanueva-Oller, Javier & Navarro-González, F.J. & Ceberio, Josu & Luebben, Giulia, 2024. "A network-based model to assess vaccination strategies for the COVID-19 pandemic by using Bayesian optimization," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    3. Emanuele Blasioli & Bahareh Mansouri & Srinivas Subramanya Tamvada & Elkafi Hassini, 2023. "Vaccine Allocation and Distribution: A Review with a Focus on Quantitative Methodologies and Application to Equity, Hesitancy, and COVID-19 Pandemic," SN Operations Research Forum, Springer, vol. 4(2), pages 1-32, June.
    4. L'aszl'o Czaller & GergH{o} T'oth & Bal'azs Lengyel, 2021. "Vaccine allocation to blue-collar workers," Papers 2104.04639, arXiv.org.
    5. Almagro, Milena & Orane-Hutchinson, Angelo, 2022. "JUE Insight: The determinants of the differential exposure to COVID-19 in New York city and their evolution over time," Journal of Urban Economics, Elsevier, vol. 127(C).
    6. Forslid, Rikard & Herzing, Mathias, 2021. "Whom to Vaccinate First - Some Important Trade-offs," CEPR Discussion Papers 15800, C.E.P.R. Discussion Papers.
    7. Ghazal, Ikram & Rachadi, Abdeljalil & Ez-Zahraouy, Hamid, 2022. "Optimal allocation strategies for prioritized geographical vaccination for Covid-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    8. Hadi Hosseini & Sujoy Sikdar & Rohit Vaish & Lirong Xia, 2022. "Fairly Dividing Mixtures of Goods and Chores under Lexicographic Preferences," Papers 2203.07279, arXiv.org.
    9. Kargar, Bahareh & MohajerAnsari, Pedram & Esra Büyüktahtakın, İ. & Jahani, Hamed & Talluri, Sri, 2024. "Data-driven modeling for designing a sustainable and efficient vaccine supply chain: A COVID-19 case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).

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    More about this item

    Keywords

    Optimal assignment; Occupational health;

    JEL classification:

    • H4 - Public Economics - - Publicly Provided Goods
    • I1 - Health, Education, and Welfare - - Health

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