IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/5c8bd.html
   My bibliography  Save this paper

COVID-19 Sex-Age Mortality Modeling - A Use Case of Risk-Based Vaccine Prioritization

Author

Listed:
  • Shapiro, Vladimir

Abstract

This research builds upon the previous publications claiming that the male sex population and both sex individuals of advanced age are more susceptible to COVID-19’s risks. Relations between sex and age gradients are explored analytically based upon the proposed log-polynomial regression model of COVID-19 mortality. This model enables predicting mortality risk at any arbitrary age, as well as the derivation of several useful secondary metrics: • Sex differential: a ratio of male-to-female death risks for a given age group. • Age parity: age at which both sexes have an equal vulnerability. • Age lag: the number of years to subtract from a male’s age to match a female’s death risk. • Male equal risk age: male’s age at which male’s odds of dying from COVID-19 will equate female’s given the cutoff age. These metrics allow solving such practical problems as, e.g., prioritizing vaccine based on COVID-19 mortality risk associated with sex and age. Modeling techniques, refined in the paper, are by no means unique to COVID-19 and would apply to analyses of other diseases.

Suggested Citation

  • Shapiro, Vladimir, 2021. "COVID-19 Sex-Age Mortality Modeling - A Use Case of Risk-Based Vaccine Prioritization," SocArXiv 5c8bd, Center for Open Science.
    • Handle: RePEc:osf:socarx:5c8bd
    DOI: 10.31219/osf.io/5c8bd
    as

    Download full text from publisher

    File URL: https://osf.io/download/60b415249096b7011163d2ff/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/5c8bd?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Leonid Gavrilov & Natalia Gavrilova, 2011. "Mortality Measurement at Advanced Ages," North American Actuarial Journal, Taylor & Francis Journals, vol. 15(3), pages 432-447.
    2. Demombynes,Gabriel, 2020. "COVID-19 Age-Mortality Curves Are Flatter in Developing Countries," Policy Research Working Paper Series 9313, The World Bank.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hui Zheng, 2014. "Aging in the Context of Cohort Evolution and Mortality Selection," Demography, Springer;Population Association of America (PAA), vol. 51(4), pages 1295-1317, August.
    2. Luis Rosero-Bixby & William H. Dow & David H. Rehkopf, 2013. "The Nicoya region of Costa Rica: a high longevity island for elderly males," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 11(1), pages 109-136.
    3. Amrita Ahuja & Susan Athey & Arthur Baker & Eric Budish & Juan Camilo Castillo & Rachel Glennerster & Scott Duke Kominers & Michael Kremer & Jean Lee & Canice Prendergast & Christopher M. Snyder & Ale, 2021. "Preparing for a Pandemic: Accelerating Vaccine Availability," AEA Papers and Proceedings, American Economic Association, vol. 111, pages 331-335, May.
    4. Mihaela ZAMFIR & Ileana CIOBANU & Mihai Viorel ZAMFIR, 2021. "Vatra Luminoasa, age friendly study of intergenerational architecture in a Bucharest neighborhood," Smart Cities International Conference (SCIC) Proceedings, Smart-EDU Hub, Faculty of Public Administration, National University of Political Studies & Public Administration, vol. 9, pages 437-460, November.
    5. Kevin Milligan & Tammy Schirle, 2021. "The evolution of longevity: Evidence from Canada," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(1), pages 164-192, February.
    6. Ting Li & Yang Yang & James Anderson, 2013. "Mortality Increase in Late-Middle and Early-Old Age: Heterogeneity in Death Processes as a New Explanation," Demography, Springer;Population Association of America (PAA), vol. 50(5), pages 1563-1591, October.
    7. Kevin Milligan, 2024. "Innis Lecture: The time of your life: The mortality and longevity of Canadians," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 57(4), pages 1088-1108, November.
    8. Mitchell, Daniel & Brockett, Patrick & Mendoza-Arriaga, Rafael & Muthuraman, Kumar, 2013. "Modeling and forecasting mortality rates," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 275-285.
    9. Lin Ma & Gil Shapira & Damien de Walque & Quy‐Toan Do & Jed Friedman & Andrei A. Levchenko, 2022. "The Intergenerational Mortality Trade‐Off Of Covid‐19 Lockdown Policies," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(3), pages 1427-1468, August.
    10. Li, Hong & Tan, Ken Seng & Tuljapurkar, Shripad & Zhu, Wenjun, 2021. "Gompertz law revisited: Forecasting mortality with a multi-factor exponential model," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 268-281.
    11. Dan A. Black & Yu-Chieh Hsu & Seth G. Sanders & Lynne Steuerle Schofield & Lowell J. Taylor, 2017. "The Methuselah Effect: The Pernicious Impact of Unreported Deaths on Old-Age Mortality Estimates," Demography, Springer;Population Association of America (PAA), vol. 54(6), pages 2001-2024, December.
    12. Alexander, Monica, 2018. "Deaths without denominators: using a matched dataset to study mortality patterns in the United States," SocArXiv q79ye, Center for Open Science.
    13. Lledó, Josep & Pavía, Jose M. & Morillas-Jurado, Francisco G., 2019. "Incorporating big microdata in life table construction: A hypothesis-free estimator," Insurance: Mathematics and Economics, Elsevier, vol. 88(C), pages 138-150.
    14. Saul Justin Newman, 2018. "Errors as a primary cause of late-life mortality deceleration and plateaus," PLOS Biology, Public Library of Science, vol. 16(12), pages 1-12, December.
    15. Yupeng Li & Kul Prasad Kapri, 2021. "Impact of Economic Factors and Policy Interventions on the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(22), pages 1-18, November.
    16. Gbari, Kock Yed Ake Samuel & Poulain, Michel & Dal, Luc & Denuit, Michel, 2016. "Extreme value analysis of mortality at the oldest ages: a case study based on individual ages at death," LIDAM Discussion Papers ISBA 2016012, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    17. Serguei Maximov & Consuelo de J. Cortes-Penagos, 2020. "A long-time asymptotic solution to the g-renewal equation for underlying distributions with nondecreasing hazard functions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 92(2), pages 311-341, October.
    18. Sabelo Nick Dlamini & Wisdom Mdumiseni Dlamini & Ibrahima Socé Fall, 2022. "Predicting COVID-19 Infections in Eswatini Using the Maximum Likelihood Estimation Method," IJERPH, MDPI, vol. 19(15), pages 1-12, July.
    19. Francesco Decarolis & Gaétan de Rassenfosse & Leonardo M. Giuffrida & Elisabetta Iossa & Vincenzo Mollisi & Emilio Raiteri & Giancarlo Spagnolo, 2021. "Buyers' role in innovation procurement: Evidence from US military R&D contracts," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 30(4), pages 697-720, November.
    20. Ruchir Agarwal & Tristan Reed, 2022. "Financing vaccine equity: funding for day-zero of the next pandemic," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 38(4), pages 833-850.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:socarx:5c8bd. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://arabixiv.org .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.