Abstract
Computing the COVID-19 vaccination priority is an urgent and ubiquitous decision problem. In this paper we propose a solution of this problem using the Logic Scoring of Preference (LSP) evaluation method. Our goal is to develop a justifiable and explainable quantitative criterion for computing a vaccination priority degree for each individual in a population. Performing vaccination in the order of the decreasing vaccination priority produces maximum positive medical, social, and ethical effects for the whole population. The presented method can be expanded and refined using additional medical and social conditions. In addition, the same methodology is suitable for solving other similar medical priority decision problems, such as priorities for organ transplants.
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Dooling, K.: Phased Allocation of COVID-19 Vaccines. ACIP COVID-19 Vaccines Work Group Meeting. https://www.cdc.gov/vaccines/acip/meetings/downloads/slides-2020-11/COVID-04-Dooling.pdf. Accessed 23 Nov 2020
Oliver, S.: EtR Framework: Public Health Problem, Resource Use and Equity Domains. ACIP COVID-19 Vaccines Work Group Meeting. https://www.cdc.gov/vaccines/acip/meetings/downloads/slides-2020-11/COVID-02-Oliver.pdf. Accessed 23 Nov 2020
Oliver, S.: EtR Framework: Values, Acceptability and Feasibility Domains. ACIP COVID-19 Vaccines Work Group Meeting. https://www.cdc.gov/vaccines/acip/meetings/downloads/slides-2020-11/COVID-03-Oliver.pdf. Accessed 23 Nov 2020
Dooling, K., et al.: The Advisory Committee on Immunization Practices’ Updated Interim Recommendation for Allocation of COVID-19 Vaccine — United States. https://www.cdc.gov/mmwr/volumes/69/wr/mm695152e2.htm?s_cid=mm695152e2_w. Accessed Dec 2020
Helene Gayle, H., Foege, W., Brown, L., Kahn, B. (eds.): Framework for Equitable Allocation of COVID-19 Vaccine. The National Academies Press, Washington, DC (2020). http://nap.edu/25917
Kates, J., Tolbert, J., Michaud, J.: The COVID-19 “Vaccination Line”: An Update on State Prioritization Plans. https://www.kff.org/coronavirus-COVID-19/issue-brief/the-COVID-19-vaccination-line-an-update-on-state-prioritization-plans/. Accessed 11 Jan 2021
COVID19.CA.GOV, Vaccines. https://covid19.ca.gov/vaccines/#California’s-vaccination-plan. Accessed 14 Nov 2021
California Department of Public Health, CDPH Allocation Guidelines for COVID-19 Vaccine During Phase 1A: Recommendations. https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/COVID-19/CDPH-Allocation-Guidelines-for-COVID-19-Vaccine-During-Phase-1A-Recommendations.aspx. Accessed 5 Dec 2020
Kaiser Permanente: Coronavirus and COVID-19. Public web site with variety of COVID-19 information. https://healthy.kaiserpermanente.org/health-wellness/coronavirus-information
Matrajt, L., Eaton, J., Leung, T., Brown, E.R.: Vaccine optimization for COVID-19: Who to vaccinate first? https://www.medrxiv.org/content/10.1101/2020.08.14.20175257v3.full.pdf. Accessed 15 Dec 2020
Bubar, K.M., et al.: Model-informed COVID-19 vaccine prioritization strategies by age and serostatus. https://www.medrxiv.org/content/10.1101/2020.09.08.20190629v3.full.pdf. Accessed 8 Jan 2021
Neimark, J.: What Is the Best Strategy to Deploy a COVID-19 Vaccine? https://undark.org/2020/11/18/best-strategy-to-deploy-covid-19-vaccine/. Accessed 18 Nov 2020
Dujmović, J.: Soft Computing Evaluation Logic. Wiley and IEEE (2018)
SEAS Co.: LSP.NT User Manual V1.2. http://www.seas.com/LSPNT/login.php. Accessed 11 Feb 2021.
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Dujmović, J., Tomasevich, D. (2022). COVID-19 Vaccination Priority Evaluation. In: Rayz, J., Raskin, V., Dick, S., Kreinovich, V. (eds) Explainable AI and Other Applications of Fuzzy Techniques. NAFIPS 2021. Lecture Notes in Networks and Systems, vol 258. Springer, Cham. https://doi.org/10.1007/978-3-030-82099-2_10
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DOI: https://doi.org/10.1007/978-3-030-82099-2_10
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