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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022 ; : 795-798, 2022.
Article in English | Scopus | ID: covidwho-2235051

ABSTRACT

Rapid development and distribution of vaccines have been a hallmark of the battle against COVID-19. While the efficacy, clinical trials, adverse health effects, and sociodemographic and clinical factors determining the distribution of vaccines have been studied extensively, there has been little effort to design cost-effective vaccine provisioning schemes. We introduce a vaccine provisioning scheme that leverages coalitional game theory to improve the cost of vaccines while meeting the epidemiological demand of neighboring zones. The proposed approach incentivizes bulk purchases by groups (or coalitions) of zones at lower prices while penalizing large coalitions to avoid logistical challenges. Moreover, it enables the policymaker to model the vaccine demand of zones based on their epidemiological profiles, such as susceptible, infected numbers or population density, or a combination thereof. We carry out experiments using the SEIRD (susceptible, exposed, infected, recovered, death) epidemic model as well as the daily confirmed cases in the five boroughs of New York City to show the efficacy of the approach. © 2022 IEEE.

2.
2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022 ; : 795-798, 2022.
Article in English | Scopus | ID: covidwho-2223056

ABSTRACT

Rapid development and distribution of vaccines have been a hallmark of the battle against COVID-19. While the efficacy, clinical trials, adverse health effects, and sociodemographic and clinical factors determining the distribution of vaccines have been studied extensively, there has been little effort to design cost-effective vaccine provisioning schemes. We introduce a vaccine provisioning scheme that leverages coalitional game theory to improve the cost of vaccines while meeting the epidemiological demand of neighboring zones. The proposed approach incentivizes bulk purchases by groups (or coalitions) of zones at lower prices while penalizing large coalitions to avoid logistical challenges. Moreover, it enables the policymaker to model the vaccine demand of zones based on their epidemiological profiles, such as susceptible, infected numbers or population density, or a combination thereof. We carry out experiments using the SEIRD (susceptible, exposed, infected, recovered, death) epidemic model as well as the daily confirmed cases in the five boroughs of New York City to show the efficacy of the approach. © 2022 IEEE.

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