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Can Subsidy Policies Reduce Vaccine Hesitancy Under Social Learning?
IEEE Transactions on Engineering Management ; : 1-15, 2022.
Article in English | Web of Science | ID: covidwho-2070470
ABSTRACT
Vaccine hesitancy refers to a delay in getting or refusing vaccinations for efficacy reviews from early vaccinated individuals (e.g., social learning). However, no reviews occur if everyone delays. To overcome vaccine hesitancy, we first introduce social learning to characterize this undesirable behavior in two-period vaccine market (composed of a government, a manufacturer, and individuals). Then, designing subsidy policies are in three aspects subsidy recipients (who should be subsidized, individuals or manufacturer), subsidy times (when subsidy policies should be set, preannounced or responsive), and subsidy paths (how the subsidy level should be adjusted over two periods, increasing or decreasing). Some results are yielded. First, if subsidy recipients are individuals, sales subsidies occur, and their equilibrium subsidy paths hinge on subsidy times. When sales subsidies are preannounced in the first period, a decreasing path is always optimal. In contrast, when these subsidies are responsive in two periods, an increasing path may be optimal. Second, these optimal sales subsidies can counter vaccine hesitancy and, further, utilize social learning to enhance vaccine coverage with different levels. Their differences are affected by two factors (government budgets and uncertain vaccine efficacy levels) that have asymmetric roles. Finally, if subsidy recipients are shifted from individuals to the manufacturer, cost subsidy occurs but it fails to overcome vaccine hesitancy.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Topics: Vaccines Language: English Journal: IEEE Transactions on Engineering Management Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Topics: Vaccines Language: English Journal: IEEE Transactions on Engineering Management Year: 2022 Document Type: Article