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Policy Trap and Optimal Subsidization Policy under Limited Supply of Vaccines

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  • Ming Yi
  • Achla Marathe

Abstract

We adopt a susceptible-infected-susceptible (SIS) model on a Barabási and Albert (BA) network to investigate the effects of different vaccine subsidization policies. The goal is to control the prevalence of the disease given a limited supply and voluntary uptake of vaccines. The results show a uniform subsidization policy is always harmful and increases the prevalence of the disease, because the lower degree individuals’ demand for vaccine crowds out the higher degree individuals’ demand. In the absence of an effective uniform policy, we explore a targeted subsidization policy which relies on a proxy variable instead of individuals’ connectivity. Findings show a poor proxy-based targeted program can still increase the disease prevalence and become a policy trap. The results are robust to general scale-free networks.

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  • Ming Yi & Achla Marathe, 2013. "Policy Trap and Optimal Subsidization Policy under Limited Supply of Vaccines," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-9, July.
    • Handle: RePEc:plo:pone00:0067249
    DOI: 10.1371/journal.pone.0067249
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    1. Beckman, Richard J. & Baggerly, Keith A. & McKay, Michael D., 1996. "Creating synthetic baseline populations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 30(6), pages 415-429, November.
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