title: Policy trap and optimal subsidization policy under limited supply of vaccines.
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.
authors.affiliation: Network Dynamics and Simulation Science Laboratory, VBI, Virginia Tech, Blacksburg, Virginia, United States of America.
authors.forename: Ming
authors.initials: M
authors.lastname: Yi
authors.forename: Achla
authors.initials: A
authors.lastname: Marathe
mesh_terms: D000465:Algorithms; D006291:Health Policy / Q000191:economics; D006801:Humans; D008962:Models, Theoretical; D012959:Socioeconomic Factors; D014612:Vaccines / Q000600:supply & distribution*
chemical_list: D014612:Vaccines