title: How influenza vaccination policy may affect vaccine logistics.
abstract: BACKGROUND
  When policymakers make decision about the target populations and timing of influenza vaccination, they may not consider the impact on the vaccine supply chains, which may in turn affect vaccine availability.
  
  
  OBJECTIVE
  Our goal is to explore the effects on the Thailand vaccine supply chain of introducing influenza vaccines and varying the target populations and immunization time-frames.
  
  
  METHODS
  We Utilized our custom-designed software HERMES (Highly Extensible Resource for Modeling Supply Chains), we developed a detailed, computational discrete-event simulation model of the Thailand's National Immunization Program (NIP) supply chain in Trang Province, Thailand. A suite of experiments simulated introducing influenza vaccines for different target populations and over different time-frames prior to and during the annual influenza season.
  
  
  RESULTS
  Introducing influenza vaccines creates bottlenecks that reduce the availability of both influenza vaccines as well as the other NIP vaccines, with provincial to district transport capacity being the primary constraint. Even covering only 25% of the Advisory Committee on Immunization Practice-recommended population while administering the vaccine over six months hinders overall vaccine availability so that only 62% of arriving patients can receive vaccines. Increasing the target population from 25% to 100% progressively worsens these bottlenecks, while increasing influenza vaccination time-frame from 1 to 6 months decreases these bottlenecks.
  
  
  CONCLUSIONS
  Since the choice of target populations for influenza vaccination and the time-frame to deliver this vaccine can substantially affect the flow of all vaccines, policy-makers may want to consider supply chain effects when choosing target populations for a vaccine.
authors.affiliation: University of Pittsburgh, Pittsburgh, PA 15213, USA.
authors.forename: Tina-Marie
authors.initials: TM
authors.lastname: Assi
authors.forename: Korngamon
authors.initials: K
authors.lastname: Rookkapan
authors.forename: Jayant
authors.initials: J
authors.lastname: Rajgopal
authors.forename: Vorasith
authors.initials: V
authors.lastname: Sornsrivichai
authors.forename: Shawn T
authors.initials: ST
authors.lastname: Brown
authors.forename: Joel S
authors.initials: JS
authors.lastname: Welling
authors.forename: Bryan A
authors.initials: BA
authors.lastname: Norman
authors.forename: Diana L
authors.initials: DL
authors.lastname: Connor
authors.forename: Sheng-I
authors.initials: SI
authors.lastname: Chen
authors.forename: Rachel B
authors.initials: RB
authors.lastname: Slayton
authors.forename: Yongjua
authors.initials: Y
authors.lastname: Laosiritaworn
authors.forename: Angela R
authors.initials: AR
authors.lastname: Wateska
authors.forename: Stephen R
authors.initials: SR
authors.lastname: Wisniewski
authors.forename: Bruce Y
authors.initials: BY
authors.lastname: Lee
mesh_terms: D006291:Health Policy; D006801:Humans; D017589:Immunization Programs / Q000600:supply & distribution*; D007252:Influenza Vaccines / Q000600:supply & distribution*; D007251:Influenza, Human / Q000517:prevention & control*; D008962:Models, Theoretical; D011156:Population Density; D012984:Software; D013785:Thailand; D013997:Time Factors
chemical_list: D007252:Influenza Vaccines