Sarah N Cox1, Patrick T Wedlock1, Sarah W Pallas2, Elizabeth A Mitgang1, Tatenda T Yemeke3, Sarah M Bartsch1, Taiwo Abimbola2, Sheryl S Sigemund1, Aaron Wallace2, Sachiko Ozawa4, Bruce Y Lee5. 1. Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York (CUNY) Graduate School of Public Health and Health Policy, New York City, NY, United States. 2. Global Immunization Division, Centers for Disease Control and Prevention (CDC), Atlanta, GA, United States. 3. Division of Practice Advancement and Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, United States. 4. Division of Practice Advancement and Clinical Education, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, United States; Department of Maternal and Child Health, UNC Gillings School of Global Health, University of North Carolina, Chapel Hill, NC, United States. 5. Public Health Informatics, Computational, and Operations Research (PHICOR), City University of New York (CUNY) Graduate School of Public Health and Health Policy, New York City, NY, United States. Electronic address: bruceleemdmba@gmail.com.
Abstract
BACKGROUND: Understanding the economics of vaccination is essential to developing immunization strategies that can be employed successfully with limited resources, especially when vaccinating populations that are hard-to-reach. METHODS: Based on the input from interviews with 24 global experts on immunization economics, we developed a systems map of the mechanisms (i.e., necessary steps or components) involved in vaccination, and associated costs and benefits, focused at the service delivery level. We used this to identify the mechanisms that may be different for hard-to-reach populations. RESULTS: The systems map shows different mechanisms that determine whether a person may or may not get vaccinated and the potential health and economic impacts of doing so. The map is divided into two parts: 1) the costs of vaccination, representing each of the mechanisms involved in getting vaccinated (n = 23 vaccination mechanisms), their associated direct vaccination costs (n = 18 vaccination costs), and opportunity costs (n = 5 opportunity costs), 2) the impact of vaccination, representing mechanisms after vaccine delivery (n = 13 impact mechanisms), their associated health effects (n = 10 health effects for beneficiary and others), and economic benefits (n = 13 immediate and secondary economic benefits and costs). Mechanisms that, when interrupted or delayed, can result in populations becoming hard-to-reach include getting vaccines and key stakeholders (e.g., beneficiaries/caregivers, vaccinators) to a vaccination site, as well as vaccine administration at the site. CONCLUSION: Decision-makers can use this systems map to understand where steps in the vaccination process may be interrupted or weak and identify where gaps exist in the understanding of the economics of vaccination. With improved understanding of system-wide effects, this map can help decision-makers inform targeted interventions and policies to increase vaccination coverage in hard-to-reach populations.
BACKGROUND: Understanding the economics of vaccination is essential to developing immunization strategies that can be employed successfully with limited resources, especially when vaccinating populations that are hard-to-reach. METHODS: Based on the input from interviews with 24 global experts on immunization economics, we developed a systems map of the mechanisms (i.e., necessary steps or components) involved in vaccination, and associated costs and benefits, focused at the service delivery level. We used this to identify the mechanisms that may be different for hard-to-reach populations. RESULTS: The systems map shows different mechanisms that determine whether a person may or may not get vaccinated and the potential health and economic impacts of doing so. The map is divided into two parts: 1) the costs of vaccination, representing each of the mechanisms involved in getting vaccinated (n = 23 vaccination mechanisms), their associated direct vaccination costs (n = 18 vaccination costs), and opportunity costs (n = 5 opportunity costs), 2) the impact of vaccination, representing mechanisms after vaccine delivery (n = 13 impact mechanisms), their associated health effects (n = 10 health effects for beneficiary and others), and economic benefits (n = 13 immediate and secondary economic benefits and costs). Mechanisms that, when interrupted or delayed, can result in populations becoming hard-to-reach include getting vaccines and key stakeholders (e.g., beneficiaries/caregivers, vaccinators) to a vaccination site, as well as vaccine administration at the site. CONCLUSION: Decision-makers can use this systems map to understand where steps in the vaccination process may be interrupted or weak and identify where gaps exist in the understanding of the economics of vaccination. With improved understanding of system-wide effects, this map can help decision-makers inform targeted interventions and policies to increase vaccination coverage in hard-to-reach populations.
Authors: Patrick T Wedlock; Elizabeth A Mitgang; Fayad Elsheikh; Jim Leonard; Jenn Bakal; Joel Welling; Jessica Crawford; Emmanuelle Assy; Bvudzai P Magadzire; Ruth Bechtel; Jay V DePasse; Sheryl S Siegmund; Shawn T Brown; Bruce Y Lee Journal: Vaccine Date: 2018-12-19 Impact factor: 3.641
Authors: Bruce Y Lee; Brigid E Cakouros; Tina-Marie Assi; Diana L Connor; Joel Welling; Souleymane Kone; Ali Djibo; Angela R Wateska; Lionel Pierre; Shawn T Brown Journal: Vaccine Date: 2012-07-10 Impact factor: 3.641
Authors: Leila A Haidari; Shawn T Brown; Marie Ferguson; Emily Bancroft; Marie Spiker; Allen Wilcox; Ramya Ambikapathi; Vidya Sampath; Diana L Connor; Bruce Y Lee Journal: Vaccine Date: 2016-06-20 Impact factor: 3.641
Authors: Leila A Haidari; Shawn T Brown; Patrick Wedlock; Diana L Connor; Marie Spiker; Bruce Y Lee Journal: Vaccine Date: 2017-04-19 Impact factor: 3.641
Authors: Jade Benjamin-Chung; Jaynal Abedin; David Berger; Ashley Clark; Veronica Jimenez; Eugene Konagaya; Diana Tran; Benjamin F Arnold; Alan E Hubbard; Stephen P Luby; Edward Miguel; John M Colford Journal: Int J Epidemiol Date: 2019-08-01 Impact factor: 7.196