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Producing Standardized Country-Level Immunization Delivery Unit Cost Estimates

Author

Listed:
  • Allison Portnoy

    (Harvard T.H. Chan School of Public Health, Center for Health Decision Science)

  • Kelsey Vaughan

    (Thinkwell)

  • Emma Clarke-Deelder

    (Harvard T.H. Chan School of Public Health)

  • Christian Suharlim

    (Harvard T.H. Chan School of Public Health, Center for Health Decision Science
    Management Sciences for Health)

  • Stephen C. Resch

    (Harvard T.H. Chan School of Public Health, Center for Health Decision Science)

  • Logan Brenzel

    (Bill & Melinda Gates Foundation)

  • Nicolas A. Menzies

    (Harvard T.H. Chan School of Public Health, Center for Health Decision Science
    Harvard T.H. Chan School of Public Health)

Abstract

Background To plan for the financial sustainability of immunization programs and make informed decisions to improve immunization coverage and equity, decision-makers need to know how much these programs cost beyond the cost of the vaccine. Non-vaccine delivery cost estimates can significantly influence the cost-effectiveness estimates used to allocate resources at the country level. However, many low- and middle-income countries (LMICs) do not have immunization delivery unit cost estimates available, or have estimates that are uncertain, unreliable, or old. We undertook a Bayesian evidence synthesis to generate country-level estimates of immunization delivery unit costs for LMICs. Methods From a database of empirical immunization costing studies, we extracted estimates of the delivery cost per dose for routine childhood immunization services, excluding vaccine costs. A Bayesian meta-regression model was used to regress delivery cost per dose estimates, stratified by cost category, against a set of predictor variables including country-level [gross domestic product per capita, reported diphtheria-tetanus-pertussis third dose coverage (DTP3), population, and number of doses in the routine vaccination schedule] and study-level (study year, single antigen or programmatic cost per dose, and financial or economic cost) predictors. The fitted prediction model was used to generate standardized estimates of the routine immunization delivery cost per dose for each LMIC for 2009–2018. Alternative regression models were specified in sensitivity analyses. Results We estimated the prediction model using the results from 29 individual studies, covering 24 countries. The predicted economic cost per dose for routine delivery of childhood vaccines (2018 US dollars), not including the price of the vaccine, was $1.87 (95% uncertainty interval $0.64–4.38) across all LMICs. By individual cost category, the programmatic economic cost per dose for routine delivery of childhood vaccines was $0.74 ($0.26–1.70) for labor, $0.26 ($0.08–0.67) for supply chain, $0.22 ($0.06–0.57) for capital, and $0.65 ($0.20–1.66) for other service delivery costs. Conclusions Accurate immunization delivery costs are necessary for assessing the cost-effectiveness and strategic planning needs of immunization programs. The cost estimates from this analysis provide a broad indication of immunization delivery costs that may be useful when accurate local data are unavailable.

Suggested Citation

  • Allison Portnoy & Kelsey Vaughan & Emma Clarke-Deelder & Christian Suharlim & Stephen C. Resch & Logan Brenzel & Nicolas A. Menzies, 2020. "Producing Standardized Country-Level Immunization Delivery Unit Cost Estimates," PharmacoEconomics, Springer, vol. 38(9), pages 995-1005, September.
  • Handle: RePEc:spr:pharme:v:38:y:2020:i:9:d:10.1007_s40273-020-00930-6
    DOI: 10.1007/s40273-020-00930-6
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    References listed on IDEAS

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    1. Cliford E. Ebong & Pierre Lévy, 2011. "Impact of the introduction of new vaccines and vaccine wastage rate on the cost-effectiveness of routine EPI: lessons from a descriptive study in a Cameroonian health district," Post-Print hal-01293723, HAL.
    2. repec:dau:papers:123456789/7742 is not listed on IDEAS
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    1. Rita Faria’s journal round-up for 14th September 2020
      by Rita Faria in The Academic Health Economists' Blog on 2020-09-14 11:00:07

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