What are the outputs? What is generated by whom? Decade of Vaccine Economics (DOVE) 18/07/2014

Transcription

1 HEALTH IMPACT ESTIMATES & ECONOMIC ANALYSES ARE CRUCIAL TO GLOBAL EFFORTS Decade of Vaccine Economics (DOVE) Costing, Financing and Funding Gap (CFF) Model Presented to IVIR June 17, 2014 Sachi Ozawa, Simi Grewal, Allison Portnoy SAGE request for better economic models and alignment between models Global Vaccine Action Plan (GVAP) GAVI Replenishment for What is generated by whom? Several modeling groups, supported by GAVI 3 Health Impact Estimates IVAC s DOVE team, supported by BMGF Economic Benefits Estimates Costing, Financing & Funding Gap (CFF) Model Led by IVAC with support from Rutgers, HERMES and GVAP CFF Steering Committee (BMGF, GAVI, UNICEF, WHO) Return on Investment (ROI) Estimates What are the outputs? Based on GAVI s SDF and ADF, estimates of: Health Impact Economic Benefits CFF 4 Cases averted Deaths averted Disabilities averted Costs of illness averted (COI) DALYs Economic and social benefits Costs of vaccine programs Avail. financing Funding gap + User-friendly model for cont d use by BMGF, GAVI, UNICEF, WHO to generate future estimates 1

2 Model Objectives & Intended Uses Key Questions for Discussion Develop a model for ongoing use by core partners (BMGF, GAVI, UNICEF, WHO) for the Global Vaccine Action Plan (GVAP) which estimates: 1. Cost of Vaccination Programs 2. Financing of Vaccination Programs 3. Funding Gap for Vaccination Programs Scope: 94 countries for , 18 antigens, US$2010, focus on global and regional analyses User friendly, transparent and readily updatable Fill in gaps in previous exercise: will be adding in scenarios and sensitivity analyses, designed to link with economic benefits 1. Considering the objective of the DOVE-CFF model, are the data sources appropriate to estimate vaccine program costs, financing and funding gap? Do methods to project vaccine prices through 2020 when forecasts are not available adequately account for price fluctuations across the decade? Could any further methods be proposed to extrapolate service delivery costs from countries with cmyp data to countries for which a cmyp was not used in the model? 2. Are the following key assumptions for the base case reasonable? With the exception of IPV, non-gavi countries are assumed to meet routine and SIA vaccine financing obligations throughout the decade. Are simplifying assumptions about the mechanisms by which supply chain costs for a country may relate to supply chain costs for a reference country appropriate? Shared personnel costs are assumed to be 100% financed for all countries across the decade. Marginal service delivery costs are assumed to increase linearly as vaccine doses increase. 5 6 CFF Model Scope: Vaccines, Countries, Years ( ) ( ) + BACKGROUND Decade of Vaccines,

3 CFF Model Scope An integrated, multi-component model 9 10 Wide array of specific outputs possible MODEL COMPONENTS

4 Costing Model Components Financing Model Components: 3 contributing groups Governments GAVI ODP Routine Immunization (RI) 17 RI Model Components Immunizationspecific transport Shared transport Storage Labor Immunizationspecific personnel Shared personnel Non-personnel (inc. training, surveillance, program management, social mobilization) Vaccine (vaccines, freight, injection equipment, safety equipment) Supplementary Immunization Activities (SIA) 10 SIA Model Components Operational Support (personnel and other operational support inc. training, transport, and social mobilization) Vaccine (vaccines, freight, injection equipment, safety equipment)

5 Data Sources: Costing DATA SOURCES Vaccine costs Prices from GAVI, UNICEF & PAHO Doses for GAVI-supported vaccines from GAVI Adjusted Demand Forecast (ADFv8) Doses for remaining vaccines from SDF-based demand forecasts developed by DOVE JHU team Supply chain costs Costs based on HERMES analysis Service delivery costs ( operational for SIAs) cmyp-derived country-specific estimates Data Sources: Financing Government financing Vaccines: GAVI co-financing based on ADFv8 + cmyp-derived financing relative to resource requirements Supply chain & Service delivery: cmyp-derived financing relative to resource requirements GAVI financing Vaccines: GAVI commitments based on ADFv8 Supply chain & Service delivery: GAVI support for vaccine introduction, separated into % supply chain vs. % service delivery Other Development Partners (ODP) financing Vaccines: cmyp-derived financing relative to resource requirements Supply chain & Service delivery: cmyp-derived financing relative to resource requirements Key Questions for Discussion 1. Considering the objective of the DOVE-CFF model, are the data sources appropriate to estimate vaccine program costs, financing and funding gap? Do methods to project vaccine prices through 2020 when forecasts are not available adequately account for price fluctuations across the decade? Could any further methods be proposed to extrapolate service delivery costs from countries with cmyp data to countries for which a cmyp was not used in the model? 2. Are the following key assumptions for the base case reasonable? With the exception of IPV, non-gavi countries are assumed to meet routine and SIA vaccine financing obligations throughout the decade. Are simplifying assumptions about the mechanisms by which supply chain costs for a country may relate to supply chain costs for a reference country appropriate? Shared personnel costs are assumed to be 100% financed for all countries across the decade. Marginal service delivery costs are assumed to increase linearly as vaccine doses increase. 5

6 Vaccine Price Projections GAVI 73 Countries GAVI-supported vaccines (defined in methods document): assumed price projections from GAVI Secretariat using ADFv8 Traditional vaccines (defined in methods document): assumed price projections from UNICEF relied on rolling 5-year averages for PAHO 4 Countries Assumed price projections from PAHO Revolving Fund for any relevant PAHO supported vaccines Assumed GAVI-supported vaccine prices were 30% higher than GAVI prices based on historical difference between GAVI and PAHO vaccine prices Non-GAVI 17 Countries Assumed price projections from UNICEF for GAVI-supported vaccines Assumed GAVI-supported vaccine prices were 32% higher than GAVI prices based on historical difference between GAVI and UNICEF vaccine prices Assumed price projections from UNICEF for traditional vaccines and relied on rolling 5-year averages for Routine Service Delivery Cost Methods Country specific service delivery cost data were abstracted from 63 cmyps, with baseline years ranging from Costs were divided by routine doses in the cmyp-specified baseline year to obtain an average cost per dose for each service delivery component (defined in methods document) For remaining 31 countries, service delivery cost data were imputed based on a regression analysis of the cmyp data Each component cost was regressed against variables that were potential drivers of routine immunization program costs including birth cohort, land area, DTP3 coverage, and percentage of the population living in rural areas Key Questions for Discussion BASE CASE ASSUMPTIONS 1. Considering the objective of the DOVE-CFF model, are the data sources appropriate to estimate vaccine program costs, financing and funding gap? Do methods to project vaccine prices through 2020 when forecasts are not available adequately account for price fluctuations across the decade? Could any further methods be proposed to extrapolate service delivery costs from countries with cmyp data to countries for which a cmyp was not used in the model? 2. Are the following key assumptions for the base case reasonable? With the exception of IPV, non-gavi countries are assumed to meet routine and SIA vaccine financing obligations throughout the decade. Are simplifying assumptions about the mechanisms by which supply chain costs for a country may relate to supply chain costs for a reference country appropriate? Shared personnel costs are assumed to be 100% financed for all countries across the decade. Marginal service delivery costs are assumed to increase linearly as vaccine doses increase

7 Base Case: Non-GAVI Countries Financing of Vaccine Costs The percentage of government financing relative to vaccine resource requirements for non-gavi countries was obtained from the WHO Joint Reporting Form (JRF) If government financing <100%, the remainder was assumed to be covered by ODP A rolling average of this percentage was used to project government financing for all vaccines except IPV For IPV, the price differential between IPV and OPV is entirely attributed to the funding gap This assumes that, except for IPV, 21 non-gavi countries will meet their vaccine financing obligations with ODP assistance Supply Chain Mechanistic Model: Base Case Simplifying Assumptions Transport Costs: Should scale by route distance and frequency Route distance should scale by square root of country area Modified by fuel costs (gas prices can serve as a proxy) Reference-to-target country matching: Morphology of supply chain (3-,4-, or 5-tier and cluster types top heavy, middle, bottom heavy within 4-tier) Storage Costs: Should scale by the number of refrigerators and freezers Which, in turn, should scale by vaccine regimen and population Modified by energy costs (electricity prices can serve as a proxy) Reference-to-target country matching: Morphology of supply chain Labor Costs: Number of personnel, which should scale by number of locations Which in turn should scale by population Modified by wages Reference-to-target country matching: Morphology of supply chain Base Case: Full Financing of Shared Personnel Costs Shared personnel costs are defined as the value of human resources that are not specific to immunization and are used by different programs or activities in the health sector Shared personnel costs that are not financed by GAVI and ODP are assumed to be financed by governments In the base case, shared personnel costs are assumed to be 100% financed, with no funding gaps Base Case: Linear Marginal Service Delivery Costs In the base case, no changes in marginal service delivery costs per dose are incorporated on the basis of vaccine schedule changes Potential projection options for vaccine schedule changes: No change in vaccine schedule and increase in doses: percentage decrease in marginal costs to account for economies of scale Addition of vaccine to schedule and increase in doses: percentage increase in marginal costs in year of vaccine introduction to account for increased investment needs In the base case, marginal costs are assumed to be constant regardless of changes in vaccination schedule

8 CFF Model: Next Steps CONCLUSIONS 1. Conduct DOVE-CFF model sensitivity analysis 2. Develop DOVE-ROI model 3. Draft DOVE-CFF user guide 4. Share DOVE-CFF model and user guide with GVAP C&F Steering Committee partner organizations 5. Review of DOVE-CFF and DOVE-ROI models with SAGE (to be confirmed) Project Researchers Johns Hopkins School of Public Health Rutgers University University of Pittsburgh Pittsburgh Supercomputing Center/Carnegie Mellon Project Contributors Sachiko Ozawa, Bruce Lee, Simrun Grewal, Allison Portnoy, Samantha Clark, Katie Gorham Anushua Sinha, Meghan Stack, Richard Arilotta Bryan Norman, Jayant Rajgopal, Leila Haidari, Erin Claypool Shawn Brown GVAP Costing & Financing Steering Committee Bill & Melinda Gates Foundation GAVI Alliance UNICEF World Health Organization Logan Brenzel, Damian Walker Santiago Cornejo, Hope Johnson Gian Gandhi, Tom O Connell Thomas Cherian, Claudio Politi Key Questions for Discussion 1. Considering the objective of the DOVE-CFF model, are the data sources appropriate to estimate vaccine program costs, financing and funding gap? Do methods to project vaccine prices through 2020 when forecasts are not available adequately account for price fluctuations across the decade? Could any further methods be proposed to extrapolate service delivery costs from countries with cmyp data to countries for which a cmyp was not used in the model? 2. Are the following key assumptions for the base case reasonable? With the exception of IPV, non-gavi countries are assumed to meet routine and SIA vaccine financing obligations throughout the decade. Are simplifying assumptions about the mechanisms by which supply chain costs for a country may relate to supply chain costs for a reference country appropriate? Shared personnel costs are assumed to be 100% financed for all countries across the decade. Marginal service delivery costs are assumed to increase linearly as vaccine doses increase