The Micronutrient Portfolio Study

1. The Micronutrient Portfolio Study Keith Lividini, Jack Fiedler, and EkinBirol HarvestPlus Socio-Economists’ Meeting to Harmonise Methods and Studies Across Target Regions October 18-19, 2012 Email: K.Lividini@cgiar.org

2. Presentation Outline • Introduction • Conceptual Overview of Portfolio • Conceptual Overview of Methodology • Analytic Challenges • HarvestPlus AIMS Model • Implications • Conclusions

3. Introduction • The Micronutrient Portfolio Study • Funded by the Bill and Melinda Gates Foundation • Biofortification, Fortification, Supplementation • Health Impacts, Cost and Cost-effectiveness • Areas of Complementation and Overlap • 30-Year Timecourse • Zambia • Uganda • Nigeria • Kenya • Bangladesh • India (Gujarat & Rajastan)

4. Conceptualizing Portfolio Management • Managing a collection of programs: supplementation, fortification and biofortification • Fortification and biofortification are themselves a combination of programs • Managing the portfolio to achieve an optimal mix implies: • Scaling some of the programs up over time • Scaling some of them down over time • Changing the coverage of the programs  programs with sub-national coverage temporarily and/or permanently  targeting

5. Managing a MN Program Portfolio-1 • Step 1: Build a common, unifying framework • Step 2: Develop country-specific models of each of the interventions building on implementation-focused cost studies • Step 3: Analyze and compare the coverage, cost and cost-effectiveness of each program

6. Managing a MN Program Portfolio-2 • Step 4: Map the coverage of the interventions • Step 5: Model changes in the coverage, cost and cost-effectiveness over time • Step 6: Assess alternative scenarios

7. Considerations

8. Conceptual Overview of Methodology

9. Estimating Coverage and Impact And Cost and Cost-Effectiveness

10. Analytic Issues • Mapping and sub-national level analysis: How to compare the interventions? National? District? • Identifying the unreached and program targeting: Temporal and spatial dimensions • Scaling-up and scaling-down: Frequent finetunings? Or more predictable adjustments reflecting key intervention characteristics? Cost implications? • Dynamics: Changing coverage potential and changing cost structures over time

11. It’s Not that Simple • Other Important Considerations • Geographic Region • Subnational Levels • Comparabilities Across Programs • Target Populations • Mix of Micronutrients • Changes over time (coverage, costs, impacts and cost-effectiveness)

12. More Realistic Interaction

13. Adoption and Impact Measurement Simulator HarvestPlus AIMS

14. Intervention Differences in Scalability (Coverage and Costs) and Ability to Target • Supplementation may be the most flexible in terms of scale and the most amenable to targeting • Fortification can be scalable and targeted: • Select specific types of foods of a geographic or target population • Modify types and levels of micronutrients in a fortificant formulation • Biofortification is least directly scalable and targeting is largely restricted to uptake promotion efforts

15. Implications of this Work • Help Inform HarvestPlus of Potential Impacts of Developing Biofortified Crops in New Countries • Help Inform Donors of the Potential Cost-Effectiveness of Biofortification • Tools for Program Implementation, Planning and Targeting • Tools for Monitoring and Evaluation

16. Conclusions • Many Considerations and Challenges • Unifying Data Sets • Programs Within Programs • Comparabilities • Levels of Disaggregation/Target Populations • Dynamics Over Time • Scenarios to Consider/Sensitivity Analyses • Results for Zambia Coming End of October 2012

17. Acknowledgements Jack L Fiedler Ekin Birol Eliab Simpungwe Mark Rosegrant Alexander J Stein JV Meenakshi MatinQaim Penelope Nestel HPS Sachdev ZulfiqarBhutta The HarvestPlus team

18. Supplemental Slides

19. Examples of AIMS Output

20. Supplemental Slides

21. The Appeal of HIES Data • Readily available—done in all countries once every 3 or 5 years • Population-based surveys, statistically representative at the national level, often sub-national (e.g., region or state/province) • They differentiate food by how it was obtained: • Purchased (most promising for fortification efforts) • Home produced • Gifted (e.g., from WFP) • Able to examine variations by age, sex, rural-urban, income quintiles, region • Able to examine and model dietary patterns and multiple food combinations

22. Limitations of HIES Data • Food expenditures, not food consumption • Household level data, not individual: Use household characteristics to calculate the number of Adult-Consumption-Equivalents and assume food is distributing within the household in direct proportion to biological need (assumes the best case scenario) • How well they proxy consumption is uncertain, but the alternative is??

23. Influential Characteristics of Program’s role, costs, sustainability and vulnerability/risk • Supplementation--Most at risk due to: • Annual competition for resources in a competitive forum • Beneficiary demand for VAS/IFA remains too low to expect it to generate significant independent support • VAS continues to be an extraordinary event: subject to health worker fatigue, consumer fatigue, shifting MOH priorities • Antenatal care platform-based IFA continues to perform miserably • Fortification: • Piggy-backs on existing market, reducing visibility and vulnerability to change • Urban-centered, though changes in food patterns and supermarket penetration preceding at a rapid pace. • Bio-fortification: • Creates new market • Longest gestation period, but then it is a public good • Rural priority. Especially well suited for South Asia’s large, rural populations

24. Mapping HCES to IMPACT

25. The H+ AIMS Model • Adoption and Impact Measurement Simulation Model • Examines adoption of biofortifiedcrops • Links to Agricultural Production data • Can be disaggregated by geographic region of the country • Calculates: • Cumulative number of adopters • Land area planted to the biofortified crop • Nutritional impact over time • Number of DALYs Averted

26. The Impact Parameters • Incorporates flexible parameters 1) Year and geographic location of implementation 2) Yearly adoption rates 3) Yearly diffusion rates 4) Yearly attrition rates 5) Initial planting rates of new adopters 6) Yearly changes in planting rates

27. The Impact Parameters Year 2 Year 3 Year 1 57,000 # Influenced to Adopt (Diffusion) 80,000 40,000 # Influenced to Adopt (Diffusion) # Adopting 36,000 # Remaining (Attrition) # Remaining (Attrition) 74,000 # Remaining (Attrition) 66,600 # New Adopters Group 2 80,000 # Influenced to Adopt (Diffusion) 40,000 # Remaining (Attrition) 74,000 # New Adopters Group 3 80,000 Total 194,000 80,000 349,600

28. Hypothetical Evolution of Micronutrient Intervention Cost Structures

29. Overview: Estimating Impact EAR = Estimated Average Requirement; DALY = Disability Adjusted Life Year

30. Potential Scope of Program Cost Study • Identifying appropriate food vehicles (stability tests, etc.) • Types and quantities of fortificant(s) • The technology of introducing the fortificant • In-plant quality assurance • Government monitoring: in-plant, at point of sales • Government enforcement / compliance regulation • Social marketing and education • Nutrition Surveillance/Maintenance and Monitoring • Development and Breeding • Farm Trials • Dissemination • Bioregulatory

31. Cost-Effectiveness

32. Summary Cost-Effectiveness, Benefit-cost Ratios and IRRs of Alternative Banana21 Packages and Scenarios

33. The Unfinished Fortification Agenda Methodology • 48 countries selected on the basis of “need” • Methods pulled together “best available” modeling tools to promote transparency, replicability, methodological convergence: • WHO Fortification Guidelines • HIES data to complement FAO FBS • Information on industrial structure • Food Fortification Formulator of Omar Dary, A2Z Project (adjusts for food vehicle consumption levels) • Harvest Plus’ DALY Estimating Tool

34. Start with a Feasibility Assessment • Identify fortifiable supply of potential food vehicles that have at minimum 25% coverage • For those foods consumed by at least 25% of the population, assess whether or not their industrial structure is conducive to fortification: • Number of plants not “excessive” • Minimum output of plants: use modern technology, not artisanal 3. Estimate the costs of only those foods that fulfill both feasibility criteria

35. Private Sector Costs • 2-4 prototype plants identified for each food based on differences in equipment and output (plant size). • Each prototype had a detailed costing template to estimates capital costs, 10 year annual incremental operating costs of fortifcation: • Capital equipment (e.g., feeders, mixers, etc. and glassware) • In-plant quality assurance costs • External quality control costs • Fortificant / premix costs • The plant-size distribution of all plants producing the food was identified or estimated • All plants were assigned to one of the prototypes • Total industry costs were estimated for each prototype • National level costs were estimated as the sum of the prototypes

36. Public Sector Costs • Capital costs (vehicle, HPLC and/or spectrophotometer and glassware, chemicals and training) • Regulatory monitoring/inspection: Two annual inspection visits/plant/ year, border monitoring and import inspections (Labor, transportation and per diem) • Social marketing (first three years only) • Nutritional status monitoring (HH survey once every 5 years) • Commercial monitoring (retail outlets) • Both start-up and annual recurrent costs (over 5 &10 years) were estimated for both the private and public sector