Zero Hunger Formula FRAMEWORK 3.0

Zero Hunger Formula Framework

Theory measurement and validation

Version 0.3 • October 22 2026 Prepared for World Food Bank Foundation and the Institute for Applied AI & RoboticsAI means artificial intelligence

Purpose and scientific status

The Zero Hunger Formula (ZHF) is a theory and diagnostic framework for coordinating food ecosystems. It draws on substantial published research and practical experience contributed by participants in agriculture, markets, finance, logistics, technology and policy. These foundations motivate the framework; they do not validate its combined equation or demonstrate that it works equally well everywhere.

The central hypothesis is that coordinated responses to linked constraints can improve food access, nutrition and resilience more effectively, and at acceptable cost, than feasible alternatives. Repeated testing across places, populations and time is essential. Reliable new evidence is expected to improve the model and its application, including by identifying relationships that should be changed or rejected.

This research and pilot edition defines the common architecture. Its companion, ZHF Implementation Handbook v0.3, supplies the operating sequence, worksheets and illustrative examples. Neither document reports new field results, establishes validated rankings or claims an approved global standard. The Scientific Working Paper v4.0 provides the fuller research discussion; the Preparatory Cover Article introduces the program to academic and philanthropic readers.

How to use this document

Section	Reader task
F1 Nine pillars	Understand the scope and prevent double counting.
F2 Formula	Inspect the candidate mathematics and its limits.
F3 Measurement	Define observations and release conditions.
F4 Geography	Keep comparisons consistent while adapting solutions.
F5 Regional portfolios	Connect regeneration, nutrition, income and resource constraints.
F6 Validation	Test measurement, causal effects and transferability.
F7 Governance and research	Assign responsibility, finance learning and revise openly.
F8 References	Locate the research and methodological foundations.

Revision from combined v0.2: the framework and handbook now have separate functions; outcome deterioration is explicitly protected against concealment by the headline; regenerative transitions and regional portfolios are operationalized; and worked examples, release gates and repeated evaluation are expanded. The candidate equations remain provisional.

F1 The nine pillars

Retain nine pillars for the pilot. They describe capacities and services that interventions may change. Food access and nutrition are outcomes; climate, conflict, market disruption, health, sanitation, tenure and exclusion are contextual or cross-cutting conditions. Their importance is not reduced by keeping them outside the nine-pillar list.

Code and pillar	Construct and scope	Candidate core measure
R Regenerative agriculture	Restore soil function while sustaining viable production.	R01 Share of sourcing hectares meeting the registered soil-function protocol.
W Water	Reliable safe service within sustainable resource limits.	W01 Share of eligible water-service requirements met under quality and ecological rules.
B Biodiversity	Maintain habitat and relevant biological functions.	B01 Share of sourcing hectares meeting the ecological-context biodiversity protocol.
P Policy	Execution of essential institutional duties.	P01 Share of registered service obligations completed to standard and on time.
S Surplus redistribution	Safe allocation of suitable surplus against need.	S01 Share of registered eligible unmet nutritional-service demand met through verified surplus.
D Storage	Safe and usable inventory service over time.	D01 Share of required commodity-storage tonne-days served to standard.
I Infrastructure	Reliable processing and delivery connections.	I01 Share of required deliveries completed in full and on time.
E Education	Ability to perform required practical tasks.	E01 Share of eligible participants demonstrating registered competencies.
C Capital	Timely and suitable access to working resources.	C01 Share of verified eligible financing need met on time under suitability rules.

These are proposed indicators. A field protocol must specify eligible denominators, sampling, verification, thresholds and observation periods before scoring. Do not reward an increase in waste, a shrinking service denominator, easier obligations or unsuitable credit. Capital access is assessed as a service; funding volume, adoption and use of a named financial product do not themselves earn points.

Distinct measures with shared dependencies

Storage measures inventory service; infrastructure measures operating connections and delivery. Regeneration measures soil-function stewardship; biodiversity measures ecological diversity and habitat. Record shared observations once and identify reuse. Test redundant indicators rather than assuming that separate labels create independent evidence. Where a core construct has no comparable operational definition, publish the diagnostic profile without a rank.

F2 Candidate formula and visual architecture

Figure 1. Proposed score construction. Arrows show aggregation, not estimated causal effects. All achievements range from 0 to 1; all gaps range from 0 to 100. Lower gaps indicate closer proximity to registered benchmarks.

Let r, w, b, p, s, d, i, e and c denote normalized achievements for the corresponding pillars. The four provisional group scores are:

g₁ = (r × w × b)^(1/3)    

g₂ = (p × s)^(1/2)g₃ = (d × i)^(1/2)          

g₄ = (e × c)^(1/2)Q = (3g₁ + 2g₂ + 2g₃ + 2g₄) / 9    

K = 100 × (1 − Q)G = (O + K + H) / 3

Operation	Modeling choice and implication
Multiplication	Complementarity within groups. A true zero forces its group to zero; sensitivity near zero requires testing.
Roots and division	Form comparable means. Roots prevent a three-factor group being mechanically depressed relative to a two-factor group.
Addition	Permits partial compensation between groups and domains. Outcome deterioration must remain separately visible.
Risk treatment	Use defined exposures and shock scenarios. Do not divide by an undefined conflict or climate term.

Weights 3:2:2:2 give equal marginal pillar influence at equal positive achievements; they do not estimate causal importance. Equal weights for O, K and H are a testable starting specification. Compare arithmetic, geometric, bottleneck and alternative groupings under composite-indicator guidance. [1]

F3 Measurement and reporting rules

Outcomes and modeled resilience

O is the mean of three normalized adverse gaps: food insecurity, healthy-diet unaffordability and child undernutrition. The nutrition gap is initially the mean of separately normalized stunting and wasting gaps. These measures overlap and omit other forms of malnutrition; the weighting and coverage require validation. Retain supplementary dietary quality, micronutrient, overweight and equity measures where feasible.

Use the Food and Agriculture Organization of the United Nations (FAO) Food Insecurity Experience Scale (FIES), the World Bank Food Prices for Nutrition approach, and established child-growth definitions used by the United Nations Children’s Fund, World Health Organization and World Bank. App users alone are not a representative population sample. [2–4]

H is the mean percentage of required nutritional-service person-days unmet in registered scenarios. A served person-day must meet the agreed nutritional, safety and delivery specification. H is simulated, not observed hunger. For initial model comparison, candidate tests are a 20% inflow reduction for 30 days and a seven-day outage of the largest critical operating node within a 30-day horizon. These are illustrative protocol candidates, not approved hazard standards. Register season, node selection, demand, substitutes and recovery assumptions. Household resilience analysis may additionally use FAO’s established Resilience Index Measurement and Analysis approach. [5]

Normalization and change

Adverse gap = 100 × clip((x − T)/(U − T), 0, 1), with worse anchor U > target T.Beneficial achievement = clip((x − L)/(T − L), 0, 1), with target T > worse anchor L.Progress = (G_previous − G_current) / elapsed years.

Clip limits values to the stated interval. Publish raw values because clipping hides differences beyond anchors. Fixed benchmarks must be registered before comparison; local annual minima and maxima cannot redefine the common scale. Missing, stale and inapplicable values remain distinct. Positive progress means gap closure; report change in O, K and H separately. Zero means registered benchmarks are met, not that every form of deprivation has disappeared.

Release and interpretation

During pilots, publish profiles and provisional scores without official league tables. A comparable ranked release requires independently reviewed construct validity, complete and sufficiently current core measures, approved common benchmarks, uncertainty analysis and geographic equivalence. Freeze methods for trends or restate earlier periods transparently. Show uncertainty bands where ordering is not reliable.

Example: O = 40, K = 60, H = 50 gives G = 50. If O worsens to 45 while K and H each improve to 30, G becomes 35. Report capacity and modeled resilience gains with worsening outcomes; do not call the headline change demonstrated hunger reduction. Register an outcome-deterioration alert and examine its uncertainty and affected groups.

Illustrative calculation

If each pillar achievement is 0.64, all four group means and Q equal 0.64, so K = 36. With O = 40 and H = 20, G = 32. If a comparable earlier G was 38 two years ago, gap closure is 3 points per year. These invented inputs demonstrate arithmetic only; the outcome trend must still be examined separately.

F4 Common measurement and local adaptation

Common across participating units	Adapted through local decisions
Indicator meaning, units and direction	Crop, livestock, fish and processing choices
Benchmarks, weighting and version	Interim milestones and intervention sequence
Minimum evidence and uncertainty rules	Language, delivery partners and local knowledge
Reference stress scenarios	Additional locally material shocks
Approved ecological-context protocols	Applicable soil, habitat and water safeguards
Geographic and denominator rules	Service boundaries, sourcing arrangements and budgets

Context protocols must demonstrate equivalent meaning before their scores are compared. A humid farming zone and a dry rangeland need different biological safeguards; identical vegetation targets would be inappropriate. Keep supplementary local measures visible but separate from the common calculation unless a reviewed version change includes them.

City country and regional views

Give each geography a stable identifier, boundary version, population reference and observation period. An importing city also needs a sourcing footprint: trace what share of its supply originates in each production zone and disclose unknown origin. Lack of farmland inside a city boundary must not be encoded as agricultural failure. Attribution rules for shared services must be registered and reconciled.

Aggregate the underlying quantities at their correct denominators, then recompute the parent measures. Use people for population access, eligible children for child outcomes, hectares for land measures and specified service units for operational measures. Do not average ranks or combine overlapping residents. The same inventory cannot cover multiple simultaneous commitments unless its allocation and replenishment support them.

For example, two disjoint districts have 200 of 1,000 and 600 of 2,000 eligible residents experiencing an adverse outcome. The combined prevalence is 800/3,000 = 26.7%, not the unweighted mean of 20% and 30%. This illustrative arithmetic does not replace survey weighting or age-specific measurement rules.

Regional coordination as a hypothesis

A regional network model should test shared storage, processing, transport and trade dependencies under simultaneous demands. National mean scores cannot reveal a mill or route on which several countries rely. Record trade costs, border delay, substitution capacity and contractual obligations. Confirm actual links before treating the proposed countries as a single functioning market.

More local flexibility should improve feasibility, not permit favorable scoring. Country teams choose solutions; the standards function safeguards comparability; independent reviewers assess whether those rules perform as intended.

F5 Regeneration and regional food portfolios

Regional Food Portfolio Design begins with what a location does well, then addresses nutritional needs, then compares feasible mixes that combine nutrition, income and resilience within ecological limits. Include fruit, vegetables, herbs, edible leaves, staple crops, legumes, livestock, fish and integrated production where locally appropriate. Safety, cultural acceptance, processing and actual demand matter alongside agronomic suitability.

Regenerative transition as a design priority

Select practices that restore biological functions and reduce avoidable dependence on harmful inputs: diverse rotations, living cover, suitable legumes and organic amendments, agroforestry, silvopasture, integrated pest management and adaptive grazing. Protect native habitat and grasslands. Tree density, stocking rate and water demand must fit the site; transferring a successful practice unchanged does not establish transferability.

Research supports soil biodiversity’s role in nutrient cycling and retention, adverse pesticide effects on non-target organisms, and benefits from diversification and African agroforestry. These findings justify testing coordinated regenerative options, not assigning universal yield or nutrition multipliers. A local silvopastoral trial provides additional evidence for context-specific testing. [8–12]

Measure practice → soil function → production and food composition → access and consumption → nutrition. Evidence at one link does not prove the entire chain. Track input toxicity and exposure, nutrient balance, infiltration, erosion, carbon stocks, biodiversity, edible output, variability, labor and net income. Input reductions must not conceal soil nutrient depletion or unmanaged pest loss. Transition support should include early cash needs, training and maintenance.

A practical portfolio model

Let x represent production, purchase, processing and trade choices by season. Compare portfolios that maximize expected net income subject to minimum nutritional access or delivery requirements, land and water limits, labor and processing capacity, biodiversity safeguards and an acceptable downside-loss constraint. Alternatively minimize cost at a specified nutrition target. Publish the trade-off frontier rather than hiding priorities inside a single arbitrary benefit score.

Resource constraints can be written A x ≤ b; nutrient deliveries N x ≥ n; and x ≥ 0, with commodity balances, seasonality and binary facility choices added where necessary. All coefficients require units, provenance and uncertainty. Population access cannot be inferred from production alone: include who receives or can afford the food. Market prices must respond in scenarios when output expansion could depress prices.

Use FAO and the International Institute for Applied Systems Analysis Global Agro-Ecological Zones resources as a starting point for suitability, supplemented by field data and consented local knowledge. [6] Handbook H4 provides the adoption sequence and candidate portfolio record.

F6 Validation and repeated learning

Scientific question	Test and revision trigger
Do indicators measure the intended construct?	Assess field feasibility, reliability, overlap and cross-context equivalence. Revise ambiguous definitions and duplicated measures.
Does the equation help diagnosis?	Compare alternative weights, groups and aggregations; propagate uncertainty. Revise unstable rankings or misleading compensation.
Do interventions cause improvement?	Prespecify outcomes and credible comparisons; evaluate implementation and spillovers. Revise effects when causal assumptions fail.
Does coordination add value?	Compare bundles with components and alternatives using the same outcome, horizon and full costs.
Will results transfer?	Test on independent places and periods. Revise applicability boundaries when replication fails.

Use randomized or phased designs where feasible and ethical. Where assignment is not random, justify the comparison and test the assumptions of the chosen design. Essential assistance must not be withheld to manufacture a control group. Prespecify sampling, minimum meaningful effects, clustering, attrition, concurrent programs and subgroup analysis. Ten countries are settings, not automatically a sufficient experimental sample. [7]

For effects measured as benefits relative to the same baseline, interaction = benefit(A+B) − benefit(A) − benefit(B). The total bundle benefit already includes the interaction; do not add it again. Observed differences need an identification strategy and uncertainty before they can be interpreted causally. A highly connected activity is a candidate for catalytic impact, not proof of it.

Evidence that can change the model

Maintain an evidence register separating participant experience, descriptive observations, credible causal estimates and independent replication. Local knowledge contributes hypotheses, context and feasible solutions. More adoption or duplicate reports do not increase scientific weight. Assess bias, independence, precision, relevance and transfer conditions; retain null and adverse findings.

Calibrate forecasts on one set of observations and test them on held-out settings or periods. Do not validate G solely against outcomes already included in O. Separate predictive accuracy from causal validity. A statistical association may predict well without identifying a useful intervention.

Before a revised method is released, preserve the prior version, document why it changed, compare performance and obtain independent review. If benchmarks or definitions change, either recalculate comparable history or mark the break. The expected strengthening of ZHF depends on evidence quality and willingness to revise, not merely the volume of data.

F7 Governance research and financing

World Food Bank Group (WFB) and World Food Bank Foundation (WFBF) coordinate proposed operational relationships. The Institute for Applied AI & Robotics (IAAIR), where AI means artificial intelligence, supports research methods, data architecture and reporting. Governments and communities retain planning authority. Establish an independent review function with authority to challenge definitions, causal claims and release eligibility. Disclose financial interests in operators, suppliers and financing products.

Role	Required accountability
Country and local owners	Approve service obligations, sequence, budget and corrective action.
WFB	Coordinate operators, agency dependencies, field delivery and learning exchange.
IAAIR	Maintain reproducible methods, data checks, models and evidence records.
Independent reviewers	Review evaluation designs, uncertainty, claims, disputes and method revisions.
Community representatives	Assess relevance and exclusion; govern agreed use of community knowledge.
Funders and partners	Finance agreed outputs while protecting independent publication.

The digital backbone links geography, observations, interventions, obligations, dependencies, money, inventory, evidence and decisions. Follow Findable, Accessible, Interoperable and Reusable (FAIR) data principles and Collective Benefit, Authority to Control, Responsibility and Ethics (CARE) principles where Indigenous data are involved. Access does not mean unrestricted publication of personal or community data. [13–14]

Multi-agent small language models may retrieve consented knowledge, translate and flag conflicting evidence. Deterministic calculations produce scores. Humans approve evidence assessments, plans and changes. Test fabricated citations, mistranslation, duplicate evidence, privacy leakage and false alerts. A dashboard may display scenarios and dependencies; it does not select projects, allocate funds or establish blame.

Research program and funding purpose

Proposed settings are Zambia, Zimbabwe, Mozambique, Botswana and Namibia; and Colombia, Costa Rica, Panama, Nicaragua and Honduras. Colombia joins four Central American countries in the Latin American group. Participation and government commitments require confirmation. Plan six to eight months of preparation, 36 months of operation and six months of synthesis, with extended follow-up for slower outcomes.

Foundation or endowment support should fund common baseline data, independent evaluation, reproducible models, field coordination and longer-term learning. Full budgets must distinguish research management from intervention delivery, operating support and institution-level support. Commercial activities need viable recurring economics; public services need dependable recurring funding and maintenance, not necessarily user fees.

Cross-agency procurement, reserve finance and insurance are optional mechanisms to evaluate. Funding and adoption remain outside the formula as direct rewards. The Handbook explains the proposed SYLO crop-value cap and separate reserve; it is a research case, not an authorization to issue insurance or financial products.

F8 References and edition record

References support established methods and mechanisms, not validation or institutional endorsement of the combined ZHF equation. Evidence selection is purposive, not a completed systematic review. Archive source versions and locally adopted protocols when registering the pilot.

[1] Organisation for Economic Co-operation and Development, European Union and European Commission Joint Research Centre. Handbook on Constructing Composite Indicators. 2008. https://doi.org/10.1787/9789264043466-en

[2] FAO. Food Insecurity Experience Scale methodology. https://www.fao.org/measuring-hunger/access-to-food/about-the-food-insecurity-experience-scale-(fies)/

[3] World Bank. Food Prices for Nutrition DataHub. https://www.worldbank.org/en/brief/2022/03/01/foodpricesfornutrition

[4] United Nations Children’s Fund, World Health Organization and World Bank. Joint Child Malnutrition Estimates. 2025 edition. https://www.who.int/publications/i/item/9789240112308

[5] FAO. Resilience Index Measurement and Analysis. https://www.fao.org/agrifood-economics/areas-of-work/rima/en/

[6] FAO and International Institute for Applied Systems Analysis. Global Agro-Ecological Zones. https://www.fao.org/gaez/en

[7] Gertler PJ et al. Impact Evaluation in Practice. Second edition. World Bank and Inter-American Development Bank; 2016. https://doi.org/10.1596/978-1-4648-0779-4

[8] Wagg C et al. Soil biodiversity and soil community composition determine ecosystem multifunctionality. Proceedings of the National Academy of Sciences. 2014;111:5266–5270. https://doi.org/10.1073/pnas.1320054111

[9] Wan NF et al. Pesticides have negative effects on non-target organisms. Nature Communications. 2025;16:1360. https://doi.org/10.1038/s41467-025-56732-x

[10] Tamburini G et al. Agricultural diversification promotes multiple ecosystem services without compromising yield. Science Advances. 2020;6:eaba1715. https://doi.org/10.1126/sciadv.aba1715

[11] Kuyah S et al. Agroforestry delivers a win-win solution for ecosystem services in sub-Saharan Africa. Agronomy for Sustainable Development. 2019;39:47. https://doi.org/10.1007/s13593-019-0589-8

[12] Narváez-Herrera JP et al. Silvopastoral systems with native forage species and their impact on milk production and quality. Agroforestry Systems. 2025;99:216. https://doi.org/10.1007/s10457-025-01292-8

[13] Wilkinson MD et al. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data. 2016;3:160018. https://doi.org/10.1038/sdata.2016.18

[14] Global Indigenous Data Alliance. CARE Principles for Indigenous Data Governance. https://www.gida-global.org/careprinciples

Companion and source documents

This edition develops the combined Framework and Handbook v0.2, the Scientific Working Paper v4.0, the Preparatory Cover Article and subsequent sponsor directions. Sponsor descriptions of Hamara, the Federal Emergency Management Agency (FEMA) ecosystem, the American Strategic Food Reserve Initiative (ASFRI) and SYLO establish proposed use cases, not independently verified results. The matching Implementation Handbook v0.3 contains the operating guidance. Earlier documents remain the historical record; this edition supplies the current pilot specification for these two companion volumes.