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In April 2017, the Institute partnered with the Micronutrient Forum to convene a two-day technical consultation to review seven tools designed to help decision makers in low middle income countries (LMIC) develop and streamline their nutrition programs and interventions. These tools were selected on the basis of their ability to elaborate nutrition policy scenarios adapted to national priorities and contexts, whether through the use of mathematical optimization routines or other evidence-based analytical approaches. Services provided by those tools range from advocacy to allocative efficiency to budget planning. The meeting highlighted the deep capabilities of those tools, and several examples were presented of successful use that confirmed their potential utility to nutrition policy making. Yet their adoption by end-users in LMICs remains limited. To palliate for this, the New York Academy of Sciences was awarded a 2.5 year grant by the Bill & Melinda Gates Foundation to create a consortium for nutrition modeling aimed at improving the usability of tools, and at increasing their uptake by end users.

What is Nutrition Modeling?

Nutrition Modeling refers mostly to computer assisted optimization routines that seek to select a best solution (with regard to some nutrition objective) among a set of available policy or program alternatives. However, not all tools represented on the Consortium follow mathematical optimization algorithms. Some use spreadsheet formula, while other use qualitative methods to drill down on nutrition data. Regardless of their design, they all share the intent of improving the use of available knowledge and data in designing nutrition policies and programs.

Consortium Mandate

The mandate of the Nutrition Modeling Consortium is to:

  • Increase end-users’ input in the specification of services to be provided by these tools.
  • Help end-users understand better how those tool can serve their nutrition programming needs.
  • Advance the joint utility and effectiveness of the modeling tools through a collective effort by nutrition modelers in order to enhance their technical inter-operability, and improve their usability to end-users.

How the Consortium Works

The Consortium of Nutrition Modelers aims to improve the use of the evidence base in policy and program decision making through the use of mathematical modeling of nutrition activities. It is led by a Scientific Organizing committee composed of nutrition modelers and end-users. The Secretariat has the responsibility of linking the SOC to the modeling community and to end-users, to coordinate the work of the Consortium and to organize and convene meetings of the Consortium.

Funding Support


Organized By

Sackler meeting

The Nutrition Modeling Consortium regroups personnel that support modeling tools, working at diverse institutions worldwide. It also includes in-country end users, such as Ministries of Health, Nutrition Departments, and implementers such as NGOs, or technical planners in-country. Membership to the Consortium is open to all stakeholders working in this area, provided they contribute to the group’s common goals.

Consortium Members

Fill the Nutrient Gap / Cost of the Diet (FNG/CotD)
Website: Tools for Food Security and Nutrition Analysis
Contact: Saskia De Pee and Frances Knight
Parent institution: World Food Programme
2 pager

Intake Modeling and Prediction Program (IMAPP)
Website: Software for Intake Distribution Estimation
Contact: Lindsay Allen and Alicia Carriquiry
Parent institutions: University of California, Davis and Iowa State University

Lives Saved Tool (LiST)
Website: The LiST page
Contact: Rebecca Heidkamp and Neff Walker
Parent institution: Johns Hopkins University

Website: MiniMOD Tool Overview
Contact: Steve Vosti and Reina Engle-Stone
Parent institution: University of California, Davis
2 pager

Outcome Modeling for Nutrition Impact (OMNI)
Website: The OMNI Tool
Contact: Luz Maria de Regil and Homero Martinez
Parent institution: Nutrition International
2 pager

Contact: Elaine Ferguson
Parent institution: London School of Hygiene and Tropical Medicine
2 pager

Optima Nutrition
Website: The Optima Nutrition Tool
Contact: Jakub Kakietek and Nick Scott
Parent institution: Burnet InstituteOptima Consortium for Decision Science and The World Bank
2 pager

Website: Profiles 
Contact: Kavita Sethuraman and Monica Woldt
Parent institution: FANTA III
2 pager

Equitable Impact Sensitive Tool (Equist)
Website: About Equist
Contact: Lakshmi Narasimhan Balaji
Parent institution: UNICEF

Upcoming Events

Micronutrient Forum Global Conference, Bangkok, Thailand 2020

EAT Food Forum, Stockholm, Sweden 2019

Past Events

SLAN Conference, Guadalajara, Mexico 2018

Optima Nutrition Training, Pretoria, South Africa 2018

African Nutritional Epidemiology Conference, Addis Ababa, Ethiopia 2018

American Society for Nutrition, Boston, Massachusetts 2018

See presentation

SUN Movement Global Gathering Parallel Workshop, Abidjan, Côte d’Ivoire 2017
Read the full report

Upcoming Trainings



Occasionally, members of the Consortium team up to jointly address special needs that are not yet covered by the group. Ongoing “work packages” are listed below:

Modeling the impact of MMS on antenatal and postnatal outcomes

Partners involved: MMS Task Force

Aim: Develop a module that allows to estimate, based on national data, the effect of switching from IFA to MMS in antenatal care programs on the following indicators: low birth weight; small for gestational age; pre-term birth; etc…)

Nutrition Theory of Change: Visualizer 

Partners involved: Led by LiST team; all consortium members participate

Aim: Provide a visualization of the various impact pathways affecting nutrition outcomes, documenting the literature, datasets, assumptions that used in the literature. This means to elaborate further the UNICEF’s Nutrition Conceptual Framework.

The Cost of Hunger in Ethiopia: Implications for the Growth and Transformation of Ethiopia
The Cost of Hunger in Malawi: Implications on National Development and Vision 2020
The Cost of Hunger in Uganda: Implications on National Development and Prosperity

The Cost of Hunger in Africa Project Summary

The Cost of Hunger in Africa: Social and Economic Impact of Child Undernutrition in Egypt, Ethiopia, Swaziland and Uganda

Country Level Nutrition Advocacy using PROFILES

The Effect of Chronic Malnutrition (Stunting) on Learning Ability, a Measure of Human Capital: A Model in PROFILES for Country-Level Advocacy (2016)

Estimating the Effect of Suboptimal Breastfeeding Practices on Child Mortality: A Model in PROFILES for Country-Level Advocacy (2015)

Investing in Nutrition Now: A Smart Start for Our Children, Our Future. Estimates of Benefits and Costs of a Comprehensive Program for Nutrition in Bangladesh, 2011– 2021

A Tool to Support Nutrition Advocacy in Ethiopia: Ethiopia PROFILES 2012 Estimates

Reducing Malnutrition in Guatemala: Estimates to Support Nutrition Advocacy—Guatemala PROFILES 2017

Reducing Malnutrition in Haiti: Estimates to Support Nutrition Advocacy – Haiti PROFILES 2013

Reducing Malnutrition in Tanzania: Estimates to Support Nutrition Advocacy: Tanzania PROFILES 2014

Reducing Malnutrition in Uganda: Estimates to Support Nutrition Advocacy – Uganda PROFILES 2013

Reducing Malnutrition in Zambia: Estimates to Support Nutrition Advocacy—Zambia Nutrition PROFILES 2017

Profiles Nutrition Advocacy by Country


Peer Review Journal Articles


Daelmans B, Ferguson E, Lutter C.K, Singh N, Pachón H, Creed-Kanashiro H, Woldt M, Mangasaryan N, Cheung E, Mir R, Pareja R, Briend A. Designing appropriate complementary feeding recommendations: tools for programmatic action. Matern Child Nutr. 2013; 9(2):116-30.

Ferguson E.L, Darmon, N, Fahmida, U, Fitriyanti, S, Harper, T.B, Premachandra, I.M. Design of optimal food-based complementary feeding recommendations and identification of key "problem nutrients" using goal programming. J Nutr. 2006; 136(9):2399-404.

Ferguson EL, Watson L, Berger J, Chea M, Chittchang U, Fahmida U, Khov K, Kounnavong S, et al. Realistic food-based approaches alone may not ensure dietary adequacy for women and young children in South-east Asia. Maternal Child Health J. 2018; Sep 29. doi: 10.1007/s10995-018-2638-3. [Epub ahead of print].

Tharrey M, Olaya G.A, Fewtrell M, Ferguson E. Adaptation of New Colombian Food-based Complementary Feeding Recommendations using Linear Programming. J Pediatr Gastroenterol Nutr. 2017; 65(6):667-672.

Ferguson E, Chege P, Kimiywe J, Wiesmann D, Hotz C. Zinc, iron and calcium are major limiting nutrients in the complementary diets of rural Kenyan children. Matern Child Nutr. 2015: 11(3):6-20.


Walker N., Tam Y., Friberg IK. Overview of the Lives Saved Tool (LiST)BMC Public Health. 2013: 13(3):S1.

Walker N, Clermont A. Nutrition Modeling in the Lives Saved Tool (LiST)J Nutr. 2017:147(11).

Walker N, Friberg IK (Ed.s). The Lives Saved Tool in 2017: Updates, applications and future directions. Supplement in BMC Public Health. 2017: 17(4).

Walker, N.  (Ed.). The Lives Saved Tool in 2013: new capabilities and applications.  Supplement of BMC Public Health. 2013:13(3).

Fox M, Marterell R, Van Den Broek N, Walker N, (Ed.s). Technical inputs, enhancements and applications of the Lives Saved Tool (LiST).  Supplement of BMC Public Health. 2011: 11(3).

Optima Nutrition

R Pearson, M Killedar, J Petravic, JJ Kakietek, N Scott, KL Grantham, RM Stuart, DJ Kedziora, CC Kerr, J Skordis-Worrall, M Shekar, DP Wilson. Optima Nutrition: an allocative efficiency tool to reduce childhood stunting by better targeting of nutrition-related interventions. BMC Public Health. 2018: 18 (384).


Engle-Stone R, Perkins A, Clermont A, Walker N, Haskell M.J, Vosti S.A, Brown K.H. Estimating Lives Saved by Achieving Dietary Micronutrient Adequacy, with a Focus on Vitamin A Intervention Programs in CameroonThe Journal of Nutrition. 2017: doi:10.3945/jn.116.242271.

Vosti S.A, Belinda R, Engle-Stone R, H. Luo. “Understanding Factors that Influence the Benefits and Costs of Rice Fortification” in Irizary, L., Prost, M-A., and D Murillo (Eds.), Scaling up Rice Fortification in Latin America and the Caribbean. Sight and Life and The World Food Programme. 2017: 176-181.

BakerS.K, Fracassi P, Kupka R, Neufeld L, M Shekar. Know Your Deficiencies, Know Your Response, Know Your Costs: A Commentary on Micronutrient Program Optimization ModelingFood and Nutrition Bulletin. 2015:36(3).

Brown K.H, Engle-Stone R, Kagin J, Rettig E, S.A Vosti. Use of Optimization Modeling for Selecting National Micronutrient Intervention Strategies. Food and Nutrition Bulletin. 2015: 36(3).

Engle-Stone R, Nankap M, Ndjebayi A.O, Vosti S.A, K.H Brown. Estimating the Effective Coverage of Programs to Control Vitamin A Deficiency and Its Consequences Among Women and Young Children in CameroonFood and Nutrition Bulletin. 2015: 36(3).

Cost of the Diet

Baldi G, Martini E, Catharina M, Muslimatun S, Fahmida U, Jahari AB, Hardinsyah, Frega R, Geniez P, Grede N, Minarto, Bloem MW, de Pee S. Cost of the Diet (CoD) tool: first results from Indonesia and applications for policy discussion on food and nutrition security. Food and Nutrition Bulletin. 2013: 34 (2).

Deptford A, Allieri T, Childs R,  Damu C, Ferguson E, Hilton J, Parham P, Perry A, Rees A, Seddon J, Hall A. Cost of the Diet: a method and software to calculate the lowest cost of meeting recommended intakes of energy and nutrients from local foods. BMC Nutrition. 2017: doi 10.1186/s40795-017-0136-4.