Modeling optimized treatment for acute malnutrition (OptiMA) for ALIMA


ALIMA is a humanitarian medical aid organization based in Dakar, Senegal. ALIMA is dedicated to continuous quality improvement in medical care in humanitarian contexts and carries out scientific research to improve innovation in healthcare delivery. Since its creation in 2009, ALIMA has treated over 2 million people, conducted 56 programs in 13 countries, and launched more than 10 research projects.


To improve standard malnutrition treatment protocols, ALIMA has developed Optimizing Treatment for Acute Malnutrition (OptiMA). OptiMA simplifies the treatment of acute malnutrition as a continuum condition under one protocol, rather than the current approach which designates two separate categories: severe acute malnutrition (SAM) and moderate acute malnutrition (MAM). OptiMA uses family-based screening at home by mid-upper arm circumference (MUAC), instead of more complex algorithms for SAM and MAM case management. A pilot study in Burkina Faso demonstrated that OptiMA is a feasible replacement for current malnutrition protocols. ALIMA hypothesizes that switching to OptiMA would result in non-inferior outcomes for children enrolled in a randomized control trial and be cost-saving due to its relative simplicity, but a comprehensive economic evaluation of the OptiMA approach has not yet been done.


Pharos is working with the Yale School of Public Health and the Harvard School of Public Health to test these hypotheses using data from two randomized control trials (RCTs) in Niger and the Democratic Republic of Congo (DRC) supplemented with data from operational pilot studies in Burkina Faso, Niger, and Mali. Pharos will estimate the comparative resource use from a health sector perspective, focusing on the cost of nutritional supplementation products, outpatient clinical care, hospitalizations, and supply chain management. The team will use decision-analytic modeling to estimate the expected health outcomes and costs of operating an acute malnutrition program at scale, comparing OptiMA to the standard national protocol.


Phase 1 (January 2020-November 2020): Cost Analysis of the OptiMA program using existing data from operational pilot projects in Burkina Faso and Niger, as well as an upcoming pilot study in Mali. The team is building a decision analytic model to estimate cost effectiveness of interventions using OptiMA.

The team will estimate the program cost of OptiMA: cost-per-cure, cost-per-case, and cost breakdown by resource use category for real-world implementation of OptiMA, and examine how treatment costs vary across patients based on factors such as MUAC, weight, height, oedema, and age at diagnosis.

Phase 2 (November 2020-April 2021): The team will use the model to estimate cost-effectiveness analysis of OptiMA compared to standard care in DRC.

Phase 3 (April 2021-July 2021): The team will use the model to estimate cost-effectiveness analysis of Optima compared to standard care in Niger.


This analysis will assist in program and financial planning, fill a major gap in evidence by calculating the incremental cost-effectiveness of the OptiMA protocol compared to the existing standard, and quantify how many more cases of acute malnutrition can be successfully treated with OptiMA given resource constraints.

Status: Ongoing

Team Members Involved: Robert Hecht, Stephen Resch, Ryoko Sato, Claire Young

For more information, contact Claire Young at

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