Severe Acute Malnutrition (SAM) Photo Diagnosis App® Project

An innovative image-based diagnosis model for acute and chronic malnutrition.

Despite significant progress over recent decades, 45% of child deaths under five years old are still attributed to malnutrition. Acute malnutrition increases the risk of morbidity and mortality in children, and therefore requires urgent treatment. Health centres need to be equipped with the tools and expertise required for diagnosing and managing cases. Moreover, caretakers should be empowered to continue the treatment and monitor the child regularly until full recovery.

While weight-for-height (WHZ) and mid-upper arm circumference (MUAC) are common techniques used for diagnosing acute malnutrition, there are still significant operational challenges for their use at scale.


Project objectives: To develop an innovative image-based diagnosis model for acute and chronic malnutrition, and integrate it in an easy-to-use mobile phone app to allow for effective and simple diagnosis in the community and enhance community management of malnutrition. Study registration can be found here.

The present project comprises three stages:


This project reinforces decentralization and sustainability of community management of malnutrition by empowering caretakers to diagnose and monitor the nutrition status of their children. Caretakers and community members will also have increased access to nutrition information for preventing and managing malnutrition.  To measure impact in the targeted communities, Action Against Hunger will track App adoption rates, number of diagnosis completed, increase recovery rates and decrease defaults and relapse rates.

The project also presents a great opportunity for governments and local health systems to revolutionize nutrition assessments and improve the impact and coverage of nutrition programs. The potential for the app to facilitate rapid and easy diagnosis of malnutrition, together with the power of Nutrition SBCC to prevent and manage malnutrition, provides a unique opportunity to address malnutrition at scale. This is an important step towards achieving the Sustainable Development Goal 2.2 (SDG 2.2) and tackling malnutrition by 2030.

Innovation for communities (user driven): While the project intends to develop a new and innovative technology, from the very beginning Action Against Hunger will involve target communities in the process to ensure that the system is easy and intuitive for them to use, considering their feedback at each step of the project and adapting the technology to their needs and context when required. The tool will also incorporate a two-way communication system that will be completely customized to the needs of end-user needs as it will be developed following a user-centered design approach.

Gender approach: Both women and men in targeted communities will be involved at each stage of the planning and rollout of the project. They will equally participate in digital literacy workshops covering the functionalities of the App, two-way communication systems and additional phone/smartphone features. These can have a high gender-transformative impact particularly on female-headed households. Men will also gain from targeted health and nutrition advice including breastfeeding practices and appropriate diets. Monitoring will include both qualitative data (a gender analysis will be conducted at the start of the project and focus group discussions with both female and male participants will be carried out throughout the project to understand specific impact) and quantitative data (sex- and age disaggregated data on App adoption will be provided).


Project Information

Thematic Area: Nutrition and Health Research
Intervention Area: Senegal
Implementation Period: Phase I. 16/11/2015 – 30/06/2018 Phase II. 01/10/2018 – 30/06/2019 Phase III. 01/10/2019 – 30/06/2021
Partners: Phase I and II Complutense University of Madrid, Spain The present project accounts with the collaboration of two research groups: EPINUT (anthropometry and nutrition) and HumLog (statistics and mathematical models applied to humanitarian contexts). Université Cheick Anta Diop, Dakar, Senegal Software S.L.: Tyris Phase II WFP
Donors: Phase I: Child Investment Fund Foundation. Phase II: WFP and Grand Challenges Canada


Laura Medialdea Principal Investigator of SAM Photo Diagnosis App® Project, Research Expert, Technical Department, ACF-Spain
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