MERIAM – Modelling Early Risk Indicators to Anticipate Malnutrition

BACKGROUND:

Fragile and conflict-affected states have some of the highest rates of hunger, acute malnutrition, and child mortality in the world today (UNICEF 2011). Weak systems and structures, as well as limited resources challenge the ability of governments to improve child nutrition and cope with stresses and shocks (e.g. conflict, disease, natural disasters, etc.) that affect undernutrition. Despite recent efforts to improve early warning systems for food insecurity in these contexts, current approaches to detect declines in nutrition security are still underdeveloped and only able to detect a nutrition crisis after it has already begun.

To be effective for nutrition, an early warning system must be able to identify an impending nutrition-related crisis and trigger a timely response before segments of the population become acutely malnourished. These systems must include indicators of nutritional vulnerability, able to detect localized increases in nutritional risk and have the capacity to differentiate how shocks and stresses (either singularly or in combination) will impact upon this relative risk in the short- and medium-term.

PROJECT SUMMARY:

The Modelling Early Risk Indicators to Anticipate Malnutrition (MERIAM) consortium aims to address this challenge head-on by:

1. identifying the leading indicators of acute malnutrition;
2. forecasting an increased risk of acute malnutrition and the key drivers of that risk; and,
3. generating scenarios that demonstrate how stresses and shocks affect this risk at a local level.

MERIAM deploys a complementary combination of innovative methodologies – both econometric and computational modelling – and leverages a variety of existing and accessible data sets to rigorously capture causal factors of acute malnutrition. Taken together, these aspects allow the project to dynamically model the fluctuation of acute malnutrition in contexts where this information is most urgently required. By better understanding the leading risk factors for acute malnutrition, MERIAM can forecast who may be most at-risk of becoming wasted, when they are likely to become wasted, and where (in what geographical area they reside).

EXPECTED IMPACT:

These aspects provide vital information to policymakers and practitioners, allowing for an earlier, proactive humanitarian and development response to be delivered those most vulnerable to becoming undernourished. MERIAM will therefore provide a timelier and cheaper alternative to traditional nutrition surveillance mechanisms, and also an alternative that is able to provide information and analysis on nutritional risk even in geographical areas that may not be immediately accessible (e.g. due to security considerations) to humanitarian actors.

Furthermore, by better understanding why individuals or communities are at risk for becoming undernourished, MERIAM is better able to identify how to minimize and/or mitigate this risk. These aspects provide vital information to policymakers and practitioners, allowing for improved targeting of human and financial resources towards the most appropriate, efficient and effective interventions in that context. Finally, MERIAM’s models will identify likely stressors or shocks, as well as how these may have an impact on resilience, behaviors, coping mechanisms, and nutrition outcomes. This information will improve diagnosis and analysis of nutrition vulnerability, as well as identify those factors that either support or inhibit nutritional resilience in a given context.