This webpage is being updated to reflect the final results of the MERIAM project - stay tuned for additional details. And in the meantime, please see some of MERIAM's current relevant work linked here:
- MERIAM Information Sheet
- Journal article in Food Security entitled "Empirical studies of factors associated with child malnutrition: highlight the evidence about climate and conflict shocks"
Undernutrition, which affects millions of children worldwide, is a significant threat to child health and contributes to nearly half of all child deaths. To prevent undernutrition, many countries have established early warning systems to alert humanitarian stakeholders to nutrition-related emergencies. These systems, however, remain dependent on late indicators (e.g. widespread presence of acute undernutrition or even mortality), which are only identified after an emergency has begun. Previous efforts to identify earlier indicators have been constrained by the quality, availability and frequency of data collection. New initiatives to strengthen nutrition information and early warning systems, as well as the growing use of new technology for collecting and disseminating data, now increase the feasibility of more effectively predicting nutritional risk to better mitigate crises.
Modelling Early Risk Indicators to Anticipate Malnutrition (MERIAM) is a four-year project funded by the UK government, which brings together an inter-disciplinary team of experts across four consortium partners: Action Against Hunger, the Graduate Institute of Geneva, John Hopkins University, and the University of Maryland. MERIAM’s primary aim is to develop, test and scale-up models to improve the prediction and monitoring of undernutrition in countries that experience frequent climate and conflict related shocks.
To accomplish this goal, the project’s work is divided between two project phases:
In Phase One [February 2017 to October 2018], the project will analyse the data landscape in MERIAM priority countries and select two countries for further elaboration. Datasets will be integrated and predictive models developed using both computational and econometric methods to test relationships between a variety of indicators. Once it is understood which indicators are connected to undernutrition outcomes, MERIAM will use statistical models to simulate the emergence of undernutrition in each country context, using historical data to test for accuracy and precision.
In Phase Two [November 2018 to May 2021], the Consortium will refine and validate its models, through both global and national-level consultation and engagement. MERIAM will address any data gaps through innovative, low-cost data collection approaches in pilot countries. The project will also create an online platform that enables users to interact directly with the data, evidence, and predictive models.
MERIAM will enable a better understanding of when and how stakeholders can measure and monitor nutritional risk; how humanitarian interventions can be better adapted to address drivers of risk in different contexts; and, how this type of analysis can be used to improve decision-making. The project will also identify and engage with potential users of the research to ensure that the evidence produced by MERIAM can inform more effective actions in policy, practice and future research.
For more information, please contact: firstname.lastname@example.org.