Citizen-H2D3 will provide an unprecedented capacity for individuals, next users, and end-users to track a series of metrics in [near] real-time. It will use its multidisciplinary team of experts to develop a system that will leverage principles of citizen science and easy-to-deploy ICT tools to provide [near] real-time intelligence on individual daily dietary diversity and other nutrition and purchasing metrics.
More about the project
Globally, almost a billion people are undernourished while more than 2 billion are overweight. In Rwanda, like many lower-middle-income countries (LMICs), nutrition transitions are underway, brought into focus by the impacts of COVID-19.
There is a need for programmes and policies designed and targeted to address malnutrition in dynamic and increasingly unstable global food systems that consider both traditional as well as emerging diet patterns.
However, government agencies and non-governmental organizations struggle to do so as they are unable to access consistent, dynamic, and spatially disaggregated food consumption and purchasing data needed to develop informed, responsive, and actionable policies and interventions.
Metrics of national or regional malnourishment in LMICs mostly consist of annual estimates based upon small samples, that allow for limited spatial and temporal disaggregation and may not allow decision-makers to adequately understand, let alone address malnutrition.
Citizen- Individual/ Household Dietary Diversity Dynamics – or Citizen-H2D3 – is a novel and user-friendly tool to shift diet data collection pathways away from static researcher-led methods, towards dynamic citizen-led systems that can be integrated with other data sources in agriculture and health.
This Inspire Challenge proposal was selected as a 2020 pilot project winner, receiving a total of US$ 100,000 to put their ideas into practice. Learn more about the Inspire Challenge Grant here.
Step by step
Project awarded US$100K Inspire Challenge grant
The project was one of seven winners of the Inspire Challenge 2020 and was awarded US$100K at the fourth annual convention of the CGIAR Platform Big Data in Agriculture, 19-23 October 2020.
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