World Agroforestry Centre (SCAN)


World Agroforestry Centre (ICRAF)

Surveillance of Climate‐Smart Agriculture for Nutrition (SCAN)

 

 

PI: Todd Rosenstock (ICRAF)

Collaborators: 
Brian DeRenzi (University of Cape Town)
Christine Lamanna (ICRAF)
Suneetha Kadiyala (LCIRAH)
Sabrina Chesterman (ICRAF)


Duration: 24 months (from September 2015)

Value: £249,999

Countries of research: ​Zambia and Ethiopia

 

 

Summary of the project:
 

This project will develop a novel compound metric and surveillance system to enable near real-time monitoring of nutrition outcomes from agricultural interventions for national and continental scale development initiatives. This demand-driven project will respond to urgent requests by the African Union’s New Economic Partnership for Africa’s Development and the African Climate-Smart Agriculture Alliance to develop methods to monitor the outcomes of their large-scale climate-smart agriculture-based development initiatives. 

This innovative research for development project will be achieved in three interdependent work packages:

1. A conceptual framework of the pathways by which agricultural interventions influence nutrition outcomes, developed as a collaborative undertaking between development partners, scientists and government representatives

The framework will guide the subsequent selection of a meaningful and practical set of indicators (e.g. cost-effective and sensitive) of agriculture and nutrition risk and status to monitor by surveillance approaches.

2. A mobile-based surveillance system

Instead of creating a unique collection platform, our approach intends to integrate existing systems used by a range of institutions and development projects. Here we seek to create unified and coherent datasets across these disparate collection methodologies. While piloting the data collection/ surveillance system in Zambia and Ethiopia, we will address critical research gaps and operational barriers facing the collection of high‐quality data via mobile reporting.

3. A novel metric based on hypervolume geometry for monitoring of agriculture and nutrition interactions

The data collected will form the input data to evaluate the potential of a novel metric based on hypervolume geometry for monitoring of agriculture and nutrition interactions, the final work package.

This unique approach allows us to capture the full complexity of variation in agriculture‐nutrition status in multiple dimensions within a population, while allowing for simple analyses of differences in outcomes for various subpopulations or under a range of agricultural interventions. 

The outputs of this project will set the benchmark for agriculture-nutrition surveillance by creating a cross-discipline and -institution platform and generate novel multi-disciplinary research contributions. The proposed surveillance system has the potential to change the conversation around agriculture and nutrition monitoring and planning. When appended to climate-smart agriculture programs, a tangible pathway emerges for the results to be immediately actionable at scale.