Improving Household Economy Analysis (HEA) model in the Sahel Expert Consultant

Source: Save The Children

TERMS OF REFERENCE

ITT-WCA-HEA-002

Improving Household Economy Analysis (HEA) model in the Sahel by integrating remote sensing and Earth Observation/Geospatial data

Contracting agency: Save the Children International, WCA RO, Dakar, Senegal

Contracted agency: Expert consultant

Period under contract: October – December 2021

Background

The Household Economy Analysis (HEA) is a core data-driven methodology led by SC and its governmental and NGO’s partners since 10 years to improve food crisis prevention and early warning systems in West-Africa and the Sahel. The HEA tool is mainly used as a food security assessment tool, a targeting method for seasonal safety nets as well as an evaluation framework for food security and poverty reduction interventions. Each years, many Early Warning Systems and humanitarian stakeholders in the region rely on HEA data and results to inform their context analysis and intervention plans.

However, countries in the Sahel are facing an alarming growth in the number of risks and stress factors. In this rapid evolving operational context, HEA data-system optimisation becomes critical in order to better integrate the complexity and patterns of risks on people’s livelihoods and allow rapid monitoring of changing conditions in specific locations.

Reinforcing complementary data collection capabilities through the access to additional existing datasets (Earth Observation data), especially in areas where access is limited and data unavailable or not reliable will lead to reinforce assumptions setting and problem specifications during the Outcome Analysis which remains fundamental to improved accuracy of analyses and reinforce the quality of Early Warning Systems analysis.

Data availability and quality

At the moment, HEA problem specification is compiled from data collected during the seasonal assessments, mostly through national statistic and surveys. Although, most of the national Early Warning systems are willing to provide agricultural production and price variation data into the HEA analysis, such information is not always available in time due to the seasonality of the agricultural data collection to fill the analysis needs. Each year in October, and for several countries, agricultural statistics are not updated or based on previsional estimation. If agricultural statistics are not available, some countries are prone to use estimated statistical data (Niger, Nigeria) and update the problems specification when definitive statistics are available (or if there is still a need to reach national consensus). Others countries (such as Senegal, Chad) are not. By consequences, HEA problem specifications on crop production are often based on estimated data by national authorities or left empty and lead to recurring difference that undermine the quality of the assumptions and the reliability of the end-result analysis.

Regarding the price projection data, all countries have the capabilities to provide accurate historical series and estimations to the HEA model (through FEWSNET and Market Information Systems). Mauritania EWS remains the only one country that face critical lack of capacities to comply with this requirement. Furthermore, the price projection remain a composite indicator (market dynamic, supply and demand, working force, etc.). Remote sensing could bring value in providing near-real time information to fill some parameters of the indicator.            

Regarding the herd dynamic information, all countries at the moment face a lack of reliability of their analysis. Despite some encouraging initiatives and new partnerships between EWS operators and experts (FEWSNET, FEG, etc.), pastoral CSO (RBM) and national authorities, the projection remain weak and most of the time inaccurate.

Objective

Global Objective

The overall objective of this consultancy is to provide support to the integration of remote sensing and earth observation data in order to improve analysis through the triangulation and convergence of evidence in order to reinforce the reliability/accuracy of the HEA problem specification.

Scope of work and timeline

Under the supervision of the WCA Regional Programme Operations Director of Save the Children, the Supplier will provide the following services / meet the following specific objectives:

1. 1.      Remote sensing data assessment

• What are Earth observation data available and where collect them ? How diversifying secondary data sources (Agricultural production, surface areas, crop yields, pastures status, hydric stress, market and population as well as price projection (staple food price mainly) and turn it into something usable by HEA model

• Which information can be used to reinforce the HEA quality and how to access and use the information? (Check and analysis data availability with external partners (REACH, CILSS, FEWSNET, satellite data providers, etc.)

1. 2.      Remote sensing data integration (in 2-3 pilot areas)

• Incorporate remote weather satellite data into the LIAS
• Support the HEA analytical process bringing technical support to the regional team

1. 3.      Remote sensing data learning

• Develop technical guidance (step-by-step methodology development) process from data gaps analysis, data acquisition and synthesis

• Develop a rapid learning exercice and knowledge acquisition from HEAP programme and the Nigerian REACH/HEA experience. Development of knowledge sharing processes and incorporation into the technical guidance.

Consultancy deliverables

Consultancy Period-Number of days

Estimated Commencement Date: October 1st  2021

Estimated End Date: December 31st 2021

Fees and other costs

The Consulting will be contracted by Save the Children International (SCI) West and Central Africa Regional Office, Dakar, Senegal.

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