Lessons Learned Research: Livelihood Sector | COVID-19 Situational Analysis

Bangladesh, Burkina Faso, Colombia, Democratic Republic of the Congo, Nigeria, Syria
December 9, 2021
Situational Analysis

Executive Summary

Since the onset of COVID-19 in March 2020, the livelihoods sector has been massively impacted due to the measures taken by the governments to control the spread of the pandemic. Due to the unprecedented nature of the pandemic, most humanitarian organizations had issues accessing relevant data for program design and delivery and policy formulation. The livelihoods sector lessons learned report has used mixed methods by reviewing and analyzing the available secondary information collected by iMMAP during the course of the project, in conjunction with primary data through Key Informant Interviews (KIIs) in countries of focus during July and August 2021. The quantitative and qualitative information was collected, grouped into major themes and collectively analyzed to understand the livelihoods data availability, quality, adaptations made for data collection and analysis, lessons learned and recommendations during COVID-19.

The data was collected remotely through mixed methods including secondary data review and key informant interviews. The major focus of the data was on crisis affected areas where organizations were working before the onset of COVID-19 and COVID-19 hotspots. iMMAP also provided support for improvement of data quality through direct involvement in data collection and analysis in some countries such as Colombia, Nigeria and Syria. Similarly, iMMAP has also used innovative online technologies such as PREMISE and RIWI to address the gaps in the livelihood data.
Overall, data availability for the livelihood sector was relatively low, especially during the 2nd quarter of 2020 (April-June) and has steadily improved during the remaining period of COVID-19 as organizations have developed tools, methodologies, and protocols for remote data collection. The major sources of data were UN organizations, NGOs and Government departments. Under the humanitarian architecture, Food Security and Livelihood (FSL) Cluster in Bangladesh, Syria, DRC,Burkina Faso and Early Recovery and Livelihood Cluster in Colombia and Nigeria provided the data. In Burkina Faso, Colombia and DRC data collected by the Government, mainly on markets and employment was also helpful. The International Labor Organization (ILO) has also conducted assessments mainly on on-farm livelihoods. Special initiatives established in response to COVID-19, such as the public-private partnership “Partnership for Evidence-Based Response to COVID-19 (PERC)” covering 20 African Union countries including DRC and Nigeria, also play a key role in data availability.

Overall, the data quality during COVID-19 was good and served the purpose for planning and delivery of short-medium term livelihood interventions. The data quality steadily improved throughout the COVID-19 period based on the learnings. Tools and methodologies that were already used in most of the countries for data collection by organizations such as Multi Sector Needs Assessment (MSNA), market/price monitoring by World Food Program (WFP) and Food and Agriculture Organization (FAO) of the United Nations and Integrated Food Security Phase Classification (IPC) were tweaked for assessing the impact of COVID-19. MSNA was used as the most common tool for multi-sectoral data collection including livelihoods. Most of the organizations conducted multi-sectoral assessments with partial focus on livelihoods and agriculture-based livelihoods were reported more compared to off-farm livelihoods.

The major adaptations during COVID-19 were switching from in-person data collection to remote data collection, mainly relying on local partners; an adjustment of existing tools and methodologies; and increased use of innovative approaches such as use of satellite images and remote sensing. The major challenges reported were difficulties in reaching some areas due to COVID-19 protocols and security in some countries; issues pertaining to remote data collection; less effective coordination among stakeholders, partially due to remote working; less funding for COVID-19 (especially at the start) and limited capacity of partners capacity for required data collection.
The major recommendations are further research especially at the end of pandemic for medium-long term economic recovery; strengthening government data collection capacity; strengthening holistic assessments covering all aspects of the livelihoods; effective coordination among stakeholders; use of harmonized tools and methodologies; strengthening contingency planning and timely funding availability.

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