Evaluating the impact of COVID-19 on multi-sectoral humanitarian needs

What did this study set out to achieve?

The COVID-19 pandemic was expected to have a uniquely damaging impact on populations affected by humanitarian crises, exacerbating pre-existing vulnerabilities and multi-sectoral needs in places where health infrastructure and public services are stretched beyond capacity, and social distancing measures are nearly impossible.

Employing a multi-stage sequential analysis, using the crisis-wide Multi-Sector Needs Assessment (MSNA) to conduct primary research, this study set out to inform prioritisation efforts in three humanitarian responses. It aimed to focus on target population groups and geographical sub-areas where the COVID-19 pandemic had most impacted the direct and indirect health needs of people affected by crisis.

2019 MSNA data was used to produce a baseline understanding of vulnerability and resilience among target populations. The 2020 MSNA exercise was then used to evaluate the longitudinal, multi-sectoral impact of COVID-19 and the unintended consequences of public health measures, including lockdowns and social distancing.

The team aimed for these datasets to inform a COVID-19 risk prediction model in humanitarian settings. Analysis of the MSNA data can inform the development of Humanitarian Needs Overviews, People in Need calculations, and Humanitarian Response Plans, with the aim of supporting data-driven aid prioritisation in crises that have been exacerbated by the COVID-19 pandemic.

What were the key findings?

• Both displaced and non-displaced populations were at risk of exclusion from healthcare services and face barriers to access. Distance to healthcare facilities limits access in already fragile systems.
• Households with elderly or disabled members are vulnerable and at risk of exclusion from essential services. Households with lower levels of income, higher expenditure on basic needs, or higher levels of debt, are at a heightened risk of exclusion.
• Washing hands regularly, was the commonly adopted preventive measure across countries. Higher income households were more likely to adopt preventive measures.
• Policies restricting movement have indirect effects on income-generation, exacerbating pre-existing vulnerabilities, notably in the sectors of health, food security, and livelihoods.
• Information on humanitarian assistance and its communication both increases and decreases the adoption of different preventive measures.

What does this mean for policymakers and practitioners?

Policy implementation by governments and the humanitarian response need to be better coordinated, to mitigate the secondary indirect impacts of the most restrictive COVID-19 prevention policies and measures.

Strategic and operational policy makers should develop humanitarian response priorities by considering the specific needs and characteristics of population groups. The interactive effects between gender, displacement status, household demographics and socioeconomic variables should be taken into account.

Reducing distance-related barriers, increasing transportation services, and enabling access is key to reducing vulnerabilities, inequality, and building resilience.

Information and awareness raising should be tailored to increase the adoption of COVID-19 preventive measures, and closely consider the needs and practices of households reliant on humanitarian aid distribution.