Submitted by Dr. Dirk-jan Omtzigt (OCHA) & Daniel Pfister (OCHA)
2 Feb 2021 , last updated 2 Feb 2021

Dealing with a crisis within a crisis: Anticipatory Action in the age of Covid-19

This is an excerpt from “Dealing with a crisis within a crisis: Anticipatory Action in the age of Covid-19”, a session on 8 December 2020 at the Global Dialogue presentation by Dr. Dirk-Jan Omtzigt, Chief Economist and Head of the Humanitarian Financing Strategy and Analysis Unit at OCHA.

At the United Nations Office for the Coordination of Humanitarian Affairs (OCHA), we decided to apply the principles, lessons and tools from the Anticipatory Approach to the COVID crisis:

1. Timely but imperfect information of people at risk is preferred to perfect but late information of people in need because it allows you to act early.

At the very beginning of the crisis, much remained unknown about the properties of the virus. Epidemiological modelling was just starting, and it would take weeks or months before these models would be validated. In the meantime, we developed a simpler index to identify countries at risk of the pandemic by combining a small number of indicators on the basis of the epidemiological literature at the time, to support the decisions that had to be taken right then. We identified factors that increase (i) Transmission risks – like population density and movement (ii) people falling seriously ill, like demographic factors, poverty incidence, food insecurity, prevalence of comorbidities – cardio-vascular disease and  diabetes  - and the (iii) ability to respond like healthcare access, institutional capacity and WASH. To construct a COVID risk index rank ordering countries on the basis of their pandemic risk.

2. Models need to be tailored and adapted to the context.

Scientists at LSHTM and Imperial did eventually develop various epidemiological models to predict the epidemiological curve, but these were mostly focused on OECD countries and there was very limited modelling of Low Income Countries. The Centre for Humanitarian Data together with the Johns Hopkins University Applied Physics Laboratory developed a bespoke model for Afghanistan, DRC, South Sudan, Sudan, Iraq and Somalia guided by the following premises:

  • Given the dynamic nature of the disease and the government response, model assumptions would need to be updated frequently. Short-term projections, updated regularly, were more helpful.
  • There was and still is large underreporting of COVID infections in these countries and the projections needed to account for this.
  • Not national but subnational projections are critical to inform operational decisions.
  • While the model is complex the results should be presented in an easily digestible way for the decision makers.

This work also contributed to the “COVID-19 data explorer on global humanitarian operations”, providing a trusted source of data for humanitarian decision makers.  

3. Developing a crisis timeline helps understand how a crisis cascades and helps to identify intervention nodes.

When we tried to understand how the crisis would evolve over time we looked for example at the impact of Ebola in Sierra Leona in 2014 and realized that the secondary socio-economic impact of the crisis would dwarf the public health impacts – and we have seen 495 million people lose their job and 150 million people are projected to fall into extreme poverty. Even if a country did not register a single COVID-19 infection it could be severely impacted by this crisis. So, we developed a crisis timeline to understand the pathways of the economic impact which depends on:

  • The levels of informal employment:
    As those jobs are most at risk of being lost due to lockdowns while workers lacking social protection and access to good health care. 
     
  • Dependence on primary exports:
    For example, oil accounts for almost the totality of South Sudan’s exports, almost all of the government revenue and more than 40% of its gross domestic product (GDP). 
     
  • Dependence on remittances:
    Massive job losses among migrant workers impact people’s ability to send resources back home, which will have knock on effects on economies and vulnerable people heavily dependent on remittances, such as Tonga, South Sudan, Kyrgyzstan, Haiti, Honduras, Tajikistan and Nepal.
     
  • Dependence on tourism:
    Tourism employs a lot of people, especially on small islands [like Seychelles and Mauritius] and accounts for significant part of the economy and hard currency income [over 25% of exports in 2017] in Ethiopia, Nepal, Rwanda and Tanzania. 

4. Nothing is happening without financing.

We can get ahead of the primary and secondary impact of the COVID crisis in LICs but this requires funding so we focused on the cost of inaction laying out a stark picture of rising probability of conflict, lost development gains and lost human capital – counted the cost in the tens of trillions and made the case that acting now costing tens of billions was the smart thing to do. We have recently developed a set of proposals for IFIs to increase support to LICs, through debt restructuring, issuance of SDRs and leveraging their balance sheet.
 
 

5. Learn lessons:

We continuously asked ourselves two questions (a) what are questions that if we look back in 3-6 months’ time we would want to have known the answer to (b) what do we learn from the COVID response that allows to have a better humanitarian system in general and improve our understanding of anticipatory action in particular. Mark Lowcock, the Emergency Relief Coordinator, presented reflections when he gave a speech at Brookings on the COVID-19 fallout and challenges for the international humanitarian system. One thing is clear – the world responded too slowly to the COVID crisis and that has turned out to be very costly – and hopefully this can be a catalyst for anticipatory action.