Humanitarian response usually takes place after the impact of a crisis is visible. But in July, with monsoon rains descending on Bangladesh, the Centre for Humanitarian Data supported OCHA and partner organizations to act before disaster hit.
Our predictive analytics team worked with colleagues from OCHA’s Humanitarian Financing Strategy and Analysis Unit, the International Federation of Red Cross and Red Crescent Societies, and the Bangladesh Red Crescent Society to develop and validate triggers to release funds for those likely to be worst affected by the floods.
On 4 July, the European Commission’s Global Flood Awareness System predicted a high probability of severe flooding in Bangladesh. That threshold was the pre-activation trigger for the United Nations Central Emergency Response Fund (CERF) to release $5.2 million to the Food and Agriculture Organization (FAO), the World Food Programme (WFP) and the United Nations Population Fund (UNFPA).
The funds would enable them to prepare to distribute assistance including cash, livestock feed, storage drums, and hygiene, dignity and health kits.
This was the fastest CERF allocation since its establishment in 2005 and the first one to take place before peak flooding, based on the available forecasts.
Less than a week later, a separate activation trigger was reached and partners were able to deliver the much needed cash and supplies, ultimately reaching 200,000 people.
The Centre created its predictive analytics workstream in 2019 based on demand from OCHA’s leadership to “use data, and especially the tools of predictive analytics to get ahead, to be more anticipatory, to predict what is about to happen and to trigger the response earlier”.
OCHA subsequently established anticipatory action frameworks in a number of high-risk countries that have three elements: a predictive model or forecast; pre-arranged financing based on triggers; and a pre-agreed action plan.
In February, the Under-Secretary-General for Humanitarian Affairs and Emergency Relief Coordinator committed to investing up to $80 million from the CERF towards anticipatory action.
This included over $5 million for Bangladesh, which is vulnerable to monsoon flooding every year from June to September, with approximately one quarter of the country inundated.
The Bangladesh pilot involved a two-step trigger system: a pre-activation trigger, based on the European Commission’s Global Flood Awareness System forecast, and an activation trigger, based on the Government of Bangladesh’s Flood Forecasting and Warning Centre forecast.
The Centre’s predictive analytics team was asked to provide technical support to analyze and validate the thresholds and triggers for the release of funds from the CERF.