Why it’s needed:

Every year, natural disasters affect thousands of vulnerable people iacross the globe with disastrous consequences. Many people lose their homes and sources of income.

As part of our mission we are collecting and integrating data to predict the impact of impending disasters on vulnerable people in natural disaster prone areas. This process is called Impact Based Forecasting or IBF and consists of three steps.

Impact Based Forecasting (IBF)

1: Understanding Risk
By collecting population and geographic data (where people live and how many people live there), 510 can develop risk models to predict vulnerable areas to assess a community’s risk.

There are many factors in calculating risk. One simple indicator for example is measuring the distance a community lives from a major hospital. The further away they are, the more vulnerable they are. These types of indicators, (and many more) are placed in an interactive map or dashboard called Community Risk Assessment.

Malawi: Measering the distance, a community lives from a major hospital and placing it in an interactive map/dashboard

2: Identify Impact

To Identify future impact on these communities, 510 combines the Community Risk Assessment data with historical events data  (how & where previous natural disasters took place) and combining it with machine learning techniques. This understanding helps to identify “trigger levels” which indicates what level of risk needs to be reached to start an overall process called Forecast Based Financing.

Forecast-Based Financing was set up by the International Red Cross. The Red Cross Red Crescent Climate Centre, a reference centre for the wider Red Cross Movement is one of the founders of Forecast-Based Financing. The purpose of this international system is to provide aid workers in the disaster areas with money to take the necessary action in the event of a disaster being predicted.

3: Forecast Triggered Action

Forecast triggered action allows for “early warning early action”. This means that when its triggered, funds will be released to allow people in the impending disaster areas to get the means to protect themselves. This system for example, allows them to evacuate a disaster at an early stage.

Result: Stronger communities capable of responding proactively to disasters through early warning and early action. Damage, suffering and costs of emergency aid are reduced.

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