People-centric impact forecasts: Predicting flood-induced loss of access to health services in the Greater Horn of Africa

Roads and healthcare facilities are critical in providing populations with basic health services. However, such critical infrastructures and the services they provide can be greatly disturbed when major natural hazards hit. Knowing which roads are still functional and where population could suffer from a loss of access to basic services before the unfolding of a hazardous event could be of great help for local authorities and for actors involved in disaster preparedness and relief.

We develop an impact forecast model aiming at predicting 1) which roads and healthcare facilities become nonfunctional in the event of a flood hazard and 2) where are populations at risk of losing access to health services. 

We combine the open-source weather and climate risk assessment model CLIMADA with flood forecasts to estimate the damage to roads and healthcare facilities and their resulting loss of functionality. We assess how the flood damage results in loss of access to health services for the population using a service-access model. We select several case studies of floods in the Greater Horn of Africa to illustrate the model's skill and fit of purpose. We use remote sensing data from the United Nations' disasters' charter mission and text reports from the International Federation of the Red Cross to compare modeled with observed impacts. We use an uncertainty and sensitivity quantification module available within the CLIMADA platform to study the sources of uncertainty in the impact forecasts, varying the input flood forecasts, exposures layers, impact functions, and parameters of the service-access module.

This research illustrates the potential benefits and challenges of a people-centric impact forecast in the context of flood hazard and showcases the development and calibration of an impact forecast model using open-source data and models.