Implementation of remote-sensing models to identify post-disaster health facility damage: Comparative approaches to the 2023 earthquake in Turkey

Paper by Anu Ramachandran, Akash Yadav, and Andrew Schroeder: “Earthquakes and other disasters can cause significant damage to health facilities. Understanding the scale of impact is important to plan for disaster response efforts and long-term health system rebuilding. Current manual methods of assessing health facility damage, however, can take several weeks to complete. Many research teams have worked to develop artificial intelligence models that use satellite imagery to detect damage to buildings, but there is still limited understanding of how these models perform in real-world settings to identify damage to healthcare facilities. Here, we take two models developed after the February 2023 earthquake in Turkey and overlay their findings with the locations of three types of health facilities: hospitals, dialysis centers, and pharmacies. We examine the accuracy and agreement between the two models and explore sources of error and uncertainty. We found that it was feasible to overlay these data to yield rapid health facility damage reports, but that the sensitivity of the models was low for the health facilities evaluated. We discuss the key sources of error and ways to improve the accuracy and usability of these models for real-world health facility analysis…(More)”.