Predicting the Number of Consultations by Emergency Medical Teams During Disasters Using a Constant Attenuation Model: Analyzing the Data of 6 Disasters in Japan and Mozambique Between 2016-2020.

Introduction: Predicting the number of emergency medical team (EMT) consultations that are needed following a natural or man-made disaster can help improve decisions regarding the dispatch and withdrawal of these teams. This study aimed to predict the number of consultations by EMTs using the K value and constant attenuation model.

Methods: Data were collected using the Japan-Surveillance in Post-Extreme Emergencies and Disasters (J-SPEED) and Minimum Data Set (MDS) for five disasters in Japan and one disaster in Mozambique. We compared the number of consultations, which was predicted based on K value and constant attenuation model with actual data collected with J-SPEED/Minimum Data Set (MDS) tools.

Results: The total number of EMT consultations per disaster ranged from 684 to 18,468. The predicted curve and actual K data were similar for each of the disasters (R² from 0.953 to 0.997), but offset adjustments were needed for the Kumamoto earthquake and the Mozambique cyclone because their R² values were below 0.985. For the six disasters, the difference between the number of consultations predicted based on K values and the measured cumulative number of consultations ranged from ±1.0% to ± 4.1%.

Conclusions: The K value and constant attenuation model, although originally developed to predict the number of patients with COVID-19, provided reliable predictions of the number of EMT consultations required during six different disasters. This simple model may be useful for the coordination of future responses of EMTs during disasters.