BackgroundRainfall-induced floods represented 70% of the disasters in Japan from 1985 to 2018 and caused various health problems. To improve preparedness and preventive measures, more information is needed on the health problems caused by heavy rain. However, it has proven challenging to collect health data surrounding disasters due to various inhibiting factors such as environmental hazards and logistical constraints. In response to the Kumamoto Heavy Rain 2020, Emergency Medical Teams (EMTs) used J-SPEED (Japan-Surveillance in Post Extreme Emergencies and Disasters) as a daily reporting tool, collecting patient data and sending it to an EMTCC (EMT Coordination Cell) during the response. We performed a descriptive epidemiological analysis using J-SPEED data to better understand the health problems arising from the Kumamoto Heavy Rain 2020 in Japan.MethodsDuring the Kumamoto Heavy Rain 2020 from July 5 to July 31, 2020, 79 EMTs used the J-SPEED form to submit daily reports to the EMTCC on the number and types of health problems they treated. We analyzed the 207 daily reports, categorizing the data by age, gender, and time period.ResultsAmong the 816 reported consultations, women accounted for 51% and men accounted for 49%. The majority of patients were elderly (62.1%), followed by adults (32.8%), and children (5%). The most common health issues included treatment interruption (12.4%), hypertension (12.0%), wounds (10.8%), minor trauma (9.6%), and disaster-related stress symptoms (7.4%). Consultations followed six phases during the disaster response, with the highest occurrence during the hyperacute and acute phases. Directly disaster-related events comprised 13.9% of consultations, indirectly related events comprised 52.0%, and unrelated events comprised 34.0%. As the response phases progressed, the proportions of directly and indirectly related events decreased while that of unrelated events increased.ConclusionBy harnessing data captured by J-SPEED, this research demonstrates the feasibility of collecting, quantifying, and analyzing data using a uniform format. Comparison of the present findings with those of two previous analyses of J-SPEED data from other disaster scenarios that varied in time, location, and/or disaster type showcases the potential to use analysis of past experiences to advancing knowledge on disaster medicine and disaster public health.
Read full abstract