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 val...
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Shahid Beheshti University of Medical Sciences
2025-03-01
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| Series: | Archives of Academic Emergency Medicine |
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| Online Access: | https://journals.sbmu.ac.ir/aaem/index.php/AAEM/article/view/2457 |
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| author | Takahito Yoshida Tomohito Hayashi Odgerel Chimed-Ochir Yui Yumiya Ami Fukunaga Akihiro Taji Takashi Nakano Yoichi Ikeda Kenji Sasaki Matchecane Cossa Isse Ussene Ryoma Kayano Flavio Sario Kouki Akahoshi Yoshiki Toyokuni Kayako Chishima Seiji Mimura Akinori Wakai Hisayoshi Kondo Yuichi Koido Tatsuhiko Kubo |
| author_facet | Takahito Yoshida Tomohito Hayashi Odgerel Chimed-Ochir Yui Yumiya Ami Fukunaga Akihiro Taji Takashi Nakano Yoichi Ikeda Kenji Sasaki Matchecane Cossa Isse Ussene Ryoma Kayano Flavio Sario Kouki Akahoshi Yoshiki Toyokuni Kayako Chishima Seiji Mimura Akinori Wakai Hisayoshi Kondo Yuichi Koido Tatsuhiko Kubo |
| author_sort | Takahito Yoshida |
| collection | DOAJ |
| description |
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.
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| format | Article |
| id | doaj-art-14f725f1afc04b5b978f5a48df19681e |
| institution | OA Journals |
| issn | 2645-4904 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Shahid Beheshti University of Medical Sciences |
| record_format | Article |
| series | Archives of Academic Emergency Medicine |
| spelling | doaj-art-14f725f1afc04b5b978f5a48df19681e2025-08-20T02:05:01ZengShahid Beheshti University of Medical SciencesArchives of Academic Emergency Medicine2645-49042025-03-0113110.22037/aaemj.v13i1.2457Predicting 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 2016-2020Takahito Yoshida0Tomohito Hayashi1Odgerel Chimed-Ochir2Yui Yumiya3Ami Fukunaga4Akihiro Taji5Takashi Nakano6Yoichi Ikeda7Kenji Sasaki8Matchecane Cossa9Isse Ussene10Ryoma Kayano11Flavio Sario12Kouki Akahoshi13Yoshiki Toyokuni14Kayako Chishima15Seiji Mimura16Akinori Wakai17Hisayoshi Kondo18Yuichi Koido19Tatsuhiko Kubo20Hiroshima UniverityHiroshima UniversityHiroshima UniversityHiroshima UniversityHiroshima UniversityHiroshima UniversityOsaka UniversityOsaka UniversityOsaka UniversityNational Program of Surgery, Ministry of Health of MozambiqueNational Program of Surgery, Ministry of Health of MozambiqueWorld Health Organization Centre for Health Development (WHO Kobe Centre) Emergency Medical Teams, World Health OrganizationNational Hospital Organization Headquarters DMAT Secretariat MHLW JapanNational Hospital Organization Headquarters DMAT Secretariat MHLW JapanNational Hospital Organization Headquarters DMAT Secretariat MHLW JapanNational Hospital Organization Headquarters DMAT Secretariat MHLW JapanNational Hospital Organization Headquarters DMAT Secretariat MHLW JapanNational Hospital Organization Headquarters DMAT Secretariat MHLW JapanNational Hospital Organization Headquarters DMAT Secretariat MHLW JapanHiroshima University 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. https://journals.sbmu.ac.ir/aaem/index.php/AAEM/article/view/2457PredictionStatistical ModelDMATEmergency Medical Team Minimum Data SetJ-SPEEDDisaster |
| spellingShingle | Takahito Yoshida Tomohito Hayashi Odgerel Chimed-Ochir Yui Yumiya Ami Fukunaga Akihiro Taji Takashi Nakano Yoichi Ikeda Kenji Sasaki Matchecane Cossa Isse Ussene Ryoma Kayano Flavio Sario Kouki Akahoshi Yoshiki Toyokuni Kayako Chishima Seiji Mimura Akinori Wakai Hisayoshi Kondo Yuichi Koido Tatsuhiko Kubo 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 Archives of Academic Emergency Medicine Prediction Statistical Model DMAT Emergency Medical Team Minimum Data Set J-SPEED Disaster |
| title | 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 |
| title_full | 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 |
| title_fullStr | 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 |
| title_full_unstemmed | 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 |
| title_short | 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 |
| title_sort | 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 |
| topic | Prediction Statistical Model DMAT Emergency Medical Team Minimum Data Set J-SPEED Disaster |
| url | https://journals.sbmu.ac.ir/aaem/index.php/AAEM/article/view/2457 |
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