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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Main Authors:	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
Format:	Article
Language:	English
Published:	Shahid Beheshti University of Medical Sciences 2025-03-01
Series:	Archives of Academic Emergency Medicine
Subjects:	Prediction Statistical Model DMAT Emergency Medical Team Minimum Data Set J-SPEED Disaster
Online Access:	https://journals.sbmu.ac.ir/aaem/index.php/AAEM/article/view/2457
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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

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