Inferring the timing of individual mobility decisions from accommodation reservation data during the COVID-19 outbreak

Understanding the changes in human mobility in response to outbreaks is important for controlling emerging infectious disease outbreaks. This requires an understanding of the mechanism of human behavioural response as well as the timing of decisions for future mobility. However, most human mobility...

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Main Authors: Koichi Ito, Shunsuke Kanemitsu, Ryusuke Kimura, Ryosuke Omori
Format: Article
Language:English
Published: The Royal Society 2025-07-01
Series:Royal Society Open Science
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Online Access:https://royalsocietypublishing.org/doi/10.1098/rsos.250554
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author Koichi Ito
Shunsuke Kanemitsu
Ryusuke Kimura
Ryosuke Omori
author_facet Koichi Ito
Shunsuke Kanemitsu
Ryusuke Kimura
Ryosuke Omori
author_sort Koichi Ito
collection DOAJ
description Understanding the changes in human mobility in response to outbreaks is important for controlling emerging infectious disease outbreaks. This requires an understanding of the mechanism of human behavioural response as well as the timing of decisions for future mobility. However, most human mobility data only record the executed mobility that results from decision-making, and not the timing of decisions. In this study, we used accommodation reservation data to extract the decision-making process in response to the changing epidemic situation and compared it with data on executed mobility, ‘stay time’ in workplaces and stay time in places other than home or workplaces to clarify when people decide on their mobility. We confirmed that the decision-making process estimated from accommodation reservation data can accurately predict human mobility. The decision-making process estimated from accommodation reservation data was more strongly associated with stay time in places other than home or workplaces than stay time in workplaces. Furthermore, the comparison between the estimated decision-making process and mobility data quantitatively revealed that mobility was the result of integrating two types of decisions made in recent weeks (within two and five weeks for mobility to workplaces and places other than home or workplaces, respectively) and previous weeks.
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spelling doaj-art-7e43d1d2bc214c879acf17dde04423fe2025-07-29T23:05:08ZengThe Royal SocietyRoyal Society Open Science2054-57032025-07-0112710.1098/rsos.250554Inferring the timing of individual mobility decisions from accommodation reservation data during the COVID-19 outbreakKoichi Ito0Shunsuke Kanemitsu1Ryusuke Kimura2Ryosuke Omori3Faculty of Science and Engineering, Doshisha University, Kyotanabe, Kyoto 610-0394, JapanData Solution Unit 2 (Marriage & Family/Automobile Business/Travel), Data Management & Planning Office, Product Development Management Office, Recruit Co., Ltd, Tokyo 100-6640, JapanSaaS Data Solution Unit, Data Management & Planning Office, Product Development Management Office, Recruit Co., Ltd, Tokyo, 100-6640, JapanDivision of Bioinformatics, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Hokkaido 001-0020, JapanUnderstanding the changes in human mobility in response to outbreaks is important for controlling emerging infectious disease outbreaks. This requires an understanding of the mechanism of human behavioural response as well as the timing of decisions for future mobility. However, most human mobility data only record the executed mobility that results from decision-making, and not the timing of decisions. In this study, we used accommodation reservation data to extract the decision-making process in response to the changing epidemic situation and compared it with data on executed mobility, ‘stay time’ in workplaces and stay time in places other than home or workplaces to clarify when people decide on their mobility. We confirmed that the decision-making process estimated from accommodation reservation data can accurately predict human mobility. The decision-making process estimated from accommodation reservation data was more strongly associated with stay time in places other than home or workplaces than stay time in workplaces. Furthermore, the comparison between the estimated decision-making process and mobility data quantitatively revealed that mobility was the result of integrating two types of decisions made in recent weeks (within two and five weeks for mobility to workplaces and places other than home or workplaces, respectively) and previous weeks.https://royalsocietypublishing.org/doi/10.1098/rsos.250554COVID-19risk reduction behavioursdata interpretationsoutbreakshuman mobilitypopulation dynamics
spellingShingle Koichi Ito
Shunsuke Kanemitsu
Ryusuke Kimura
Ryosuke Omori
Inferring the timing of individual mobility decisions from accommodation reservation data during the COVID-19 outbreak
Royal Society Open Science
COVID-19
risk reduction behaviours
data interpretations
outbreaks
human mobility
population dynamics
title Inferring the timing of individual mobility decisions from accommodation reservation data during the COVID-19 outbreak
title_full Inferring the timing of individual mobility decisions from accommodation reservation data during the COVID-19 outbreak
title_fullStr Inferring the timing of individual mobility decisions from accommodation reservation data during the COVID-19 outbreak
title_full_unstemmed Inferring the timing of individual mobility decisions from accommodation reservation data during the COVID-19 outbreak
title_short Inferring the timing of individual mobility decisions from accommodation reservation data during the COVID-19 outbreak
title_sort inferring the timing of individual mobility decisions from accommodation reservation data during the covid 19 outbreak
topic COVID-19
risk reduction behaviours
data interpretations
outbreaks
human mobility
population dynamics
url https://royalsocietypublishing.org/doi/10.1098/rsos.250554
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