Human movement avoidance decisions during Coronavirus disease 2019 in Japan
Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved..
Understanding host behavioral change in response to epidemics is important to forecast the disease dynamics. To predict the behavioral change relevant to the epidemic situation (e.g., the number of reported cases), we need to know the epidemic situation at the moment of decision, which is difficult to identify from the records of actually performed human mobility. In this study, the largest travel accommodation reservation data covering half of the existed accommodations in Japan was analyzed to observe decision-making timings and how it responded to the changing epidemic situation during Japan's Coronavirus Disease 2019 until February 2023. To this end, we measured mobility avoidance index proposed in Ito et al., 2022 to indicate people's decision of mobility avoidance and quantified it using the time-series of the accommodation booking/cancellation data. We observed matches of the peak dates of the mobility avoidance and the number of reported cases, and mobility avoidance changed proportional to the logarithmic number of reported cases. We also found that the slope of mobility avoidance against the change of the logarithmic number of reported cases were similar among the epidemic waves, while the intercept of that was much reduced as the first epidemic wave passed by. People measure the intensity of epidemic by logarithm of the number of reported cases. The sensitivity of their response is established during the first wave and the people's response became weakened after the first experience, as if the number of reported cases were multiplied by a constant small factor.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:585 |
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| Enthalten in: |
Journal of theoretical biology - 585(2024) vom: 21. Apr., Seite 111795 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Omori, Ryosuke [VerfasserIn] |
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| Links: |
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| Themen: |
COVID-19 |
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| Anmerkungen: |
Date Completed 08.04.2024 Date Revised 08.04.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.jtbi.2024.111795 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a Understanding host behavioral change in response to epidemics is important to forecast the disease dynamics. To predict the behavioral change relevant to the epidemic situation (e.g., the number of reported cases), we need to know the epidemic situation at the moment of decision, which is difficult to identify from the records of actually performed human mobility. In this study, the largest travel accommodation reservation data covering half of the existed accommodations in Japan was analyzed to observe decision-making timings and how it responded to the changing epidemic situation during Japan's Coronavirus Disease 2019 until February 2023. To this end, we measured mobility avoidance index proposed in Ito et al., 2022 to indicate people's decision of mobility avoidance and quantified it using the time-series of the accommodation booking/cancellation data. We observed matches of the peak dates of the mobility avoidance and the number of reported cases, and mobility avoidance changed proportional to the logarithmic number of reported cases. We also found that the slope of mobility avoidance against the change of the logarithmic number of reported cases were similar among the epidemic waves, while the intercept of that was much reduced as the first epidemic wave passed by. People measure the intensity of epidemic by logarithm of the number of reported cases. The sensitivity of their response is established during the first wave and the people's response became weakened after the first experience, as if the number of reported cases were multiplied by a constant small factor | ||
| 650 | 4 | |a Journal Article | |
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| 650 | 4 | |a Data Interpretations, Statistical | |
| 650 | 4 | |a Epidemiology | |
| 650 | 4 | |a Population dynamics | |
| 650 | 4 | |a Risk Reduction Behaviors | |
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| 700 | 1 | |a Kanemitsu, Shunsuke |e verfasserin |4 aut | |
| 700 | 1 | |a Kimura, Ryusuke |e verfasserin |4 aut | |
| 700 | 1 | |a Iwasa, Yoh |e verfasserin |4 aut | |
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