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1.
IJID regions ; 2023.
Article in English | EuropePMC | ID: covidwho-2317721

ABSTRACT

Importance : On an ecological scale, the lag time between COVID-19 infection and related fatality has varied among different infection waves and prefectures in Japan. The variability in lag across areas of Japan during the seventh distinct infection phases can help derive a more appropriate estimation of the weekly confirmed case fatality rate (CFR) of COVID-19. Objective : Because of the ongoing COVID-19 pandemic, this study aims to estimate the seven days-moving average CFR across area block level in Japan from February 2020 t July 2022 using the lag time between the COVID-19 infection and related fatality. Main outcomes and measures : Seven days-moving average CFR of COVID-19 for area block in Japan considering the lag time between infection and death (total and subgroup analysis of elderly). Results : We found that the lag varied substantially among prefectures in Japan from the first to the seventh phase of the COVID-19 epidemic. The estimated seven days-moving average CFR based on the lag time reflects the Japanese COVID-19 pandemic and related policy intervention (e.g., vaccination for elderly people) well rather than other standard CFR estimations. Conclusions and relevance : The variation in the estimated lag time across prefectures in Japan for different infection waves indicates that it is inadequate to directly use the clinical results of the period from the start of infection to death for ecological-scale evaluation of the CFR. Moreover, we found that the lag time between infection and related fatality could be either shorter or longer than the clinically reported period. This revealed that preliminary reports of CFR may be overestimated or underestimated even if they consider the lag based on clinical reports.

2.
Sci Rep ; 13(1): 115, 2023 01 03.
Article in English | MEDLINE | ID: covidwho-2186071

ABSTRACT

The Japanese government adopted policies to control human mobility in 2020 to prevent the spread of severe acute respiratory syndrome coronavirus 2, which causes coronavirus disease 2019 (COVID-19). The present study examined the impact of human mobility on COVID-19 cases at the prefectural level in Japan by devising an indicator to have a relationship between the number of infected people and on human mobility. We calculated origin-destination travel mobility within prefectures in Japan from March 1st to December 31st, 2020, using mobile phone data. A cross-correlation function (CCF) was used to examine the relationship between human mobility and a COVID-19 infection acceleration indicator (IAI), which represents the rate of change in the speed of COVID-19 infection. The CCF of intraprefectural human mobility and the IAI in Tokyo showed a maximum value of 0.440 at lag day 12, and the IAI could be used as an indicator to predict COVID-19 cases. Therefore, the IAI and human mobility during the COVID-19 pandemic were useful for predicting infection status. The number of COVID-19 cases was associated with human mobility at the prefectural level in Japan in 2020. Controlling human mobility could help control infectious diseases in a pandemic, especially prior to starting vaccination.


Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Japan/epidemiology , Pandemics/prevention & control , SARS-CoV-2 , Tokyo
3.
Clin Epidemiol Glob Health ; 17: 101149, 2022.
Article in English | MEDLINE | ID: covidwho-2060497

ABSTRACT

Background/objectives: Japan has responded to the spread of COVID-19 through declaration of a state of emergency to regulate human mobility. Although the declaration was enforced by the government for prefectures, there is limited evidence as to whether the public complied with requests for voluntary stay at home. In this study, we evaluated the impact of declaring a state of emergency on human mobility during the COVID-19 pandemic in Japan. Methods: We utilized daily human mobility data for 47 prefectures in Japan. Data were collected via mobile phone from February 1, 2020 to April 30, 2021. Difference-in-difference analysis was utilized to estimate the effects of the declaration of a state of emergency on prefectures in the Tokyo Metropolitan Area (Tokyo, Kanagawa, Saitama, and Chiba) in comparison to other prefectures where the state of emergency was first lifted (Osaka, Hyogo, Fukuoka, and Aichi). Results: Human mobility was suppressed during the second state of emergency, from January 8 to March 21, 2021. However, the impact was weaker for the second state of emergency compared to the first. Conclusion: In Japan, government requests for stay at home, such as the declaration of a state of emergency, were temporarily able to control human mobility. However, the second state of emergency was not as effective as the first. If additional need to regulate human mobility arises, self-restraint with stronger enforcement should be considered.

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