ArticleTransportation research. Part A, Policy and practice2022
Role of stay-at-home requests and travel restrictions in preventing the spread of COVID-19 in Japan.
Article in Transportation research. Part A, Policy and practice, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 41 citations in OpenAlex.
- Age-specific impact of COVID-19 on birth rates in Japan: An interrupted time-series analysis using national vital statistics.PloS one · 2026Article
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- Long- and Short-Term Trends in Outpatient Attendance by Speciality in Japan: A Joinpoint Regression Analysis in the Context of the COVID-19 Pandemic.International journal of environmental research and public health · 2023Observational
- Changes in the cause of death in Japan before and during the COVID-19 pandemic.Archives of gerontology and geriatrics · 2023Article
- The Role of "Hierarchical and Classified Prevention and Control Measures (HCPC)" Strategy for SARS-CoV-2 Delta Variant in Guangzhou: A Modeling Study.Journal of epidemiology and global health · 2023Article
- Interaction between travel restriction policies and the spread of COVID-19.Transport policy · 2023Article
- Systematic literature review on impacts of COVID-19 pandemic and corresponding measures on mobility.Transportation · 2023Article
- The impact of traffic control measures on the spread of COVID-19 within urban agglomerations based on a modified epidemic model.Cities (London, England) · 2023Article
- COVID-19, travel restrictions and environmental consequences.Environment, development and sustainability · 2023Article
- Sustaining self-restraint until the middle of the COVID-19 pandemic in Tokyo.Scientific reports · 2022Article
- Correlation between national surveillance and search engine query data on respiratory syncytial virus infections in Japan.BMC public health · 2022Article
- How Effective Is a Traffic Control Policy in Blocking the Spread of COVID-19? A Case Study of Changsha, China.International journal of environmental research and public health · 2022Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
COVID-19 is one of the worst global health crises in a century. Japan confirmed its first case of COVID-19 in mid-January and declared a state of emergency in April and May 2020, urging people to stay at home and reduce travel. Using Mobile Spatial Statistics (i.e., population statistics created from operational data of mobile terminal networks), we estimated daily intra- and inter-prefectural population mobility in the Tokyo Megalopolis Region, Japan in 2020. Then, we developed a compartmental model with population mobility to explore the role of stay-at-home requests and travel restrictions in preventing the spread of COVID-19. This model describes the COVID-19 pandemic through a susceptible-exposed-presymptomatic infectious-undocumented and documented infectious-removed (SEPIR) process and incorporates intra- and inter-prefectural population mobility into the transmission process. We found that people significantly reduced travel during the state of emergency, although stay-at-home requests and travel restrictions were recommended rather than mandatory. The reduction in population mobility, combined with other control measures, resulted in a substantial reduction in effective reproduction numbers to below 1, thus controlling the first wave of the pandemic. Moreover, the relationship between population mobility and COVID-19 transmission changed over time. The dampening of the second wave of the pandemic indicated that smaller reductions in population mobility could result in pandemic control, probably because of other social distancing behaviors. Our proposed model can be used to analyze the impact of different public health interventions, and our findings shed light on the effectiveness of soft containments in curbing the spread of COVID-19.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.