The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
The impact of government measures and human mobility trend on COVID-19 related deaths in the UK
Open accessAbstract
The COVID-19 global pandemic has rapidly expanded, with the UK being one of the countries with the highest number of cases and deaths in proportion to its population. Major clinical and human behavioural measures have been taken by the UK government to control the spread of the pandemic and to support the health system. It remains unclear how exactly human mobility restrictions have affected the virus spread in the UK. This research uses driving, walking and transit real-time data to investigate the impact of government control measures on human mobility reduction, as well as the connection between trends in human-mobility and severe COVID-19 outcomes. Human mobility was observed to gradually decrease as the government was announcing more measures and it stabilized at a scale of around 80% after a lockdown was imposed. The study shows that human-mobility reduction had a significant impact on reducing COVID-19-related deaths, thus providing crucial evidence in support of such government measures.
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Cites
Zhou, F., Yu, T., Du, R., Fan, G., Liu, Y., Liu, Z., Xiang, J., Wang, Y., Song, B., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30566-3 · Cited by 27,263
A novel coronavirus outbreak of global health concern
Wang, C., Horby, P. W., Hayden, F. G., & Gao, G. F. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30185-9 · Cited by 7,700
Presumed Asymptomatic Carrier Transmission of COVID-19
Bai, Y., Yao, L., Wei, T., Tian, F., Jin, D.-Y., Chen, L., & Wang, M. (2020) · JAMA · doi:10.1001/jama.2020.2565 · Cited by 4,498
The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak
Chinazzi, M., Davis, J. T., Ajelli, M., Gioannini, C., Litvinova, M., Merler, S., Pastore y Piontti, A., Mu, K., Rossi, L., Sun, K., et al. (2020) · Science · doi:10.1126/science.aba9757 · Cited by 3,694
Docherty, A. B., Harrison, E. M., Green, C. A., Hardwick, H. E., Pius, R., Norman, L., Holden, K. A., Read, J. M., Dondelinger, F., Carson, G., et al. (2020) · BMJ · doi:10.1136/bmj.m1985 · Cited by 3,481
The effect of human mobility and control measures on the COVID-19 epidemic in China
Kraemer, M. U. G., Yang, C.-H., Gutierrez, B., Wu, C.-H., Klein, B., Pigott, D. M., Open COVID-19 Data Working Group, du Plessis, L., Faria, N. R., Li, R., et al. (2020) · Science · doi:10.1126/science.abb4218 · Cited by 2,950
Tian, H., Liu, Y., Li, Y., Wu, C.-H., Chen, B., Kraemer, M. U. G., Li, B., Cai, J., Xu, B., Yang, Q., et al. (2020) · Science · doi:10.1126/science.abb6105 · Cited by 2,010
Effect of non-pharmaceutical interventions to contain COVID-19 in China
Lai, S., Ruktanonchai, N. W., Zhou, L., Prosper, O., Luo, W., Floyd, J. R., Wesolowski, A., Santillana, M., Zhang, C., Du, X., et al. (2020) · Nature · doi:10.1038/s41586-020-2293-x · Cited by 1,375
Review and analysis of current responses to COVID-19 in Indonesia: Period of January to March 2020
Djalante, R., Lassa, J., Setiamarga, D., Sudjatma, A., Indrawan, M., Haryanto, B., Mahfud, C., Sinapoy, M. S., Djalante, S., Rafliana, I., et al. (2020) · Progress in Disaster Science · doi:10.1016/j.pdisas.2020.100091 · Cited by 1,234
The effect of COVID-19 and subsequent social distancing on travel behavior
De Vos, J. (2020) · Transportation Research Interdisciplinary Perspectives · doi:10.1016/j.trip.2020.100121 · Cited by 961
Cited by
Vaccination and non-pharmaceutical interventions for COVID-19: a mathematical modelling study
Moore, S., Hill, E. M., Tildesley, M. J., Dyson, L., & Keeling, M. J. (2021) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(21)00143-2 · Cited by 537
Metadata
- Authors
- Hadjidemetriou, G. M., Sasidharan, M., Kouyialis, G., & Parlikad, A. K.
- Venue
- Transportation Research Interdisciplinary Perspectives
- Publisher
- Elsevier BV
- Published
- 2020-07
- Volume
- 6
- Pages
- 100167
- ISSN
- 2590-1982 (ISSN-L)
- OpenAlex
- W3039136074
- Cited by
- 253
- References
- 21
- FWCI
- 8.73
- Type
- journal article
- Language
- en
- Open access
- gold
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- Hadjidemetriou, G. M., Sasidharan, M., Kouyialis, G., & Parlikad, A. K. (2020). The impact of government measures and human mobility trend on COVID-19 related deaths in the UK. Transportation Research Interdisciplinary Perspectives. https://doi.org/10.1016/j.trip.2020.100167
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.