Project
More details can be found on this website:
https://www.ucl.ac.uk/health-informatics/groups/public-health-data-science/research/virus-watchPartner:
This is the largest and most comprehensive community cohort study of COVID-19 in the U.K., with a team of multi-disciplinary researchers from across ten UCL Departments and Clinicians from University College London (UCLH) and Royal Free Hospitals. Our part in this study is to study people's movement during this pandemic. The findings will facilitate decision making.
Policy of non-pharmaceutical interventions (containing the virus via tiers system and lockdowns)
The economic and social impact of extra cycling lanes setting up in London by TfL during the pandemic
The impact of public transport for virus transmission
More details can be found on this website:
https://www.ucl.ac.uk/health-informatics/groups/public-health-data-science/research/virus-watch
Global Covid-19 Case Comparison
Cheng, T., Zhong, X., Liu, Y., Zhang, Y. & Dong, G.,
(2021) Dynamic Spreading of COVID-19 vs. Community Mobility in Regions of England.
https://doi.org/10.1007/978-3-030-72808-3_12Shaw, S., Sui, D., (eds).
Mapping COVID-19 in Space and Time: Understanding the Spatial and Temporal Dynamics of a Global Pandemic.
https://www.springer.com/gp/book/9783030728076Ibrahim, M., Haworth, J., Lipani, A., Aslam, N., Cheng, T., & Christie, N.,
(2021) Variational-LSTM autoencoder to forecast the spread of coronavirus across the globe, PLoS ONE, 16(1): e0246120.
https://doi.org/10.1371/journal.pone.0246120Cheng, T., Lu, T., Liu, Y., Gao, X., & Zhang, X
(2021) Revealing Spatiotemporal Transmission Patterns and Stages of COVID-19 in China using Patients Trajectory Data. Computational Urban Science.
https://doi.org/10.1007/s43762-021-00009-8