ArticleCities (London, England)2020
Evaluating the effect of city lock-down on controlling COVID-19 propagation through deep learning and network science models.
Article in Cities (London, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed.
- 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
- Psychological Impact of COVID-19 Lockdown and Its Evolution: A Case Study Based on Internet Searching Data during the Lockdown of Wuhan 2020 and Shanghai 2022.Healthcare (Basel, Switzerland) · 2023Article
- The road to recovery: Sensing public opinion towards reopening measures with social media data in post-lockdown cities.Cities (London, England) · 2023Article
- Interrogating the lack of diversity of thought in the pandemic response that led to mistakes - holistic evidence-based approach to deal with future pandemics.Frontiers in public health · 2023Article
- Do governmental policy interventions help urban economic recovery? Experimental evidence from China's provinces governance amid the COVID-19 pandemic.Growth and change · 2022Article
- A systematic review of COVID-19 transport policies and mitigation strategies around the globe.Transportation research interdisciplinary perspectives · 2022Article
- COVID-19 forecasts using Internet search information in the United States.Scientific reports · 2022Article
- Impact of the COVID-19 pandemic on urban human mobility - A multiscale geospatial network analysis using New York bike-sharing data.Cities (London, England) · 2022Article
- Mathematical model optimized for prediction and health care planning for COVID-19.Medicina intensiva · 2022Article
- Post-pandemic urban design: The equilibrium between social distancing and social interactions within the built environment.Cities (London, England) · 2022Article
- We shall endure: Exploring the impact of government information quality and partisanship on citizens' well-being during the COVID-19 pandemic.Government information quarterly · 2022Article
- Health-Based Geographic Information Systems for Mapping and Risk Modeling of Infectious Diseases and COVID-19 to Support Spatial Decision-Making.Advances in experimental medicine and biology · 2022Review
- Application of artificial intelligence in COVID-19 medical area: a systematic review.Journal of thoracic disease · 2021Review
- Making sense of the COVID-19 pandemic: A qualitative longitudinal study investigating the first and second wave in Italy.Heliyon · 2021Article
- Airborne Coronaviruses: Observations from Veterinary Experience.Pathogens (Basel, Switzerland) · 2021Review
- Changes in local travel behaviour before and during the COVID-19 pandemic in Hong Kong.Cities (London, England) · 2021Article
- Mathematical model optimized for prediction and health care planning for COVID-19.Medicina intensiva · 2021Article
- Analysis of Policies Based on the Multi-Fuzzy Regression Discontinuity, in Terms of the Number of Deaths in the Coronavirus Epidemic.Healthcare (Basel, Switzerland) · 2021Article
- Chasing the ghost of infection past: identifying thresholds of change during the COVID-19 infection in Spain.Epidemiology and infection · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The special epistemic characteristics of the COVID-19, such as the long incubation period and the infection through asymptomatic cases, put severe challenge to the containment of its outbreak. By the end of March 2020, China has successfully controlled the within- spreading of COVID-19 at a high cost of locking down most of its major cities, including the epicenter, Wuhan. Since the low accuracy of outbreak data before the mid of Feb. 2020 forms a major technical concern on those studies based on statistic inference from the early outbreak. We apply the supervised learning techniques to identify and train NP-Net-SIR model which turns out robust under poor data quality condition. By the trained model parameters, we analyze the connection between population flow and the cross-regional infection connection strength, based on which a set of counterfactual analysis is carried out to study the necessity of lock-down and substitutability between lock-down and the other containment measures. Our findings support the existence of non-lock-down-typed measures that can reach the same containment consequence as the lock-down, and provide useful guideline for the design of a more flexible containment strategy.
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