ArticlePloS one2021
The effect of human mobility restrictions on the COVID-19 transmission network in China.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Forecasting Thailand's mobility trends using Feature Engineered XGBoost for pandemic crisis movement management.PloS one · 2026Article
- Modelling the spread of infectious diseases in public transport systems under varying demand patterns and capacity constraints.Scientific reports · 2025Article
- Multi-region infectious disease prediction modeling based on spatio-temporal graph neural network and the dynamic model.PLoS computational biology · 2025Article
- The impact of COVID-19 mobility restrictions on dengue transmission in urban areas.PLoS neglected tropical diseases · 2024Article
- Uncovering COVID-19 transmission tree: identifying traced and untraced infections in an infection network.Frontiers in public health · 2024Article
- Analyzing the Robustness of Complex Networks with Attack Success Rate.Entropy (Basel, Switzerland) · 2023Article
- Policy evaluation during a pandemic.Journal of econometrics · 2023Article
- Impact of the COVID-19 pandemic on cancer healthcare utilization in southwestern China on March 2021.Cancer medicine · 2023Article
- Understanding the impact of mobility on COVID-19 spread: A hybrid gravity-metapopulation model of COVID-19.PLoS computational biology · 2023Article
- Impact of network centrality and income on slowing infection spread after outbreaks.Applied network science · 2023Article
- A community-level study on COVID-19 transmission and policy interventions in Wuhan, China.Cities (London, England) · 2022Article
- Exploring the impact of mobility restrictions on the COVID-19 spreading through an agent-based approach.Journal of transport & health · 2022Article
- Genome Evolution and Early Introductions of the SARS-CoV-2 Omicron Variant in Mexico.Virus evolution · 2022Article
- Autoregressive count data modeling on mobility patterns to predict cases of COVID-19 infection.Stochastic environmental research and risk assessment : research journal · 2022Article
- On the use of aggregated human mobility data to estimate the reproduction number.Scientific reports · 2021Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCOVID-19 poses a severe threat worldwide. This study analyzes its propagation and evaluates statistically the effect of mobility restriction policies on the spread of the disease.
methodsWe apply a variation of the stochastic Susceptible-Infectious-Recovered model to describe the temporal-spatial evolution of the disease across 33 provincial regions in China, where the disease was first identified. We employ Bayesian Markov Chain Monte-Carlo methods to estimate the model and to characterize a dynamic transmission network, which enables us to evaluate the effectiveness of various local and national policies.
resultsThe spread of the disease in China was predominantly driven by community transmission within regions, which dropped substantially after local governments imposed various lockdown policies. Further, Hubei was only the epicenter of the early epidemic stage. Secondary epicenters, such as Beijing and Guangdong, had already become established by late January 2020. The transmission from these epicenters substantially declined following the introduction of mobility restrictions across regions.
conclusionsThe spatial transmission network is able to differentiate the effect of the local lockdown policies and the cross-region mobility restrictions. We conclude that both are important policy tools for curbing the disease transmission. The coordination between central and local governments is important in suppressing the spread of infectious diseases.
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