tetano
Editor, Senior Moderator
PLoS One
. 2020 Nov 24;15(11):e0242761.
doi: 10.1371/journal.pone.0242761. eCollection 2020.
Modeling and interpreting the COVID-19 intervention strategy of China: A human mobility view
Haonan Chen[SUP] 1 [/SUP], Jing He[SUP] 2 [/SUP], Wenhui Song[SUP] 1 [/SUP], Lianchao Wang[SUP] 1 [/SUP], Jiabao Wang[SUP] 1 [/SUP], Yijin Chen[SUP] 1 [/SUP]
Affiliations
Abstract
The Coronavirus Disease 2019 (COVID-19) has proved a globally prevalent outbreak since December 2019. As a focused country to alleviate the epidemic impact, China implemented a range of public health interventions to prevent the disease from further transmission, including the pandemic lockdown in Wuhan and other cities. This paper establishes China's mobility network by a flight dataset and proposes a model without epidemiological parameters to indicate the spread risks through the network, which is termed as epidemic strength. By simply adjusting an intervention parameter, traffic volumes under different travel-restriction levels can be simulated to analyze how the containment strategy can mitigate the virus dissemination through traffic. This approach is successfully applied to a network of Chinese provinces and the epidemic strength is smoothly interpreted by flow maps. Through this node-to-node interpretation of transmission risks, both overall and detailed epidemic hazards are properly analyzed, which can provide valuable intervention advice during public health emergencies.
. 2020 Nov 24;15(11):e0242761.
doi: 10.1371/journal.pone.0242761. eCollection 2020.
Modeling and interpreting the COVID-19 intervention strategy of China: A human mobility view
Haonan Chen[SUP] 1 [/SUP], Jing He[SUP] 2 [/SUP], Wenhui Song[SUP] 1 [/SUP], Lianchao Wang[SUP] 1 [/SUP], Jiabao Wang[SUP] 1 [/SUP], Yijin Chen[SUP] 1 [/SUP]
Affiliations
- PMID: 33232385
- DOI: 10.1371/journal.pone.0242761
Abstract
The Coronavirus Disease 2019 (COVID-19) has proved a globally prevalent outbreak since December 2019. As a focused country to alleviate the epidemic impact, China implemented a range of public health interventions to prevent the disease from further transmission, including the pandemic lockdown in Wuhan and other cities. This paper establishes China's mobility network by a flight dataset and proposes a model without epidemiological parameters to indicate the spread risks through the network, which is termed as epidemic strength. By simply adjusting an intervention parameter, traffic volumes under different travel-restriction levels can be simulated to analyze how the containment strategy can mitigate the virus dissemination through traffic. This approach is successfully applied to a network of Chinese provinces and the epidemic strength is smoothly interpreted by flow maps. Through this node-to-node interpretation of transmission risks, both overall and detailed epidemic hazards are properly analyzed, which can provide valuable intervention advice during public health emergencies.