Author: Liu, Ming; Ning, Jing; Du, Yurui; Cao, Jie; Zhang, Ding; Wang, Jiangang; Chen, Mingjun
Title: Modelling the evolution trajectory of COVID-19 in Wuhan, China: Experience and suggestions Cord-id: ubgimbfg Document date: 2020_5_12
ID: ubgimbfg
Snippet: Abstract Objectives In December 2019, a novel coronavirus disease (COVID-19) emerged in Wuhan city, China, which has subsequently led to a global pandemic. At the time of writing, COVID-19 in Wuhan appears to be in the final phase and under control. However, many other countries, especially the US, Italy and Spain, are still in the early phases and dealing with increasing cases every day. Therefore, this article aims to summarise and share the experience of controlling the spread of COVID-19 in
Document: Abstract Objectives In December 2019, a novel coronavirus disease (COVID-19) emerged in Wuhan city, China, which has subsequently led to a global pandemic. At the time of writing, COVID-19 in Wuhan appears to be in the final phase and under control. However, many other countries, especially the US, Italy and Spain, are still in the early phases and dealing with increasing cases every day. Therefore, this article aims to summarise and share the experience of controlling the spread of COVID-19 in Wuhan and provide effective suggestions to enable other countries to save lives. Study Design Data from the National Health Commission of China is used to investigate the evolution trajectory of COVID-19 in Wuhan and discuss the impacts of the intervention strategies. Methods A four-stage modified Susceptible-Exposed-Infectious-Removed (SEIR) model is presented. This model considers many influencing factors, including chunyun (the Spring festival), sealing off the city and constructing the Fang Cang shelter hospitals. In addition, a novel method is proposed to address the abnormal data on 12-13 February as a result of changing diagnostic criteria. Four different scenarios are considered to capture different intervention measures in practice. The exposed population in Wuhan who moved out prior to sealing off the city have also been identified and an analysis on where they had gone was performed using the Baidu migration index. Results The results demonstrate that the four-stage model was effective in forecasting the peak, size and duration of COVID-19. We found that the combined intervention measures are the only effective way to control the spread and not a single one of them can be omitted. We estimate that England will be another epicentre due to its incorrect response at the initial stages of COVID-19. Fortunately, big data technology can help provide early warnings to new areas of the pandemic. Conclusions The four-stage SEIR model was effective in capturing the evolution trajectory of COVID-19. Based on the model analysis, several effective suggestions are proposed to prevent and control the pandemic for countries that are still in the initial phases.
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