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Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Public+Health 2020 ; 183 (ä): 76-80 Nephropedia Template TP
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Modelling the evolution trajectory of COVID-19 in Wuhan, China: experience and suggestions #MMPMID32442842
Liu M; Ning J; Du Y; Cao J; Zhang D; Wang J; Chen M
Public Health 2020[Jun]; 183 (ä): 76-80 PMID32442842show ga
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 are 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 Fangcang 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 before 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 owing 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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Public+Health 2020 ; 183 (ä): 76-80
