tetano
Editor, Senior Moderator
Front Med (Lausanne)
. 2020 Jun 18;7:321.
doi: 10.3389/fmed.2020.00321. eCollection 2020.
Spread and Impact of COVID-19 in China: A Systematic Review and Synthesis of Predictions From Transmission-Dynamic Models
Yi-Fan Lin[SUP] 1 [/SUP], Qibin Duan[SUP] 2 3 [/SUP], Yiguo Zhou[SUP] 1 [/SUP], Tanwei Yuan[SUP] 1 [/SUP], Peiyang Li[SUP] 4 [/SUP], Thomas Fitzpatrick[SUP] 5 [/SUP], Leiwen Fu[SUP] 1 [/SUP], Anping Feng[SUP] 1 [/SUP], Ganfeng Luo[SUP] 1 [/SUP], Yuewei Zhan[SUP] 1 [/SUP], Bowen Liang[SUP] 1 [/SUP], Song Fan[SUP] 4 [/SUP], Yong Lu[SUP] 4 [/SUP], Bingyi Wang[SUP] 1 6 7 [/SUP], Zhenyu Wang[SUP] 4 [/SUP], Heping Zhao[SUP] 1 [/SUP], Yanxiao Gao[SUP] 1 [/SUP], Meijuan Li[SUP] 1 [/SUP], Dahui Chen[SUP] 1 [/SUP], Xiaoting Chen[SUP] 8 [/SUP], Yunlong Ao[SUP] 8 [/SUP], Linghua Li[SUP] 8 [/SUP], Weiping Cai[SUP] 8 [/SUP], Xiangjun Du[SUP] 1 [/SUP], Yuelong Shu[SUP] 1 [/SUP], Huachun Zou[SUP] 1 3 9 10 [/SUP]
Affiliations
Abstract
Background: Coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China, in December 2019 and quickly spread throughout China and the rest of the world. Many mathematical models have been developed to understand and predict the infectiousness of COVID-19. We aim to summarize these models to inform efforts to manage the current outbreak. Methods: We searched PubMed, Web of science, EMBASE, bioRxiv, medRxiv, arXiv, Preprints, and National Knowledge Infrastructure (Chinese database) for relevant studies published between 1 December 2019 and 21 February 2020. References were screened for additional publications. Crucial indicators were extracted and analysed. We also built a mathematical model for the evolution of the epidemic in Wuhan that synthesised extracted indicators. Results: Fifty-two articles involving 75 mathematical or statistical models were included in our systematic review. The overall median basic reproduction number (R[SUB]0[/SUB]) was 3.77 [interquartile range (IQR) 2.78-5.13], which dropped to a controlled reproduction number (R[SUB]c[/SUB]) of 1.88 (IQR 1.41-2.24) after city lockdown. The median incubation and infectious periods were 5.90 (IQR 4.78-6.25) and 9.94 (IQR 3.93-13.50) days, respectively. The median case-fatality rate (CFR) was 2.9% (IQR 2.3-5.4%). Our mathematical model showed that, in Wuhan, the peak time of infection is likely to be March 2020 with a median size of 98,333 infected cases (range 55,225-188,284). The earliest elimination of ongoing transmission is likely to be achieved around 7 May 2020. Conclusions: Our analysis found a sustained R[SUB]c[/SUB] and prolonged incubation/ infectious periods, suggesting COVID-19 is highly infectious. Although interventions in China have been effective in controlling secondary transmission, sustained global efforts are needed to contain an emerging pandemic. Alternative interventions can be explored using modelling studies to better inform policymaking as the outbreak continues.
Keywords: fatality; incubation; infectious period; mathematical model; the reproduction number.
. 2020 Jun 18;7:321.
doi: 10.3389/fmed.2020.00321. eCollection 2020.
Spread and Impact of COVID-19 in China: A Systematic Review and Synthesis of Predictions From Transmission-Dynamic Models
Yi-Fan Lin[SUP] 1 [/SUP], Qibin Duan[SUP] 2 3 [/SUP], Yiguo Zhou[SUP] 1 [/SUP], Tanwei Yuan[SUP] 1 [/SUP], Peiyang Li[SUP] 4 [/SUP], Thomas Fitzpatrick[SUP] 5 [/SUP], Leiwen Fu[SUP] 1 [/SUP], Anping Feng[SUP] 1 [/SUP], Ganfeng Luo[SUP] 1 [/SUP], Yuewei Zhan[SUP] 1 [/SUP], Bowen Liang[SUP] 1 [/SUP], Song Fan[SUP] 4 [/SUP], Yong Lu[SUP] 4 [/SUP], Bingyi Wang[SUP] 1 6 7 [/SUP], Zhenyu Wang[SUP] 4 [/SUP], Heping Zhao[SUP] 1 [/SUP], Yanxiao Gao[SUP] 1 [/SUP], Meijuan Li[SUP] 1 [/SUP], Dahui Chen[SUP] 1 [/SUP], Xiaoting Chen[SUP] 8 [/SUP], Yunlong Ao[SUP] 8 [/SUP], Linghua Li[SUP] 8 [/SUP], Weiping Cai[SUP] 8 [/SUP], Xiangjun Du[SUP] 1 [/SUP], Yuelong Shu[SUP] 1 [/SUP], Huachun Zou[SUP] 1 3 9 10 [/SUP]
Affiliations
- PMID: 32626719
- PMCID: PMC7314927
- DOI: 10.3389/fmed.2020.00321
Abstract
Background: Coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China, in December 2019 and quickly spread throughout China and the rest of the world. Many mathematical models have been developed to understand and predict the infectiousness of COVID-19. We aim to summarize these models to inform efforts to manage the current outbreak. Methods: We searched PubMed, Web of science, EMBASE, bioRxiv, medRxiv, arXiv, Preprints, and National Knowledge Infrastructure (Chinese database) for relevant studies published between 1 December 2019 and 21 February 2020. References were screened for additional publications. Crucial indicators were extracted and analysed. We also built a mathematical model for the evolution of the epidemic in Wuhan that synthesised extracted indicators. Results: Fifty-two articles involving 75 mathematical or statistical models were included in our systematic review. The overall median basic reproduction number (R[SUB]0[/SUB]) was 3.77 [interquartile range (IQR) 2.78-5.13], which dropped to a controlled reproduction number (R[SUB]c[/SUB]) of 1.88 (IQR 1.41-2.24) after city lockdown. The median incubation and infectious periods were 5.90 (IQR 4.78-6.25) and 9.94 (IQR 3.93-13.50) days, respectively. The median case-fatality rate (CFR) was 2.9% (IQR 2.3-5.4%). Our mathematical model showed that, in Wuhan, the peak time of infection is likely to be March 2020 with a median size of 98,333 infected cases (range 55,225-188,284). The earliest elimination of ongoing transmission is likely to be achieved around 7 May 2020. Conclusions: Our analysis found a sustained R[SUB]c[/SUB] and prolonged incubation/ infectious periods, suggesting COVID-19 is highly infectious. Although interventions in China have been effective in controlling secondary transmission, sustained global efforts are needed to contain an emerging pandemic. Alternative interventions can be explored using modelling studies to better inform policymaking as the outbreak continues.
Keywords: fatality; incubation; infectious period; mathematical model; the reproduction number.