Phase-adjusted estimation of the number of Coronavirus Disease 2019 cases in Wuhan, China

Wang, Huwen; Wang, Zezhou; Dong, Yinqiao; Chang, Ruijie; Xu, Chen; Yu, Xiaoyue; Zhang, Shuxian; Tsamlag, Lhakpa; Shang, Meili; Huang, Jinyan; Ying, Wang; Xu, Gang; Shen, Tian; Zhang, Xinxin; Cai, Yong

doi:10.1101/2020.02.18.20024281

Cited by 164 publications

(234 citation statements)

References 22 publications

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“…9 These values showed that SARS-CoV-2 is highly contagious and it was projected that without any control measures the infected population would exceed 200 000 in Wuhan by the end of February 2020. 10 Other researchers estimated infected numbers of 191 529 (95% CI: 132 751 to 273 649) by 4 February 2020. 11 In the absence of an effective vaccine, 12 social distancing measures were needed to prevent transmission of the virus.…”

Section: Introductionmentioning

confidence: 99%

Modelling the effects of Wuhan’s lockdown during COVID-19, China

Yuan

Xiao

Dai

et al. 2020

Bull. World Health Organ.

104

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Objective To design a simple model to assess the effectiveness of measures to prevent the spread of coronavirus disease 2019 (COVID-19) to different regions of mainland China. Methods We extracted data on population movements from an internet company data set and the numbers of confirmed cases of COVID-19 from government sources. On 23 January 2020 all travel in and out of the city of Wuhan was prohibited to control the spread of the disease. We modelled two key factors affecting the cumulative number of COVID-19 cases in regions outside Wuhan by 1 March 2020: (i) the total the number of people leaving Wuhan during 20-26 January 2020; and (ii) the number of seed cases from Wuhan before 19 January 2020, represented by the cumulative number of confirmed cases on 29 January 2020. We constructed a regression model to predict the cumulative number of cases in non-Wuhan regions in three assumed epidemic control scenarios. Findings Delaying the start date of control measures by only 3 days would have increased the estimated 30 699 confirmed cases of COVID-19 by 1 March 2020 in regions outside Wuhan by 34.6% (to 41 330 people). Advancing controls by 3 days would reduce infections by 30.8% (to 21 235 people) with basic control measures or 48.6% (to 15 796 people) with strict control measures. Based on standard residual values from the model, we were able to rank regions which were most effective in controlling the epidemic. Conclusion The control measures in Wuhan combined with nationwide traffic restrictions and self-isolation reduced the ongoing spread of COVID-19 across China. Research COVID-19 epidemic control measures, mainland China Zheming Yuan et al.

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Section: Introductionmentioning

confidence: 99%

Modelling the effects of Wuhan’s lockdown during COVID-19, China

Yuan

Xiao

Dai

et al. 2020

Bull. World Health Organ.

104

View full text Add to dashboard Cite

show abstract

“…Based on the meta-data of five countries' evacuation action from January 29 to February 2, Zhao et al (2020) estimated that almost 110,000 (CI: 40,000-310,000) individuals were infected with SARS-CoV-2 in Wuhan by February 2. Wang et al (2020) estimated 4 phases divided by the dates when various levels of prevention and control measures were taken in effect in Wuhan, the number of infections would reach the peak 58, 077-84,520 or 55,869-81,393 in late February.…”

Section: How Many Wuhan Residents Were Infected With Sars-cov-2mentioning

confidence: 99%

A simple model to assess Wuhan lock-down effect and region efforts during COVID-19 epidemic in China Mainland

Yuan

Chen

2020

Preprint

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Since COVID-19 emerged in early December, 2019 in Wuhan and swept across China Mainland, a series of large-scale public health interventions, especially Wuhan lock-down combined with nationwide traffic restrictions and Stay At Home Movement, have been taken by the government to control the epidemic. Based onBaidu Migration data and the confirmed cases data, we identified two key factors affecting the later (e.g February 27, 2020) cumulative confirmed cases in non-Wuhan region (y). One is the sum travelers from Wuhan during January 20 to January 26 (x1), which had higher infected probability but lower transmission ability because the human-to-human transmission risk of COVID-19 was confirmed and announced on January 20. The other is the "seed cases" from Wuhan before January 19, which had higher transmission ability and could be represented with the confirmed cases before January 29 (x2) due to a mean 10-day delay between infection and detection. A simple yet effective regression model then was established as follow: y= 70.0916+0.0054×x1+2.3455×x2 (n = 44, R 2 = 0.9330, P<10 -7 ). Even the lock-down date only delay or in advance 3 days, the estimated confirmed cases by February 27 in non-Wuhan region will increase 35.21% or reduce 30.74% -48.59%. Although the above interventions greatly reduced the human mobility, Wuhan lock-down combined with nationwide traffic restrictions and Stay At Home Movement do have a determining effect on the ongoing spread of COVID-19 across China Mainland. The strategy adopted by China has changed the fast-rising curve of newly diagnosed cases, the international community should learn from lessons of Wuhan and experience from China. Efforts of 29 Provinces and 44 prefecture-level cities against COVID-19 were also assessed preliminarily according to the interpretive model. Big data has played and will continue playing an important role in public health.

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“…The first human cases of COVID-19, the disease caused by the novel coronavirus causing COVID-19, subsequently named SARS-CoV-2 were first reported by officials in Wuhan City, China, in December 2019 [1]. Retrospective investigations by Chinese authorities have identified human cases with onset of symptoms in early December 2019 [2]. While some of the earliest known cases had a link to a wholesale food market in Wuhan, some did not.…”

Section: Introductionmentioning

confidence: 99%

Does the Incidence of COVID-19 Pandemic Affect Rice Yield? Lessons from Southeast Nigeria

Esiobu¹

2021

Recent Advances in Rice Research

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Across Nigeria, while rice farmers are still battling the negative impact of climate change, the COVID-19 pandemic has brought a new risk that threatens not only farmers' livelihoods but also the most important global food security crop "rice". Every farming season, rice farmers face risks such as low rainfall, price volatility, and poor government policies. But the present risks from the COVID-19 pandemic are putting new challenges in front of rice value-chain that is already under serious threat. As a matter of urgency, farmers must respond to this new threat by choosing measures that increase their yield. Incidentally, empirical studies that documented the effect of COVID-19 pandemic on rice yield cannot be found as at the time of this study. These create emptiness in research. With this present threat, Nigeria is likely to experience a reversal in the development gains already achieved and will be unlikely to achieve the Agenda 2030 Goals.

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Phase-adjusted estimation of the number of Coronavirus Disease 2019 cases in Wuhan, China

Abstract: An outbreak of clusters of viral pneumonia due to a novel coronavirus (2019-nCoV / SARS-

Cited by 164 publications

References 22 publications

Modelling the effects of Wuhan’s lockdown during COVID-19, China

Modelling the effects of Wuhan’s lockdown during COVID-19, China

A simple model to assess Wuhan lock-down effect and region efforts during COVID-19 epidemic in China Mainland

Does the Incidence of COVID-19 Pandemic Affect Rice Yield? Lessons from Southeast Nigeria

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