Population movement, city closure and spatial transmission of the 2019-nCoV infection in China

Ai, Siqi; Zhu, Guanghu; Tian, Fei; Li, Huan; Gao, Yuan; Wu, Yinglin; Liu, Qiyong; Lin, Hualiang

doi:10.1101/2020.02.04.20020339

Cited by 45 publications

(37 citation statements)

References 20 publications

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“…The timing and location of the outbreak facilitated the rapid transmission of the virus within a highly mobile population. The initial reporting of observed cases occurred during the traditional Chinese New Year, when the largest population movement takes place every year (Ai et al, 2020). Further, Wuhan is a highly populated city with more than 11 million residents and is connected to many cities in China through public transportation, such as buses, trains, and flights (Lai et al, 2020;Read, Bridgen, Cummings, Ho, & Jewell, 2020).…”

Section: Introductionmentioning

confidence: 99%

Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020

Roosa

Lee

Luo

et al. 2020

Infectious Disease Modelling

630

548

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a b s t r a c tThe initial cluster of severe pneumonia cases that triggered the COVID-19 epidemic was identified in Wuhan, China in December 2019. While early cases of the disease were linked to a wet market, human-to-human transmission has driven the rapid spread of the virus throughout China. The Chinese government has implemented containment strategies of city-wide lockdowns, screening at airports and train stations, and isolation of suspected patients; however, the cumulative case count keeps growing every day. The ongoing outbreak presents a challenge for modelers, as limited data are available on the early growth trajectory, and the epidemiological characteristics of the novel coronavirus are yet to be fully elucidated. We use phenomenological models that have been validated during previous outbreaks to generate and assess short-term forecasts of the cumulative number of confirmed reported cases in Hubei province, the epicenter of the epidemic, and for the overall trajectory in China, excluding the province of Hubei. We collect daily reported cumulative confirmed cases for the 2019-nCoV outbreak for each Chinese province from the National Health Commission of China. Here, we provide 5, 10, and 15 day forecasts for five consecutive days, February 5th through February 9th, with quantified uncertainty based on a generalized logistic growth model, the Richards growth model, and a sub-epidemic wave model. Our most recent forecasts reported here, based on data up until February 9, 2020, largely agree across the three models presented and suggest an average range of 7409e7496 additional confirmed cases in Hubei and 1128e1929 additional cases in other provinces within the next five days. Models also predict an average total cumulative case count between 37,415 and 38,028 in Hubei and 11,588e13,499 in other provinces by February 24, 2020. Mean estimates and uncertainty bounds for both Hubei and other provinces have remained relatively stable in the last three reporting dates (February 7th e 9th). We also observe that each of the models predicts that the epidemic has reached saturation in both Hubei and other provinces. Our findings suggest that the containment strategies implemented in China are successfully reducing transmission and that the epidemic growth has slowed in recent days.

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Section: Introductionmentioning

confidence: 99%

Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020

Roosa

Lee

Luo

et al. 2020

Infectious Disease Modelling

630

548

View full text Add to dashboard Cite

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“…The best available scientific evidence is therefore required to design effective NPI strategies and disseminate this knowledge urgently to help policy makers assess the potential benefits and costs of NPIs to contain COVID-19 outbreaks. Some previous studies have preliminarily explored the lockdown of Wuhan, [25][26][27] travel restrictions, [28][29][30] airport screening, 31,32 and the isolation of cases and contact tracing for containing virus transmission, respectively. 33,34 The conclusions of these studies are persuasive, there are still key knowledge gaps on the effectiveness of different interventions.…”

Section: Introductionmentioning

confidence: 99%

Effect of non-pharmaceutical interventions for containing the COVID-19 outbreak in China

Lai

Ruktanonchai

Zhou

et al. 2020

Preprint

228

231

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BackgroundThe COVID-19 outbreak containment strategies in China based on non-pharmaceutical interventions (NPIs) appear to be effective. Quantitative research is still needed however to assess the efficacy of different candidate NPIs and their timings to guide ongoing and future responses to epidemics of this emerging disease across the World. MethodsWe built a travel network-based susceptible-exposed-infectious-removed (SEIR) model to simulate the outbreak across cities in mainland China. We used epidemiological parameters estimated for the early stage of outbreak in Wuhan to parameterise the transmission before NPIs were implemented. To quantify the relative effect of various NPIs, daily changes of delay from illness onset to the first reported case in each county were used as a proxy for the improvement of case identification and isolation across the outbreak. Historical and near-real time human movement data, obtained from Baidu location-based service, were used to derive the intensity of travel restrictions and contact reductions across China. The model and outputs were validated using daily reported case numbers, with a series of sensitivity analyses conducted. FindingsWe estimated that there were a total of 114,325 COVID-19 cases (interquartile range [IQR] 76,776 -164,576) in mainland China as of February 29, 2020, and these were highly correlated (p<0.001, R 2 =0.86) with reported incidence.Without NPIs, the number of COVID-19 cases would likely have shown a 67-fold increase (IQR: 44 -94), with the effectiveness of different interventions varying. The early detection and isolation of cases was estimated to prevent more infections than travel restrictions and contact reductions, but integrated NPIs would achieve the strongest and most rapid effect. If NPIs could have been conducted one week, two weeks, or three weeks earlier in China, cases could have been reduced by 66%, 86%, and 95%, respectively, together with significantly reducing the number of affected areas. However, if NPIs were conducted one week, two weeks, or three weeks later, the number of cases . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.is the (which was not peer-reviewed) The copyright holder for this preprint .

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“…On Feb.9, 2020, X. Li et al [8] simulated the dynamics of the 2019-nCOV (COVID-19), on account of the strict control measures in Wuhan and Beijing. They showed that after the the traffic blockage on Jan.23,2020, the reproductive number in Wuhan will be 2.5, significantly lower than before.…”

Section: Introductionmentioning

confidence: 99%

Estimating the Efficacy of Quarantine and Traffic Blockage for the Epidemic Caused by 2019-nCoV (COVID-19):A Simulation Analysis

Liu

et al. 2020

Preprint

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Background: Since the 2019-nCoV outbreaks in Wuhan, China, the cumulative number of confirmed cases is increasing every day, and a large number of populations all over the world are at risk. The quarantine and traffic blockage can alleviate the risk of the epidemic and the infections, henceforth evaluating the efficacy of such actions is essential to inform policy makers and raise the public awareness of the importance of self-isolation and quarantine. Method:We collected confirmed case data and the migration data, and introduced the quarantine factor and traffic blockage factor to the Flow-SEIR model. By varying the quarantine factor and traffic blockage factor, we simulated the change of the peak number and arrival time of infections, then the efficacy of these two intervation measures can be analyzed in our simulation. In our study, the self-protection at home is also included in quarantine. Results:In the simulated results, the quarantine and traffic blockage are effective for epidemic control. For Hubei province, the current quarantine factor is estimaed to be 0.405, which means around 40.5% of suceptibles who are close contacting with are in quarantine, and the current traffic blockage factor is estimaed to be 0.66, which indicates around 34% of suceptibles who had flowed out from Hubei. For the other provinces outside Hubei, the current quarantine factor is estimated to be 0.285, and the current traffic blockage factor is estimated to be 0.26. With the quarantine and traffic blockage factor increasing, the number of infections decrease dramatically. We also simulated the start dates of quarantine and traffic blockage at four time points, the simulated results show that the early of warning is also effective for epidemic containing.However, provincial level traffic blockage can only alleviate 21.06% -22.38% of the peak number of infections. In general, the quarantine is much more effective than the traffic blockage control.

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Population movement, city closure and spatial transmission of the 2019-nCoV infection in China

Cited by 45 publications

References 20 publications

Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020

Real-time forecasts of the COVID-19 epidemic in China from February 5th to February 24th, 2020

Effect of non-pharmaceutical interventions for containing the COVID-19 outbreak in China

Estimating the Efficacy of Quarantine and Traffic Blockage for the Epidemic Caused by 2019-nCoV (COVID-19):A Simulation Analysis

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