Risk Assessment of Novel Coronavirus COVID-19 Outbreaks Outside China

Boldog, Péter; Tekeli, Tamás; Vizi, Zsolt; Dénes, Attila; Bartha, F.; Röst, Gergely

doi:10.1101/2020.02.04.20020503

Cited by 136 publications

(150 citation statements)

References 23 publications

(12 reference statements)

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“…From either estimate, we conclude that COVID-19 has substantial potential to spread via human-to-human transmission. However, R0 > 1 does not guarantee that a single exported (and untraced) case would immediately lead to a major epidemic in the destination country as government responses such as border control, isolation of suspected cases, and intensive surveillance should serve to reduce opportunities for transmission to occur [17][18][19].…”

Section: Discussionmentioning

confidence: 99%

Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases

Jung

Akhmetzhanov

Hayashi

et al. 2020

Preprint

186

189

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The exported cases of 2019 novel coronavirus infection that were confirmed outside of China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number-the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December, 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January, 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% CI: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.

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Section: Discussionmentioning

confidence: 99%

Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases

Jung

Akhmetzhanov

Hayashi

et al. 2020

Preprint

186

189

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“…Apart from India, a few models are also available for other countries, primarily for China, Italy and USA, as the numbers of infected patients are high. Studies like [12][13][14][15][16] worked on various mathematical models to determine the spread of the disease, predict the number of infected patients, commenting on the preparedness for each country in tackling COVID-19 spread and finding the patterns of flattening curve in different conditions. A lot of researches are still in preprint stage for the world level and are yet to be peer reviewed.…”

Section: Literature Reviewmentioning

confidence: 99%

A Comprehensive Analysis of COVID-19 Outbreak situation in India

Gupta

Pandey

2020

Preprint

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The outbreak of COVID-19 in different parts of the world is a major concern for all the administrative units of respective countries. India is also facing this very tough task for controlling the virus outbreak and has managed its growth rate through some strict measures. This study presents the current situation of coronavirus spread in India along with the impact of various measures taken for it. With the help of data sources (till 7 th -8 th April 2020) from various state units of India and Ministry of Health and Family Welfare, Government of India, this study presents various trends and patterns. This study answers six different research questions in a comprehensive manner. It has been reported that growth rate of infected cases has been controlled with the help of National Lockdown, however some uncontrolled mass level events had a negative impact on the infected cases. With the help of exponential and polynomial regression modelling, the predictions of up to 75000 cases have been done by the end of April 2020. It has also been seen that there are some prominent clusters and patient nodes in the network of patients which are the major influencers for COVID-19 spread. Also, death rate case predictions have been done through two-class classification models with an accuracy of 60%. At the end, strategies for continuation for lockdown has been discussed and presented. It appears that only essential services should be open for the citizens of India and the national lockdown should be carried on for next 2-4 weeks. This study will be useful for the Government of India and various states of India, Administrative Units of India, Frontline health workforce of India, researchers and scientists. This study will also be favorable for the administrative units of other countries to consider various aspects related to the control of COVID-19 outspread in their respective regions.

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“…Since the 2019-nCoV (COVID-19) 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 recent study [1][2][3][4] on the efficacy of traffic blockage for the COVID-19 indicated that the the population flows will certainly increase the cumulative number of cases and the quarantine and traffic blockage will lower this risk.…”

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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Risk Assessment of Novel Coronavirus COVID-19 Outbreaks Outside China

Cited by 136 publications

References 23 publications

Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases

Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases

A Comprehensive Analysis of COVID-19 Outbreak situation in India

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

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