scholarly journals Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2)

Science ◽  
2020 ◽  
Vol 368 (6490) ◽  
pp. 489-493 ◽  
Author(s):  
Ruiyun Li ◽  
Sen Pei ◽  
Bin Chen ◽  
Yimeng Song ◽  
Tao Zhang ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Transmission Rate ◽  
Credible Interval ◽  
Metapopulation Model ◽  
Mobility Data ◽  
Geographic Spread ◽  
Travel Restrictions ◽  
Rapid Dissemination ◽  
Novel Coronavirus ◽  
Epidemiological Characteristics

Estimation of the prevalence and contagiousness of undocumented novel coronavirus [severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2)] infections is critical for understanding the overall prevalence and pandemic potential of this disease. Here, we use observations of reported infection within China, in conjunction with mobility data, a networked dynamic metapopulation model, and Bayesian inference, to infer critical epidemiological characteristics associated with SARS-CoV-2, including the fraction of undocumented infections and their contagiousness. We estimate that 86% of all infections were undocumented [95% credible interval (CI): 82–90%] before the 23 January 2020 travel restrictions. The transmission rate of undocumented infections per person was 55% the transmission rate of documented infections (95% CI: 46–62%), yet, because of their greater numbers, undocumented infections were the source of 79% of the documented cases. These findings explain the rapid geographic spread of SARS-CoV-2 and indicate that containment of this virus will be particularly challenging.

scholarly journals A data-driven assessment of early travel restrictions related to the spreading of the novel COVID-19 within mainland China

2020 ◽  
Author(s):  
Alberto Aleta ◽  
Qitong Hu ◽  
Jiachen Ye ◽  
Peng Ji ◽  
Yamir Moreno
Keyword(s):  
Mainland China ◽  
Behavioral Changes ◽  
The Novel ◽  
Metapopulation Model ◽  
Short Term ◽  
Effective Measure ◽  
Mobility Data ◽  
Health Authorities ◽  
Travel Restrictions ◽  
Novel Coronavirus

Two months after it was firstly reported, the novel coronavirus disease COVID-19 has already spread worldwide. However, the vast majority of reported infections have occurred in China. To assess the effect of early travel restrictions adopted by the health authorities in China, we have implemented an epidemic metapopulation model that is fed with mobility data corresponding to 2019 and 2020. This allows to compare two radically different scenarios, one with no travel restrictions and another in which mobility is reduced by a travel ban. Our findings indicate that i) travel restrictions are an effective measure in the short term, however, ii) they are ineffective when it comes to completely eliminate the disease. The latter is due to the impossibility of removing the risk of seeding the disease to other regions. Our study also highlights the importance of developing more realistic models of behavioral changes when a disease outbreak is unfolding.

scholarly journals Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (COVID-19)

2020 ◽  
Author(s):  
Ruiyun Li ◽  
Sen Pei ◽  
Bin Chen ◽  
Yimeng Song ◽  
Tao Zhang ◽  
...  
Keyword(s):  
Virus Transmission ◽  
Control Measures ◽  
Reproductive Number ◽  
Force Of Infection ◽  
Mobility Data ◽  
Source Of Infection ◽  
Travel Restrictions ◽  
Novel Coronavirus ◽  
And Control ◽  
Epidemiological Characteristics

AbstractBackgroundEstimation of the fraction and contagiousness of undocumented novel coronavirus (COVID-19) infections is critical for understanding the overall prevalence and pandemic potential of this disease. Many mild infections are typically not reported and, depending on their contagiousness, may support stealth transmission and the spread of documented infection.MethodsHere we use observations of reported infection and spread within China in conjunction with mobility data, a networked dynamic metapopulation model and Bayesian inference, to infer critical epidemiological characteristics associated with the emerging coronavirus, including the fraction of undocumented infections and their contagiousness.ResultsWe estimate 86% of all infections were undocumented (95% CI: [82%-90%]) prior to the Wuhan travel shutdown (January 23, 2020). Per person, these undocumented infections were 52% as contagious as documented infections ([44%-69%]) and were the source of infection for two-thirds of documented cases. Our estimate of the reproductive number (2.23; [1.77-3.00]) aligns with earlier findings; however, after travel restrictions and control measures were imposed this number falls considerably.ConclusionsA majority of COVID-19 infections were undocumented prior to implementation of control measures on January 23, and these undocumented infections substantially contributed to virus transmission. These findings explain the rapid geographic spread of COVID-19 and indicate containment of this virus will be particularly challenging. Our findings also indicate that heightened awareness of the outbreak, increased use of personal protective measures, and travel restriction have been associated with reductions of the overall force of infection; however, it is unclear whether this reduction will be sufficient to stem the virus spread.

scholarly journals Modeling the Novel Coronavirus (SARS-CoV-2) Outbreak in Sicily, Italy

2020 ◽  
Vol 17 (14) ◽  
pp. 4964 ◽  
Author(s):  
Andrea Maugeri ◽  
Martina Barchitta ◽  
Sebastiano Battiato ◽  
Antonella Agodi
Keyword(s):  
Transmission Rate ◽  
Control Measures ◽  
Transmission Dynamics ◽  
The Novel ◽  
Epidemic Spread ◽  
Transmission Rates ◽  
Contact Precautions ◽  
Travel Restrictions ◽  
Novel Coronavirus ◽  
Reported Data

Italy was the first country in Europe which imposed control measures of travel restrictions, quarantine and contact precautions to tackle the epidemic spread of the novel coronavirus (SARS-CoV-2) in all its regions. While such efforts are still ongoing, uncertainties regarding SARS-CoV-2 transmissibility and ascertainment of cases make it difficult to evaluate the effectiveness of restrictions. Here, we employed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model to assess SARS-CoV-2 transmission dynamics, working on the number of reported patients in intensive care unit (ICU) and deaths in Sicily (Italy), from 24 February to 13 April. Overall, we obtained a good fit between estimated and reported data, with a fraction of unreported SARS-CoV-2 cases (18.4%; 95%CI = 0–34.0%) before 10 March lockdown. Interestingly, we estimated that transmission rate in the community was reduced by 32% (95%CI = 23–42%) after the first set of restrictions, and by 80% (95%CI = 70–89%) after those adopted on 23 March. Thus, our estimates delineated the characteristics of SARS-CoV2 epidemic before restrictions taking into account unreported data. Moreover, our findings suggested that transmission rates were reduced after the adoption of control measures. However, we cannot evaluate whether part of this reduction might be attributable to other unmeasured factors, and hence further research and more accurate data are needed to understand the extent to which restrictions contributed to the epidemic control.

scholarly journals Global COVID-19 transmission rate is influenced by precipitation seasonality and the speed of climate temperature warming

2020 ◽  
Author(s):  
Katsumi Chiyomaru ◽  
Kazuhiro Takemoto
Keyword(s):  
Growth Rate ◽  
Transmission Rate ◽  
Global Climate ◽  
Human Life ◽  
Life Quality ◽  
Lower Growth ◽  
Climate Parameters ◽  
Precipitation Seasonality ◽  
Travel Restrictions ◽  
Novel Coronavirus

AbstractThe novel coronavirus disease 2019 (COVID-19) became a rapidly spreading worldwide epidemic; thus, it is a global priority to reduce the speed of the epidemic spreading. Several studies predicted that high temperature and humidity could reduce COVID-19 transmission. However, exceptions exist to this observation, further thorough examinations are thus needed for their confirmation. In this study, therefore, we used a global dataset of COVID-19 cases and global climate databases and comprehensively investigated how climate parameters could contribute to the growth rate of COVID-19 cases while statistically controlling for potential confounding effects using spatial analysis. We also confirmed that the growth rate decreased with the temperature; however, the growth rate was affected by precipitation seasonality and warming velocity rather than temperature. In particular, a lower growth rate was observed for a higher precipitation seasonality and lower warming velocity. These effects were independent of population density, human life quality, and travel restrictions. The results indicate that the temperature effect is less important compared to these intrinsic climate characteristics, which might thus be useful for explaining the exceptions. However, the contributions of the climate parameters to the growth rate were moderate; rather, the contribution of travel restrictions in each country was more significant. Although our findings are preliminary owing to data-analysis limitations, they may be helpful when predicting COVID-19 transmission.

scholarly journals Country distancing reveals the effectiveness of travel restrictions during COVID-19

2020 ◽  
Author(s):  
Lu Zhong ◽  
Mamadou Diagne ◽  
Weiping Wang ◽  
Jianxi Gao
Keyword(s):  
Mainland China ◽  
Credible Interval ◽  
Economic Loss ◽  
Geographic Area ◽  
Strategic Action ◽  
Infected Case ◽  
Travel Restrictions ◽  
In Series ◽  
Backbone Tree ◽  
Novel Coronavirus

Travel restrictions are the current central strategy to globally stop the transmission of the novel coronavirus disease (COVID-19). Despite remarkably successful approaches in predicting the spatiotemporal patterns of the ongoing pandemic, we lack an intrinsic understanding of the travel restriction's effectiveness. We fill this gap by developing a surprisingly simple measure, country distancing, that is analogical to the effective resistance in series and parallel circuits and captures the propagation backbone tree from the outbreak locations globally. This approach enables us to map the effectiveness of travel restrictions to arrival time delay (ATD) or infected case reduction (ICR) systematically. Our method estimates that 50.8\% of travel restrictions as of Apr-4 are ineffective, resulting in zero ATD or ICR worldwide. Instead, by imposing Hubei's lockdown on Jan-23 and national lockdown on Feb-8, mainland China alone leads to 11.66 [95\% credible interval (CI), 9.71 to 13.92] days of ATD per geographic area and 1,012,233 (95\% CI, 208,210 -4,959,094) ICR in total as of Apr-4. Our result unveils the trade-off between the country distancing increase and economic loss, offering practical guidance for strategic action about when and where to implement travel restrictions, tailed to the real-time national context.

scholarly journals Country distancing increase reveals the effectiveness of travel restrictions in stopping COVID-19 transmission

2020 ◽  
Author(s):  
Lu Zhong ◽  
Mamadou Diagne ◽  
Weiping Wang ◽  
Jianxi Gao
Keyword(s):  
Arrival Time ◽  
Geographical Area ◽  
Credible Interval ◽  
Disease Spread ◽  
Travel Restrictions ◽  
Efficiency And Effectiveness ◽  
In Series ◽  
Arrival Time Delay ◽  
Backbone Tree ◽  
Novel Coronavirus

Abstract Non-pharmaceutical interventions are the current central strategy to stop transmitting the novel coronavirus disease (COVID-19) globally. Despite remarkably successful approaches in predicting the ongoing pandemic's spatiotemporal patterns, we lack an intrinsic understanding of the travel restrictions' efficiency and effectiveness. We fill this gap by examining the countries' closeness based on disease spread using country distancing that is analogical to the effective resistance in series and parallel circuits and captures the propagation backbone tree from the outbreak locations globally. Our method estimates that 53.6\% of travel restrictions as of June 1, 2020, are ineffective. Our analytical results unveil that the optimal and coordinated travel restrictions postpone per geographical area by 22.56 [95\% credible interval (CI), 18.57 to 26.59] days of the disease's arrival time and protect the world by reducing 1,872,295 (95\% CI, 216,029 to 23,606,312) infected cases till June 1, 2020, which are significantly better than the existing travel restrictions achieving 12.87 (95\% CI, 10.59 to 15.17) days of arrival time delay and 861,867 (95\% CI, 238,250 to 3,879,638) infected cases reduction. Our approach offers a practical guide that indicates when and where to implement travel restrictions, tailed to the real-time national context.

scholarly journals Control Strategies against COVID-19 in China: Significance of Effective Testing in the Long Run

2020 ◽  
Author(s):  
Yatang Lin ◽  
Fangyuan Peng
Keyword(s):  
Control Strategies ◽  
Credible Interval ◽  
Personal Contact ◽  
Mobility Data ◽  
Long Run ◽  
Intercity Travel ◽  
Travel Restrictions ◽  
Short Run ◽  
Short And Long Term

The coronavirus disease 2019 (COVID-19) outbreak is reasonably contained in China. In this paper, we evaluated the effectiveness of different containment strategies in halting the pandemic spread in both short- and long-term. We combined a networked metapopulation SEIR model featuring undocumented infections, actual mobility data and Bayesian inference to simulate the counterfactual outbreak scenarios removing each one or a combination of the following three policies in place: i) city lockdowns, ii) intercity travel bans, and iii) testing, detection, and quarantine. Our estimates revealed that 11.4% [95% credible interval (CI): 9.7-13.0%] of the infected cases were unidentified before January 23, 2020. The rate grew to 92.5% [95% credible interval (CI): 85.9-94.5%] in early March, thanks to the boost in coronavirus testing capacity. We show that increasing the detection rate of infections from 11.4% to 92.5% alone would explain 75% of the reduction in infections from a no-policy baseline by March 15, 2020. The most pronounced policy implication is that city lockdowns appeared to be the more effective intervention in the short-run but effective testing is essential in containing the COVID-19 spread in the long run. By March 15, restoring within-city personal contact to its 2019 level would lead to a 678% growth in infections with all the other interventions remaining unaffected. Removing intercity travel restrictions and effective detection measures would lead to 3% and 477% growth, respectively. Extending the time horizon to July 15, the counterfactual increase in infections would become 581%, 3% and 30000% had the three classes of interventions been lifted individually.

scholarly journals Modeling the Novel Coronavirus (SARS-CoV-2) Outbreak in Sicily, Italy

2020 ◽  
Author(s):  
Andrea Maugeri ◽  
Martina Barchitta ◽  
Sebastiano Battiato ◽  
Antonella Agodi
Keyword(s):  
Transmission Rate ◽  
Control Measures ◽  
Transmission Dynamics ◽  
The Novel ◽  
Epidemic Spread ◽  
Contact Precautions ◽  
Its Regions ◽  
Travel Restrictions ◽  
Novel Coronavirus ◽  
Reported Data

Italy was the first country in Europe which imposed control measures of travel restrictions, quarantine and contact precautions to tackle the epidemic spread of the novel coronavirus (SARS-CoV-2) in all its regions. While such efforts are still ongoing, uncertainties regarding SARS-CoV-2 transmissibility and ascertainment of cases make it difficult to evaluate the effectiveness of restrictions. Here, we employed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model to assess SARS-CoV-2 transmission dynamics, working on the number of reported patients in intensive care unit (ICU) and deaths in Sicily (Italy), from 24 February to 13 April. Overall, we obtained a good fit between estimated and reported data, with a small fraction of unreported SARS-CoV-2 cases (19.5%; 95%CI=0%-34.7%) before 10 March lockdown. Interestingly, we estimated that the first set of restrictions reduced transmission rate in the community by 42% (95%CI=38%-46%), and that more stringent measures adopted on 23 March succeeded to drastically curb the transmission rate by 84% (95%CI=80%-88%). Thus, our estimates delineated the characteristics of SARS-CoV2 epidemic before restrictions taking into account unreported data. Further modeling after the adoption of control measures, moreover, indicated that restrictions reduced SARS-CoV2 transmission considerably.

An approach to the understanding of the clinical-etiopathological aspect of COVID-19 (SARS-CoV-2)

2020 ◽  
Vol 11 (SPL1) ◽  
pp. 862-869
Author(s):  
Meena Kumari ◽  
Monika Agrawal ◽  
Rakesh Kumar Singh ◽  
Parameswarappa S Byadgi
Keyword(s):  
World Health ◽  
Apical Surface ◽  
Therapy Assessment ◽  
Differentiated Cells ◽  
The World ◽  
Polarized Epithelia ◽  
Well Differentiated ◽  
Novel Coronavirus ◽  
Health Organization ◽  
Epidemiological Characteristics

Currently, the world is facing a health and socioeconomic crisis caused by the novel coronavirus disease COVID-19. On 11 March 2020, the World Health Organization (WHO) has declared this disease as a pandemic. The condition (COVID-19) is an infectious disorder triggered by a newly discovered severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2. Most of the COVID-19 infected patients will experience mild to moderate respiratory symptoms and recover without any unique therapy. Assessment of the clinical and epidemiological characteristics of SARS-CoV-2 cases suggests the infected patients will not be contagious until the onset of severe symptoms and affects the other organs. Well-differentiated cells of apical airway epithelia communicating with ACE2 were promptly infected to SARS-CoV-2 virus. But the expression of ACE 2 in poorly differentiated epithelia facilitated SARS spike (S) protein-pseudo typed virus entry and it is replicated in polarized epithelia and especially exited via the apical surface. Limiting the transmission of COVID-19 infection & its prevention can be regarded as a hierarchy of controls. In this article, we briefly discuss the most recent advances in respect to aetiology, pathogenesis and clinical progression of the disease COVID-19.

scholarly journals Government management capacities and the containment of COVID-19: a repeated cross-sectional study across Chinese cities

BMJ Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. e041516
Author(s):  
Wenchao Li ◽  
Jing Li ◽  
Junjian Yi
Keyword(s):  
Outcome Measures ◽  
Cross Sectional Study ◽  
Control Measures ◽  
Secondary Outcome ◽  
Cross Sectional ◽  
Travel Restrictions ◽  
Government Management ◽  
The Government ◽  
Laws And Policies ◽  
Novel Coronavirus

ObjectivesBetter understanding of the dynamics of the COVID-19 (2019 novel coronavirus disease) pandemic to curb its spread is now a global imperative. While travel restrictions and control measures have been shown to limit the spread of the disease, the effectiveness of the enforcement of those measures should depend on the strength of the government. Whether, and how, the government plays a role in fighting the disease, however, has not been investigated. Here, we show that government management capacities are critical to the containment of the disease.SettingWe conducted a statistical analysis based on cross-city comparisons within China. China has undergone almost the entire cycle of the anticoronavirus campaign, which allows us to trace the full dynamics of the outbreak, with homogeneity in standards for statistics recording.Primary and secondary outcome measuresOutcome measures include city-specific COVID-19 case incidence and recoveries in China.ResultsThe containment of COVID-19 depends on the effectiveness of the enforcement of control measures, which in turn depends on the local government’s management capacities. Specifically, government efficiency, capacity for law enforcement, and the transparency of laws and policies significantly reduce COVID-19 prevalence and increase the likelihood of recoveries. The organisation size of the government, which is not closely related to its capacity for management, has a limited role.

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