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

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Lu Zhong ◽  
Mamadou Diagne ◽  
Weiping Wang ◽  
Jianxi Gao
Keyword(s):  
Arrival Time ◽  
Geographical Area ◽  
The Novel ◽  
Parallel Circuits ◽  
Travel Restrictions ◽  
In Series ◽  
Disease Spreading ◽  
Backbone Tree ◽  
Novel Coronavirus ◽  
Distance Approach

AbstractDespite a number of successful approaches in predicting the spatiotemporal patterns of the novel coronavirus (COVID-19) pandemic and quantifying the effectiveness of non-pharmaceutical interventions starting from data about the initial outbreak location, we lack an intrinsic understanding as outbreak locations shift and evolve. Here, we fill this gap by developing a country distance approach to capture the pandemic’s propagation backbone tree from a complex airline network with multiple and evolving outbreak locations. We apply this approach, which is analogous to the effective resistance in series and parallel circuits, to examine countries’ closeness regarding disease spreading and evaluate the effectiveness of travel restrictions on delaying infections. In particular, we find that 63.2% of travel restrictions implemented as of 1 June 2020 are ineffective. The remaining percentage postponed the disease arrival time by 18.56 days per geographical area and resulted in a total reduction of 13,186,045 infected cases. Our approach enables us to design optimized and coordinated travel restrictions to extend the delay in arrival time and further reduce more infected cases while preserving air travel.

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 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 How to Better Manage Tourism on Pandemic-Times? Moving Forward on a Discussion We Should Have Had Before the 2020 Crisis

2020 ◽  
Author(s):  
Laura Sinay ◽  
Maria Cristina Fogliatti de Sinay
Keyword(s):  
Literature Review ◽  
Research Funding ◽  
Tourism Industry ◽  
The Novel ◽  
Scholarly Community ◽  
Pandemic Virus ◽  
Funding Agencies ◽  
Travel Restrictions ◽  
Novel Coronavirus

Taking advantage of tourists’ intensive flow, the SARS-CoV-2 virus rapidly spread causing thousands of deaths globally. Trying to contain the already pandemic virus, government travel restrictions were suddenly imposed. Consequently, the tourism industry, which at that moment employed one in ten workers globally, suddenly collapsed. Hundreds of thousands of workers immediately lost their income. Flights were cancelled, and thousands of tourists were stuck abroad with no means to return to their home countries. The gravity of the situation raised the question of whether there was scholarly knowledge that could have helped manage tourism during the current pandemic. To answer this question, a methodical literature review was performed, allowing for up to 900 publications to be analysed. Keywords used were pandemic, tourism, tourist and travel. Based on this process, 63 publications were selected for further analysis. Among these, less than 5% were focused on the tourism side of the problem. As such, this research concludes that, by the time the novel coronavirus emerged, there was, virtually, no scholarly knowledge on how to manage tourism during pandemic times so as to avoid chaos, and that the scholarly community studying related issues is very small. Moving forward, this article recommends that research funding agencies and universities encourage the sound development of this area of knowledge. Aspects that should be investigated include when, how and by whom should tourism be halted, as well as the feasibility of a Tourism World Fund for supporting related costs.

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 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 An Evaluation of COVID-19 in Italy: A data-driven modeling analysis

2020 ◽  
Author(s):  
Yongmei Ding ◽  
Liyuan Gao
Keyword(s):  
Real Data ◽  
Data Driven ◽  
The Novel ◽  
State Variables ◽  
Infected People ◽  
Modeling Analysis ◽  
Travel Restrictions ◽  
Novel Coronavirus ◽  
Data Driven Modeling ◽  
Global Travel

Abstract The novel coronavirus (COVID-19) that has been spreading worldwide since December 2019 has sickened millions of people, shut down major cities and some countries, prompted unprecedented global travel restrictions. Real data-driven modeling is an effort to help evaluate and curb the spread of the novel virus. Lockdowns and the effectiveness of reduction in the contacts in Italy has been measured via our modified model, with the addition of auxiliary and state variables that represent contacts, contacts with infected, conversion rate, latent propagation. Results show the decrease in infected people due to stay-at-home orders and tracing quarantine intervention. The effect of quarantine and centralized medical treatment was also measured through numerical modeling analysis.

scholarly journals Early dynamics of transmission and control of COVID-19: a mathematical modelling study

2020 ◽  
Author(s):  
Adam J Kucharski ◽  
Timothy W Russell ◽  
Charlie Diamond ◽  
Yang Liu ◽  
John Edmunds ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Control Measures ◽  
Transmission Model ◽  
The Novel ◽  
Transmission Potential ◽  
Travel Restrictions ◽  
Gates Foundation ◽  
Novel Coronavirus ◽  
And Control ◽  
Over Time

AbstractBackgroundAn outbreak of the novel coronavirus SARS-CoV-2 has led to 46,997 confirmed cases as of 13th February 2020. Understanding the early transmission dynamics of the infection and evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission to occur in new areas.MethodsWe combined a stochastic transmission model with data on cases of novel coronavirus disease (COVID-19) in Wuhan and international cases that originated in Wuhan to estimate how transmission had varied over time during January and February 2020. Based on these estimates, we then calculated the probability that newly introduced cases might generate outbreaks in other areas.FindingsWe estimated that the median daily reproduction number, Rt, declined from 2.35 (95% CI: 1.15-4.77) one week before travel restrictions were introduced on 23rd January to 1.05 (95% CI: 0.413-2.39) one week after. Based on our estimates of Rt,we calculated that in locations with similar transmission potential as Wuhan in early January, once there are at least four independently introduced cases, there is a more than 50% chance the infection will establish within that population.InterpretationOur results show that COVID-19 transmission likely declined in Wuhan during late January 2020, coinciding with the introduction of control measures. As more cases arrive in international locations with similar transmission potential to Wuhan pre-control, it is likely many chains of transmission will fail to establish initially, but may still cause new outbreaks eventually.FundingWellcome Trust (206250/Z/17/Z, 210758/Z/18/Z), HDR UK (MR/S003975/1), Gates Foundation (INV-003174), NIHR (16/137/109)

scholarly journals COVID-19 and Thrombosis Predisposition

2020 ◽  
Vol 5 (3) ◽  
pp. 86-90
Author(s):  
Renata Gerculy ◽  
Camelia Libenciuc ◽  
Nora Rat ◽  
Monica Chitu ◽  
Imre Benedek
Keyword(s):  
Infectious Disease ◽  
Current Knowledge ◽  
The Novel ◽  
Coagulation Disorders ◽  
Healthy Individuals ◽  
The World ◽  
Life Threatening ◽  
Thrombotic Complications ◽  
Disease Spreading ◽  
Novel Coronavirus

AbstractThe novel coronavirus disease first appeared in Wuhan (China) is an infectious disease spreading throughout the world, causing life-threatening conditions in vulnerable or even healthy individuals. The great impact of this virus on healthcare urges physicians to investigate all aspects of the disease in order to overcome its complications. A particularly investigated aspect of the SARS-CoV-2 infection is represented by the coagulation disorders among infected and critically ill patients. Several studies observed modified blood coagulation parameters such as D-dimers, fibrinogen, and coagulation times. Moreover, the severe thrombotic complications, mainly pulmonary embolism, could be responsible for the high mortality and poorer outcomes of COVID-19 infected patients. The aim of this article is to present the current knowledge related to thrombosis predisposition in patients infected with the new coronavirus.

scholarly journals A Method to Model Outbreaks of New Infectious Diseases with Pandemic Potential such as COVID-19

2020 ◽  
Author(s):  
Willem G. Odendaal
Keyword(s):  
Infectious Disease ◽  
Monte Carlo ◽  
Financial Markets ◽  
Infectious Agent ◽  
The Novel ◽  
Acceptable Accuracy ◽  
The World ◽  
Travel Restrictions ◽  
The Usa ◽  
Novel Coronavirus

AbstractThe emergence of the novel coronavirus (a.k.a. COVID-19, SARS-CoV-2) out of Wuhan, Hubei Province, China caught the world by surprise. As the outbreak began to spread outside of China, too little was known about the virus to model its transmission with any acceptable accuracy. World governments responded to rampant misinformation about the virus leading to collateral disasters, such as plunging financial markets, that could have been avoided if better models of the outbreak had been available. This is an engineering approach to model the spread of a new infectious disease from sparse data when little is known about the infectious agent itself. The paper is not so much about the model itself - because there are many good scientific approaches to model an epidemic - as it is about crunching numbers when there are barely any numbers to crunch. The coronavirus outbreak in USA is used to illustrate the implementation of this modeling approach. A Monte Carlo approach is implemented by using incubation period and testing efficiency as variables. Among others it is demonstrated that imposing early travel restrictions from infected countries slowed down the outbreak in the USA by about 26 days.

Coronavirus shows how China has changed since SARS

2020 ◽  
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Information Control ◽  
The Novel ◽  
Content Type ◽  
Spring Festival ◽  
Travel Restrictions ◽  
Novel Coronavirus ◽  
The City ◽  
Emergency Measures

Subject The government's response to the novel coronavirus in Wuhan. Significance A novel coronavirus that emerged in the city of Wuhan last month has now spread nationwide. The authorities have responded with heavy travel restrictions and other emergency measures that are affecting tens of millions of people during the Spring Festival public holiday travel season. The outbreak has parallels with the outbreak of SARS (severe acute respiratory syndrome) in China in 2002-03. Impacts Centralisation and information control are here to stay; the crisis will not shake the Party’s faith in their necessity. Some restrictive emergency measures may outlast the crisis. Novel diseases are likely to continue emerging from China every few years.

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