Outbreak dynamics of COVID-19 in Europe and the effect of travel restrictions

Linka, Kevin; Peirlinck, Mathias; Costabal, Francisco Sahli; Kuhl, Ellen

doi:10.1080/10255842.2020.1759560

Cited by 270 publications

(167 citation statements)

References 24 publications

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“…Using equations (6,3), new functions and may be defined to represent the rate of new infections and the rate of transfer in and out of exposed and infectious compartments. Therefore, the matrices and are defined, as shown in equations (7,8).…”

Section: Basic Reproduction Number ( ) For the Modified Seir Modelmentioning

confidence: 99%

“…The base compartment epidemiology model is Susceptible-Infectious-Recovered (SIR) [5] and the extension of it is Susceptible-Exposed-Infectious-Recovered (SEIR). To study the dynamics of the COVID-19 epidemic, several modified SEIR models have been used to incorporate various measures, especially social distancing, testing, public responses, and mobility restrictions [2,[6][7][8][9]. The modified models have a large number of parameters that increase the complexity.…”

Section: Introductionmentioning

confidence: 99%

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COVID-19 Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered (SEIR) Model

Ahmad¹

2020

Cureus

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The coronavirus disease 2019 (COVID-19) pandemic has created unprecedented healthcare emergencies across the globe. The World Health Organization (WHO) has proposed social distancing (SD) as a prudent measure to contain the pandemic and, hence, governments have been enacting lockdowns of varied nature. These lockdowns, causing economic and social strain, warrant the development of quantitative models to optimally manage the pandemic. Similarly, extensive testing aids in early detection and isolation, hence containing the spread of the pandemic. Compartment epidemiology models have been used extensively in modeling such infectious diseases. This paper attempts to utilize the modified Susceptible-Exposed-Infectious-Recovered (SEIR) model incorporating the SD, testing, and infectiousness of exposed and infectious compartments to study the COVID-19 pandemic in Saudi Arabia. Saudi Arabia has put restrictions on the movement of people in different phases to ascertain SD. Timedependent parameters based on the timeline of restrictions and testing in Saudi Arabia have been introduced to capture SD and testing. The arrived model has been validated through statistical tests. The (R naught), basic reproduction number, value has ranged between 0.6014 and 2.7860 with an average of 1.4904 and currently holds at 0.8952. In the absence of SD and testing measures, the model predicts the threshold herd immunity to be 69.31% and value as 3.26. Further, scenario analysis has been conducted for alleviating the SD measure. The results show that early lifting of all restrictions may undo all efforts in the containment of the COVID-19 pandemic. The outcome of results will help policymakers and medical practitioners prepare better to manage the pandemic and lockdown.

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Section: Basic Reproduction Number ( ) For the Modified Seir Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

COVID-19 Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered (SEIR) Model

Ahmad¹

2020

Cureus

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“…Zheng et al (2020) indicate that COVID-19 cases imported via transportation are a key factor in the pandemic spread. Linka et al (2020) suggest that an unconstrained mobility would have significantly accelerated the spread of the COVID-19 pandemic, particularly in Central Europe, Spain and France. According to Muller et al (2020) and Musselwhite et al (2020) public transport plays a significant role in the spread of infectious diseases, thus attempts to control the spread of infections via public transportation reduces the infection speed.…”

Section: Introductionmentioning

confidence: 99%

Decline in Mobility: Public Transport in Poland in the time of the COVID-19 Pandemic

2020

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The aim of the paper is to assess changes in mobility in public transport in Poland, as a consequence of the development of the COVID-19 pandemic. We analyse the problem from the country and regional (voivodeships) perspective. The data come from Google COVID19 Community Mobility Reports, the Ministry of Health of Poland, and the Oxford COVID-19 Government Response Tracker. The research covers the period between 2 March and 19 July 2020. The obtained results show that there is negative but insignificant relationship between human mobility changes in public transport and the number of new confirmed COVID-19 cases in Poland. The strength and statistical significance of the correlation varies substantially across voivodeships. As far as the relationship between changes in mobility in public transport and the stringency of Polish government’s anti-COVID-19 policy is concerned, the results confirm a strong, negative and significant correlation between analysed variables at the national and regional level. Moreover, based on one factor variance analysis (ANOVA) and the Tukey’s honest significance test (Tukey’s HSD test) we indicate that there are significant differences observed regarding the changes in mobility in public transport depending on the level of stringency of anti-COVID-19 regulation policy both in Poland and all voivodeships. The results might indicate that the forced lockdown to contain the development of the COVID-19 pandemic has effectively contributed to social distancing in public transport in Poland and that government restrictions, rather than a local epidemic status, induce a greater decrease in mobility.

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“…11Modelling data which predicted the potential numbers of cases, deaths and impact on health service capacity informed the decisions to implement strong containment strategies and in particular, restrictive border measures, rst with restriction of travel from China and then more broadly when analysis of transmission identi ed travel from other countries and cruise ships as factors introducing the epidemic in Australia. (12)(13)(14) Australian modelling studies had shown that in order to mitigate disease spread in Australia, isolation, quarantine and social distancing were required to ensure that Intensive Care Units (ICU) and the hospital system more broadly were not overwhelmed by a rapid increase in COVID-19 cases. (15)(16)(17).…”

Section: Incidentsmentioning

confidence: 99%

Control of COVID-19 in Australia through quarantine: the role of Special Health Accommodation (SHA) in New South Wales, Australia

Fotheringham

Anderson

Shaw

et al. 2020

Preprint

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Background The first COVID-19 cases were diagnosed in Australia on 25 January 2020. Initial epidiemiology showed that the majority of cases were in returned travellers from overseas. One aspect of Public Health response was to introduce compulsory 14 day quarantine for all travellers returning to NSW by air or sea in Special Health Accommodation (SHA).MethodsThe SHA was established with a comprehensive governance structure, clinical management through rpavirtual hospital remote management and site management with health care workers, NSW Police and accommodation staff.Findings From 29 March to 29 April 2020, 373 returned travellers were admitted to the SHA from Sydney Airport. 88 (26.1%) of those swabbed were positive for SARS-CoV 2, 0.91% of all returning air travellers. The day of diagnosis of COVID-19 varied from Day 1 to Day 13, with 63.6% (n=56) of these in the first week of quarantine. 50% of the people in the SHA were referred to rpavirtual for ongoing clinical management. 7 patients required admission to hospital for ongoing clinical care.InterpretationThe Public Health response to COVID-19 in Australia included early and increased case detection through testing, tracing of contacts of confirmed cases, social distancing and prohibition of gatherings. In addition to these measures, the introduction of mandated self-quarantine for travellers to Australia was integral to the successful containment of COVID-19 in NSW and in Australia through the prevention of transmission locally and interstate from returning travellers.

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Outbreak dynamics of COVID-19 in Europe and the effect of travel restrictions

Cited by 270 publications

References 24 publications

COVID-19 Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered (SEIR) Model

COVID-19 Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered (SEIR) Model

Decline in Mobility: Public Transport in Poland in the time of the COVID-19 Pandemic

Control of COVID-19 in Australia through quarantine: the role of Special Health Accommodation (SHA) in New South Wales, Australia

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