scholarly journals Understanding the Spreading Patterns of COVID-19 in UK and Its Impact on Exit Strategies

2020 ◽  
Author(s):  
Maziar Nekovee
Keyword(s):  
Exponential Growth ◽  
Slow Growth ◽  
Contact Tracing ◽  
Mixing Models ◽  
Epidemic Spreading ◽  
Seir Model ◽  
Infected Population ◽  
Exit Strategies ◽  
Spatial Epidemic ◽  
Second Wave

Prior to lockdown the spread of COVID-19 in UK is found to be exponential, with an exponent α=0.207 In case of COVID-19 this spreading patterns is quantitatively better described with mobility-driven SIR-SEIR model [2] rather than the homogenous mixing models Lockdown has dramatically slowed down the spread of COVID-19 in UK, and even more significantly has changed the growth in the total number of infected from exponential to quadratic. This significant change is due a transition from a mobility-driven epidemic spreading to a spatial epidemic which is dominated by slow growth of spatially isolated clusters of infected population. Our results strongly indicated that, to avoid a return to exponential growth of COVID-19 (also known as “second wave”) mobility restrictions should not be prematurely lifted. Instead mobility should be kept restricted while new measures, such as wearing mask and contact tracing, get implemented in order to allow a safe exit from lockdown.

scholarly journals Understanding the spreading patterns of COVID-19 in UK and its impact on exit strategies

2020 ◽  
Author(s):  
Maziar Nekovee
Keyword(s):  
Health Services ◽  
Exponential Growth ◽  
Slow Growth ◽  
Contact Tracing ◽  
Mixing Models ◽  
Epidemic Spreading ◽  
Seir Model ◽  
Infected Population ◽  
Spatial Epidemic ◽  
Second Wave

Prior to lockdown the spread of COVID-19 in UK is found to be exponential, with an exponent 0.207. In case of COVID-19 this spreading behaviour is quantitatively better described with a mobility-driven SIR-SEIR model [2] rather than the homogenous mixing models. Lockdown has dramatically slowed down the spread of COVID-19 in UK, and even more significantly, has changed the growth in the total number of infected from exponential to quadratic. This significant change is due to a transition from a mobility-driven epidemic spreading to a spatial epidemic which is dominated by slow growth of spatially isolated clusters of infected population. Our results strongly indicate that, to avoid a return to exponential growth of COVID-19 (also known as second wave), mobility restrictions should not be prematurely lifted. Instead mobility should be kept restricted while new measures, such as wearing of masks and contact tracing, get implemented in order to prevent health services becoming overwhelmed due to a resurgence of exponential growth.

scholarly journals Discontinuous epidemic transition due to limited testing

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Davide Scarselli ◽  
Nazmi Burak Budanur ◽  
Marc Timme ◽  
Björn Hof
Keyword(s):  
Exponential Growth ◽  
Growth Period ◽  
High Impact ◽  
Contact Tracing ◽  
Epidemic Dynamics ◽  
Slowing Down ◽  
Containment Measures ◽  
Second Wave ◽  
Limited Testing ◽  
Pharmaceutical Interventions

AbstractHigh impact epidemics constitute one of the largest threats humanity is facing in the 21st century. In the absence of pharmaceutical interventions, physical distancing together with testing, contact tracing and quarantining are crucial in slowing down epidemic dynamics. Yet, here we show that if testing capacities are limited, containment may fail dramatically because such combined countermeasures drastically change the rules of the epidemic transition: Instead of continuous, the response to countermeasures becomes discontinuous. Rather than following the conventional exponential growth, the outbreak that is initially strongly suppressed eventually accelerates and scales faster than exponential during an explosive growth period. As a consequence, containment measures either suffice to stop the outbreak at low total case numbers or fail catastrophically if marginally too weak, thus implying large uncertainties in reliably estimating overall epidemic dynamics, both during initial phases and during second wave scenarios.

scholarly journals A single-agent extension of the SIR model describes the impact of mobility restrictions on the COVID-19 epidemic

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Matteo Paoluzzi ◽  
Nicoletta Gnan ◽  
Francesca Grassi ◽  
Marco Salvetti ◽  
Nicola Vanacore ◽  
...  
Keyword(s):  
Exponential Growth ◽  
Single Agent ◽  
Sir Model ◽  
Epidemic Spreading ◽  
Peak Reduction ◽  
Slowing Down ◽  
Individual Mobility ◽  
Simple Rules ◽  
The Impact ◽  
Second Wave

AbstractMobility restrictions are successfully used to contain the diffusion of epidemics. In this work we explore their effect on the epidemic growth by investigating an extension of the Susceptible-Infected-Removed (SIR) model in which individual mobility is taken into account. In the model individual agents move on a chessboard with a Lévy walk and, within each square, epidemic spreading follows the standard SIR model. These simple rules allow to reproduce the sub-exponential growth of the epidemic evolution observed during the Covid-19 epidemic waves in several countries and which cannot be captured by the standard SIR model. We show that we can tune the slowing-down of the epidemic spreading by changing the dynamics of the agents from Lévy to Brownian and we investigate how the interplay among different containment strategies mitigate the epidemic spreading. Finally we demonstrate that we can reproduce the epidemic evolution of the first and second COVID-19 waves in Italy using only 3 parameters, i.e , the infection rate, the removing rate, and the mobility in the country. We provide an estimate of the peak reduction due to imposed mobility restrictions, i. e., the so-called flattening the curve effect. Although based on few ingredients, the model captures the kinetic of the epidemic waves, returning mobility values that are consistent with a lock-down intervention during the first wave and milder limitations, associated to a weaker peak reduction, during the second wave.

scholarly journals Bayesian small-area modelling of COVID-19 cases and deaths in England and association with key risk factors: a combined space–time Susceptible-Exposed-Infected-Removed (SEIR) model

2020 ◽  
Author(s):  
Benn Sartorius ◽  
Andrew Lawson ◽  
Rachel L. Pullan
Keyword(s):  
Risk Factors ◽  
Small Area ◽  
Mortality Rates ◽  
Space Time ◽  
Spatiotemporal Variability ◽  
Population Mobility ◽  
Seir Model ◽  
Social Distancing ◽  
The Impact ◽  
Second Wave

Abstract Background: COVID-19 caseloads in England appear have passed through a first peak, with evidence of an emerging second wave. To ensure continued response to the epidemic is most effective, it is imperative to better understand both retrospectively and prospectively the geographical evolution of COVID-19 caseloads and deaths, identify localised areas in space-time at significantly higher risk, quantify the impact of changes in localised population mobility (or movement) on caseloads, identify localised risk factors for increased mortality and project the likely course of the epidemic at small-area resolution in coming weeks.Methods: We applied a Bayesian space–time SEIR model to assess the spatiotemporal variability of COVID-19 caseloads (transmission) and deaths at small-area scale in England (Middle Layer Super Output Area [MSOA], 6791 units) and by week (using observed data from week 5 to 34), including key determinants, the modelled transmission dynamics and spatial-temporal random effects. We also estimate the number of cases and deaths at small-area resolution with uncertainty projected forward in time by MSOA (up to week 51 of 2020), the impact mobility reductions (and subsequent easing) have had on COVID-19 caseloads and quantify the impact of key socio-demographic risk factors on COVID-19 related mortality risk by MSOA.Results: Reductions in population mobility due the course of the first lockdown had a significant impact on the reduction of COVID-19 caseloads across England, however local authorities have had a varied rate of reduction in population movement which our model suggest has substantially impacted the geographic heterogeneity in caseloads at small-area scale. The steady gain in population mobility, observed from late April, appears to have contributed to a slowdown in caseload reductions towards late June and subsequent steady increase signalling the start of the second wave. MSOA with higher proportions of elderly (70+ years of age) and elderly living in deprivation, both with very distinct geographic distributions, have a significantly elevated COVID-19 mortality rates.Conclusions: While non-pharmaceutical interventions (that is, reductions in population mobility and social distancing) had a profound impact on the trajectory of the first wave of the COVID-19 outbreak in England, increased population mobility appears to have contributed to the current increase signalling the start of the second wave. A number of contiguous small-areas appear to be at a significant elevated risk of high COVID-19 transmission, many of which are also at increased risk for higher mortality rates. A geographically staggered re-introduction of intensified social distancing measures is advised and limited cross MSOA movement if the magnitude and geographic extent of the second wave is to be reduced.

scholarly journals Estimating the burden of SARS-CoV-2 in France

Science ◽  
2020 ◽  
Vol 369 (6500) ◽  
pp. 208-211 ◽  
Author(s):  
Henrik Salje ◽  
Cécile Tran Kiem ◽  
Noémie Lefrancq ◽  
Noémie Courtejoie ◽  
Paolo Bosetti ◽  
...  
Keyword(s):  
Intensive Care ◽  
Severe Acute Respiratory Syndrome ◽  
Credible Interval ◽  
Control Measures ◽  
Reproductive Number ◽  
Infected Population ◽  
Population Immunity ◽  
The Impact ◽  
Second Wave ◽  
Death Data

France has been heavily affected by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic and went into lockdown on 17 March 2020. Using models applied to hospital and death data, we estimate the impact of the lockdown and current population immunity. We find that 2.9% of infected individuals are hospitalized and 0.5% of those infected die (95% credible interval: 0.3 to 0.9%), ranging from 0.001% in those under 20 years of age to 8.3% in those 80 years of age or older. Across all ages, men are more likely to be hospitalized, enter intensive care, and die than women. The lockdown reduced the reproductive number from 2.90 to 0.67 (77% reduction). By 11 May 2020, when interventions are scheduled to be eased, we project that 3.5 million people (range: 2.1 million to 6.0 million), or 5.3% of the population (range: 3.3 to 9.3%), will have been infected. Population immunity appears to be insufficient to avoid a second wave if all control measures are released at the end of the lockdown.

Uncertainties over COVID-19 impacts fuel market fears

2020 ◽  
Keyword(s):  
Global Economy ◽  
Contact Tracing ◽  
Bond Markets ◽  
Market Reactions ◽  
Content Type ◽  
Corporate Earnings ◽  
The Us ◽  
Viable Approach ◽  
Equity Index ◽  
Second Wave

Subject Financial market reactions to the pandemic Significance While policymakers and epidemiologists broadly agree that the only viable approach for substantially relaxing lockdowns and social distancing measures is mass community testing and contact tracing, there are significant differences of opinion on how sharply infection curves need to flatten before restrictions are eased. The risk that lockdowns -- which have become dangerously politicised -- will be lifted prematurely, causing a second wave of infections, poses a significant threat to the global economy and markets. Impacts The US S&P 500 equity index has surged since late March, but the bleak corporate earnings outlook means this is unlikely to be a bull run. The spread between Italian and German bonds has widened since late March, reflecting investors' persistent doubts about EU cooperation. The major central banks are likely to invest more than twice as much in sovereign and corporate bonds as in 2008, distorting bond markets.

scholarly journals Human mobility and time spent at destination: Impact on spatial epidemic spreading

2013 ◽  
Vol 338 ◽  
pp. 41-58 ◽  
Author(s):  
Chiara Poletto ◽  
Michele Tizzoni ◽  
Vittoria Colizza
Keyword(s):  
Human Mobility ◽  
Epidemic Spreading ◽  
Spatial Epidemic

scholarly journals COVID-19 Pandemic & Bureaucracy: The Crisis Inside the Crisis

2021 ◽  
Vol 9 ◽  
Author(s):  
Katalyn Roßmann ◽  
Heike Wegner ◽  
Hans Stark ◽  
Gerd Großmann ◽  
Andreas Jansen ◽  
...  
Keyword(s):  
Public Health ◽  
Armed Forces ◽  
Contact Tracing ◽  
Public Health Approach ◽  
Outbreak Management ◽  
Public Health Agencies ◽  
German Armed Forces ◽  
Health Agencies ◽  
Crisis Support ◽  
Second Wave

The Medical Intelligence and Information (MI2) Unit of the German Armed Forces (Bundeswehr) is experienced in crisis support in military missions since several years. It gained additional experiences during the current coronavirus 2019 (COVID-19) pandemic on different levels of the response to crisis and was requested to share the findings and expertise with the overloaded civil public health agencies inside Germany. Since the beginning of the pandemic, the unit is constantly developing new products for crisis communication, knowledge sharing techniques in new databases, dashboards for leadership, and training for laypersons in contact tracing. Hence, trying to innovate in crisis since the first severe acute respiratory syndrome coronavirus (SARS-CoV)-2-disease wave. During the second wave, the unit was requested to evaluate the outbreak management of different national civil public health agencies in southern Germany, and to support the development of dashboards in a comprehensive public health approach as a necessary start toward digitalization.

scholarly journals Agent-Based Simulation for Evaluation of Contact-Tracing Policies Against the Spread of SARS-CoV-2

2020 ◽  
Author(s):  
Martin Bicher ◽  
Claire Rippinger ◽  
Christoph Urach ◽  
Dominik Brunmeir ◽  
Uwe Siebert ◽  
...  
Keyword(s):  
Case Studies ◽  
Exploratory Analysis ◽  
Contact Tracing ◽  
Agent Based Simulation ◽  
Effective Measure ◽  
Agent Based ◽  
The World ◽  
Different Characteristics ◽  
Second Wave ◽  
Restrictive Policy

AbstractThe decline of active COVID-19 cases in many countries in the world has proved that lockdown policies are indeed a very effective measure to stop the exponential spread of the virus. Still, the danger of a second wave of infections is omnipresent and it is clear, that every policy of the lockdown has to be carefully evaluated and possibly replaced by a different, less restrictive policy, before it can be lifted. Tracing of contacts and consequential tracing and breaking of infection-chains is a promising and comparably straightforward strategy to help containing the disease, although its precise impact on the epidemic is unknown. In order to quantify the benefits of tracing and similar policies we developed an agent-based model that not only validly depicts the spread of the disease, but allows for exploratory analysis of containment policies. We will describe our model and perform case studies in which we use the model to quantify impact of contact tracing in different characteristics and draw valuable conclusions about contact tracing policies in general.

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