scholarly journals Modeling the second wave of COVID-19 infections in France and Italy via a stochastic SEIR model

2020 ◽  
Vol 30 (11) ◽  
pp. 111101 ◽  
Author(s):  
Davide Faranda ◽  
Tommaso Alberti
Keyword(s):  
Seir Model ◽  
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 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 Modeling the COVID-19 transmission in Italy: The roles of asymptomatic cases, social distancing, and lockdowns in the first and the second waves

2021 ◽  
Author(s):  
Muhamad Khairul Bahri
Keyword(s):  
Behavioral Measures ◽  
Seir Model ◽  
Social Distancing ◽  
The World ◽  
Second Wave ◽  
Very High

AbstractThe SEIR model of COVID-19 is developed to investigate the roles of physical distancing, lockdowns and asymptomatic cases in Italy. In doing so, two types of policies including behavioral measures and lockdown measures are embedded in the model. Compared with existing models, the model successfully reproduces similar multiple observed outputs such as infected and recovered patients in Italy by July 2020. This study concludes that the first policy is important once the number of infected cases is relatively low. However, once the number of infected cases is very high so the society cannot identify infected and disinfected people, the second policy must be applied soon. It is thus this study suggests that relaxed lockdowns lead to the second wave of the COVID-19 around the world. It is hoped that the model can enhance our understanding on the roles of behavioral measures, lockdowns, and undocumented cases, so-called asymptomatic cases, on the COVID-19 flow.

scholarly journals Modelling of the second (and subsequent) waves of the coronavirus epidemic. Spain and Germany as case studies

2020 ◽  
Author(s):  
Francisco de Castro
Keyword(s):  
Case Studies ◽  
Mortality Rates ◽  
Time Dependent ◽  
Seir Model ◽  
Considerable Uncertainty ◽  
Second Wave

AbstractThe first wave of the coronavirus pandemic is waning in many countries. Some of them are starting to lift the confinement measures adopted to control it, but there is considerable uncertainty about if it is too soon and it may cause a second wave of the epidemic. To explore this issue, I fitted a SEIR model with time-dependent transmission and mortality rates to data from Spain and Germany as contrasting case studies. The model reached an excellent fit to the data. I then simulated the post-confinement epidemic under several scenarios. The model shows that (in the absence of a vaccine) a second wave is likely inevitable and will arrive soon, and that a strategy of adaptive confinement may be effective to control it. The model also shows that just a few days delay in starting the confinement may have caused and excess of thousands of deaths in Spain.

scholarly journals Predicted effects of summer holidays and seasonality on the SARS-Cov-2 epidemic in France

2020 ◽  
Author(s):  
Louis Duchemin ◽  
Philippe Veber ◽  
Mathilde Paris ◽  
Bastien Boussau
Keyword(s):  
Death Rate ◽  
Reproduction Number ◽  
Seir Model ◽  
Low Level ◽  
Death Toll ◽  
Reproduction Numbers ◽  
Second Wave ◽  
Epidemic Wave ◽  
Do So

1AbstractThe SARS-CoV-2 epidemic in France has had a large death toll. It has not affected all regions similarly, since the death rate can vary several folds between regions where the epidemic has remained at a low level and regions where it got an early burst. The epidemic has been slowed down by a lockdown that lasted for almost eight weeks, and individuals can now move between metropolitan French regions without restriction. In this report we investigate the effect on the epidemic of summer holidays, during which millions of individuals will move between French regions. Additionally, we evaluate the effect of strong or weak seasonality and of several values for the reproduction number on the epidemic, in particular on the timing, the height and the spread of a second wave. To do so, we extend a SEIR model to simulate the effect of summer migrations between regions on the number and distribution of new infections. We find that the model predicts little effect of summer migrations on the epidemic. However, all the reproduction numbers above 1.0 and the seasonality parameters we tried result in a second epidemic wave, with a peak date that can vary between October 2020 and April 2021. If the sanitary measures currently in place manage to keep the reproduction number below 1.0, the second wave will be avoided. If they keep the reproduction number at a low value, for instance at 1.1 as in one of our simulations, the second wave is flattened and could be similar to the first wave.

scholarly journals Modelling of the second (and subsequent) waves of the coronavirus epidemic. Spain and Germany as case studies

2020 ◽  
Author(s):  
Francisco de Castro
Keyword(s):  
Case Studies ◽  
Mortality Rates ◽  
Time Dependent ◽  
Seir Model ◽  
Considerable Uncertainty ◽  
Second Wave

Abstract The first wave of the coronavirus pandemic is waning in many countries. Some of them are starting to lift the confinement measures adopted to control it, but there is considerable uncertainty about if it is too soon and it may cause a second wave of the epidemic. To explore this issue, I fitted a SEIR model with time-dependent transmission and mortality rates to data from Spain and Germany as contrasting case studies. The model reached an excellent fit to the data. I then simulated the post-confinement epidemic under several scenarios. The model shows that (in the absence of a vaccine) a second wave is likely inevitable and will arrive soon, and that a strategy of adaptive confinement may be effective to control it. The model also shows that just a few days delay in starting the confinement may have caused and excess of thousands of deaths in Spain.

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 Analysis and Simulation of COVID-19

2021 ◽  
Vol 10 (7) ◽  
pp. 51-54
Author(s):  
Ritika Singh* ◽  
Nilansh Panchani ◽  
Aastha , Bhatnagar
Keyword(s):  
Compartmental Model ◽  
Seir Model ◽  
Model Based ◽  
Second Wave

India is facing a severe second wave of COVID-19 which is much worse than the first wave. It is spreading much faster. India has now surpassed U.S. in terms of daily COVID-19 cases. This paper aims to analyze the trend of COVID 19 and examine why second wave happened and why it is so bad by simulating a simple SEIR model. Which is a compartmental model based on 4 compartments Susceptible, Exposed, Infectious, Recovered.

scholarly journals Understanding the First and the Second Waves of the COVID-19 in Germany: Is our Social Behavior Enough to Protect us from the Pandemic?

2021 ◽  
Vol 18 (15) ◽  
Author(s):  
Muhamad KHAIRULBAHRI
Keyword(s):  
Young People ◽  
Computer Model ◽  
Health Workers ◽  
Public Spaces ◽  
Unknown Parameters ◽  
Behavioral Measures ◽  
Seir Model ◽  
Resource Needs ◽  
Second Wave ◽  
Death Cases

Like other European countries, Germany has experienced the 2nd wave of the COVID-19 amid obligations of social distancing and wearing of face masks in public spaces. Although Germany successfully contained the virus during the 1st wave, it has faced difficulties in controlling the COVID-19 during the 2nd wave. This study develops a computer model representing the COVID-19 flow in Germany by comparing the effects of the measures taken during the 1st and the 2nd waves. The computer model is based on the SEIR concept and the system dynamics (SD) approach in which some unknown parameters are estimated through the calibration process. Moreover, the SEIR computer model is developed by considering different cases in older and young people and the SEIR model successfully reproduces similar patterns of infected, recovered, and death cases in the 1st and the 2nd waves in Germany. The SEIR model also shows that the measures taken in the 1st wave have different efficacies than those in the 2nd wave, leading to higher infected cases during the 2nd wave. Since the SEIR model can successfully reproduce similar patterns, the SEIR model can be a basis for further studies in estimating other resource needs such as health workers, and bed capacities. HIGHLIGHTS The SEIR model estimates the efficacies of behavioral measures and lockdowns Behavioral measures are less effective than lockdowns Germany experienced higher infected cases in the first wave than in the second wave Relaxed lockdowns lead to higher infected cases in the second wave Lockdowns are the key to curb COVID-19 flow GRAPHICAL ABSTRACT

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