scholarly journals Interim estimates of increased transmissibility, growth rate, and reproduction number of the Covid-19 B.1.617.2 variant of concern in the United Kingdom

2021 ◽  
Author(s):  
John S Dagpunar
Keyword(s):  
Growth Rate ◽  
Simple Model ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Actual Distribution ◽  
Sanger Institute ◽  
The United Kingdom ◽  
Point Estimates ◽  
Reproduction Numbers ◽  
The Uk

This paper relates to data from the Wellcome Sanger Institute, UK, regarding Covid-19 genomic surveillance. We use a simple model to give point estimates of the effective reproduction numbers of the B.1.617.2 and B.1.1.7 lineages in England, from sequenced data as at 15 May 2021. Comparison with the estimated reproduction number of B.1.1.7 enables an estimate of the increased transmissibility of B.1.617.2. We conclude that it is almost certain that there is increased transmissibility that will rapidly lead to B.1.617.2 becoming the prevailing variant in the UK. The derived estimates of increased transmissibility have uncertainty relating to the actual distribution of the generation interval, but they do point, under present conditions of vaccination coverage and NPIs, to exponential growth of positive cases.

scholarly journals Growth, reproduction numbers and factors affecting the spread of SARS-CoV-2 novel variants of concern in the UK from October 2020 to July 2021: a modelling analysis

BMJ Open ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. e056636
Author(s):  
Thomas Ward ◽  
Alex Glaser ◽  
Alexander Johnsen ◽  
Feng Xu ◽  
Ian Hall ◽  
...  
Keyword(s):  
Growth Rate ◽  
Exponential Growth ◽  
Doubling Time ◽  
Reproduction Number ◽  
Age Groups ◽  
Instantaneous Growth Rate ◽  
Rt Pcr ◽  
Gene Target ◽  
Novel Variants ◽  
The Uk

ObjectivesImportations of novel variants of concern (VOC), particularly B.1.617.2, have become the impetus behind recent outbreaks of SARS-CoV-2. Concerns around the impact on vaccine effectiveness, transmissibility and severity are now driving the public health response to these variants. This paper analyses the patterns of growth in hospitalisations and confirmed cases for novel VOCs by age groups, geography and ethnicity in the context of changing behaviour, non-pharmaceutical interventions (NPIs) and the UK vaccination programme. We seek to highlight where strategies have been effective and periods that have facilitated the establishment of new variants.DesignWe have algorithmically linked the most complete testing and hospitalisation data in England to create a data set of confirmed infections and hospitalisations by SARS-CoV-2 genomic variant. We have used these linked data sets to analyse temporal, geographic and demographic distinctions.Setting and participantsThe setting is England from October 2020 to July 2021. Participants included all COVID-19 tests that included RT-PCR CT gene target data or underwent sequencing and hospitalisations that could be linked to these tests.MethodsTo calculate the instantaneous growth rate for VOCs we have developed a generalised additive model fit to multiple splines and varying day of the week effects. We have further modelled the instantaneous reproduction number Rt for the B.1.1.7 and B.1.617.2 variants and included a doubly interval censored model to temporally adjust the confirmed variant cases.ResultsWe observed a clear replacement of the predominant B.1.1.7 by the B.1.617.2 variant without observing sustained exponential growth in other novel variants. Modelled exponential growth of RT PCR gene target triple-positive cases was initially detected in the youngest age groups, although we now observe across all ages a very small doubling time of 10.7 (95% CI 9.1 to 13.2) days and 8 (95% CI 6.9 to 9.1) days for cases and hospitalisations, respectively. We observe that growth in RT PCR gene target triple-positive cases was first detected in the Indian ethnicity group in late February, with a peak of 0.06 (95% CI 0.07 to 0.05) in the instantaneous growth rate, but is now maintained by the white ethnicity groups, observing a doubling time of 6.8 (95% CI 4.9 to 11) days. Rt analysis indicates a reproduction number advantage of 0.45 for B.1.617.2 relative to B.1.1.7, with the Rt value peaking at 1.85 for B.1.617.2.ConclusionsOur results illustrate a clear transmission advantage for the B.1.617.2 variant and the growth in hospitalisations illustrates that this variant is able to maintain exponential growth within age groups that are largely doubly vaccinated. There are concerning signs of intermittent growth in the B.1.351 variant, reaching a 28-day doubling time peak in March 2021, although this variant is presently not showing any evidence of a transmission advantage over B.1.617.2. Step 1b of the UK national lockdown easing was sufficient to precipitate exponential growth in B.1.617.2 cases for most regions and younger adult age groups. The final stages of NPI easing appeared to have a negligible impact on the growth of B.1.617.2 with every region experiencing sustained exponential growth from step 2. Nonetheless, early targeted local NPIs appeared to markedly reduced growth of B.1.617.2. Later localised interventions, at a time of higher prevalence and greater geographic dispersion of this variant, appeared to have a negligible impact on growth.

scholarly journals Assessing the lockdown effect from excess mortalities

2021 ◽  
Author(s):  
Alexej Weber
Keyword(s):  
Growth Rate ◽  
South Korea ◽  
Growth Rates ◽  
Excess Mortality ◽  
Reproduction Number ◽  
Average Growth Rate ◽  
Average Growth ◽  
Reproduction Numbers ◽  
The Difference ◽  
Pharmaceutical Interventions

AbstractBackground and AimsThe reported case numbers of COVID-19 are often used to estimate the reproduction number or the growth rate. We use the excess mortality instead, showing the difference between most restrictive non-pharmaceutical interventions (mrNPIs) and less restrictive NPIs (lrNPIs) with respect to the growth rate and death counts.MethodsWe estimate the COVID-19 growth rate for Sweden, South Korea, Italy and Germany from the excess mortality. We use the average growth rate obtained for Sweden and South Korea, two countries with lrNPIs, to estimate additional death numbers in Germany and Italy (two countries with mrNPIs) in a hypothetic lrNPIs scenario.ResultsThe growth rate estimated from excess mortality decreased faster for Germany and Italy than for Sweden and South Korea, suggesting that the mrNPIs have a non-negligible effect. This is not visible when the growth rate is calculated using the reported case numbers of COVID-19. This results in approximately 4 500 and 12 000 more death numbers for Germany and Italy, respectively.ConclusionThe reproduction numbers or growth rates obtained from reported COVID-19 cases are most likely biased. Expanding testing capacity led to an overestimation of the growth rate across all countries analyzed, masking the true decrease already visible in the excess mortality. Using our method, a more realistic estimate of the growth rate is obtained. Conclusions made for the reproduction number derived from the reported case numbers like the insignificance of most restrictive non-pharmaceutical interventions (lockdowns) might be wrong and have to be reevaluated using the growth rates obtained with our method.

scholarly journals Precautionary breaks: planned, limited duration circuit breaks to control the prevalence of COVID-19

2020 ◽  
Author(s):  
Matt J. Keeling ◽  
Glen Guyver-Fletcher ◽  
Alex Holmes ◽  
Louise Dyson ◽  
Michael J. Tildesley ◽  
...  
Keyword(s):  
Growth Rate ◽  
Exponential Growth ◽  
Negative Impact ◽  
Control Measures ◽  
Contact Tracing ◽  
Societal Costs ◽  
Alternative Approach ◽  
Age Structured ◽  
The Uk ◽  
Limited Duration

AbstractThe COVID-19 pandemic in the UK has been characterised by periods of exponential growth and decline, as different non-pharmaceutical interventions (NPIs) are brought into play. During the early uncontrolled phase of the outbreak (early March 2020) there was a period of prolonged exponential growth with epidemiological observations such as hospitalisation doubling every 3-4 days (growth rate r ≈ 0.2). The enforcement of strict lockdown measures led to a noticeable decline in all epidemic quantities (r ≈ −0.06) that slowed during the summer as control measures were relaxed (r ≈ −0.02). Since August, infections, hospitalisations and deaths have been rising (precise estimation of the current growth rate is difficult due to extreme regional heterogeneity and temporal lags between the different epidemiological observations) and various NPIs have been applied locally throughout the UK in response.Controlling any rise in infection is a compromise between public health and societal costs, with more stringent NPIs reducing cases but damaging the economy and restricting freedoms. Currently, NPI imposition is made in response to the epidemiological state, are of indefinite length and are often imposed at short notice, greatly increasing the negative impact. An alternative approach is to consider planned, limited duration periods of strict NPIs aiming to purposefully reduce prevalence before such emergency NPIs are required. These “precautionary breaks” may offer a means of keeping control of the epidemic, while their fixed duration and the forewarning may limit their society impact. Here, using simple analysis and age-structured models matched to the unfolding UK epidemic, we investigate the action of precautionary breaks. In particular we consider their impact on the prevalence of infection, as well as the total number of predicted hospitalisations and deaths. We find that precautionary breaks provide the biggest gains when the growth rate is low, but offer a much needed brake on increasing infection when the growth rate is higher, potentially allowing other measures (such as contact tracing) to regain control.

scholarly journals Epidemic Potential of COVID-19 in Omsk Region during Anti-Epidemic Measures

2020 ◽  
pp. 36-42
Author(s):  
A. I. Blokh ◽  
N. A. Pen’evskaya ◽  
N. V. Rudakov ◽  
I. I. Lazarev ◽  
O. A. Mikhailova ◽  
...  
Keyword(s):  
Growth Rate ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Herd Immunity ◽  
Case Fatality ◽  
Community Acquired Pneumonia ◽  
Cumulative Number ◽  
Exponential Growth Rate ◽  
Epidemic Size ◽  
Threshold Data

Aim. To study the spread of COVID-19 among the population of the Omsk Region during 24 weeks of the epidemic on the background of anti-epidemic measures.Materials and methods. A descriptive epidemiological study was carried out based on publically available data и data from the Center for Hygiene and Epidemiology in the Omsk Region on the official registration and epidemiological investigation of detected COVID-19 cases in the Omsk Region for the period from March 27 to September 10, 2020. To assess the potential of COVID-19 to spread, the following indicators were calculated: exponential growth rate (r), basic reproduction number (R0), effective reproduction number (Rt), expected natural epidemic size and herd immunity threshold. Data processing was performed using MS Excel 2010. The cartogram was built using the QGIS 3.12-Bukuresti application in the EPSG: 3576 coordinate system.Results and discussion. For the period from March 27 to September 10, 2020, a total of 9779 cases of COVID-19 were registered in the Omsk Region, the cumulative incidence was 507,6 per 100000 (95 % CI 497,5÷517,6), the case-fatality rate for completed cases was 2.9 %, for identified cases – 2.4 %. The most active spread of COVID-19 was noted in Omsk and 4 out of 32 districts of the region (Moskalensky, Azov German National, Mariyanovsky, Novovarshavsky). During the ongoing anti-epidemic measures, the exponential growth rate of the cumulative number of COVID-19 cases was 4.5 % per day, R0 – 1.4–1.5, Rt – 1.10, herd immunity threshold – 28.6 %. The expected size of the epidemic in case of sustained anti-epidemic measures can reach 58.0 % of the recovered population. A decrease in the number of detected virus carriers, incomplete detection of COVID-19 among patients with community-acquired pneumonia introduced additional risks for the latent spread of infection and complications of the epidemic situation. Maintaining restrictive  measures and increasing the proportion of the immune population (over 28.6 %) may significantly reduce the risks of increasing the spread of COVID-19 in the Omsk Region. 

Dynamic modelling of entrainment in rapid landslides

2005 ◽  
Vol 42 (5) ◽  
pp. 1437-1448 ◽  
Author(s):  
Scott McDougall ◽  
Oldrich Hungr
Keyword(s):  
Growth Rate ◽  
Simple Model ◽  
Computer Model ◽  
Exponential Growth ◽  
Debris Flows ◽  
Dynamic Modelling ◽  
Back Analysis ◽  
Simple Material ◽  
3D Terrain ◽  
Rapid Landslide

Entrainment of path material is an important feature of many rapid landslides. The associated increases in volume and changes in flow character can significantly influence mobility. A simple material entrainment algorithm, based on the assumption of natural exponential growth with displacement, has been incorporated into a new computer model designed to simulate rapid landslide motion across 3D terrain. The user controls the growth rate and can also implement a change in rheology at the onset of entrainment. A hypothetical example is used to demonstrate the influence of the mass and momentum transfer assumptions. A back-analysis of the 1999 Nomash River landslide is included to show that the simple model is capable of simulating the bulk characteristics of a complex event involving substantial entrainment.Key words: landslides, debris flows, rock avalanches, entrainment, erosion, dynamic modelling.

scholarly journals TRACKING THE MUTANT: FORECASTING AND NOWCASTING COVID-19 IN THE UK IN 2021

2021 ◽  
Vol 256 ◽  
pp. 110-126
Author(s):  
Andrew Harvey ◽  
Paul Kattuman ◽  
Craig Thamotheram
Keyword(s):  
Growth Rate ◽  
Time Series ◽  
Reproduction Number ◽  
Time Series Models ◽  
Daily Number ◽  
New Class ◽  
Bivariate Models ◽  
The Uk ◽  
Different Sources

A new class of time series models is used to track the progress of the COVID-19 epidemic in the UK in early 2021. Models are fitted to England and the regions, as well as to the UK as a whole. The growth rate of the daily number of cases and the instantaneous reproduction number are computed regularly and compared with those produced by SAGE. The results from figures published each day are compared with results based on figures by specimen date, which may be more accurate but are subject to substantial revisions. It is then shown how data from the two different sources can be combined in bivariate models.

scholarly journals Malthus Model applied to exponential growth of Covid 19

2020 ◽  
Vol 9 (11) ◽  
pp. 159-164
Author(s):  
Eduardo Ibarguen-Mondragon ◽  
Mawency Vergel-Ortega ◽  
Carlos Sebastián Gómez Vergel
Keyword(s):  
United States ◽  
Growth Rate ◽  
United Kingdom ◽  
Growth Model ◽  
Exponential Growth ◽  
The United States ◽  
Dynamic Processes ◽  
The United Kingdom ◽  
Malthusian Theory

The Malthus growth model is the most widely used law to model dynamic processes. In this work, we use the Malthusian theory to estimate the growth rate of new daily cases of COVID-19 infection and two periods of time in which this type of growth occurred, the first of 41 days and the second of 101 days. In the first one, the growth rate was 10 times greater than in the second one. From the results, it is concluded that the United States, Spain, France, Italy, Germany and the United Kingdom were the countries that had the greatest impact on exponential growth during the first period, while the Americas, Russia and India were the ones that contributed the most in the second one.  

scholarly journals Estimation of exponential growth rate and basic reproduction number of the coronavirus disease 2019 (COVID-19) in Africa

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Salihu S. Musa ◽  
Shi Zhao ◽  
Maggie H. Wang ◽  
Abdurrazaq G. Habib ◽  
Umar T. Mustapha ◽  
...  
Keyword(s):  
Growth Rate ◽  
Basic Reproduction Number ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Exponential Growth Rate

scholarly journals Estimation of the basic reproduction number (R0) for the novel coronavirus disease in Sri Lanka

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Samath Dharmaratne ◽  
Supun Sudaraka ◽  
Ishanya Abeyagunawardena ◽  
Kasun Manchanayake ◽  
Mahen Kothalawala ◽  
...  
Keyword(s):  
Growth Rate ◽  
Maximum Likelihood ◽  
Sri Lanka ◽  
Basic Reproduction Number ◽  
Exponential Growth ◽  
Reproduction Number ◽  
Likelihood Method ◽  
Exponential Growth Rate ◽  
Rate Method ◽  
The Basic Reproduction Number

Abstract Background The basic reproduction number (R0) is the number of cases directly caused by an infected individual throughout his infectious period. R0 is used to determine the ability of a disease to spread within a given population. The reproduction number (R) represents the transmissibility of a disease. Objectives We aimed to calculate the R0 of Coronavirus disease-2019 (COVID-19) in Sri Lanka and to describe the variation of R, with its implications to the prevention and control of the disease. Methods Data was obtained from daily situation reports of the Epidemiology Unit, Sri Lanka and a compartmental model was used to calculate the R0 using estimated model parameters. This value was corroborated by using two more methods, the exponential growth rate method and maximum likelihood method to obtain a better estimate for R0. The variation of R was illustrated using a Bayesian statistical inference-based method. Results The R0 calculated by the first model was 1.02 [confidence interval (CI) of 0.75–1.29] with a root mean squared error of 7.72. The exponential growth rate method and the maximum likelihood estimation method yielded an R0 of 0.93 (CI of 0.77–1.10) and a R0 of 1.23 (CI of 0.94–1.57) respectively. The variation of R ranged from 0.69 to 2.20. Conclusion The estimated R0 for COVID-19 in Sri Lanka, calculated by three different methods, falls between 0.93 and 1.23, and the transmissibility R has reduced, indicating that measures implemented have achieved a good control of disease.

scholarly journals Estimation of exponential growth rate and basic reproduction number of the coronavirus disease 2019 (COVID-19) in Africa

2020 ◽  
Author(s):  
Salihu S Musa ◽  
Shi Zhao ◽  
Maggie H Wang ◽  
Abdurrazaq G Habib ◽  
Umar T Mustapha ◽  
...  
Keyword(s):  
Growth Rate ◽  
Basic Reproduction Number ◽  
Exponential Growth ◽  
Initial Phase ◽  
Reproduction Number ◽  
Exponential Growth Rate ◽  
Preparedness Planning ◽  
First Case ◽  
Exponential Growth Model ◽  
The Basic Reproduction Number

Abstract Since the first case of coronavirus disease 2019 (COVID-19) was detected on February 14, 2020, the cumulative confirmations reached 834 including 17 deaths by March 19, 2020. We analyzed the initial phase of the epidemic of COVID-19 in Africa between 1 March and 19 March 2020, by using the simple exponential growth model. We estimated the exponential growth rate as 0.22 per day (95%CI: 0.20 – 0.24), and the basic reproduction number to be 2.37 (95%CI: 2.22-2.51) based on the assumption that the exponential growth starting from 1 March, 2020. Our estimates should be useful in preparedness planning.

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