scholarly journals PIN50 Leveraging Publicly Available Data to Estimate a Real-Time Reproduction Number (Rt) for Covid-19: A Comparison of Two Methods

2021 ◽  
Vol 24 ◽  
pp. S114
Author(s):  
S. Emerson ◽  
K. Johnston ◽  
A. Howarth ◽  
J. Schneider ◽  
M. Friesen ◽  
...  
Keyword(s):  
Real Time ◽  
Reproduction Number ◽  
Time Reproduction

scholarly journals Modelling the impact of the tier system on SARS-CoV-2 transmission in the UK between the first and second national lockdowns

BMJ Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. e050346
Author(s):  
Daniel J Laydon ◽  
Swapnil Mishra ◽  
Wes R Hinsley ◽  
Pantelis Samartsidis ◽  
Seth Flaxman ◽  
...  
Keyword(s):  
Real Time ◽  
Reproduction Number ◽  
Secondary Outcome ◽  
Bayesian Hierarchical ◽  
Time Reproduction ◽  
Tier System ◽  
The Uk ◽  
National Trends ◽  
Tier 3 ◽  
The Impact

ObjectiveTo measure the effects of the tier system on the COVID-19 pandemic in the UK between the first and second national lockdowns, before the emergence of the B.1.1.7 variant of concern.DesignThis is a modelling study combining estimates of real-time reproduction number Rt (derived from UK case, death and serological survey data) with publicly available data on regional non-pharmaceutical interventions. We fit a Bayesian hierarchical model with latent factors using these quantities to account for broader national trends in addition to subnational effects from tiers.SettingThe UK at lower tier local authority (LTLA) level. 310 LTLAs were included in the analysis.Primary and secondary outcome measuresReduction in real-time reproduction number Rt.ResultsNationally, transmission increased between July and late September, regional differences notwithstanding. Immediately prior to the introduction of the tier system, Rt averaged 1.3 (0.9–1.6) across LTLAs, but declined to an average of 1.1 (0.86–1.42) 2 weeks later. Decline in transmission was not solely attributable to tiers. Tier 1 had negligible effects. Tiers 2 and 3, respectively, reduced transmission by 6% (5%–7%) and 23% (21%–25%). 288 LTLAs (93%) would have begun to suppress their epidemics if every LTLA had gone into tier 3 by the second national lockdown, whereas only 90 (29%) did so in reality.ConclusionsThe relatively small effect sizes found in this analysis demonstrate that interventions at least as stringent as tier 3 are required to suppress transmission, especially considering more transmissible variants, at least until effective vaccination is widespread or much greater population immunity has amassed.

scholarly journals Short-Term Projection of COVID 19 Cases in Kenya using an Exponential Model

2020 ◽  
Author(s):  
Samuel Kiruri Kirichu
Keyword(s):  
Growth Rate ◽  
Real Time ◽  
Case Fatality Rate ◽  
Reproduction Number ◽  
Case Fatality ◽  
Daily Growth Rate ◽  
Daily Growth ◽  
The Real ◽  
Time Reproduction ◽  
First Case

Abstract Introduction: The COVID-19 disease has spread to over 200 countries and territories since the first case was recorded in Wuhan, China in December 2019. In Kenya, the first case of COVID-19 was recorded on 13th March 2020 and since then over five thousand cases have been confirmed as of 26th June 2020. In the same period, one hundred and forty four mortality cases had been recorded in the country. With the rapid changing situation, timely and reliable data is required for monitoring, planning and rapid decision making with an aim of reversing the already deteriorating situation (economic, health, learning among others) in the country. Methods: The study used the exponential growth model to estimate the daily growth rate and the real-time-effective reproduction number. The study also estimated the naïve and the adjusted Case Fatality Rates. Results: The naïve-Case Fatality Rate of 26th June 2020 which was the 106 day after the first case was confirmed in Kenya was estimated as 2.5% while the adjusted Case Fatality Rate with a lag of 2 days was estimated as 2.6%. The daily exponential growth rate was estimated as 0.22 while the real-time reproduction number as of 26th June 2020 was estimated as 1.28 [95% CI: 1.27 – 1.29]. Conclusion: The daily growth rate and the real-time reproduction number indicated that the outbreak was still growing as of the time of analysis.

scholarly journals Analyzing the Effectiveness of COVID-19 Lockdown Policies Using the Time-Dependent Reproduction Number and the Regression Discontinuity Framework: Comparison between Countries

2021 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Shangjun Liu ◽  
Tatiana Ermolieva ◽  
Guiying Cao ◽  
Gong Chen ◽  
Xiaoying Zheng
Keyword(s):  
Risk Perception ◽  
Real Time ◽  
Regression Discontinuity ◽  
Reproduction Number ◽  
Epidemic Models ◽  
Time Dependent ◽  
Time Reproduction ◽  
Long Period ◽  
Infection Dynamics ◽  
The Usa

This study compares the effectiveness of COVID-19 control policies on the virus’s spread and on the change of the infection dynamics in China, Germany, Austria, and the USA relying on a regression discontinuity in time and ‘earlyR’ epidemic models. The effectiveness of policies is measured by real-time reproduction number and cases counts. Comparison between the two lockdowns within each country showed the importance of people's risk perception for the effectiveness of the measures. Results suggest that restrictions applied for a long period or reintroduced later may cause at-tenuated effect on the circulation of the virus and the number of casualties.

scholarly journals Impact of the Tier system on SARS-CoV-2 transmission in the UK between the first and second national lockdowns

2021 ◽  
Author(s):  
Daniel J Laydon ◽  
Swapnil Mishra ◽  
Wes R Hinsley ◽  
Pantelis Samartsidis ◽  
Seth Flaxman ◽  
...  
Keyword(s):  
Real Time ◽  
Statistical Power ◽  
Reproduction Number ◽  
Secondary Outcome ◽  
List Type ◽  
Time Reproduction ◽  
Population Immunity ◽  
Tier System ◽  
The Uk ◽  
Tier 3

AbstractObjectiveMeasure the effects of the Tier system on the COVID-19 pandemic in the UK between the first and second national lockdowns, before the emergence of the B.1.1.7 variant of concern.DesignModelling study combining estimates of the real-time reproduction number Rt (derived from UK case, death and serological survey data) with publicly available data on regional non-pharmaceutical interventions. We fit a Bayesian hierarchical model with latent factors using these quantities, to account for broader national trends in addition to subnational effects from Tiers.SettingThe UK at Lower Tier Local Authority (LTLA) level.Primary and secondary outcome measuresReduction in real-time reproduction number Rt.ResultsNationally, transmission increased between July and late September, regional differences notwithstanding. Immediately prior to the introduction of the tier system, Rt averaged 1.3 (0.9 – 1.6) across LTLAs, but declined to an average of 1.1 (0.86 – 1.42) two weeks later. Decline in transmission was not solely attributable to Tiers. Tier 1 had negligible effects. Tiers 2 and 3 respectively reduced transmission by 6% (5%-7%) and 23% (21%-25%). 93% of LTLAs would have begun to suppress their epidemics if every LTLA had gone into Tier 3 by the second national lockdown, whereas only 29% did so in reality.ConclusionsThe relatively small effect sizes found in this analysis demonstrate that interventions at least as stringent as Tier 3 are required to suppress transmission, especially considering more transmissible variants, at least until effective vaccination is widespread or much greater population immunity has amassed.Strengths and limitations of this studyFirst study to measure effects of UK Tier system for SARS-CoV-2 control at national and regional level.Model makes minimal assumptions and is primarily data driven.Insufficient statistical power to estimate effects of individual interventions that comprise Tiers, or their interaction.Estimates show that Tiers 1 and 2 are insufficient to suppress transmission, at least until widespread population immunity has amassed. Emergence of more transmissible variants of concern unfortunately supports this conclusion.

Virtual Space Teleconferencing: Real-Time Reproduction of 3D Human Images

1995 ◽  
Vol 6 (1) ◽  
pp. 1-25 ◽  
Author(s):  
Jun Ohya ◽  
Yasuichi Kitamura ◽  
Fumio Kishino ◽  
Nobuyoshi Terashima ◽  
Haruo Takemura ◽  
...  
Keyword(s):  
Real Time ◽  
Virtual Space ◽  
Time Reproduction

scholarly journals TW-SIR: Time-window based SIR for COVID-19 forecasts

2020 ◽  
Author(s):  
Zhifang Liao ◽  
Peng Lan ◽  
Zhingning Liao ◽  
Yan Zhang ◽  
Shengzong Liu
Keyword(s):  
Real Time ◽  
Reproduction Number ◽  
Time Window ◽  
Data Sets ◽  
Machine Learning Method ◽  
The Real ◽  
Multiple Data ◽  
Multiple Data Sets ◽  
Time Changes ◽  
Epidemic Diseases

Abstract Since the outbreak of COVID-19, many COVID-19 research studies have proposed different models for predicting trend of COVID-19. Among them, the prediction model based on mathematical epidemiology (SIR) is the most widely used, but most of these models are adapted in special situations based on various assumptions. In order to reflect the real-time trend of the epidemic in the process of infection for different areas, different policies and different epidemic diseases, a general adapted time- window based SIR model is proposed, which is characterized by introducing a time window mechanism for dynamic data analysis and using machine learning method predicts the Basic reproduction number R0 and the exponential growth rate of the epidemic. Multiple data sets of epidemic diseases are analyzed, and the numerical results showed that the framework can effectively measure the real-time changes of the parameters during the epidemic, and error rate of predicting the number of COVID-19 infections in a single day is within 5%

scholarly journals Real-time Nowcasting and Forecasting of COVID-19 Dynamics in England: the first wave?

2020 ◽  
Author(s):  
Paul J Birrell ◽  
Joshua Blake ◽  
Edwin van Leeuwen ◽  
Nick Gent ◽  
Daniela De Angelis ◽  
...  
Keyword(s):  
Real Time ◽  
Reproduction Number ◽  
Mitigation Measures ◽  
Contact Tracing ◽  
The Real ◽  
South West ◽  
Effective Contact ◽  
Ongoing Work ◽  
Reproduction Numbers ◽  
Second Wave

England has been heavily affected by the SARS-CoV-2 pandemic, with severe 'lock-down' mitigation measures now gradually being lifted. The real-time pandemic monitoring presented here has contributed to the evidence informing this pandemic management. Estimates on the 10th May showed lock-down had reduced transmission by 75%, the reproduction number falling from 2.6 to 0.61. This regionally-varying impact was largest in London of 81% (95% CrI: 77%-84%). Reproduction numbers have since slowly increased, and on 19th June the probability that the epidemic is growing was greater than 50% in two regions, South West and London. An estimated 8% of the population had been infected, with a higher proportion in London (17%). The infection-to-fatality ratio is 1.1% (0.9%-1.4%) overall but 17% (14%-22%) among the over-75s. This ongoing work will be key to quantifying any widespread resurgence should accrued immunity and effective contact tracing be insufficient to preclude a second wave.

scholarly journals Real-Time Estimation of Rt for Supporting Public-Health Policies Against COVID-19

2020 ◽  
Vol 8 ◽  
Author(s):  
Sebastián Contreras ◽  
H. Andrés Villavicencio ◽  
David Medina-Ortiz ◽  
Claudia P. Saavedra ◽  
Álvaro Olivera-Nappa
Keyword(s):  
Public Health ◽  
Real Time ◽  
Reproduction Number ◽  
Case Reports ◽  
Mathematical Formulation ◽  
Time Estimation ◽  
Consensus Protocol ◽  
Viral Spread ◽  
Effective Interventions ◽  
Secondary Infections

In the absence of a consensus protocol to slow down the spread of SARS-CoV-2, policymakers need real-time indicators to support decisions in public health matters. The Effective Reproduction Number (Rt) represents the number of secondary infections generated per each case and can be dramatically modified by applying effective interventions. However, current methodologies to calculate Rt from data remain somewhat cumbersome, thus raising a barrier between its timely calculation and application by policymakers. In this work, we provide a simple mathematical formulation for obtaining the effective reproduction number in real-time using only and directly daily official case reports, obtained by modifying the equations describing the viral spread. We numerically explore the accuracy and limitations of the proposed methodology, which was demonstrated to provide accurate, timely, and intuitive results. We illustrate the use of our methodology to study the evolution of the pandemic in different iconic countries, and to assess the efficacy and promptness of different public health interventions.

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