scholarly journals Comparing the responses of the UK, Sweden and Denmark to COVID-19 using counterfactual modelling

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Swapnil Mishra ◽  
James A. Scott ◽  
Daniel J. Laydon ◽  
Seth Flaxman ◽  
Axel Gandy ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Mechanistic Model ◽  
Total Mortality ◽  
Control Measures ◽  
Mortality Data ◽  
Time Varying ◽  
Per Capita ◽  
The Uk ◽  
The Impact ◽  
Counterfactual Approach

AbstractThe UK and Sweden have among the worst per-capita COVID-19 mortality in Europe. Sweden stands out for its greater reliance on voluntary, rather than mandatory, control measures. We explore how the timing and effectiveness of control measures in the UK, Sweden and Denmark shaped COVID-19 mortality in each country, using a counterfactual assessment: what would the impact have been, had each country adopted the others’ policies? Using a Bayesian semi-mechanistic model without prior assumptions on the mechanism or effectiveness of interventions, we estimate the time-varying reproduction number for the UK, Sweden and Denmark from daily mortality data. We use two approaches to evaluate counterfactuals which transpose the transmission profile from one country onto another, in each country’s first wave from 13th March (when stringent interventions began) until 1st July 2020. UK mortality would have approximately doubled had Swedish policy been adopted, while Swedish mortality would have more than halved had Sweden adopted UK or Danish strategies. Danish policies were most effective, although differences between the UK and Denmark were significant for one counterfactual approach only. Our analysis shows that small changes in the timing or effectiveness of interventions have disproportionately large effects on total mortality within a rapidly growing epidemic.

scholarly journals Modelling the Evolution of COVID-19 in High-Incidence European Countries and Regions: Estimated Number of Infections and Impact of Past and Future Intervention Measures

2020 ◽  
Vol 9 (6) ◽  
pp. 1825 ◽  
Author(s):  
Juan Fernández-Recio
Keyword(s):  
Reproduction Number ◽  
Mechanistic Model ◽  
Control Measures ◽  
European Countries ◽  
Intervention Measures ◽  
High Incidence ◽  
Future Outcomes ◽  
Long Term Impact ◽  
The Impact

A previously developed mechanistic model of COVID-19 transmission has been adapted and applied here to study the evolution of the disease and the effect of intervention measures in some European countries and territories where the disease has had a major impact. A clear impact of the major intervention measures on the reproduction number (Rt) has been found in all studied countries and territories, as already suggested by the drop in the number of deaths over time. Interestingly, the impact of such major intervention measures seems to be the same in most of these countries. The model has also provided realistic estimates of the total number of infections, active cases and future outcomes. While the predictive capabilities of the model are much more uncertain before the peak of the outbreak, we could still reliably predict the evolution of the disease after a major intervention by assuming the subsequent reproduction number from the current study. A greater challenge is to foresee the long-term impact of softer intervention measures, but this model can estimate the outcome of different scenarios and help to plan changes for the implementation of control measures in a given country or region.

scholarly journals Modelling the evolution of COVID-19 in high-incidence European countries and regions: estimated number of infections and impact of past and future intervention measures

2020 ◽  
Author(s):  
Juan Fernandez-Recio
Keyword(s):  
Reproduction Number ◽  
Mechanistic Model ◽  
Control Measures ◽  
European Countries ◽  
Intervention Measures ◽  
High Incidence ◽  
Long Term Impact ◽  
The Impact ◽  
Over Time

A previously developed mechanistic model of COVID-19 transmission has been adapted and applied here to study the evolution of the disease and the effect of intervention measures in some European countries and territories where the disease had major impact. A clear impact of the major intervention measures on the reproduction number (Rt) has been found in all studied countries and territories, as already suggested by the drop in the number of deaths over time. Interestingly, the impact of such major intervention measures seems to be the same in most of these countries. The model has also provided realistic estimates of the total number of infections, active cases and future outcome. While the predictive capabilities of the model are much more uncertain before the peak of the outbreak, we could still reliably predict the evolution of the disease after a major intervention by assuming the afterwards reproduction number from current study. More challenging is to foresee the long-term impact of softer intervention measures, but this model can estimate the outcome of different scenarios and help planning changes in the implementation of control measures in a given country or region.

scholarly journals Comparative Analysis of Early Dynamic Trends in Novel Coronavirus Outbreak: A Modeling Framework

2020 ◽  
Author(s):  
Huazhen Lin ◽  
Wei Liu ◽  
Hong Gao ◽  
Jinyu Nie ◽  
Qiao Fan
Keyword(s):  
Growth Model ◽  
Control Measures ◽  
Peak Time ◽  
Time Varying ◽  
Modeling Framework ◽  
Epidemic Size ◽  
Significant Public Health ◽  
Novel Coronavirus ◽  
The Uk ◽  
The Impact

AbstractBackgroundThe 2019 coronavirus disease (COVID-19) represents a significant public health threat globally. Here we describe efforts to compare epidemic growth, size and peaking time for countries in Asia, Europe, North America, South America and Australia in the early epidemic phase.MethodsUsing the time series of cases reported from January 20, 2020 to February 13, 2020 and transportation data from December 1, 2019 to January 23, 2020 we have built a novel time-varying growth model to predict the epidemic trend in China. We extended our method, using cases reported from January 26, 2020 - or the date of the earliest case reported, to April 9, 2020 to predict future epidemic trend and size in 41 countries. We estimated the impact of control measures on the epidemic trend.ResultsOur time-varying growth model yielded high concordance in the predicted epidemic size and trend with the observed figures in C hina. Among the other 41 countries, the peak time has been observed in 28 countries before or around April 9, 2020; the peak date and epidemic size were highly consistent with our estimates. We predicted the remaining countries would peak in April or May 2020, except India in July and Pakistan in August. The epidemic trajectory would reach the plateau in May or June for the majority of countries in the current wave. Countries that could emerge to be new epidemic centers are India, Pakistan, Brazil, Mexico, and Russia with a prediction of 105 cases for these countries. The effective reproduction number Rt displayed a downward trend with time across countries, revealing the impact of the intervention remeasures i.e. social distancing. Rt remained the highest in the UK (median 2.62) and the US (median 2.19) in the fourth week after the epidemic onset.ConclusionsNew epidemic centers are expected to continue to emerge across the whole world. Greater challenges such as those in the healthcare system would be faced by developing countries in hotspots. A domestic approach to curb the pandemic must align with joint international efforts to effectively control the spread of COVID-19. Our model promotes a reliable transmissibility characterization and epidemic forecasting using the incidence of cases in the early epidemic phase.

scholarly journals Estimated Dissemination Ratio—A Practical Alternative to the Reproduction Number for Infectious Diseases

2021 ◽  
Vol 9 ◽  
Author(s):  
Francisco J. Pérez-Reche ◽  
Nick Taylor ◽  
Chris McGuigan ◽  
Philip Conaglen ◽  
Ken J. Forbes ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Infectious Diseases ◽  
Real Time ◽  
Early Warning ◽  
Reproduction Number ◽  
Transmission Rate ◽  
Control Measures ◽  
Epidemic Curve ◽  
The Uk ◽  
The Impact

Policymakers require consistent and accessible tools to monitor the progress of an epidemic and the impact of control measures in real time. One such measure is the Estimated Dissemination Ratio (EDR), a straightforward, easily replicable, and robust measure of the trajectory of an outbreak that has been used for many years in the control of infectious disease in livestock. It is simple to calculate and explain. Its calculation and use are discussed below together with examples from the current COVID-19 outbreak in the UK. These applications illustrate that EDR can demonstrate changes in transmission rate before they may be clear from the epidemic curve. Thus, EDR can provide an early warning that an epidemic is resuming growth, allowing earlier intervention. A conceptual comparison between EDR and the commonly used reproduction number is also provided.

scholarly journals Collective or Individual? What Types of Tourism Reduce Economic Inequality in Peripheral Regions?

2021 ◽  
Vol 13 (9) ◽  
pp. 4898
Author(s):  
Andrzej Tucki ◽  
Korneliusz Pylak
Keyword(s):  
Peripheral Region ◽  
Time Varying ◽  
Tourism Impacts ◽  
Economic Distress ◽  
Regional Inequalities ◽  
Local Agriculture ◽  
Northeastern Poland ◽  
Per Capita ◽  
The Impact

Regional inequalities are a major concern for governments and policymakers. There is no doubt that tourism impacts the reduction of inequalities, but this impact is not entirely clear. We consider this ambiguity to be related to both the level of study and type of accommodation. In the present study, we examine the inequality level measured by the Gini coefficient in 108 municipalities of the peripheral region of northeastern Poland from 2009 to 2018. We employ a directional spillover index to measure the impact of two accommodation types on tax incomes per capita. The empirical results indicate that collective accommodation-based tourism only reduced inequality during the financial crisis, while individual accommodation-based tourism started to reduce inequality from 2014, when Russian sanctions hit local agriculture and businesses. These results indicate that the role of accommodation types is time-varying and evident in measuring economic distress during and after shocks.

scholarly journals Heterogeneity and effectiveness analysis of COVID-19 prevention and control in major cities in China through time-varying reproduction number estimation

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Qing Cheng ◽  
Zeyi Liu ◽  
Guangquan Cheng ◽  
Jincai Huang
Keyword(s):  
Prevention And Control ◽  
Large Scale ◽  
Reproduction Number ◽  
Correlation Method ◽  
Control Measures ◽  
Time Varying ◽  
Short Period ◽  
Significant Difference ◽  
Prevention And Control Measures ◽  
And Control

AbstractBeginning on December 31, 2019, the large-scale novel coronavirus disease 2019 (COVID-19) emerged in China. Tracking and analysing the heterogeneity and effectiveness of cities’ prevention and control of the COVID-19 epidemic is essential to design and adjust epidemic prevention and control measures. The number of newly confirmed cases in 25 of China’s most-affected cities for the COVID-19 epidemic from January 11 to February 10 was collected. The heterogeneity and effectiveness of these 25 cities’ prevention and control measures for COVID-19 were analysed by using an estimated time-varying reproduction number method and a serial correlation method. The results showed that the effective reproduction number (R) in 25 cities showed a downward trend overall, but there was a significant difference in the R change trends among cities, indicating that there was heterogeneity in the spread and control of COVID-19 in cities. Moreover, the COVID-19 control in 21 of 25 cities was effective, and the risk of infection decreased because their R had dropped below 1 by February 10, 2020. In contrast, the cities of Wuhan, Tianmen, Ezhou and Enshi still had difficulty effectively controlling the COVID-19 epidemic in a short period of time because their R was greater than 1.

scholarly journals The Dynamic Impacts of the COVID-19 Pandemic on Log Prices in China: An Analysis Based on the TVP-VAR Model

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 449
Author(s):  
Chenlu Tao ◽  
Gang Diao ◽  
Baodong Cheng
Keyword(s):  
Exchange Rate ◽  
Structural Changes ◽  
Raw Materials ◽  
Supply And Demand ◽  
Oil Prices ◽  
Control Measures ◽  
Var Model ◽  
Time Varying ◽  
Wood Industry ◽  
The Impact

China’s wood industry is vulnerable to the COVID-19 pandemic since wood raw materials and sales of products are dependent on the international market. This study seeks to explore the speed of log price recovery under different control measures, and to perhaps find a better way to respond to the pandemic. With the daily data, we utilized the time-varying parameter autoregressive (TVP-VAR) model, which can incorporate structural changes in emergencies into the model through time-varying parameters, to estimate the dynamic impact of the pandemic on log prices at different time points. We found that the impact of the pandemic on oil prices and Renminbi exchange rate is synchronized with the severity of the pandemic, and the ascending in the exchange rate would lead to an increase in log prices, while oil prices would not. Moreover, the impulse response in June converged faster than in February 2020. Thus, partial quarantine is effective. However, the pandemic’s impact on log prices is not consistent with changes of the pandemic. After the pandemic eased in June 2020, the impact of the pandemic on log prices remained increasing. This means that the COVID-19 pandemic has long-term influences on the wood industry, and the work resumption was not smooth, thus the imbalance between supply and demand should be resolved as soon as possible. Therefore, it is necessary to promote the development of the domestic wood market and realize a “dual circulation” strategy as the pandemic becomes a “new normal”.

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 Estimating the impact of reopening schools on the reproduction number of SARS-CoV-2 in England, using weekly contact survey data

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
James D. Munday ◽  
Christopher I. Jarvis ◽  
Amy Gimma ◽  
Kerry L. M. Wong ◽  
Kevin van Zandvoort ◽  
...  
Keyword(s):  
Reproduction Number ◽  
Transmission Rate ◽  
Transmission Risk ◽  
Individual Level ◽  
Face To Face ◽  
School Settings ◽  
Contact Rates ◽  
Contact Survey ◽  
The Uk ◽  
The Impact

Abstract Background Schools were closed in England on 4 January 2021 as part of increased national restrictions to curb transmission of SARS-CoV-2. The UK government reopened schools on 8 March. Although there was evidence of lower individual-level transmission risk amongst children compared to adults, the combined effects of this with increased contact rates in school settings and the resulting impact on the overall transmission rate in the population were not clear. Methods We measured social contacts of > 5000 participants weekly from March 2020, including periods when schools were both open and closed, amongst other restrictions. We combined these data with estimates of the susceptibility and infectiousness of children compared with adults to estimate the impact of reopening schools on the reproduction number. Results Our analysis indicates that reopening all schools under the same measures as previous periods that combined lockdown with face-to-face schooling would be likely to increase the reproduction number substantially. Assuming a baseline of 0.8, we estimated a likely increase to between 1.0 and 1.5 with the reopening of all schools or to between 0.9 and 1.2 reopening primary or secondary schools alone. Conclusion Our results suggest that reopening schools would likely halt the fall in cases observed between January and March 2021 and would risk a return to rising infections, but these estimates relied heavily on the latest estimates or reproduction number and the validity of the susceptibility and infectiousness profiles we used at the time of reopening.

scholarly journals Real-time estimation of the influenza-associated excess mortality in Hong Kong

2019 ◽  
Vol 147 ◽  
Author(s):  
Jessica Y. Wong ◽  
Edward Goldstein ◽  
Vicky J. Fang ◽  
Benjamin J. Cowling ◽  
Peng Wu
Keyword(s):  
Hong Kong ◽  
Real Time ◽  
Excess Mortality ◽  
Time Estimation ◽  
Surveillance Data ◽  
Control Measures ◽  
Influenza Surveillance ◽  
Mortality Data ◽  
Real Time Estimation ◽  
The Impact

Abstract Statistical models are commonly employed in the estimation of influenza-associated excess mortality that, due to various reasons, is often underestimated by laboratory-confirmed influenza deaths reported by healthcare facilities. However, methodology for timely and reliable estimation of that impact remains limited because of the delay in mortality data reporting. We explored real-time estimation of influenza-associated excess mortality by types/subtypes in each year between 2012 and 2018 in Hong Kong using linear regression models fitted to historical mortality and influenza surveillance data. We could predict that during the winter of 2017/2018, there were ~634 (95% confidence interval (CI): (190, 1033)) influenza-associated excess all-cause deaths in Hong Kong in population ⩾18 years, compared to 259 reported laboratory-confirmed deaths. We estimated that influenza was associated with substantial excess deaths in older adults, suggesting the implementation of control measures, such as administration of antivirals and vaccination, in that age group. The approach that we developed appears to provide robust real-time estimates of the impact of influenza circulation and complement surveillance data on laboratory-confirmed deaths. These results improve our understanding of the impact of influenza epidemics and provide a practical approach for a timely estimation of the mortality burden of influenza circulation during an ongoing epidemic.

Sign in / Sign up

Export Citation Format

Share Document