scholarly journals Impact of Relaxing Covid-19 Social Distancing Measures on Rural North Wales: A Simulation Analysis

2020 ◽  
Vol 8 ◽  
Author(s):  
Rhodri P. Hughes ◽  
Dyfrig A. Hughes
Keyword(s):  
Simulation Analysis ◽  
Model Averaging ◽  
Incidence Rates ◽  
Mortality Data ◽  
Rural Regions ◽  
Social Distancing ◽  
North Wales ◽  
The Uk ◽  
Sigmoidal Growth ◽  
Related Mortality

Background: Social distancing policies aimed to limit Covid-19 across the UK were gradually relaxed between May and August 2020, as peak incidences passed. Population density is an important driver of national incidence rates; however peak incidences in rural regions may lag national figures by several weeks. We aimed to forecast the timing of peak Covid-19 mortality rate in rural North Wales.Methods: Covid-19 related mortality data up to 7/5/2020 were obtained from Public Health Wales and the UK Government. Sigmoidal growth functions were fitted by non-linear least squares and model averaging used to extrapolate mortality to 24/8/2020. The dates of peak mortality incidences for North Wales, Wales and the UK; and the percentage of predicted mortality at 24/8/2020 were calculated.Results: The peak daily death rates in Wales and the UK were estimated to have occurred on the 14/04/2020 and 15/04/2020, respectively. For North Wales, this occurred on the 07/05/2020, corresponding to the date of analysis. The number of deaths reported in North Wales on 07/05/2020 represents 33% of the number predicted to occur by 24/08/2020, compared with 74 and 62% for Wales and the UK, respectively.Conclusion: Policies governing the movement of people in the gradual release from lockdown are likely to impact significantly on areas–principally rural in nature–where cases of Covid-19, deaths and immunity are likely to be much lower than in populated areas. This is particularly difficult to manage across jurisdictions, such as between England and Wales, and in popular holiday destinations.

scholarly journals Impact of relaxing Covid-19 social distancing measures on rural North Wales: a simulation analysis

2020 ◽  
Author(s):  
Rhodri P Hughes ◽  
Dyfrig A Hughes
Keyword(s):  
Simulation Analysis ◽  
Model Averaging ◽  
Incidence Rates ◽  
Cumulative Number ◽  
Social Distancing ◽  
Daily Data ◽  
North Wales ◽  
The Uk ◽  
Incident Cases ◽  
The Impact

Background: Social distancing policies aimed to limit Covid-19 are gradually being relaxed as nationally reported peaks in incident cases are passed. Population density is an important driver of national incidence rates; however peak incidences in rural regions may lag national figures by several weeks. We aimed to forecast the impact of relaxed social distancing rules on rural North Wales. Methods: Daily data on the deaths of people with a positive test for Covid-19 were obtained from Public Health Wales and the UK Government. Sigmoidal growth functions were fitted by non-linear least squares and model averaging used to extrapolate mortality over time. The dates of peak mortality incidences for North Wales, Wales and the UK; and the percentage predicted maximum mortality (as of 7th May 2020) were estimated. Results: The peak daily death rates in Wales and the UK were estimated to have occurred on the 14/04/2020 and 15/04/2020, respectively. For North Wales, this occurred on the 07/05/2020, corresponding to the date of analysis. The number of deaths reported in North Wales represents 31% of the predicted total cumulative number, compared with 71% and 60% for Wales and the UK, respectively. Conclusion: Policies governing the movement of people in the gradual release from lockdown are likely to impact significantly on areas −principally rural in nature− where cases of Covid-19, deaths and immunity are likely to be much lower than in populated areas. This is particularly difficult to manage across jurisdictions, such as between England and Wales, and in popular holiday destinations.

scholarly journals Modelling exit strategies for the UK Covid-19 lockdown with revised mortality data

2020 ◽  
Author(s):  
Anthony D. Lander ◽  
Thejasvi Subramanian
Keyword(s):  
Social Interactions ◽  
National Policy ◽  
Mortality Data ◽  
Daily Mortality ◽  
Social Distancing ◽  
The Public ◽  
Hospital Deaths ◽  
Historic Data ◽  
The Uk ◽  
Second Wave

The number of daily deaths, reported by Public Health England (PHE) during the UK Covid-19 epidemic, initially omitted out-of-hospital deaths in England. The epidemic has been mitigated by social distancing and the lockdown introduced on 17 and 23 March 2020 respectively. We recently reported a stochastic model of a mitigated epidemic which incorporated changes in social interactions and daily movements and whose simulations were consistent with the initial PHE daily mortality data. However, on 29 April, PHE revised their historic data to include out-of-hospital deaths in England. Out-of-hospital deaths occur sooner than in-hospital deaths. Here we show that if 20% of deaths, representing out-of-hospital deaths, are assigned a shorter illness period, then simulated daily mortality matches the revised PHE mortality at least until 4 May. We now predict that if the lockdown is gently relaxed in late May, whilst maintaining social distancing, there would be a modest second-wave which may be acceptable when weighed against the risks of maintaining the lockdown. Our model complements other more sophisticated work currently guiding national policy but which is not presently in the public domain.

scholarly journals The Impact of Social Distancing on The Course of The Covid-19 Pandemic in Four European Countries

2020 ◽  
Author(s):  
Andrew Shardlow
Keyword(s):  
European Countries ◽  
Mortality Data ◽  
Daily Mortality ◽  
Data Set ◽  
Model Type ◽  
Social Distancing ◽  
Strict Enforcement ◽  
The Uk ◽  
The Impact ◽  
Logistic Functions

In this article the mortality data from four European countries arising from the Covid-19 pandemic is modelled using logistic functions. The countries chosen for examination are Spain, Italy, France and the UK. They have been selected because in each the pandemic is advanced, mortality high and any prospect of containment has passed. They have also been selected because in each social distancing has been used in an attempt to reduce peak daily mortality with relatively strict enforcement following a defined date. The choices of data set and model type is justified. The impact, if any, of social distancing is examined.

scholarly journals Social distancing, population density, and spread of COVID-19 in England: a longitudinal study

BJGP Open ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. bjgpopen20X101116 ◽  
Author(s):  
Peter Tammes
Keyword(s):  
Population Density ◽  
Incidence Rate ◽  
Longitudinal Design ◽  
Incidence Rates ◽  
Social Distancing ◽  
Life Expectancy At Birth ◽  
Adjusted Incidence Rate ◽  
The Mean ◽  
The Uk ◽  
Adjusted Incidence

BackgroundThe UK government introduced social distancing measures between 16–22 March 2020, aiming to slow down transmission of COVID-19.AimTo explore the spreading of COVID-19 in relation to population density after the introduction of social distancing measures.Design & settingLongitudinal design with 5-weekly COVID-19 incidence rates per 100 000 people for 149 English Upper Tier Local Authorities (UTLAs), between 16 March and 19 April 2020.MethodMultivariable multilevel model to analyse weekly incidence rates per 100 000 people; time was level-1 unit and UTLA level-2 unit. Population density was divided into quartiles. The model included an interaction between week and population density. Potential confounders were percentage aged ≥65, percentage non-white British, and percentage in two highest classes of the National Statistics Socioeconomic Classification. Co-variates were male life expectancy at birth, and COVID-19 prevalence rate per 100 000 people on March 15. Confounders and co-variates were standardised around the mean.ResultsIncidence rates per 100 000 people peaked in the week of March 30–April 5, showing higher adjusted incidence rate per 100 000 people (46.2; 95% confidence interval [CI] = 40.6 to 51.8) in most densely populated ULTAs (quartile 4) than in less densely populated ULTAs (quartile 1: 33.3, 95% CI = 27.4 to 37.2; quartile 2: 35.9, 95% CI = 31.6 to 40.1). Thereafter, incidence rate dropped in the most densely populated ULTAs resulting in rate of 22.4 (95% CI = 16.9 to 28.0) in the week of April 13–19; this was lower than in quartiles 1, 2, and 3, respectively 31.4 (95% CI = 26.5 to 36.3), 34.2 (95% CI = 29.9 to 38.5), and 43.2 (95% CI = 39.0 to 47.4).ConclusionAfter the introduction of social distancing measures, the incidence rates per 100 000 people dropped stronger in most densely populated ULTAs.

scholarly journals Releasing the lockdown in the UK Covid-19 epidemic: a stochastic model

2020 ◽  
Author(s):  
Anthony Lander
Keyword(s):  
Viral Transmission ◽  
Exponential Phase ◽  
Added Value ◽  
Mortality Data ◽  
Early Exponential Phase ◽  
Susceptible Population ◽  
Cumulative Mortality ◽  
Social Distancing ◽  
The Uk ◽  
Second Wave

AbstractBackgroundIn a classic epidemic, the infected population has an early exponential phase, before slowing and fading to its peak. Mitigating interventions may change the exponent during the rising phase and a plateau can replace a peak. With interventions comes the risk that relaxation causes a second-wave. In the UK Covid-19 epidemic, infections cannot be counted, but their influence is seen in the curve of the mortality data. This work simulated social distancing and the lockdown in the UK Covid-19 epidemic to explore strategies for relaxation.MethodsCumulative mortality data was transposed 20 days earlier to identify three doubling periods separated by the 17th March—social distancing, and 23rd March—lockdown. A set of stochastic processes simulated viral transmission between interacting individuals using Covid-19 incubation and illness durations. Social distancing and restrictions on interactions were imposed and later relaxed.Principal FindingsDaily mortality data, consistent with that seen in the UK Covid-19 epidemic to 24th April 2020 was simulated. This output predicts that under a lockdown maintained till early July 2020, UK deaths will exceed 31,000, but leave a large susceptible population and a requirement for vaccination or quarantine. An earlier staged relaxation carries a risk of a second-wave. The model allows exploration of strategies for lifting the lockdown.InterpretationSocial distancing and the lockdown have had an impressive impact on the UK Covid-19 epidemic and saved lives, caution is now needed in planning its relaxation.FundingUnfunded research.Research in contextEvidence before this studyThe classical Susceptible, Infected, Recovered, (SIR) epidemiological model with additional compartments and sophistications have been widely used to make forecasts in the Covid-19 pandemic but are not easily accessible.Added value of this studyThis study adds reassurance that the interventions of social distancing introduced on the 17th March and the lockdown of the 23rd March 2020 have reduced mortality. The risks of a second-wave on their relaxation are real and illustrated graphically.Implications of all the available evidenceTogether with other models, credence is given to the risks of a second-wave in the UK Covid-19 epidemic on the relaxation of restrictions.

scholarly journals Sex differences in the association between major cardiovascular risk factors in midlife and dementia: a cohort study using data from the UK Biobank

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jessica Gong ◽  
Katie Harris ◽  
Sanne A. E. Peters ◽  
Mark Woodward
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Sex Differences ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Sex Difference ◽  
Incidence Rates ◽  
Cox Proportional Hazards ◽  
Uk Biobank ◽  
The Uk

Abstract Background Sex differences in major cardiovascular risk factors for incident (fatal or non-fatal) all-cause dementia were assessed in the UK Biobank. The effects of these risk factors on all-cause dementia were explored by age and socioeconomic status (SES). Methods Cox proportional hazards models were used to estimate hazard ratios (HRs) and women-to-men ratio of HRs (RHR) with 95% confidence intervals (CIs) for systolic blood pressure (SBP) and diastolic blood pressure (DBP), smoking, diabetes, adiposity, stroke, SES and lipids with dementia. Poisson regression was used to estimate the sex-specific incidence rate of dementia for these risk factors. Results 502,226 individuals in midlife (54.4% women, mean age 56.5 years) with no prevalent dementia were included in the analyses. Over 11.8 years (median), 4068 participants (45.9% women) developed dementia. The crude incidence rates were 5.88 [95% CI 5.62–6.16] for women and 8.42 [8.07–8.78] for men, per 10,000 person-years. Sex was associated with the risk of dementia, where the risk was lower in women than men (HR = 0.83 [0.77–0.89]). Current smoking, diabetes, high adiposity, prior stroke and low SES were associated with a greater risk of dementia, similarly in women and men. The relationship between blood pressure (BP) and dementia was U-shaped in men but had a dose-response relationship in women: the HR for SBP per 20 mmHg was 1.08 [1.02–1.13] in women and 0.98 [0.93–1.03] in men. This sex difference was not affected by the use of antihypertensive medication at baseline. The sex difference in the effect of raised BP was consistent for dementia subtypes (vascular dementia and Alzheimer’s disease). Conclusions Several mid-life cardiovascular risk factors were associated with dementia similarly in women and men, but not raised BP. Future bespoke BP-lowering trials are necessary to understand its role in restricting cognitive decline and to clarify any sex difference.

scholarly journals Temporal trends in annual incidence rates for psychiatric disorders and self-harm among children and adolescents in the UK, 2003–2018

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Lukasz Cybulski ◽  
Darren M. Ashcroft ◽  
Matthew J. Carr ◽  
Shruti Garg ◽  
Carolyn A. Chew-Graham ◽  
...  
Keyword(s):  
Eating Disorders ◽  
Young People ◽  
Anxiety Disorders ◽  
Children And Adolescents ◽  
Autism Spectrum ◽  
Incidence Rates ◽  
Annual Incidence ◽  
Health Crisis ◽  
Self Harm ◽  
The Uk

Abstract Background There has been growing concern in the UK over recent years that a perceived mental health crisis is affecting children and adolescents, although published epidemiological evidence is limited. Methods Two population-based UK primary care cohorts were delineated in the Aurum and GOLD datasets of the Clinical Practice Research Datalink (CPRD). We included data from 9,133,246 individuals aged 1–20 who contributed 117,682,651 person-years of observation time. Sex- and age-stratified annual incidence rates were estimated for attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) (age groups: 1–5, 6–9, 10–12, 13–16, 17–19), depression, anxiety disorders (6–9, 10–12, 13–16, 17–19), eating disorders and self-harm (10–12, 13–16, 17–19) during 2003–2018. We fitted negative binomial regressions to estimate incidence rate ratios (IRRs) to examine change in incidence between the first (2003) and final year (2018) year of observation and to examine sex-specific incidence. Results The results indicated that the overall incidence has increased substantially in both boys and girls in between 2003 and 2018 for anxiety disorders (IRR 3.51 95% CI 3.18–3.89), depression (2.37; 2.03–2.77), ASD (2.36; 1.72–3.26), ADHD (2.3; 1.73–3.25), and self-harm (2.25; 1.82–2.79). The incidence for eating disorders also increased (IRR 1.3 95% CI 1.06–1.61), but less sharply. The incidence of anxiety disorders, depression, self-harm and eating disorders was in absolute terms higher in girls, whereas the opposite was true for the incidence of ADHD and ASD, which were higher among boys. The largest relative increases in incidence were observed for neurodevelopmental disorders, particularly among girls diagnosed with ADHD or ASD. However, in absolute terms, the incidence was much higher for depression and anxiety disorders. Conclusion The number of young people seeking help for psychological distress appears to have increased in recent years. Changes to diagnostic criteria, reduced stigma, and increased awareness may partly explain our results, but we cannot rule out true increases in incidence occurring in the population. Whatever the explanation, the marked rise in demand for healthcare services means that it may be more challenging for affected young people to promptly access the care and support that they need.

scholarly journals Cardiovascular-related deaths at the beginning of the COVID-19 outbreak: a prospective analysis based on the UK Biobank

BMJ Open ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. e046931
Author(s):  
Junren Wang ◽  
Jianwei Zhu ◽  
Huazhen Yang ◽  
Yao Hu ◽  
Yajing Sun ◽  
...  
Keyword(s):  
Primary Diagnosis ◽  
Secondary Outcome ◽  
Hospital Inpatient ◽  
Reference Period ◽  
Stress Reactions ◽  
Uk Biobank ◽  
The Uk ◽  
The Impact ◽  
Distinct Increase ◽  
Related Mortality

ObjectiveTo assess the impact of the COVID-19 outbreak on cardiovascular disease (CVD) related mortality and hospitalisation.DesignCommunity-based prospective cohort study.SettingThe UK Biobank.Participants421 372 UK Biobank participants who were registered in England and alive as of 1 January 2020.Primary and secondary outcome measuresThe primary outcome of interest was CVD-related death, which was defined as death with CVD as a cause in the death register. We retrieved information on hospitalisations with CVD as the primary diagnosis from the UK Biobank hospital inpatient data. The study period was 1 January 2020 to June 30 2020, and we used the same calendar period of the three preceding years as the reference period. In order to control for seasonal variations and ageing of the study population, standardised mortality/incidence ratios (SMRs/SIRs) with 95% CIs were used to estimate the relative risk of CVD outcomes during the study period, compared with the reference period.ResultsWe observed a distinct increase in CVD-related deaths in March and April 2020, compared with the corresponding months of the three preceding years. The observed number of CVD-related deaths (n=218) was almost double in April, compared with the expected number (n=120) (SMR=1.82, 95% CI 1.58 to 2.07). In addition, we observed a significant decline in CVD-related hospitalisations from March onwards, with the lowest SIR observed in April (0.45, 95% CI 0.41 to 0.49).ConclusionsThere was a distinct increase in the number of CVD-related deaths in the UK Biobank population at the beginning of the COVID-19 outbreak. The shortage of medical resources for hospital care and stress reactions to the pandemic might have partially contributed to the excess CVD-related mortality, underscoring the need of sufficient healthcare resources and improved instructions to the public about seeking healthcare in a timely way.

scholarly journals 503. The Misappropriation of COVID-19 Related TV Ad Expenditures

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S317-S317
Author(s):  
Kartavya J Vyas
Keyword(s):  
Cost Effectiveness ◽  
Performance Metrics ◽  
Control Measures ◽  
Mortality Data ◽  
Preventive Interventions ◽  
Social Distancing ◽  
Epidemic Curve ◽  
Incidence And Mortality ◽  
The Cost ◽  
The U.S

Abstract Background With nearly three-fourths of the U.S. population isolated in their homes between early March and the end of May, almost all of whom regularly watch television (TV), it was no surprise that companies began to purchase airtime on major television networks to advertise (ad) their brands and showcase their empathy with the populace. But how would the coronavirus disease 2019 (COVID-19) epidemic curve have changed had these same dollars been allocated to proven preventive interventions? Methods Performance and activity metrics on all COVID-19 related TV ads that have aired in the U.S. between February 26th and June 7th, 2020, were provided by iSpot.tv, Inc., including expenditures. COVID-19 incidence and mortality data were collected from the Centers for Disease Control and Prevention (CDC). Descriptive statistics were performed to calculate total TV ad expenditures and other performance metrics across industry categories. Leveraging a previously published stochastic agent-based model that was used to assess the cost-effectiveness of non-pharmaceutical interventions to control COVID-19, the number of cases that would have been prevented had these same dollars been used for preventive interventions was calculated using cost-effectiveness ratios (CERs), the cost divided by cases prevented. Results A total of 1,513 companies purchased TV airtime during the study period, totaling approximately 1.1 million airings, 215.5 billion impressions, and $2.7 billion in expenditures; most of the expenditures were spent by the restaurant (15.9%), electronics and communications (15.4%), and vehicle (13.7%) industries. The CERs for PPE and social distancing measures were $13,856 and $29,552, respectively; therefore, had all of these TV ad dollars instead been allocated to PPE or social distancing measures, approximately 194,908 and 91,386 cases of COVID-19 may have been prevented by the end of the study period, respectively. Figure 2. COVID-19 cases prevented had TV ad expenditures been reallocated for interventions. Conclusion Americans were inundated with COVID-19 related TV ads during the early months of the pandemic and companies are now showing some signs to relent. In times of disaster, however, it is paramount that the private sector go beyond showcasing their empathy and truly become socially responsible by allocating their funds to proven prevention and control measures. Disclosures All Authors: No reported disclosures

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