#Coronial #autopsies identify the indirect #effects of #COVID19 (Lancet Pub Health, summary)

[Source: Lancet Public Health, full page: (LINK). Summary, edited.]

Coronial autopsies identify the indirect effects of COVID-19

Robert Pell, Eve Fryer, Sanjiv Manek, Lucinda Winter, Ian S D Roberts

Open Access | Published: August 10, 2020 | DOI: https://doi.org/10.1016/S2468-2667(20)30180-8

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Indirect increases in morbidity and mortality resulting from movement restrictions  imposed during the COVID-19 pandemic have been identified as a public health  concern.1  Deaths registered in England and Wales exceeded the 5-year average by  almost 50 000 during the first 2 months of lockdown, which started on March 23, 2020.2 Confirmed COVID-19 accounted for the majority of deaths; the remaining excess deaths  (>12 000) could reflect undiagnosed COVID-19 or alternatively, deaths from unrelated  conditions. Similarly, in the USA, only 65% of excess deaths during March and April, 2020, were attributed to COVID-19.3

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Keywords: SARS-CoV-2; COVID-19; England; UK.

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#Clinical characteristics and #predictors of outcomes of hospitalized patients with #COVID19 in a multi – #ethnic #London #NHS #Trust: a retrospective cohort study (Clin Infect Dis., abstract)

[Source: Clinical Infectious Diseases, full page: (LINK). Abstract, edited.]

Clinical characteristics and predictors of outcomes of hospitalized patients with COVID-19 in a multi-ethnic London NHS Trust: a retrospective cohort study

Pablo N Perez-Guzman, MD, MSc, Anna Daunt, MD, Sujit Mukherjee, MD, Peter Crook, MD, Roberta Forlano, MD, Mara D Kont, MSc, Alessandra Løchen, MSc, Michaela Vollmer, PhD, Paul Middleton, MD, Rebekah Judge, MD, Christopher Harlow, MD, Anet Soubieres, MD, Graham Cooke, MD, Peter J White, PhD, Timothy B Hallett, PhD, Paul Aylin, MD, Neil Ferguson, PhD, Katharina Hauck, PhD, Mark R Thursz, MD, Shevanthi Nayagam, MD, PhD

Clinical Infectious Diseases, ciaa1091, https://doi.org/10.1093/cid/ciaa1091

Published: 07 August 2020

 

Abstract

Background

Emerging evidence suggests ethnic minorities are disproportionately affected by COVID-19. Detailed clinical analyses of multi-cultural hospitalized patient cohorts remain largely undescribed.

Methods

We performed regression, survival and cumulative competing risk analyses to evaluate factors associated with mortality in patients admitted for COVID-19 in three large London hospitals between February 25 and April 5, censored as of May 1, 2020.

Results

Of 614 patients (median age 69 years, (IQR 25) and 62% male), 381 (62%) had been discharged alive, 178 (29%) died and 55 (9%) remained hospitalized at censoring. Severe hypoxemia (aOR 4.25, 95%CI 2.36-7.64), leukocytosis (aOR 2.35, 95%CI 1.35-4.11), thrombocytopenia (aOR 1.01, 95%CI 1.00-1.01, increase per 10×9 decrease), severe renal impairment (aOR 5.14, 95%CI 2.65-9.97), and low albumin (aOR 1.06, 95%CI 1.02-1.09, increase per g decrease) were associated with death. Forty percent (244) were from black, Asian and other minority ethnic (BAME) groups, 38% (235) white and for 22% (135) ethnicity was unknown. BAME patients were younger and had fewer comorbidities. Whilst the unadjusted odds of death did not differ by ethnicity, when adjusting for age, sex and comorbidities, black patients were at higher odds of death compared to whites (aOR 1.69, 95%CI 1.00-2.86). This association was stronger when further adjusting for admission severity (aOR 1.85 95% CI 1.06-3.24).

Conclusions

BAME patients were over-represented in our cohort and, when accounting for demographic and clinical profile of admission, black patients were at increased odds of death. Further research is needed into biologic drivers of differences in COVID-19 outcomes by ethnicity.

COVID-19, mortality, ethnic minority groups

Issue Section:  Major Article

This content is only available as a PDF.

© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Keywords: SARS-CoV-2; COVID-19; England; UK.

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Excess #mortality from #COVID19 in an #English #sentinel #network population (Lancet Infect Dis., summary)

[Source: Lancet Infectious Diseases, full page: (LINK). Summary, edited.]

Excess mortality from COVID-19 in an English sentinel network population

Mark Joy, F D Richard Hobbs, Dylan McGagh, Oluwafunmi Akinyemi, Simon de Lusignan

Published: August 04, 2020 | DOI: https://doi.org/10.1016/S1473-3099(20)30632-0

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There have been several attempts to predict mortality from COVID-19 in the UK,  including calculation of age-based case fatality rates1  and relative risk (RR) of  mortality.2  David Spiegelhalter said that “roughly speaking, we might say that getting  COVID-19 is like packing a year’s worth of risk into a week or two”.3 In response to these  predictions, we decided to calculate the excess mortality in the Oxford Royal College of  General Practitioners (RCGP) Research and Surveillance Centre (RSC) cohort. The RCGP  RSC cohort has been recruited to be nationally representative,4  and the mortality data for the cohort align well with those from the Office of National Statistics (ONS; appendix p 1).

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Keywords: SARS-CoV-2; COVID-19; England; UK.

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Determining the optimal #strategy for reopening #schools, the impact of #test and trace #interventions, and the #risk of occurrence of a second #COVID19 epidemic wave in the UK: a modelling study (Lancet Child Adolesc Health, abstract)

[Source: Lancet Child and Adolescent Health, full page: (LINK). Abstract, edited.]

Determining the optimal strategy for reopening schools, the impact of test and trace interventions, and the risk of occurrence of a second COVID-19 epidemic wave in the UK: a modelling study

Jasmina Panovska-Griffiths, DPhil, Cliff C Kerr, PhD, Robyn M Stuart, PhD, Dina Mistry, PhD, Daniel J Klein, PhD, Russell M Viner, PhD †, Chris Bonell, PhD †

Published: August 03, 2020 | DOI: https://doi.org/10.1016/S2352-4642(20)30250-9

 

Summary

Background

As lockdown measures to slow the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection begin to ease in the UK, it is important to assess the impact of any changes in policy, including school reopening and broader relaxation of physical distancing measures. We aimed to use an individual-based model to predict the impact of two possible strategies for reopening schools to all students in the UK from September, 2020, in combination with different assumptions about relaxation of physical distancing measures and the scale-up of testing.

Methods

In this modelling study, we used Covasim, a stochastic individual-based model for transmission of SARS-CoV-2, calibrated to the UK epidemic. The model describes individuals’ contact networks stratified into household, school, workplace, and community layers, and uses demographic and epidemiological data from the UK. We simulated six different scenarios, representing the combination of two school reopening strategies (full time and a part-time rota system with 50% of students attending school on alternate weeks) and three testing scenarios (68% contact tracing with no scale-up in testing, 68% contact tracing with sufficient testing to avoid a second COVID-19 wave, and 40% contact tracing with sufficient testing to avoid a second COVID-19 wave). We estimated the number of new infections, cases, and deaths, as well as the effective reproduction number (R) under different strategies. In a sensitivity analysis to account for uncertainties within the stochastic simulation, we also simulated infectiousness of children and young adults aged younger than 20 years at 50% relative to older ages (20 years and older).

Findings

With increased levels of testing (between 59% and 87% of symptomatic people tested at some point during an active SARS-CoV-2 infection, depending on the scenario), and effective contact tracing and isolation, an epidemic rebound might be prevented. Assuming 68% of contacts could be traced, we estimate that 75% of individuals with symptomatic infection would need to be tested and positive cases isolated if schools return full-time in September, or 65% if a part-time rota system were used. If only 40% of contacts could be traced, these figures would increase to 87% and 75%, respectively. However, without these levels of testing and contact tracing, reopening of schools together with gradual relaxing of the lockdown measures are likely to induce a second wave that would peak in December, 2020, if schools open full-time in September, and in February, 2021, if a part-time rota system were adopted. In either case, the second wave would result in R rising above 1 and a resulting second wave of infections 2·0–2·3 times the size of the original COVID-19 wave. When infectiousness of children and young adults was varied from 100% to 50% of that of older ages, we still found that a comprehensive and effective test–trace–isolate strategy would be required to avoid a second COVID-19 wave.

Interpretation

To prevent a second COVID-19 wave, relaxation of physical distancing, including reopening of schools, in the UK must be accompanied by large-scale, population-wide testing of symptomatic individuals and effective tracing of their contacts, followed by isolation of diagnosed individuals.

Funding

None.

Keywords: SARS-CoV-2; COVID-19; School closure; Diagnostic tests; UK.

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#Risk of #COVID19 among front-line #HCWs and the general #community: a prospective cohort study (Lancet Pub Health, abstract)

[Source: The Lancet Public Health, full page: (LINK). Abstract, edited.]

Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study

Long H Nguyen, MD *, David A Drew, PhD *, Mark S Graham, PhD *, Amit D Joshi, PhD, Chuan-Guo Guo, MS, Wenjie Ma, ScD, Raaj S Mehta, MD, Erica T Warner, ScD, Daniel R Sikavi, MD, Chun-Han Lo, MD, Sohee Kwon, MD, Mingyang Song, ScD, Prof Lorelei A Mucci, ScD, Prof Meir J Stampfer, MD, Prof Walter C Willett, MD, A Heather Eliassen, ScD, Jaime E Hart, ScD, Jorge E Chavarro, MD, Janet W Rich-Edwards, ScD, Richard Davies, MA, Joan Capdevila, PhD, Karla A Lee, MBBCh, Mary Ni Lochlainn, MBBCh, Thomas Varsavsky, MSc, Carole H Sudre, PhD, M Jorge Cardoso, PhD, Jonathan Wolf, MA, Prof Tim D Spector, MD, Prof Sebastien Ourselin, PhD †, Claire J Steves, PhD †, Prof Andrew T Chan,  MD  † on behalf of the COronavirus Pandemic Epidemiology Consortium ‡

Open Access | Published: July 31, 2020 | DOI: https://doi.org/10.1016/S2468-2667(20)30164-X

 

Summary

Background

Data for front-line health-care workers and risk of COVID-19 are limited. We sought to assess risk of COVID-19 among front-line health-care workers compared with the general community and the effect of personal protective equipment (PPE) on risk.

Methods

We did a prospective, observational cohort study in the UK and the USA of the general community, including front-line health-care workers, using self-reported data from the COVID Symptom Study smartphone application (app) from March 24 (UK) and March 29 (USA) to April 23, 2020. Participants were voluntary users of the app and at first use provided information on demographic factors (including age, sex, race or ethnic background, height and weight, and occupation) and medical history, and subsequently reported any COVID-19 symptoms. We used Cox proportional hazards modelling to estimate multivariate-adjusted hazard ratios (HRs) of our primary outcome, which was a positive COVID-19 test. The COVID Symptom Study app is registered with ClinicalTrials.gov, NCT04331509.

Findings

Among 2 035 395 community individuals and 99 795 front-line health-care workers, we recorded 5545 incident reports of a positive COVID-19 test over 34 435 272 person-days. Compared with the general community, front-line health-care workers were at increased risk for reporting a positive COVID-19 test (adjusted HR 11·61, 95% CI 10·93–12·33). To account for differences in testing frequency between front-line health-care workers and the general community and possible selection bias, an inverse probability-weighted model was used to adjust for the likelihood of receiving a COVID-19 test (adjusted HR 3·40, 95% CI 3·37–3·43). Secondary and post-hoc analyses suggested adequacy of PPE, clinical setting, and ethnic background were also important factors.

Interpretation

In the UK and the USA, risk of reporting a positive test for COVID-19 was increased among front-line health-care workers. Health-care systems should ensure adequate availability of PPE and develop additional strategies to protect health-care workers from COVID-19, particularly those from Black, Asian, and minority ethnic backgrounds. Additional follow-up of these observational findings is needed.

Funding

Zoe Global, Wellcome Trust, Engineering and Physical Sciences Research Council, National Institutes of Health Research, UK Research and Innovation, Alzheimer’s Society, National Institutes of Health, National Institute for Occupational Safety and Health, and Massachusetts Consortium on Pathogen Readiness.

Keywords: SARS-CoV-2; COVID-19; HCWs; USA; UK.

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Point-of-care #serological #assays for delayed #SARS-CoV-2 case #identification among #HCWs in the #UK: a prospective multicentre cohort study (Lancet Resp Med., abstract)

[Source: Lancet Respiratory Medicine, full page: (LINK). Abstract, edited.]

Point-of-care serological assays for delayed SARS-CoV-2 case identification among health-care workers in the UK: a prospective multicentre cohort study

Capt Scott J C Pallett, MBBS, Michael Rayment, FRCP, Aatish Patel, MBBS, Sophia A M Fitzgerald-Smith, MBChB, Sarah J Denny, MBBS, Esmita Charani, PhD, Annabelle L Mai, MSc, Kimberly C Gilmour, PhD, James Hatcher, FRCPath, Christopher Scott, FRCP, Paul Randell, MBBCh, Nabeela Mughal, FRCPath, Rachael Jones, FRCP, Luke S P Moore, PhD †, Gary W Davies, MD †

Published: July 24, 2020 | DOI: https://doi.org/10.1016/S2213-2600(20)30315-5

 

Summary

Background

Health-care workers constitute a high-risk population for acquisition of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Capacity for acute diagnosis via PCR testing was limited for individuals with mild to moderate SARS-CoV-2 infection in the early phase of the COVID-19 pandemic and a substantial proportion of health-care workers with suspected infection were not tested. We aimed to investigate the performance of point-of-care and laboratory serology assays and their utility in late case identification, and to estimate SARS-CoV-2 seroprevalence.

Methods

We did a prospective multicentre cohort study between April 8 and June 12, 2020, in two phases. Symptomatic health-care workers with mild to moderate symptoms were eligible to participate 14 days after onset of COVID-19 symptoms, as per the Public Health England (PHE) case definition. Health-care workers were recruited to the asymptomatic cohort if they had not developed PHE-defined COVID-19 symptoms since Dec 1, 2019. In phase 1, two point-of-care lateral flow serological assays, the Onsite CTK Biotech COVID-19 split IgG/IgM Rapid Test (CTK Bitotech, Poway, CA, USA) and the Encode SARS-CoV-2 split IgM/IgG One Step Rapid Test Device (Zhuhai Encode Medical Engineering, Zhuhai, China), were evaluated for performance against a laboratory immunoassay (EDI Novel Coronavirus COVID-19 IgG ELISA kit [Epitope Diagnostics, San Diego, CA, USA]) in 300 samples from health-care workers and 100 pre-COVID-19 negative control samples. In phase 2 (n=6440), serosurveillance was done among 1299 (93·4%) of 1391 health-care workers reporting symptoms, and in a subset of asymptomatic health-care workers (405 [8·0%] of 5049).

Findings

There was variation in test performance between the lateral flow serological assays; however, the Encode assay displayed reasonable IgG sensitivity (127 of 136; 93·4% [95% CI 87·8–96·9]) and specificity (99 of 100; 99·0% [94·6–100·0]) among PCR-proven cases and good agreement (282 of 300; 94·0% [91·3–96·7]) with the laboratory immunoassay. By contrast, the Onsite assay had reduced sensitivity (120 of 136; 88·2% [95% CI 81·6–93·1]) and specificity (94 of 100; 94·0% [87·4–97·8]) and agreement (254 of 300; 84·7% [80·6–88·7]). Five (7%) of 70 PCR-positive cases were negative across all assays. Late changes in lateral flow serological assay bands were recorded in 74 (9·3%) of 800 cassettes (35 [8·8%] of 400 Encode assays; 39 [9·8%] of 400 Onsite assays), but only seven (all Onsite assays) of these changes were concordant with the laboratory immunoassay. In phase 2, seroprevalence among the workforce was estimated to be 10·6% (95% CI 7·6–13·6) in asymptomatic health-care workers and 44·7% (42·0–47·4) in symptomatic health-care workers. Seroprevalence across the entire workforce was estimated at 18·0% (95% CI 17·0–18·9).

Interpretation

Although a good positive predictive value was observed with both lateral flow serological assays and ELISA, this agreement only occurred if the pre-test probability was modified by a strict clinical case definition. Late development of lateral flow serological assay bands would preclude postal strategies and potentially home testing. Identification of false-negative results among health-care workers across all assays suggest caution in interpretation of IgG results at this stage; for now, testing is perhaps best delivered in a clinical setting, supported by government advice about physical distancing.

Funding

None.

Keywords: SARS-CoV-2; COVID-19; Serology; Seroprevalence; HCWs; UK.

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#Mental #health before and during the #COVID19 pandemic: a longitudinal probability sample #survey of the #UK population (Lancet Psychiatry, abstract)

[Source: Lancet Psychiatry, full page: (LINK). Abstract, edited.]

Mental health before and during the COVID-19 pandemic: a longitudinal probability sample survey of the UK population

Matthias Pierce, PhD, Holly Hope, PhD, Prof Tamsin Ford, PhD, Prof Stephani Hatch, PhD, Prof Matthew Hotopf, PhD, Prof Ann John, PhD, Prof Evangelos Kontopantelis, PhD, Prof Roger Webb, PhD, Prof Simon Wessely, FMedSci, Sally McManus, MSc †, Prof Kathryn M Abel, MD †

Published: July 21, 2020 | DOI: https://doi.org/10.1016/S2215-0366(20)30308-4

 

Summary

Background

The potential impact of the COVID-19 pandemic on population mental health is of increasing global concern. We examine changes in adult mental health in the UK population before and during the lockdown.

Methods

In this secondary analysis of a national, longitudinal cohort study, households that took part in Waves 8 or 9 of the UK Household Longitudinal Study (UKHLS) panel, including all members aged 16 or older in April, 2020, were invited to complete the COVID-19 web survey on April 23–30, 2020. Participants who were unable to make an informed decision as a result of incapacity, or who had unknown postal addresses or addresses abroad were excluded. Mental health was assessed using the 12-item General Health Questionnaire (GHQ-12). Repeated cross-sectional analyses were done to examine temporal trends. Fixed-effects regression models were fitted to identify within-person change compared with preceding trends.

Findings

Waves 6–9 of the UKHLS had 53 351 participants. Eligible participants for the COVID-19 web survey were from households that took part in Waves 8 or 9, and 17 452 (41·2%) of 42 330 eligible people participated in the web survey. Population prevalence of clinically significant levels of mental distress rose from 18·9% (95% CI 17·8–20·0) in 2018–19 to 27·3% (26·3–28·2) in April, 2020, one month into UK lockdown. Mean GHQ-12 score also increased over this time, from 11·5 (95% CI 11·3–11·6) in 2018–19, to 12·6 (12·5–12·8) in April, 2020. This was 0·48 (95% CI 0·07–0·90) points higher than expected when accounting for previous upward trends between 2014 and 2018. Comparing GHQ-12 scores within individuals, adjusting for time trends and significant predictors of change, increases were greatest in 18–24-year-olds (2·69 points, 95% CI 1·89–3·48), 25–34-year-olds (1·57, 0·96–2·18), women (0·92, 0·50–1·35), and people living with young children (1·45, 0·79–2·12). People employed before the pandemic also averaged a notable increase in GHQ-12 score (0·63, 95% CI 0·20–1·06).

Interpretation

By late April, 2020, mental health in the UK had deteriorated compared with pre-COVID-19 trends. Policies emphasising the needs of women, young people, and those with preschool aged children are likely to play an important part in preventing future mental illness.

Funding

None.

Keywords: SARS-CoV-2; COVID-19; Psychiatry; Society; UK.

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The #impact of the #COVID19 pandemic on #cancer #deaths due to #delays in #diagnosis in #England, #UK: a national, population-based, modelling study (Lancet Oncol., abstract)

[Source: Lancet Oncology, full page: (LINK). Abstract, edited.]

The impact of the COVID-19 pandemic on cancer deaths due to delays in diagnosis in England, UK: a national, population-based, modelling study

Camille Maringe, PhD, Prof James Spicer, PhD, Melanie Morris, PhD, Prof Arnie Purushotham, MD, Prof Ellen Nolte, PhD, Prof Richard Sullivan, PhD, Prof Bernard Rachet, PhD †, Ajay Aggarwal, PhD  †

Open Access | Published: July 20, 2020 | DOI: https://doi.org/10.1016/S1470-2045(20)30388-0

 

Summary

Background

Since a national lockdown was introduced across the UK in March, 2020, in response to the COVID-19 pandemic, cancer screening has been suspended, routine diagnostic work deferred, and only urgent symptomatic cases prioritised for diagnostic intervention. In this study, we estimated the impact of delays in diagnosis on cancer survival outcomes in four major tumour types.

Methods

In this national population-based modelling study, we used linked English National Health Service (NHS) cancer registration and hospital administrative datasets for patients aged 15–84 years, diagnosed with breast, colorectal, and oesophageal cancer between Jan 1, 2010, and Dec 31, 2010, with follow-up data until Dec 31, 2014, and diagnosed with lung cancer between Jan 1, 2012, and Dec 31, 2012, with follow-up data until Dec 31, 2015. We use a routes-to-diagnosis framework to estimate the impact of diagnostic delays over a 12-month period from the commencement of physical distancing measures, on March 16, 2020, up to 1, 3, and 5 years after diagnosis. To model the subsequent impact of diagnostic delays on survival, we reallocated patients who were on screening and routine referral pathways to urgent and emergency pathways that are associated with more advanced stage of disease at diagnosis. We considered three reallocation scenarios representing the best to worst case scenarios and reflect actual changes in the diagnostic pathway being seen in the NHS, as of March 16, 2020, and estimated the impact on net survival at 1, 3, and 5 years after diagnosis to calculate the additional deaths that can be attributed to cancer, and the total years of life lost (YLLs) compared with pre-pandemic data.

Findings

We collected data for 32 583 patients with breast cancer, 24 975 with colorectal cancer, 6744 with oesophageal cancer, and 29 305 with lung cancer. Across the three different scenarios, compared with pre-pandemic figures, we estimate a 7·9–9·6% increase in the number of deaths due to breast cancer up to year 5 after diagnosis, corresponding to between 281 (95% CI 266–295) and 344 (329–358) additional deaths. For colorectal cancer, we estimate 1445 (1392–1591) to 1563 (1534–1592) additional deaths, a 15·3–16·6% increase; for lung cancer, 1235 (1220–1254) to 1372 (1343–1401) additional deaths, a 4·8–5·3% increase; and for oesophageal cancer, 330 (324–335) to 342 (336–348) additional deaths, 5·8–6·0% increase up to 5 years after diagnosis. For these four tumour types, these data correspond with 3291–3621 additional deaths across the scenarios within 5 years. The total additional YLLs across these cancers is estimated to be 59 204–63 229 years.

Interpretation

Substantial increases in the number of avoidable cancer deaths in England are to be expected as a result of diagnostic delays due to the COVID-19 pandemic in the UK. Urgent policy interventions are necessary, particularly the need to manage the backlog within routine diagnostic services to mitigate the expected impact of the COVID-19 pandemic on patients with cancer.

Funding

UK Research and Innovation Economic and Social Research Council.

Keywords: SARS-CoV-2; COVID-19; Cancer; England; UK.

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#Effect of #delays in the 2-week-wait #cancer #referral pathway during the #COVID19 pandemic on cancer #survival in the #UK: a modelling study (Lancet, abstract)

[Source: Lancet Oncology, full page: (LINK). Abstract, edited.]

Effect of delays in the 2-week-wait cancer referral pathway during the COVID-19 pandemic on cancer survival in the UK: a modelling study

Amit Sud, PhD †, Bethany Torr, MSc †, Michael E Jones, PhD, John Broggio, MSci, Stephen Scott, BSc, Chey Loveday, PhD, Alice Garrett, MSc, Firza Gronthoud, MD, David L Nicol, FRACS, Shaman Jhanji, PhD, Stephen A Boyce, PhD, Matthew Williams, PhD, Prof Elio Riboli, MD, David C Muller, PhD, Emma Kipps, PhD, Prof James Larkin, PhD, Neal Navani, PhD, Prof Charles Swanton, FRS, Prof Georgios Lyratzopoulos, PhD, Ethna McFerran, PhD, Prof Mark Lawler, PhD, Prof Richard Houlston, DSc, Prof Clare Turnbull, PhD

Published: July 20, 2020 | DOI: https://doi.org/10.1016/S1470-2045(20)30392-2

 

Summary

Background

During the COVID-19 lockdown, referrals via the 2-week-wait urgent pathway for suspected cancer in England, UK, are reported to have decreased by up to 84%. We aimed to examine the impact of different scenarios of lockdown-accumulated backlog in cancer referrals on cancer survival, and the impact on survival per referred patient due to delayed referral versus risk of death from nosocomial infection with severe acute respiratory syndrome coronavirus 2.

Methods

In this modelling study, we used age-stratified and stage-stratified 10-year cancer survival estimates for patients in England, UK, for 20 common tumour types diagnosed in 2008–17 at age 30 years and older from Public Health England. We also used data for cancer diagnoses made via the 2-week-wait referral pathway in 2013–16 from the Cancer Waiting Times system from NHS Digital. We applied per-day hazard ratios (HRs) for cancer progression that we generated from observational studies of delay to treatment. We quantified the annual numbers of cancers at stage I–III diagnosed via the 2-week-wait pathway using 2-week-wait age-specific and stage-specific breakdowns. From these numbers, we estimated the aggregate number of lives and life-years lost in England for per-patient delays of 1–6 months in presentation, diagnosis, or cancer treatment, or a combination of these. We assessed three scenarios of a 3-month period of lockdown during which 25%, 50%, and 75% of the normal monthly volumes of symptomatic patients delayed their presentation until after lockdown. Using referral-to-diagnosis conversion rates and COVID-19 case-fatality rates, we also estimated the survival increment per patient referred.

Findings

Across England in 2013–16, an average of 6281 patients with stage I–III cancer were diagnosed via the 2-week-wait pathway per month, of whom 1691 (27%) would be predicted to die within 10 years from their disease. Delays in presentation via the 2-week-wait pathway over a 3-month lockdown period (with an average presentational delay of 2 months per patient) would result in 181 additional lives and 3316 life-years lost as a result of a backlog of referrals of 25%, 361 additional lives and 6632 life-years lost for a 50% backlog of referrals, and 542 additional lives and 9948 life-years lost for a 75% backlog in referrals. Compared with all diagnostics for the backlog being done in month 1 after lockdown, additional capacity across months 1–3 would result in 90 additional lives and 1662 live-years lost due to diagnostic delays for the 25% backlog scenario, 183 additional lives and 3362 life-years lost under the 50% backlog scenario, and 276 additional lives and 5075 life-years lost under the 75% backlog scenario. However, a delay in additional diagnostic capacity with provision spread across months 3–8 after lockdown would result in 401 additional lives and 7332 life-years lost due to diagnostic delays under the 25% backlog scenario, 811 additional lives and 14 873 life-years lost under the 50% backlog scenario, and 1231 additional lives and 22 635 life-years lost under the 75% backlog scenario. A 2-month delay in 2-week-wait investigatory referrals results in an estimated loss of between 0·0 and 0·7 life-years per referred patient, depending on age and tumour type.

Interpretation

Prompt provision of additional capacity to address the backlog of diagnostics will minimise deaths as a result of diagnostic delays that could add to those predicted due to expected presentational delays. Prioritisation of patient groups for whom delay would result in most life-years lost warrants consideration as an option for mitigating the aggregate burden of mortality in patients with cancer.

Funding

None.

Keywords: SARS-CoV-2; COVID-19; Cancer; UK.

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#Knowledge and #Perceptions of #COVID19 Among the General #Public in the #USA and the #UK: A Cross-sectional #Online #Survey (Ann Intern Med., abstract)

[Source: Annals of Internal Medicine, full page: (LINK). Abstract, edited.]

Knowledge and Perceptions of COVID-19 Among the General Public in the United States and the United Kingdom: A Cross-sectional Online Survey

Pascal Geldsetzer, MBChB, ScD, MPH

DOI: https://doi.org/10.7326/M20-0912

 

Abstract

Background:

The behavior of the general public will probably have an important bearing on the course of the coronavirus disease 2019 (COVID-19) epidemic. Human behavior is influenced by people’s knowledge and perceptions (1).

Objective:

To assess knowledge and perceptions about COVID-19 among a convenience sample of the general public in the United States and United Kingdom.

Methods and Findings:

This study is a cross-sectional survey conducted on an online platform managed by Prolific Academic Ltd. The platform’s pool of participants numbers approximately 80 000 individuals, of whom approximately 43% reside in the United Kingdom and 33% in the United States (2). For this study, Prolific selected a convenience sample of 3000 participants residing in the United States and 3000 participants residing in the United Kingdom who were chosen to have approximately the same distribution of age, sex, and ethnicity (and each combination thereof) as the U.S. and U.K. general population (by using numbers from the last census in each country). Specifically, Prolific established population strata (Table 1) with a predetermined number of open slots into which eligible participants in the online pool could enroll on a first-come, first-served basis.

Keywords: SARS-CoV-2; COVID-19; USA; UK; Society.

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