The impact of community asymptomatic rapid antigen testing on COVID-19 hospital admissions: a synthetic control study

ObjectiveTo analyse the impact on hospital admissions for COVID-19 of large-scale, voluntary, public open access rapid testing for SARS-CoV-2 antigen in Liverpool (UK) between 6th November 2020 and 2nd January 2021. DesignSynthetic control analysis comparing hospital admissions for small areas in the intervention population to a group of control areas weighted to be similar in terms of prior COVID-19 hospital admission rates and socio-demographic factors. InterventionCOVID-SMART (Systematic Meaningful Asymptomatic Repeated Testing), a national pilot of large-scale, voluntary rapid antigen testing for people without symptoms of COVID-19 living or working in the City of Liverpool, deployed with the assistance of the British Army from the 6th November 2020 in an unvaccinated population. This pilot informed the UK roll-out of SARS-CoV-2 antigen rapid testing, and similar policies internationally. Main outcome measureWeekly COVID-19 hospital admissions for neighbourhoods in England. ResultsThe intensive introduction of COVID-SMART community testing was associated with a 43% (95% confidence interval: 29% to 57%) reduction in COVID-19 hospital admissions in Liverpool compared to control areas for the initial period of intensive testing with military assistance in national lockdown from 6th November to 3rd December 2020. A 25% (11% to 35%) reduction was estimated across the overall intervention period (6th November 2020 to 2nd January 2021), involving fewer testing centres, before Englands national roll-out of community testing, after adjusting for regional differences in Tiers of COVID-19 restrictions from 3rd December 2020 to 2nd January 2021. ConclusionsThe worlds first voluntary, city-wide SARS-CoV-2 rapid antigen testing pilot in Liverpool substantially reduced COVID-19 hospital admissions. Large scale asymptomatic rapid testing for SARS-CoV-2 can help reduce transmission and prevent hospital admissions. Summary boxO_ST_ABSWhat is already known on this topicC_ST_ABS- Previous studies on managing the spread of SARS-CoV-2 have identified asymptomatic transmission as significant challenges for controlling the pandemic. - Along with non-pharmaceutical measures, many countries rolled out population-based asymptomatic testing programmes to further limit transmission. - Evidence is required on whether large scale voluntary testing of communities for COVID-19 reduces severe disease, by breaking chains of transmission. What this study adds- The findings of this study suggest that large scale rapid antigen testing of communities for SARS-CoV-2, within an agile local public health campaign, can reduce transmission and prevent hospital admissions. - The results indicate that policy makers should integrate such testing into comprehensive, local public health programmes targeting high risk groups, supporting those required to isolate and adapting promptly to prevailing biological, behavioural and environmental circumstances.

Changing patterns of SARS-CoV-2 infection through Delta and Omicron waves by vaccination status, previous infection and neighbourhood deprivation: A cohort analysis of 2.7M people.

ObjectiveTo examine if SARS-CoV-2 infections vary by vaccination status, if an individual had previously tested positive and by neighbourhood socioeconomic deprivation across the Delta and Omicron epidemic waves of SARS-CoV-2. DesignCohort study using electronic health records SettingCheshire and Merseyside, England (3rd June 2021 to 1st March 2022) Participants2.7M residents Main Outcome measureRegistered positive test for SARS-CoV-2 ResultsSocial inequalities in registered positive tests were dynamic during the study. Originally higher SARS-CoV-2 rates in the most socioeconomically deprived neighbourhoods changed to being higher in the least deprived neighbourhoods from the 1st September 2021. While the introduction of Omicron initially reset inequalities, they continued to be dynamic and inconsistent. Individuals who were fully vaccinated (two doses) were associated with fewer registered positive tests (e.g., between 1st September and 27th November 2021: (i) individuals engaged in testing - Hazards Ratio (HR) = 0.48, 95% Confidence Intervals (CIs) = 0.47-0.50; (ii) individuals engaged with healthcare - HR = 0.34, 95% CIs = 0.33-0.34). Individuals with a previous registered positive test were also less likely to have a registered positive test (e.g., between 1st September and 27th November 2021: (i) individuals engaged in testing - HR = 0.16, 95% CIs = 0.15-0.18; (ii) individuals engaged with healthcare - HR = 0.14, 95% CIs = 0.13-0.16). However, Omicron is disrupting these associations due to immune escape resulting in smaller effect sizes for both measures. ConclusionsChanging patterns of SARS-CoV-2 infections during the Delta and Omicron waves reveals a dynamic pandemic that continues to affect diverse communities in sometimes unexpected ways.

Effectiveness of the BNT162b2 (Pfizer-BioNTech) and the ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines for reducing susceptibility to infection with the Delta variant(B.1.617.2) of SARS-CoV-2

BackgroundFrom January to May 2021 the alpha variant (B.1.1.7) of SARS-CoV-2 was the most commonly detected variant in the UK, but since then the Delta variant (B.1.617.2), first detected in India, has become the predominant variant. The UK COVID-19 vaccination programme started on 8th December 2020. Most vaccine effectiveness studies to date have focused on the alpha variant. We therefore aimed to estimate the effectiveness of the BNT162b2 (Pfizer-BioNTech) and the ChAdOx1 nCoV-19 (Oxford-AstraZeneca) vaccines in preventing infection with respect to the Delta variant in a UK setting. MethodsWe used anonymised public health record data linked to infection data (PCR) using the Combined Intelligence for Population Health Action resource. We then constructed an SIR epidemic model to explain SARS-CoV-2 infection data across the Cheshire and Merseyside region of the UK. ResultsWe determined that the effectiveness of the Oxford-AstraZeneca vaccine in reducing susceptibility to infection is 39% (95% credible interval [34,43]) and 64% (95% credible interval [61,67]) for a single dose and a double dose respectively. For the Pfizer-BioNTech vaccine, the effectiveness is 20% (95% credible interval [10,28]) and 84% (95% credible interval [82,86]) for a single-dose and a double dose respectively. ConclusionVaccine effectiveness for reducing susceptibility to SARS-CoV-2 infection shows noticeable improvement after receiving two doses of either vaccine. Findings also suggest that a full course of the Pfizer-BioNTech provides the optimal protection against infection with the Delta variant. This would advocate for completing the full course programme to maximise individual protection and reduce transmission.

Soft drinks can be misused to give false false positive SARS-CoV-2 lateral flow device results

BackgroundThe COVID-19 pandemic created the need for very large scale, rapid testing to prevent and contain transmission of the SARS-CoV-2 virus. Lateral flow device (LFD) immunoassays meet this need by indicating the presence of SARS-CoV-2 antigen from nose/throat swab washings in 30 minutes without laboratory processing, and can be manufactured quickly at low cost. Since March 2021, UK schools have asked pupils without symptoms to test twice weekly. Pupils have posted on social media about using soft drinks to create positive results. The aim of this study was to systematically test a variety soft drinks to determine whether they can cause false "false positive" LFD results. MethodsThis study used 14 soft drinks and 4 artificial sweeteners to determine the outcome of misusing them as analyte for the Innova SARS-CoV-2 antigen rapid qualitative LFD. The pH value, sugar content and ingredients of each sample are described. The LFD results were double read and a subset was repeated using the same devices and fake analytes but differently sourced. FindingsOne sample (1/14; 7%), spring water, produced a negative result. Ten drinks (10/14; 71%) produced a positive or weakly positive result. Three samples (3/14; 21%) produced void results, mostly the fruit concentrate drinks. There was no apparent correlation between the pH value (pH 5.0 in 13/14, 93%; pH 6.5 in 1/14; 7%) or the sugar content (range 0-10.7 grams per 100mls) of the drinks and their LFD result. The 4 artificial sweeteners all produced negative results. A subset of the results was fully replicated with differently sourced materials. InterpretationSeveral soft drinks can be misused to give false positive SARS-CoV-2 LFD results. Daily LFD testing should be performed first thing in the morning, prior to the consumption of any food or drinks, and supervised where feasible. FundingThis work was self-funded by author LO and the LFD were gifted for use in this study. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSO_LILateral flow devices (LFD) for SARS-CoV-2 antigen testing have been used extensively in the UK and internationally in COVID-19 pandemic responses, providing rapid testing at low cost C_LIO_LIRecent reports from young people on social media suggested soft drinks might be misused as LFD analyte and produce a seemingly positive result C_LI Added value of this studyO_LIVarious common soft drinks used as fake analyte can produce false positive SARS-CoV-2 LFD results C_LIO_LIArtificial sweeteners alone in fake analyte solution did not produce false positive results C_LI Implications of all the available evidenceO_LISoft drinks misused as analyte can produce false "false positive" SARS-CoV-2 LFD results C_LIO_LIDaily testing is best done first thing in the morning, prior to any food or drink, and under supervision where possible C_LI

Recalibrating SARS-CoV-2 antigen rapid lateral flow test relative sensitivity from validation studies to absolute sensitivity for detecting individuals with live virus

Testing for SARS-CoV-2 internationally has focused on COVID-19 diagnosis among symptomatic individuals using reverse transcriptase polymerase chain reaction (PCR) tests. Recently, however, SARS-CoV-2 antigen rapid lateral flow tests (LFT) have been rolled out in several countries for testing asymptomatic individuals in public health programmes. Validation studies for LFT have been largely cross-sectional, reporting sensitivity, specificity and predictive values of LFT relative to PCR. However, because PCR detects genetic material left behind for a long period when the individual is no longer infectious, these statistics can under-represent sensitivity of LFT for detecting infectious individuals, especially when sampling asymptomatic populations. LFTs (intended to detect individuals with live virus) validated against PCR (intended to diagnose infection) are not reporting against a gold standard of equivalent measurements. Instead, these validation studies have reported relative performance statistics that need recalibrating to the purpose for which LFT is being used. We present an approach to this recalibration. We derive a formula for recalibrating relative performance statistics from LFT vs PCR validation studies to give likely absolute sensitivity of LFT for detecting individuals with live virus. We show the differences between widely reported apparent sensitivities of LFT and its absolute sensitivity as a test of presence of live virus. After accounting for within-individual viral kinetics and epidemic dynamics within asymptomatic populations we show that a highly performant test of live virus should show a LFT-to-PCR relative sensitivity of less than 50% in conventional validation studies, which after re-calibration would be an absolute sensitivity of more than 80%. Further studies are needed to ascertain the absolute sensitivity of LFT as a test of infectiousness in COVID-19 responses. These studies should include sampling for viral cultures and longitudinal series of LFT and PCR, ideally in cohorts sampled from both contacts of cases and the general population.

Evaluating the impacts of tiered restrictions introduced in England, during October and December 2020 on COVID-19 cases: A synthetic control study.

BackgroundIn 2020, a second wave of COVID-19 cases unevenly affected places in England leading to the introduction of a tiered system of controls with different geographical areas subject to different levels of restrictions. Whilst previous research has examined the impact of national lockdowns on transmission, there has been limited research examining the marginal effect of differences in localised restrictions or how these effects vary between socioeconomic contexts. We therefore examined how Tier 3 restrictions in England implemented between October-December 2020, which included additional restrictions on the hospitality sector and people meeting outdoors affected COVID-19 case rates, compared to Tier 2 restrictions, and how these effects varied by level of deprivation. MethodsWe used data on weekly reported COVID-19 cases for 7201 neighbourhoods in England and adjusted these for changing case-detection rates to provide an estimate of weekly SARS-CoV-2 infections in each neighbourhood. We identified those areas that entered Tier 3 restrictions at two time points in October and December, and constructed a synthetic control group of similar places that had entered Tier 2 restrictions, using calibration weights to match them on a wide range of covariates that may influence transmission. We then compared the change in weekly infections between those entering Tier 3 to the synthetic control group to estimate the proportional reduction of cases resulting from Tier 3 restrictions compared to Tier 2 restrictions, over a 4-week period. We further used interaction analysis to estimate whether this effect differed based on the level of socioeconomic deprivation in each neighbourhood and whether effects were modified by the prevalence of a new more infectious variant of SARS-CoV-2 (B.1.1.7) in each area. ResultsThe introduction of Tier 3 restrictions in October and December was associated with a 14% (95% CI 10% to 19%) and 20% (95% CI 13% to 29%) reduction in infections respectively, compared to the rates expected if only Tier 2 restrictions had been in place in those areas. We found that effects were similar across levels of deprivation and limited evidence that Tier 3 restrictions had a greater effect in areas where the new more infectious variant was more prevalent. InterpretationAdditional restrictions on hospitality and meeting outdoors introduced in Tier 3 areas in England had a moderate effect on transmission and these restrictions did not appear to increase inequalities, having a similar impact across areas with differing levels of socioeconomic deprivation. Where transmission risks vary between geographical areas a tiered approach of local restrictions on outdoor mixing and hospitality can contribute to control of SARS-CoV-2 and is unlikely to increases inequalities in transmission.

Evaluating social and spatial inequalities of large scale rapid lateral flow SARS-CoV-2 antigen testing in COVID-19 management: An observational study of Liverpool, UK (November 2020 to January 2021)

ObjectiveTo explore social and spatial inequalities in uptake and case-detection of rapid lateral flow SARS-CoV-2 antigen tests (LFTs) offered to people without symptoms of COVID-19. DesignObservational study. SettingLiverpool, UK. Participants496 784 residents. InterventionFree LFTs to all people living and working in Liverpool (6th November 2020 to 31st January 2021). Main outcome measuresResidents who received a LFT, residents who had multiple LFTs, and positive test results. Results214 525 residents (43%) received a LFT identifying 5557 individuals as positive cases of COVID-19 (1.3%) between 6th November 2020 and 31st January 2021. 89 047 residents had more than one test (18%). Uptake was highest in November when there was military assistance. High uptake was observed again in the week preceding Christmas and was sustained into a national lockdown. Overall uptake and repeat testing were lower among males (e.g. 40% uptake over the whole period), Black Asian and other Minority Ethnic groups (e.g. 27% uptake for Mixed ethnicity) and in the most deprived areas (e.g. 32% uptake in most deprived areas). These population groups were also more likely to have received positive tests for COVID-19. Spatial regression models demonstrated that uptake and repeat testing were lower in areas of higher deprivation, areas located further from test sites and areas containing populations less confident in the using Internet technologies. Positive tests were spatially clustered in deprived areas. ConclusionsLarge-scale voluntary asymptomatic community testing saw social, ethnic, and spatial inequalities in an inverse care pattern, but with an added digital exclusion factor. COVID-19 testing and support to isolate need to be more accessible to the vulnerable communities most impacted by the pandemic, including non-digital means of access. What is already known on this topicO_LITesting asymptomatic individuals with rapid lateral flow SARS-CoV-2 antigen devices detects the most infectious individuals who otherwise would have been unaware they were likely to infect others. C_LIO_LILiverpool (UK) conducted the worlds first whole population, open-access, voluntary asymptomatic testing programme for COVID-19 management. C_LIO_LIThe impacts of such testing on inequalities are unknown. C_LI What this study addsO_LITesting uptake was lower, and test positivity was higher, among deprived populations, Black Asian and other Minority Ethnic groups and areas classified as having low Internet use. C_LIO_LIPopulation-wide asymptomatic testing programmes need to account for social, spatial, and digital access issues in their design, communication and delivery to minimise inequalities in outcomes. C_LI

Development and validation of the 4C Deterioration model for adults hospitalised with COVID-19

Prognostic models to predict the risk of clinical deterioration in acute COVID-19 are required to inform clinical management decisions. Among 75,016 consecutive adults across England, Scotland and Wales prospectively recruited to the ISARIC Coronavirus Clinical Characterisation Consortium (ISARIC4C) study, we developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) using 11 routinely measured variables. We used internal-external cross-validation to show consistent measures of discrimination, calibration and clinical utility across eight geographical regions. We further validated the final model in held-out data from 8,252 individuals in London, with similarly consistent performance (C-statistic 0.77 (95% CI 0.75 to 0.78); calibration-in-the-large 0.01 (-0.04 to 0.06); calibration slope 0.96 (0.90 to 1.02)). Importantly, this model demonstrated higher net benefit than using other candidate scores to inform decision-making. Our 4C Deterioration model thus demonstrates unprecedented clinical utility and generalisability to predict clinical deterioration among adults hospitalised with COVID-19.

Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score

ObjectivesTo develop and validate a pragmatic risk score to predict mortality for patients admitted to hospital with covid-19. DesignProspective observational cohort study: ISARIC WHO CCP-UK study (ISARIC Coronavirus Clinical Characterisation Consortium [4C]). Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited between 21 May and 29 June 2020. Setting260 hospitals across England, Scotland, and Wales. ParticipantsAdult patients ([≥]18 years) admitted to hospital with covid-19 admitted at least four weeks before final data extraction. Main outcome measuresIn-hospital mortality. ResultsThere were 34 692 patients included in the derivation dataset (mortality rate 31.7%) and 22 454 in the validation dataset (mortality 31.5%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea, and C-reactive protein (score range 0-21 points). The 4C risk stratification score demonstrated high discrimination for mortality (derivation cohort: AUROC 0.79; 95% CI 0.78 - 0.79; validation cohort 0.78, 0.77-0.79) with excellent calibration (slope = 1.0). Patients with a score [≥]15 (n = 2310, 17.4%) had a 67% mortality (i.e., positive predictive value 67%) compared with 1.0% mortality for those with a score [≤]3 (n = 918, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (AUROC range 0.60-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73). ConclusionsWe have developed and validated an easy-to-use risk stratification score based on commonly available parameters at hospital presentation. This outperformed existing scores, demonstrated utility to directly inform clinical decision making, and can be used to stratify inpatients with covid-19 into different management groups. The 4C Mortality Score may help clinicians identify patients with covid-19 at high risk of dying during current and subsequent waves of the pandemic. Study registrationISRCTN66726260

Estrogen and COVID-19 symptoms: associations in women from the COVID Symptom Study

BackgroundMen and older women have been shown to be at higher risk of adverse COVID-19 outcomes. Animal model studies of SARS-CoV and MERS suggest that the age and sex difference in COVID-19 symptom severity may be due to a protective effect of the female sex hormone estrogen. Females have shown an ability to mount a stronger immune response to a variety of viral infections because of more robust humoral and cellular immune responses. ObjectivesWe sought to determine whether COVID-19 positivity increases in women entering menopause. We also aimed to identify whether premenopausal women taking exogenous hormones in the form of the combined oral contraceptive pill (COCP) and post-menopausal women taking hormone replacement therapy (HRT) have lower predicted rates of COVID-19, using our published symptom-based model. DesignThe COVID Symptom Study developed by Kings College London and Zoe Global Limited was launched in the UK on 24th March 2020. It captured self-reported information related to COVID-19 symptoms. Data used for this study included records collected between 7th May - 15th June 2020. Main outcome measuresWe investigated links between COVID-19 rates and 1) menopausal status, 2) COCP use and 3) HRT use, using symptom-based predicted COVID-19, tested COVID-19, and disease severity based on requirement for hospital attendance or respiratory support. ParticipantsFemale users of the COVID Symptom Tracker Application in the UK, including 152,637 women for menopause status, 295,689 for COCP use, and 151,193 for HRT use. Analyses were adjusted for age, smoking and BMI. ResultsPost-menopausal women aged 40-60 years had a higher rate of predicted COVID (P=0.003) and a corresponding range of symptoms, with consistent, but not significant trends observed for tested COVID-19 and disease severity. Women aged 18-45 years taking COCP had a significantly lower predicted COVID-19 (P=8.03E-05), with a reduction in hospital attendance (P=0.023). Post-menopausal women using HRT or hormonal therapies did not exhibit consistent associations, including increased rates of predicted COVID-19 (P=2.22E-05) for HRT users alone. ConclusionsOur findings support a protective effect of estrogen on COVID-19, based on positive association between predicted COVID-19 and menopausal status, and a negative association with COCP use. HRT use was positively associated with COVID-19 symptoms; however, the results should be considered with caution due to lack of data on HRT type, route of administration, duration of treatment, and potential comorbidities. Trial registrationThe App Ethics has been approved by KCL ethics Committee REMAS ID 18210, review reference LRs-19/20-18210

Inequalities in COVID19 mortality related to ethnicity and socioeconomic deprivation

BackgroundInitial reports suggest that ethnic minorities may be experiencing more severe coronavirus disease 2019 (COVID19) outcomes. We therefore assessed the association between ethnic composition, income deprivation and COVID19 mortality rates in England. MethodsWe performed a cross-sectional ecological analysis across Englands upper-tier local authorities. We assessed the association between the proportion of the population from Black, Asian and Minority Ethnic (BAME) backgrounds, income deprivation and COVID19 mortality rates using multivariable negative binomial regression, adjusting for population density, proportion of the population aged 50-79 and 80+ years, and the duration of the epidemic in each area. FindingsLocal authorities with a greater proportion of residents from ethnic minority backgrounds had statistically significantly higher COVID19 mortality rates, as did local authorities with a greater proportion of residents experiencing deprivation relating to low income. After adjusting for income deprivation and other covariates, each percentage point increase in the proportion of the population from BAME backgrounds was associated with a 1% increase in the COVID19 mortality rate [IRR=1.01, 95%CI 1.01-1.02]. Each percentage point increase in the proportion of the population experiencing income deprivation was associated with a 2% increase in the COVID19 mortality rate [IRR=1.02, 95%CI 1.01-1.04]. InterpretationThis study provides evidence that both income deprivation and ethnicity are associated with greater COVID19 mortality. To reduce these inequalities, Government needs to target effective control and recovery measures at these disadvantaged communities, proportionate to their greater needs and vulnerabilities, during and following the pandemic. FundingNational Institute of Health Research; Medical Research Council