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Following primary SARS-CoV-2 vaccination, understanding the relative extent of protection against SARS-CoV-2 infection from boosters or from breakthrough infections (i.e. infection in the context of previous vaccination) has important implications for vaccine policy. In this study, we investigated correlates of protection against Omicron BA.4/5 infections and anti-spike IgG antibody trajectories after a third/booster vaccination or breakthrough infection following second vaccination in 154,149 adults [≥]18y from the United Kingdom general population. We found that higher anti-spike IgG antibody levels were associated with increased protection against Omicron BA.4/5 infection and that breakthrough infections were associated with higher levels of protection at any given antibody level than booster vaccinations. Breakthrough infections generated similar antibody levels to third/booster vaccinations, and the subsequent declines in antibody levels were similar to or slightly slower than those after third/booster vaccinations. Taken together our findings show that breakthrough infection provides longer lasting protection against further infections than booster vaccinations. For example, considering antibody levels associated with 67% protection against infection, a third/booster vaccination did not provide long-lasting protection, while a Delta/Omicron BA.1 breakthrough infection could provide 5-10 months of protection against Omicron BA.4/5 reinfection. 50-60% of the vaccinated UK population with a breakthrough infection would still be protected by the end of 2022, compared to <15% of the triple-vaccinated UK population without previous infection. Although there are societal impacts and risks to some individuals associated with ongoing transmission, breakthrough infection could be an efficient immune-boosting mechanism for subgroups of the population, including younger healthy adults, who have low risks of adverse consequences from infection.
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BackgroundMonitoring infection trends is vital to informing public health strategy. Detecting and quantifying changes in growth rates can inform policymakers rationale for implementing or continuing interventions aimed at reducing impact. Substantial changes in SARS-CoV-2 prevalence with emergence of variants provides opportunity to investigate different methods to do this. MethodsWe included PCR results from all participants in the UKs COVID-19 Infection Survey between 1 August 2020-30 June 2022. Change-points for growth rates were identified using iterative sequential regression (ISR) and second derivatives of generalised additive models (GAMs). Consistency between methods and timeliness of detection were compared. FindingsOf 8,799,079 visits, 147,278 (1{middle dot}7%) were PCR-positive. Over the time period, change-points associated with emergence of major variants were estimated to occur a median 4 days earlier (IQR 0-8) in GAMs versus ISR, with only 2/48 change-points identified by only one method. Estimating recent change-points using successive data periods, four change-points (4/96) identified by GAMs were not found when adding later data or by ISR; 77% (74/96) of change-points identified by successive GAMs were identified by ISR. Change-points were detected 3-5 weeks after they occurred in both methods but could be detected earlier within specific subgroups. InterpretationChange-points in growth rates of SARS-CoV-2 can be detected in near real-time using ISR and second derivatives of GAMs. To increase certainty about changes in epidemic trajectories both methods could be run in parallel. Running either method in near real-time on different infection surveillance data streams could provide timely warnings of changing underlying epidemiology. FundingUK Health Security Agency, Department of Health and Social Care (UK), Welsh Government, Department of Health (on behalf of the Northern Ireland Government), Scottish Government, National Institute for Health Research.
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BackgroundThe SARS-CoV-2 Delta variant has been replaced by the highly transmissible Omicron BA.1 variant, and subsequently by Omicron BA.2. It is important to understand how these changes in dominant variants affect reported symptoms, while also accounting for symptoms arising from other co-circulating respiratory viruses. MethodsIn a nationally representative UK community study, the COVID-19 Infection Survey, we investigated symptoms in PCR-positive infection episodes vs. PCR-negative study visits over calendar time, by age and vaccination status, comparing periods when the Delta, Omicron BA.1 and BA.2 variants were dominant. ResultsBetween October-2020 and April-2022, 120,995 SARS-CoV-2 PCR-positive episodes occurred in 115,886 participants, with 70,683 (58%) reporting symptoms. The comparator comprised 4,766,366 PCR-negative study visits (483,894 participants); 203,422 (4%) reporting symptoms. Symptom reporting in PCR-positives varied over time, with a marked reduction in loss of taste/smell as Omicron BA.1 dominated, maintained with BA.2 (44%/45% 17 October 2021, 16%/13% 2 January 2022, 15%/12% 27 March 2022). Cough, fever, shortness of breath, myalgia, fatigue/weakness and headache also decreased after Omicron BA.1 dominated, but sore throat increased, the latter to a greater degree than concurrent increases in PCR-negatives. Fatigue/weakness increased again after BA.2 dominated, although to a similar degree to concurrent increases in PCR-negatives. Symptoms were consistently more common in adults aged 18-65 years than in children or older adults. ConclusionsIncreases in sore throat (also common in the general community), and a marked reduction in loss of taste/smell, make Omicron harder to detect with symptom-based testing algorithms, with implications for institutional and national testing policies. SummaryIn a UK community study, loss of taste/smell was markedly less commonly reported with Omicron BA.1/BA.2 than Delta SARS-CoV-2 infections, with smaller declines in reported shortness of breath, myalgia and fatigue/weakness, but increases in sore throat, challenging symptom-based testing algorithms.
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Genome sequencing is pivotal to SARS-CoV-2 surveillance, elucidating the emergence and global dissemination of acquired genetic mutations. Amplicon sequencing has proven very effective for sequencing SARS-CoV-2, but prevalent mutations disrupting primer binding sites have necessitated the revision of sequencing protocols in order to maintain performance for emerging virus lineages. We compared the performance of Oxford Nanopore Technologies (ONT) Midnight and ARTIC tiling amplicon protocols using 196 Delta lineage SARS-CoV-2 clinical specimens, and 71 mostly Omicron lineage samples with S gene target failure (SGTF), reflecting circulating lineages in the United Kingdom during December 2021. 96-plexed nanopore sequencing was used. For Delta lineage samples, ARTIC v4 recovered the greatest proportion of [≥]90% complete genomes (81.1%; 159/193), followed by Midnight (71.5%; 138/193) and ARTIC v3 (34.1%; 14/41). Midnight protocol however yielded higher average genome recovery (mean 98.8%) than ARTIC v4 (98.1%) and ARTIC v3 (75.4%), resulting in less ambiguous final consensus assemblies overall. Explaining these observations were ARTIC v4s superior genome recovery in low viral titre/high cycle threshold (Ct) samples and inferior performance in high titre/low Ct samples, where Midnight excelled. We evaluated Omicron sequencing performance using a revised Midnight primer mix alongside prototype ARTIC v4.1 primers, head-to-head with the existing commercially available Midnight and ARTIC v4 protocols. The revised protocols both improved considerably the recovery of Omicron genomes and exhibited similar overall performance to one another. Revised Midnight protocol recovered [≥]90% complete genomes for 85.9% (61/71) of Omicron samples vs. 88.7% (63/71) for ARTIC v4.1. Approximate cost per sample for Midnight ({pound}12) is lower than ARTIC ({pound}16) while hands-on time is considerably lower for Midnight ([~]7 hours) than ARTIC protocols ([~]9.5 hours).
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Given high SARS-CoV-2 incidence, coupled with slow and inequitable vaccine roll-out, there is an urgent need for evidence to underpin optimum vaccine deployment, aiming to maximise global population immunity at speed. We evaluate whether a single vaccination in previously infected individuals generates similar initial and subsequent antibody responses to two vaccinations in those without prior infection. We compared anti-spike IgG antibody responses after a single dose of ChAdOx1, BNT162b2, or mRNA-1273 SARS-CoV-2 vaccines in the COVID-19 Infection Survey in the UK general population. In 100,849 adults who received at least one vaccination, 13,404 (13.3%) had serological and/or PCR evidence of prior infection. Prior infection significantly boosted antibody responses for all three vaccines, producing a higher peak level and longer half-life, and a response comparable to those without prior infection receiving two vaccinations. In those with prior infection, median time above the positivity threshold was estimated to last for >1 year after the first dose. Single-dose vaccination targeted to those previously infected may provide protection in populations with high rates of previous infection faced with limited vaccine supply, as an interim measure while vaccine campaigns are scaled up.
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ObjectiveTo describe the impact of the SARS-CoV-2 pandemic on the incidence of paediatric viral respiratory tract infection in Oxfordshire, UK. MethodsData on paediatric Emergency Department (ED) attendances (0-15 years inclusive), respiratory virus testing, vital signs and mortality at Oxford University Hospitals were summarised using descriptive statistics. ResultsBetween 1-March-2016 and 30-July-2021, 155,056 ED attendances occurred and 7,195 respiratory virus PCRs were performed. Detection of all pathogens was suppressed during the first national lockdown. Rhinovirus and adenovirus rates increased when schools reopened September-December 2020, then fell, before rising in March-May 2021. The usual winter RSV peak did not occur in 2020/21, with an inter-seasonal rise (32/1,000 attendances in 0-3yr olds) in July 2021. Influenza remained suppressed throughout. A higher Paediatric Early Warning Score (PEWS) was seen for attendees with adenovirus during the pandemic compared to pre-pandemic (p=0.04, Mann-Witney U test), no other differences in PEWS were seen. ConclusionsSARS-CoV-2 caused major changes in the incidence of paediatric respiratory viral infection in Oxfordshire, with implications for clinical service demand, testing strategies, timing of palivizumab RSV prophylaxis, and highlighting the need to understand which public health interventions are most effective for preventing respiratory virus infections.
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We investigated anti-spike IgG antibody responses and correlates of protection following second doses of ChAdOx1 or BNT162b2 SARS-CoV-2 vaccines in the UK general population. In 222,493 individuals, we found significant boosting of anti-spike IgG by second doses of both vaccines in all ages and using different dosing intervals, including the 3-week interval for BNT162b2. After second vaccination, BNT162b2 generated higher peak levels than ChAdOX1. Older individuals and males had lower peak levels with BNT162b2 but not ChAdOx1, while declines were similar across ages and sexes with ChAdOX1 or BNT162b2. Prior infection significantly increased antibody peak level and half-life with both vaccines. Anti-spike IgG levels were associated with protection from infection after vaccination and, to an even greater degree, after prior infection. At least 67% protection against infection was estimated to last for 2-3 months after two ChAdOx1 doses and 5-8 months after two BNT162b2 doses in those without prior infection, and 1-2 years for those unvaccinated after natural infection. A third booster dose may be needed, prioritised to ChAdOx1 recipients and those more clinically vulnerable.
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BackgroundThe COVID-19 pandemic is rapidly evolving, with emerging variants and fluctuating control policies. Real-time population screening and identification of groups in whom positivity is highest could help monitor spread and inform public health messaging and strategy. MethodsTo develop a real-time screening process, we included results from nose and throat swabs and questionnaires taken 19 July 2020-17 July 2021 in the UKs national COVID-19 Infection Survey. Fortnightly, associations between SARS-CoV-2 positivity and 60 demographic and behavioural characteristics were estimated using logistic regression models adjusted for potential confounders, considering multiple testing, collinearity, and reverse causality. FindingsOf 4,091,537 RT-PCR results from 482,677 individuals, 29,903 (0{middle dot}73%) were positive. As positivity rose September-November 2020, rates were independently higher in younger ages, and those living in Northern England, major urban conurbations, more deprived areas, and larger households. Rates were also higher in those returning from abroad, and working in healthcare or outside of home. When positivity peaked December 2020-January 2021 (Alpha), high positivity shifted to southern geographical regions. With national vaccine roll-out from December 2020, positivity reduced in vaccinated individuals. Associations attenuated as rates decreased between February-May 2021. Rising positivity rates in June-July 2021 (Delta) were independently higher in younger, male, and unvaccinated groups. Few factors were consistently associated with positivity. 25/45 (56%) confirmed associations would have been detected later using 28-day rather than 14-day periods. InterpretationPopulation-level demographic and behavioural surveillance can be a valuable tool in identifying the varying characteristics driving current SARS-CoV-2 positivity, allowing monitoring to inform public health policy. FundingDepartment of Health and Social Care (UK), Welsh Government, Department of Health (on behalf of the Northern Ireland Government), Scottish Government, National Institute for Health Research.
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BackgroundSeveral community-based studies have assessed the ability of different symptoms to identify COVID-19 infections, but few have compared symptoms over time (reflecting SARS-CoV-2 variants) and by vaccination status. MethodsUsing data and samples collected by the COVID-19 Infection Survey at regular visits to representative households across the UK, we compared symptoms in new PCR-positives and comparator test-negative controls. ResultsFrom 26/4/2020-7/8/2021, 27,869 SARS-CoV-2 PCR-positive episodes occurred in 27,692 participants (median 42 years (IQR 22-58)); 13,427 (48%) self-reported symptoms ("symptomatic positive episodes"). The comparator group comprised 3,806,692 test-negative visits (457,215 participants); 130,612 (3%) self-reported symptoms ("symptomatic negative visit"). Reporting of any symptoms in positive episodes varied over calendar time, reflecting changes in prevalence of variants, incidental changes (e.g. seasonal pathogens, schools re-opening) and vaccination roll-out. There was a small increase in sore throat reporting in symptomatic positive episodes and negative visits from April-2021. After May-2021 when Delta emerged there were substantial increases in headache and fever in positives, but not in negatives. Although specific symptom reporting in symptomatic positive episodes vs. negative visits varied by age, sex, and ethnicity, only small improvements in symptom-based infection detection were obtained; e.g. adding fatigue/weakness or all eight symptoms to the classic four symptoms (cough, fever, loss of taste/smell) increased sensitivity from 74% to 81% to 90% but tests per positive from 4.6 to 5.3 to 8.7. ConclusionsWhilst SARS-CoV-2-associated symptoms vary by variant, vaccination status and demographics, differences are modest and do not warrant large-scale changes to targeted testing approaches given resource implications. SummaryWithin the COVID-19 Infection Survey, recruiting representative households across the UK general population, SARS-CoV-2-associated symptoms varied by viral variant, vaccination status and demographics. However, differences are modest and do not currently warrant large-scale changes to targeted testing approaches.
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We estimated the duration and determinants of antibody response after SARS-CoV-2 infection in the general population using representative data from 7,256 United Kingdom COVID-19 infection survey participants who had positive swab SARS-CoV-2 PCR tests from 26-April-2020 to 14-June-2021. A latent class model classified 24% of participants as non-responders not developing anti-spike antibodies. These seronegative non-responders were older, had higher SARS-CoV-2 cycle threshold values during infection (i.e. lower viral burden), and less frequently reported any symptoms. Among those who seroconverted, using Bayesian linear mixed models, the estimated anti-spike IgG peak level was 7.3-fold higher than the level previously associated with 50% protection against reinfection, with higher peak levels in older participants and those of non-white ethnicity. The estimated anti-spike IgG half-life was 184 days, being longer in females and those of white ethnicity. We estimated antibody levels associated with protection against reinfection likely last 1.5-2 years on average, with levels associated with protection from severe infection present for several years. These estimates could inform planning for vaccination booster strategies.
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Real-world data on antibody response post-vaccination in the general population are limited. 45,965 adults in the UKs national COVID-19 Infection Survey receiving Pfizer-BioNTech or Oxford-AstraZeneca vaccines had 111,360 anti-spike IgG measurements. Without prior infection, seroconversion rates and quantitative antibody levels post single dose were lower in older individuals, especially >60y. Two doses achieved high responses across all ages, particularly increasing seroconversion in older people, to similar levels to those achieved after prior infection followed by a single dose. Antibody levels rose more slowly and to lower levels with Oxford-AstraZeneca vs Pfizer-BioNTech, but waned following a single Pfizer-BioNTech dose. Latent class models identified four responder phenotypes: older people, males, and those having long-term health conditions were more commonly low responders. Where supplies are limited, vaccines should be prioritised for those not previously infected, and second doses to individuals >60y. Further data on the relationship between vaccine-mediated protection and antibody responses are needed.
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ObjectivesTo assess the effectiveness of COVID-19 vaccination in preventing SARS-CoV-2 infection in the community. DesignProspective cohort study. SettingThe UK population-representative longitudinal COVID-19 Infection Survey. Participants373,402 participants aged [≥]16 years contributing 1,610,562 RT-PCR results from nose and throat swabs between 1 December 2020 and 3 April 2021. Main outcome measuresNew RT-PCR-positive episodes for SARS-CoV-2 overall, by self-reported symptoms, by cycle threshold (Ct) value (<30 versus [≥]30), and by gene positivity (compatible with the B.1.1.7 variant versus not). ResultsOdds of new SARS-CoV-2 infection were reduced 65% (95% CI 60 to 70%; P<0.001) in those [≥]21 days since first vaccination with no second dose versus unvaccinated individuals without evidence of prior infection (RT-PCR or antibody). In those vaccinated, the largest reduction in odds was seen post second dose (70%, 95% CI 62 to 77%; P<0.001).There was no evidence that these benefits varied between Oxford-AstraZeneca and Pfizer-BioNTech vaccines (P>0.9).There was no evidence of a difference in odds of new SARS-CoV-2 infection for individuals having received two vaccine doses and with evidence of prior infection but not vaccinated (P=0.89). Vaccination had a greater impact on reducing SARS-CoV-2 infections with evidence of high viral shedding Ct<30 (88% reduction after two doses; 95% CI 80 to 93%; P<0.001) and with self-reported symptoms (90% reduction after two doses; 95% CI 82 to 94%; P<0.001); effects were similar for different gene positivity patterns. ConclusionVaccination with a single dose of Oxford-AstraZeneca or Pfizer-BioNTech vaccines, or two doses of Pfizer-BioNTech, significantly reduced new SARS-CoV-2 infections in this large community surveillance study. Greater reductions in symptomatic infections and/or infections with a higher viral burden are reflected in reduced rates of hospitalisations/deaths, but highlight the potential for limited ongoing transmission from asymptomatic infections in vaccinated individuals. RegistrationThe study is registered with the ISRCTN Registry, ISRCTN21086382.
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BackgroundSerological tests are widely used in various medical disciplines for diagnostic and monitoring purposes. Unfortunately, the sensitivity and specificity of test systems is often poor, leaving room for false positive and false negative results. However, conventional methods used to increase specificity decrease sensitivity and vice versa. Using SARS-CoV-2 serology as an example, we propose here a novel testing strategy: the "Sensitivity Improved Two-Test" or " SIT2" algorithm. MethodsSIT2 involves confirmatory re-testing of samples with results falling in a predefined retesting-zone of an initial screening test, with adjusted cut-offs to increase sensitivity. We verified and compared the performance of SIT2 to single tests and orthogonal testing (OTA) in an Austrian cohort (1,117 negative, 64 post-COVID positive samples) and validated the algorithm in an independent British cohort (976 negatives, 536 positives). ResultsThe specificity of SIT2 was superior to single tests and non-inferior to OTA. The sensitivity was maintained or even improved using SIT2 when compared to single tests or OTA. SIT2 allowed correct identification of infected individuals even when a live virus neutralization assay could not detect antibodies. Compared to single testing or OTA, SIT2 significantly reduced total test errors to 0.46% (0.24-0.65) or 1.60% (0.94-2.38) at both 5% or 20% seroprevalence. ConclusionFor SARS-CoV-2 serology, SIT2 proved to be the best diagnostic choice at both 5% and 20% seroprevalence in all tested scenarios. It is an easy to apply algorithm and can potentially be helpful for the serology of other infectious diseases.
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BackgroundSARS-CoV-2 IgG antibody measurements can be used to estimate the proportion of a population exposed or infected and may be informative about the risk of future infection. Previous estimates of the duration of antibody responses vary. MethodsWe present 6 months of data from a longitudinal seroprevalence study of 3217 UK healthcare workers (HCWs). Serial measurements of IgG antibodies to SARS-CoV-2 nucleocapsid were obtained. Bayesian mixed linear models were used to investigate antibody waning and associations with age, gender, ethnicity, previous symptoms and PCR results. ResultsIn this cohort of working age HCWs, antibody levels rose to a peak at 24 (95% credibility interval, CrI 19-31) days post-first positive PCR test, before beginning to fall. Considering 452 IgG seropositive HCWs over a median of 121 days (maximum 171 days) from their maximum positive IgG titre, the mean estimated antibody half-life was 85 (95%CrI, 81-90) days. The estimated mean time to loss of a positive antibody result was 137 (95%CrI 127-148) days. We observed variation between individuals; higher maximum observed IgG titres were associated with longer estimated antibody half-lives. Increasing age, Asian ethnicity and prior self-reported symptoms were independently associated with higher maximum antibody levels, and increasing age and a positive PCR test undertaken for symptoms with longer antibody half-lives. ConclusionIgG antibody levels to SARS-CoV-2 nucleocapsid wane within months, and faster in younger adults and those without symptoms. Ongoing longitudinal studies are required to track the long-term duration of antibody levels and their association with immunity to SARS-CoV-2 reinfection. SummarySerially measured SARS-CoV-2 anti-nucleocapsid IgG titres from 452 seropositive healthcare workers demonstrate levels fall by half in 85 days. From a peak result, detectable antibodies last a mean 137 days. Levels fall faster in younger adults and following asymptomatic infection.
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Information on SARS-CoV-2 in representative community surveillance is limited, particularly cycle threshold (Ct) values (a proxy for viral load). Of 3,312,159 nose and throat swabs taken 26-April-2020 to 13-March-2021 in the UKs national COVID-19 Infection Survey, 27,902(0.83%) were RT-PCR-positive, 10,317(37%), 11,012(40%) and 6,550(23%) for 3, 2 or 1 of the N, S and ORF1ab genes respectively, with median Ct=29.2 ([~]215 copies/ml; IQR Ct=21.9-32.8, 14-56,400 copies/ml). Independent predictors of lower Cts (i.e. higher viral load) included self-reported symptoms and more genes detected, with at most small effects of sex, ethnicity and age. Single-gene positives almost invariably had Ct>30, but Cts varied widely in triple-gene positives, including without symptoms. Population-level Cts changed over time, with declining Ct preceding increasing SARS-CoV-2 positivity. Of 6,189 participants with IgG S-antibody tests post-first RT-PCR-positive, 4,808(78%) were ever antibody-positive; Cts were significantly higher in those remaining antibody-negative. Community SARS-CoV-2 Ct values could be a useful epidemiological early-warning indicator. IMPACT STATEMENTCt values from SARS-CoV-2 RT-PCR tests vary widely and over calendar time. They have the potential to be used more broadly in public testing programmes as an "early-warning" system for shifts in infectious load and hence transmission.
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The increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the current COVID-19 pandemic, has resulted in an urgent need for rapid and sensitive diagnostic methods. Here, we present a methodology for virus detection and identification that uses a convolutional neural network to distinguish between microscopy images of single intact particles of different viruses. Our assay achieves labeling, imaging and virus identification in less than five minutes and does not require any lysis, purification or amplification steps. The trained neural network was able to differentiate SARS-CoV-2 from negative clinical samples, as well as from other common respiratory pathogens such as influenza and seasonal human coronaviruses. Additionally, we were able to differentiate closely related strains of influenza, as well as SARS-CoV-2 variants. Single-particle imaging combined with deep learning therefore offers a promising alternative to traditional viral diagnostic and genomic sequencing methods, and has the potential for significant impact.
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Serological detection of antibodies to SARS-CoV-2 is essential for establishing rates of seroconversion in populations, detection of seroconversion after vaccination, and for seeking evidence for a level of antibody that may be protective against COVID-19 disease. Several high-performance commercial tests have been described, but these require centralised laboratory facilities that are comparatively expensive, and therefore not available universally. Red cell agglutination tests have a long history in blood typing, and general serology through linkage of reporter molecules to the red cell surface. They do not require special equipment, are read by eye, have short development times, low cost and can be applied as a Point of Care Test (POCT). We describe a red cell agglutination test for the detection of antibodies to the SARS-CoV-2 receptor binding domain (RBD). We show that the Haemagglutination Test ("HAT") has a sensitivity of 90% and specificity of 99% for detection of antibodies after a PCR diagnosed infection. The HAT can be titrated, detects rising titres in the first five days of hospital admission, correlates well with a commercial test that detects antibodies to the RBD, and can be applied as a point of care test. The developing reagent is composed of a previously described nanobody to a conserved glycophorin A epitope on red cells, linked to the RBD from SARS-CoV-2. It can be lyophilised for ease of shipping. We have scaled up production of this reagent to one gram, which is sufficient for ten million tests, at a cost of [~]0.27 UK pence per test well. Aliquots of this reagent are ready to be supplied to qualified groups anywhere in the world that need to detect antibodies to SARS-CoV-2, but do not have the facilities for high throughput commercial tests.
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LamPORE is a novel diagnostic platform for the detection of SARS-CoV-2 RNA that combines loop-mediated isothermal amplification with nanopore sequencing, which could potentially be used to analyse thousands of samples per day on a single instrument. We evaluated the performance of LamPORE against RT-PCR using RNA extracted from spiked respiratory samples and from stored nose and throat swabs collected at two UK hospitals. The limit of detection of LamPORE was 7-10 genome copies/{micro}l of extracted RNA. This is above the limit achievable by RT-PCR but was not associated with a significant reduction of sensitivity in clinical samples. Positive clinical specimens came mostly from patients with acute symptomatic infection, and among these LamPORE had a diagnostic sensitivity of 99.1% (226/228 [95% CI 96.9-99.9%]). Among negative clinical specimens, including 153 with other respiratory pathogens detected, LamPORE had a diagnostic specificity of 99.6% (278/279 [98.0-100.0%]). Overall, 1.4% (7/514 [0.5-2.9]) of samples produced an indeterminate result on first testing, and repeat LamPORE testing on the same RNA extract had a reproducibility of 96.8% (478/494 [94.8-98.1]). This indicates that LamPORE has a similar performance to RT-PCR for the diagnosis of SARS-CoV-2 infection in symptomatic patients, and offers a promising approach to high-throughput testing.
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BackgroundLaboratory diagnosis of SARS-CoV-2 infection (the cause of COVID-19) uses PCR to detect viral RNA (vRNA) in respiratory samples. SARS-CoV-2 RNA has also been detected in other sample types, but there is limited understanding of the clinical or laboratory significance of its detection in blood. MethodsWe undertook a systematic literature review to assimilate the evidence for the frequency of vRNA in blood, and to identify associated clinical characteristics. We performed RT-PCR in serum samples from a UK clinical cohort of acute and convalescent COVID-19 cases (n=212), together with convalescent plasma samples collected by NHS Blood and Transplant (NHSBT) (n=111 additional samples). To determine whether PCR-positive blood samples could pose an infection risk, we attempted virus isolation from a subset of RNA-positive samples. ResultsWe identified 28 relevant studies, reporting SARS-CoV-2 RNA in 0-76% of blood samples; pooled estimate 10% (95%CI 5-18%). Among serum samples from our clinical cohort, 27/212 (12.7%) had SARS-CoV-2 RNA detected by RT-PCR. RNA detection occurred in samples up to day 20 post symptom onset, and was associated with more severe disease (multivariable odds ratio 7.5). Across all samples collected [≥]28 days post symptom onset, 0/143 (0%, 95%CI 0.0-2.5%) had vRNA detected. Among our PCR-positive samples, cycle threshold (ct) values were high (range 33.5-44.8), suggesting low vRNA copy numbers. PCR-positive sera inoculated into cell culture did not produce any cytopathic effect or yield an increase in detectable SARS-CoV-2 RNA. ConclusionsvRNA was detectable at low viral loads in a minority of serum samples collected in acute infection, but was not associated with infectious SARS-CoV-2 (within the limitations of the assays used). This work helps to inform biosafety precautions for handling blood products from patients with current or previous COVID-19.
