David H. Wyllie

Understanding the genetic and environmental risk factors for serious bacterial infections in ageing populations remains incomplete. Utilising the UK Biobank (UKB), a prospective cohort study of 500,000 adults aged 40–69 years at recruitment (2006–2010), can help address this. Partial implementation of such a system helped groups around the world make rapid progress understanding risk factors for SARS-CoV-2 infection and COVID-19, with insights appearing as early as May 2020. In principle, such approaches could also to be used for bacterial isolations. Here we report feasibility testing of linking an England-wide dataset of microbial reporting to UKB participants, to enable characterisation of microbial infections within the UKB Cohort. These records pertain mainly to bacterial isolations; SARS-CoV-2 isolations were not included. Microbiological infections occurring in patients in England, as recorded in the Public Health England second generation surveillance system (SGSS), were linked to UKB participants using pseudonymised identifiers. By January 2015, ascertainment of laboratory reports from UKB participants by SGSS was estimated at 98%. 4.5% of English UKB participants had a positive microbiological isolate in 2015. Half of UKB isolates came from 12 laboratories, and 70% from 21 laboratories. Incidence rate ratios for microbial isolation, which is indicative of serious infection, from the UKB cohort relative to the comparably aged general population ranged from 0.6 to 1, compatible with the previously described healthy participant bias in UKB. Data on microbial isolations can be linked to UKB participants from January 2015 onwards. This linked data would offer new opportunities for research into the role of bacterial agents on health and disease in middle to-old age.

Previous research has demonstrated an association between the detection of antibodies to SARS-CoV-2 following natural infection and protection from subsequent symptomatic SARS-CoV-2 infection. Lateral flow immunoassays (LFIAs) detecting anti-SARS-CoV-2 IgG are a cheap, readily deployed technology that has been used on a large scale in population screening programs, yet no studies have investigated whether LFIA results are associated with subsequent SARS-CoV-2 infection.

There is a need to identify microbial sequences that may form part of transmission chains, or that may represent importations across national boundaries, amidst large numbers of SARS-CoV-2 and other bacterial or viral sequences. Reference-based compression is a sequence analysis technique that allows both a compact storage of sequence data and comparisons between sequences. Published implementations of the approach are being challenged by the large sample collections now being generated. Our aim was to develop a fast software detecting highly similar sequences in large collections of microbial genomes, including millions of SARS-CoV-2 genomes. To do so, we developed Catwalk, a tool that bypasses bottlenecks in the generation, comparison and in-memory storage of microbial genomes generated by reference mapping. It is a compiled solution, coded in Nim to increase performance. It can be accessed via command line, rest api or web server interfaces. We tested Catwalk using both SARS-CoV-2 and Mycobacterium tuberculosis genomes generated by prospective public-health sequencing programmes. Pairwise sequence comparisons, using clinically relevant similarity cut-offs, took about 0.39 and 0.66 μs, respectively; in 1 s, between 1 and 2 million sequences can be searched. Catwalk operates about 1700 times faster than, and uses about 8 % of the RAM of, a Python reference-based compression and comparison tool in current use for outbreak detection. Catwalk can rapidly identify close relatives of a SARS-CoV-2 or M. tuberculosis genome amidst millions of samples.

Background: SARS-CoV-2 vaccine coverage remains incomplete, being only 15% in low income countries. Rapid point of care tests predicting SARS-CoV-2 infection susceptibility in the unvaccinated might assist in risk management and vaccine prioritisation. Methods: We conducted a prospective cohort study in 2,826 participants working in hospitals and Fire and Police services in England, UK, during the pandemic ( ISRCTN5660922 ). Plasma taken at recruitment in June 2020 was tested using four lateral flow immunoassay (LFIA) devices and two laboratory immunoassays detecting antibodies against SARS-CoV-2 (UK Rapid Test Consortium’s AbC-19™ Rapid Test, OrientGene COVID IgG/IgM Rapid Test Cassette, SureScreen COVID-19 Rapid Test Cassette, and Biomerica COVID-19 IgG/IgM Rapid Test; Roche N and EUROIMMUN S laboratory assays). We monitored participants for microbiologically-confirmed SARS-CoV-2 infection for 200 days. We estimated associations between test results at baseline and subsequent infection, using Poisson regression models adjusted for baseline demographic risk factors for SARS-CoV-2 exposure. Findings: Positive IgG results on each of the four LFIAs were associated with lower rates of subsequent infection: adjusted incidence rate ratios (aIRRs) 0.00 (95% confidence interval 0.00-0.01), 0.03 (0.02-0.05), 0.07 (0.05-0.10), and 0.09 (0.07-0.12) respectively. The protective association was strongest for AbC-19 and SureScreen. The aIRR for the laboratory Roche N antibody assay at the manufacturer-recommended threshold was similar to those of the two best performing LFIAs at 0.03 (0.01-0.10). Interpretation: Lateral flow devices measuring SARS-CoV-2 IgG predicted disease risk in unvaccinated individuals over 200 day follow-up. The association of some LFIAs with subsequent infection was similar to laboratory immunoassays. Funding: UK Government Research in context: Evidence before this study: We searched PubMed for research articles, using the search terms (“COVID-19” OR “SARS-CoV-2” OR “2019-nCoV” OR “coronavirus”) AND (“Antibody” OR “IgG”) AND ((“protection” OR “infection”) identifying studies of cohorts of unvaccinated individuals which reported antibody-associated disease protection published between Dec 1 2019 and 1 April 2022. Additionally, we reviewed studies matching “SARS-CoV-2” and “lateral flow” and “antibody” over the same period. Multiple cohort studies in healthy populations have demonstrated an association between the detection of antibodies to SARS-CoV-2 following natural infection and protection from subsequent symptomatic infection with SARS-CoV-2. Protection estimates were about 85% protection in two overlapping meta-analyses, while in several larger studies increased protection with higher antibody levels was observed. Lateral flow immunoassays (LFIAs) detecting anti-SARS-CoV-2 IgG are a cheap, readily deployed technology which has been used on a large scale in population screening programs. However, there are wide variations in sensitivity and specificity of antibody detection between different devices. No studies have investigated whether LFIA results are associated with subsequent SARS-CoV-2 infection. Added value of this study: In a prospective cohort study of 2,826 UK key workers, we found positivity in lateral flow test results had a strong negative association with subsequent SARS-CoV-2 infection within 200 days in an unvaccinated population. The performance of different devices in predicting disease protection differed: positivity on more specific but less sensitive tests was associated with markedly decreased rate of disease. By contrast, protection associated with testing positive using more sensitive devices detecting lower levels of anti-SARS-CoV-2 IgG was more modest. Implications of all the available evidence: If the field performance of these tests against contemporary SARS-CoV-2 infection was similar to that observed in this study, lateral flow tests with high specificity may have a role in estimation of SARS-CoV-2 disease risk in unvaccinated populations and individuals.

Objectives: To define risk factors for SARS-CoV-2 infection in University of Cambridge students during a period of increased incidence in October and November 2020. Study design: Survey Methods: Routine public health surveillance identified a marked increase in the numbers of University of Cambridge students with respiratory illness and SARS-CoV-2 positivity in the 10 days after a national lockdown was announced in the UK on 5 November 2020. Cases were identified both through symptom-triggered testing and a universal asymptomatic testing program. An online questionnaire was sent to all University of Cambridge students on 25 November to investigate risk factors for testing positive in the period after 30 ^th October 2020. This asked about symptoms, SARS-CoV-2 test results, in-person teaching settings, other aspects of University life, and attendance at social events in the period just prior to lockdown, from 30 ^th October and 4 ^th November 2020. Univariate and multivariable analyses were undertaken evaluating potential risk factors for SARS-CoV-2 positivity. Results: Among 3,980 students responding to the questionnaire, 99 (2.5%) reported testing SARS-CoV-2 positive in the period studied; 28 (28%) were asymptomatic. We found strong independent associations with SARS-CoV-2 positivity were attendance at two social settings in the City of Cambridge (adjusted odds ratio favouring disease 13.0 (95% CI 6.2,26.9) and 14.2 (95% CI 2.9,70)), with weaker evidence of association with three further social settings. By contrast, we did not observe strong independent associations between disease risk and type of accommodation or attendance at, or participation in, a range of activities associated with the University curriculum. Conclusions: Attendance at social settings can facilitate widespread SARS-CoV-2 transmission in University students. Constraint of transmission in higher education settings needs to emphasise risks outside University premises, as well as a COVID-safe environment within University premises. Highlights: In a population of University students, a large increase in individuals testing positive for SARS-CoV-2 occurred in the days following a national lockdown. Attendance at particular social gatherings was strongly linked to the development of disease, independent of other risk factors. By contrast, a range of risk factors including age, gender, ethnicity, accommodation type, shared kitchen facilities, attendance at supermarkets, and attending teaching sessions were not significantly associated with SARS-CoV-2 risk. These data emphasise the increased risk associated with University students attending social settings with large numbers of others, even when other risks associated with university attendance are well controlled.

Background: SARS-CoV-2 antibody tests are used for population surveillance and might have a future role in individual risk assessment. Lateral flow immunoassays (LFIAs) can deliver results rapidly and at scale, but have widely varying accuracy. Methods: In a laboratory setting, we performed head-to-head comparisons of four LFIAs: the Rapid Test Consortium’s AbC-19 ^™ Rapid Test, OrientGene COVID IgG/IgM Rapid Test Cassette, SureScreen COVID-19 Rapid Test Cassette, and Biomerica COVID-19 IgG/IgM Rapid Test. We analysed blood samples from 2,847 key workers and 1,995 pre-pandemic blood donors with all four devices. Findings: We observed a clear trade-off between sensitivity and specificity: the IgG band of the SureScreen device and the AbC-19 ^™ device had higher specificities but OrientGene and Biomerica higher sensitivities. Based on analysis of pre-pandemic samples, SureScreen IgG band had the highest specificity (98.9%, 95% confidence interval 98.3 to 99.3%), which translated to the highest positive predictive value across any pre-test probability: for example, 95.1% (95%CI 92.6, 96.8%) at 20% pre-test probability. All four devices showed higher sensitivity at higher antibody concentrations (“spectrum effects”), but the extent of this varied by device. Interpretation: The estimates of sensitivity and specificity can be used to adjust for test error rates when using these devices to estimate the prevalence of antibody. If tests were used to determine whether an individual has SARS-CoV-2 antibodies, in an example scenario in which 20% of individuals have antibodies we estimate around 5% of positive results on the most specific device would be false positives. Funding: Public Health England. Research in context: Evidence before this study: We searched for evidence on the accuracy of the four devices compared in this study: OrientGene COVID IgG/IgM Rapid Test Cassette, SureScreen COVID-19™ Rapid Test Cassette, Biomerica COVID-19 IgG/IgM Rapid Test and the UK Rapid Test Consortium’s AbC-19™ Rapid Test. We searched Ovid MEDLINE (In-Process & Other Non-Indexed Citations and Daily), PubMed, MedRxiv/BioRxiv and Google Scholar from January 2020 to 16 ^th January 2021. Search terms included device names AND ((SARS-CoV-2) OR (covid)). Of 303 records assessed, data were extracted from 24 studies: 18 reporting on the accuracy of the OrientGene device, 7 SureScreen, 2 AbC-19™ and 1 Biomerica. Only three studies compared the accuracy of two or more of the four devices. With the exception of our previous report on the accuracy of the AbC-19™ device, which the current manuscript builds upon, sample size ranged from 7 to 684. For details, see Supplementary Materials. The largest study compared OrientGene, SureScreen and Biomerica. SureScreen was estimated to have the highest specificity (99.8%, 95% CI 98.9 to 100%) and OrientGene the highest sensitivity (92.6%), but with uncertainty about the latter result due to small sample sizes. The other two comparative studies were small (n = 65, n = 67) and therefore provide very uncertain results. We previously observed spectrum effects for the AbC-19™ device, such that sensitivity is upwardly biased if estimated only from PCR-confirmed cases. The vast majority of previous studies estimated sensitivity in this way. Added value of this study: We performed a large scale (n = 4,842), head-to-head laboratory-based evaluation and comparison of four lateral flow devices, which were selected for evaluation by the UK Department of Health and Social Care’s New Tests Advisory Group, on the basis of a survey of test and performance data available. We evaluated the performance of diagnosis based on both IgG and IgM bands, and the IgG band alone. We found a clear trade-off between sensitivity and specificity across devices, with the SureScreen and AbC-19™ devices being more specific and OrientGene and Biomerica more sensitive. Based on analysis of 1,995 pre-pandemic blood samples, we are 99% confident that SureScreen (IgG band reading) has the highest specificity of the four devices (98.9%, 95% CI 98.3, 99.3%). We found evidence that all four devices have reduced sensitivity at lower antibody indices, i.e. spectrum effects. However, the extent of this varies by device and appears to be less for other devices than for AbC-19. Our estimates of sensitivity and specificity are likely to be higher than would be observed in real use of these devices, as they were based on majority readings of three trained laboratory personnel. Implications of all the available evidence: When used in epidemiological studies of antibody prevalence, the estimates of sensitivity and specificity provided in this study can be used to adjust for test errors. Increased precision in error rates will translate to increased precision in seroprevalence estimates. If lateral flow devices were used for individual risk assessment, devices with maximum specificity would be preferable. However, if, for an example, 20% of the tested population had antibodies, we estimate that around 1 in 20 positive results on the most specific device would be incorrect.

Objective To assess the accuracy of the AbC-19 Rapid Test lateral flow immunoassay for the detection of previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Design Test accuracy study. Setting Laboratory based evaluation. Participants 2847 key workers (healthcare staff, fire and rescue officers, and police officers) in England in June 2020 (268 with a previous polymerase chain reaction (PCR) positive result (median 63 days previously), 2579 with unknown previous infection status); and 1995 pre-pandemic blood donors. Main outcome measures AbC-19 sensitivity and specificity, estimated using known negative (pre-pandemic) and known positive (PCR confirmed) samples as reference standards and secondly using the Roche Elecsys anti-nucleoprotein assay, a highly sensitive laboratory immunoassay, as a reference standard in samples from key workers. Results Test result bands were often weak, with positive/negative discordance by three trained laboratory staff for 3.9% of devices. Using consensus readings, for known positive and negative samples sensitivity was 92.5% (95% confidence interval 88.8% to 95.1%) and specificity was 97.9% (97.2% to 98.4%). Using an immunoassay reference standard, sensitivity was 94.2% (90.7% to 96.5%) among PCR confirmed cases but 84.7% (80.6% to 88.1%) among other people with antibodies. This is consistent with AbC-19 being more sensitive when antibody concentrations are higher, as people with PCR confirmation tended to have more severe disease whereas only 62% (218/354) of seropositive participants had had symptoms. If 1 million key workers were tested with AbC-19 and 10% had actually been previously infected, 84 700 true positive and 18 900 false positive results would be projected. The probability that a positive result was correct would be 81.7% (76.8% to 85.8%). Conclusions AbC-19 sensitivity was lower among unselected populations than among PCR confirmed cases of SARS-CoV-2, highlighting the scope for overestimation of assay performance in studies involving only PCR confirmed cases, owing to “spectrum bias.” Assuming that 10% of the tested population have had SARS-CoV-2 infection, around one in five key workers testing positive with AbC-19 would be false positives. Study registration ISRCTN 56609224.