Statistical methods
DISEASE, RECRUITMENT
A Statistical Analysis Plan was written before the analysis was performed and is available in Supplemental Material. We calculated the prevalence of positive RT-PCR results, and the sensitivity, specificity and predictive values for each index test alongside exact 95% confidence intervals. Index test results were presented graphically in relation to the RT-PCR cycle threshold. Prespecified subgroup analyses split results by participant characteristics including age, sex, ethnicity, spectrum of disease, recruitment method and recruiting practice. We also performed a post-hoc analysis of diagnostic performance against time since symptom onset. We summarised recruitment rates, variation in disease prevalence over time, and baseline characteristics and symptom progression using appropriate summary statistics and graphs, with the number of participants with missing data reported separately.We used two methods to allow for imperfect reference standard bias. Firstly, for individuals with discordant results between either index test and the reference standard, we created an enhanced composite reference standard using a combination of antibody testing results, additional RT-PCR test results, and linked hospitalisation and mortality records [To allow for discrepancies between recorded recruitment date and recorded swab dates from some participants, two sensitivity analyses were performed: firstly, a stricter scenario excluding all individuals for whom these dates did not match exactly, and secondly, a less strict scenario in which date discrepancies of up to a week were allowed (as discrepancies may have reflected date recording errors).Statistical analysis was performed using RStudio 2022.02.3 including the epiR package [