Identification of undetected SARS-CoV-2 infections by clustering of Nucleocapsid antibody trajectories

During the COVID-19 pandemic, numerous SARS-CoV-2 infections remained undetected. Serological testing could potentially aid their identification. We combined results from routine monthly nose and throat swabs, and self-reported positive swab tests, from a UK household survey, linked to national swab testing programme data from England and Wales, together with Nucleocapsid (N-) antibody trajectories clustered using a longitudinal variation of K-means to estimate the number of infections undetected by either approach (N=185,646). After combining N-antibody (hypothetical) infections with swab-positivity, we estimated that 7.4% of all true infections would have remained undetected, 25.8% by swab-positivity-only and 28.6% by trajectory-based N-antibody classifications only. Congruence with swab-positivity was much poorer using a fixed threshold to define N-antibody infections. Additionally, using multivariable logistic regression N-antibody seroconversion was more likely as age increased between 30 and 60 years, in non-white participants, those less (recently/frequently) vaccinated, for lower Ct values in the range above 30, in symptomatic and Delta (vs BA.1) infections. Comparing swab-positivity data sources showed that routine monthly swabs were not sufficient to detect infections by swab-positivity only and incorporating national testing programme/self-reported data substantially increased detection rates. Overall, whilst N-antibody serosurveillance can identify infections undetected by swab-positivity, optimal use requires trajectory-based analysis.