Agreement Between Self‐Reported COVID‐19 and Dried Blood Spot Serology: A Cross‐Sectional Study

Background and Aims Identifying COVID‐19 cases with high accuracy is essential for epidemiological research on the pandemic's health effects. We aimed to investigate the agreement between a validated self‐report questionnaire for COVID‐19 and dried blood spot serology for SARS‐CoV‐2 antibodies. Methods We conducted a cross‐sectional analysis of combined survey and SARS‐CoV‐2 antibody data. Between June and October 2023, 311 adults completed a validated self‐report COVID‐19 questionnaire and provided fingertip blood samples, which underwent Enzyme Linked Immunosorbent Assay to quantify IgG antibodies to SARS‐CoV‐2 nucleocapsid (N)‐proteins. We applied several statistical approaches to assess agreement: Cohen's κ of inter‐rater reliability; positive (PPV) and negative (NPV) predictive values; and logistic and linear regressions of the year of most recent self‐reported COVID‐19 on serostatus and N‐protein antibody concentrations. Results Two‐thirds (203, 65%) of participants self‐reported a history of COVID‐19 whereas one‐third (98, 32%) were seropositive for SARS‐CoV‐2 N‐protein antibodies, reflecting only “fair” agreement (κ = 0.23 [95% CI 0.15–0.31]). Self‐reported COVID‐19 had a PPV of 41% and an NPV of 87% for SARS‐CoV‐2 seropositivity. PPV was low for those whose most recent self‐reported cases were in 2020–21 (36%) and 2022 (33%), but higher for 2023 (75%). Compared to participants with no self‐reported history of COVID‐19, those reporting SARS‐CoV‐2 infection in 2023 had 23 times greater odds of being seropositive (95% CI: 9.18–62.5) and had 1078% (617–1836%) higher N‐protein concentrations, after adjustment for confounders. Conclusion While overall agreement self‐reported COVID‐19 and serostatus is only fair, there was a strong relationship exhibited between the two for recent self‐reported cases, when serology is most accurate. This suggests that self‐reported COVID‐19 is reasonably accurate for identifying people who have previously had COVID‐19 as well as determining roughly when infections occurred.