Evidence map›Paper›PMID 41970415›Full record

ArticleHealth science reports2026

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

Nicola Sheppard, Matthew T C Carroll, Brigitte M Borg, Zheng Quan Toh, Paul V Licciardi, Catherine L Smith, Jillian F Ikin, Michael J Abramson, Karen Walker-Bone, Tyler J Lane

Abstract read
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Article in Health science reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Nicola SheppardSchool of Public Health and Preventive Medicine Monash University Melbourne Victoria Australia.
Matthew T C CarrollMonash Rural Health Churchill Monash University Churchill Victoria Australia.
Brigitte M BorgSchool of Public Health and Preventive Medicine Monash University Melbourne Victoria Australia.
Zheng Quan TohInfection, Immunity and Global Health Theme Murdoch Children's Research Institute Parkville Victoria Australia.ORCID https://orcid.org/0000-0002-0282-5837
Paul V LicciardiInfection, Immunity and Global Health Theme Murdoch Children's Research Institute Parkville Victoria Australia.
Catherine L SmithSchool of Public Health and Preventive Medicine Monash University Melbourne Victoria Australia.
Jillian F IkinSchool of Public Health and Preventive Medicine Monash University Melbourne Victoria Australia.
Michael J AbramsonSchool of Public Health and Preventive Medicine Monash University Melbourne Victoria Australia.
Karen Walker-BoneSchool of Public Health and Preventive Medicine Monash University Melbourne Victoria Australia.
Tyler J LaneSchool of Public Health and Preventive Medicine Monash University Melbourne Victoria Australia.ORCID https://orcid.org/0000-0001-6089-1827

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Identifiers

PMID41970415
PMCPMC13062492

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