Test performance evaluation of SARS-CoV-2 serological assays

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Abstract

Background:

Serological tests are crucial tools for assessments of SARS-CoV-2 exposure, infection and potential immunity. Their appropriate use and interpretation require accurate assay performance data.

Method:

We conducted an evaluation of 10 lateral flow assays (LFAs) and two ELISAs to detect anti-SARS-CoV-2 antibodies. The specimen set comprised 128 plasma or serum samples from 79 symptomatic SARS-CoV-2 RT-PCR-positive individuals; 108 pre-COVID-19 negative controls; and 52 recent samples from individuals who underwent respiratory viral testing but were not diagnosed with Coronavirus Disease 2019 (COVID-19). Samples were blinded and LFA results were interpreted by two independent readers, using a standardized intensity scoring system.

Results:

Among specimens from SARS-CoV-2 RT-PCR-positive individuals, the percent seropositive increased with time interval, peaking at 81.8–100.0% in samples taken >20 days after symptom onset. Test specificity ranged from 84.3–100.0% in pre-COVID-19 specimens. Specificity was higher when weak LFA bands were considered negative, but this decreased sensitivity. IgM detection was more variable than IgG, and detection was highest when IgM and IgG results were combined. Agreement between ELISAs and LFAs ranged from 75.7–94.8%. No consistent cross-reactivity was observed.

Conclusion:

Our evaluation showed heterogeneous assay performance. Reader training is key to reliable LFA performance, and can be tailored for survey goals. Informed use of serology will require evaluations covering the full spectrum of SARS-CoV-2 infections, from asymptomatic and mild infection to severe disease, and later convalescence. Well-designed studies to elucidate the mechanisms and serological correlates of protective immunity will be crucial to guide rational clinical and public health policies.

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Most cited references 20

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Virological assessment of hospitalized patients with COVID-2019

Roman Wölfel, Victor M Corman, Wolfgang Guggemos … (2020)

Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in late 20191,2. Initial outbreaks in China involved 13.8% of cases with severe courses, and 6.1% of cases with critical courses3. This severe presentation may result from the virus using a virus receptor that is expressed predominantly in the lung2,4; the same receptor tropism is thought to have determined the pathogenicity-but also aided in the control-of severe acute respiratory syndrome (SARS) in 20035. However, there are reports of cases of COVID-19 in which the patient shows mild upper respiratory tract symptoms, which suggests the potential for pre- or oligosymptomatic transmission6-8. There is an urgent need for information on virus replication, immunity and infectivity in specific sites of the body. Here we report a detailed virological analysis of nine cases of COVID-19 that provides proof of active virus replication in tissues of the upper respiratory tract. Pharyngeal virus shedding was very high during the first week of symptoms, with a peak at 7.11 × 108 RNA copies per throat swab on day 4. Infectious virus was readily isolated from samples derived from the throat or lung, but not from stool samples-in spite of high concentrations of virus RNA. Blood and urine samples never yielded virus. Active replication in the throat was confirmed by the presence of viral replicative RNA intermediates in the throat samples. We consistently detected sequence-distinct virus populations in throat and lung samples from one patient, proving independent replication. The shedding of viral RNA from sputum outlasted the end of symptoms. Seroconversion occurred after 7 days in 50% of patients (and by day 14 in all patients), but was not followed by a rapid decline in viral load. COVID-19 can present as a mild illness of the upper respiratory tract. The confirmation of active virus replication in the upper respiratory tract has implications for the containment of COVID-19.

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Temporal dynamics in viral shedding and transmissibility of COVID-19

Xi. He, Eric Lau, Peng Wu … (2020)

We report temporal patterns of viral shedding in 94 patients with laboratory-confirmed COVID-19 and modeled COVID-19 infectiousness profiles from a separate sample of 77 infector-infectee transmission pairs. We observed the highest viral load in throat swabs at the time of symptom onset, and inferred that infectiousness peaked on or before symptom onset. We estimated that 44% (95% confidence interval, 25-69%) of secondary cases were infected during the index cases' presymptomatic stage, in settings with substantial household clustering, active case finding and quarantine outside the home. Disease control measures should be adjusted to account for probable substantial presymptomatic transmission.

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Presumed Asymptomatic Carrier Transmission of COVID-19

Yan Bai, Lingsheng Yao, Tao Wei … (2020)

This study describes possible transmission of novel coronavirus disease 2019 (COVID-19) from an asymptomatic Wuhan resident to 5 family members in Anyang, a Chinese city in the neighboring province of Hubei.

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Author and article information

Journal

Journal ID (nlm-ta): medRxiv

Journal ID (publisher-id): MEDRXIV

Title: medRxiv

Publisher: Cold Spring Harbor Laboratory

Publication date (Electronic): 17 May 2020

Electronic Location Identifier: 2020.04.25.20074856

Affiliations

[1. ]Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA 94143, USA

[2. ]Medical Scientist Training Program, University of California, San Francisco, CA 94143, USA

[3. ]Biomedical Sciences Graduate Program, University of California, San Francisco, CA 94143, USA

[4. ]J. David Gladstone Institutes, San Francisco, CA 94158, USA

[5. ]Department of Microbiology and Immunology, University of California, San Francisco, CA 94143, USA

[6. ]Innovative Genomics Institute, University of California, Berkeley, CA 94720, USA

[7. ]Diabetes Center, University of California, San Francisco, San Francisco, CA 94143, USA

[8. ]Howard Hughes Medical Institute, University of California, San Francisco

[9. ]Department of Medicine, Division of Infectious Diseases, University of California, San Francisco, San Francisco, CA 94143, USA

[10. ]Department of Surgery, University of California, San Francisco, CA 94143, USA

[11. ]Department of Medicine, University of California, San Francisco, San Francisco, CA 94143, USA

[12. ]Department of Neurology, University of California, San Francisco, CA 94158, USA

[13. ]Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94158, USA

[14. ]Department of Dermatology, University of California, San Francisco, San Francisco, CA 94158, USA

[15. ]Program in Quantitative Biology, University of California, San Francisco, San Francisco, CA 94158, USA

[16. ]School of Medicine, University of California, San Francisco, San Francisco, CA 94158, USA

[17. ]Department of Pathology, University of California, San Francisco, San Francisco, CA, 94158, USA

[18. ]Division of Experimental Medicine, Department of Medicine, University of California San Francisco, San Francisco CA, USA

[19. ]Infectious Diseases and Immunity Graduate Group, University of California Berkeley, Berkeley, CA, USA

[20. ]Department of Bioengineering, University of California, Berkeley, Berkeley CA 94720 USA

[21. ]Department of Integrative Biology, University of California, Berkeley, Berkeley CA 94720 USA

[22. ]Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, CA

[23. ]Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA 94158, USA

[24. ]UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA

[25. ]Scientific Affairs, American Red Cross, Gaithersburg, MD

[26. ]Department of Anesthesia and Perioperative Care, University of California, San Francisco, San Francisco, CA 94158

[27. ]Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, CA 94158

[28. ]Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA

[29. ]Chan Zuckerberg Biohub, San Francisco, CA, USA

[30. ]Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA

[31. ]Division of Rheumatology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA

[32. ]Institute of Computational Health Sciences, University of California, San Francisco, San Francisco, CA, USA

[33. ]Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA

[34. ]Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA 94158, USA

[35. ]Quantitative Biosciences Institute, University of California, San Francisco, CA 94158, USA

[36. ]Department of Pathology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA

[37. ]Division of Infectious Diseases, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA

Author notes

[*]

Co-first author

[**]

Co-corresponding author

Correspondence to: Alexander Marson, M.D., Ph.D. alexander.marson@ 123456ucsf.edu , Patrick Hsu, Ph.D. pdhsu@ 123456berkeley.edu , Caryn Bern, M.D., M.P.H. caryn.bern2@ 123456ucsf.edu

Article

DOI: 10.1101/2020.04.25.20074856

PMC ID: 7273265

PubMed ID: 32511497

SO-VID: 3ab47e51-3ce4-4686-acfb-66d09f62eeb5

License:

It is made available under a CC-BY-NC-ND 4.0 International license.

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Test performance evaluation of SARS-CoV-2 serological assays

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Abstract

Background:

Method:

Results:

Conclusion:

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 20

Virological assessment of hospitalized patients with COVID-2019

Temporal dynamics in viral shedding and transmissibility of COVID-19

Presumed Asymptomatic Carrier Transmission of COVID-19

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Cited by 88

Most referenced authors 1,288