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Review 1: "Seroprevalence of SARS-COV-2 Antibodies in Scottish Healthcare Workers"

This study reports a greater seroprevalence for antibodies among healthcare workers compared to the general population. Reviewers mentioned concerns over selection of the general population, response bias, and adjusting for potential cross-reactivity with other coronaviruses.

Published onDec 17, 2020
Review 1: "Seroprevalence of SARS-COV-2 Antibodies in Scottish Healthcare Workers"
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key-enterThis Pub is a Review of
Seroprevalence of SARS-COV-2 Antibodies in Scottish Healthcare Workers
Description

Abstract Introduction Healthcare workers are believed to be at increased risk of SARS-CoV-2 infection. The extent of that increased risk compared to the general population and the groups most at risk have not been extensively studied.Methods A prospective observational study of health and social care workers in NHS Tayside (Scotland, UK) from May to September 2020. The Siemens SARS-CoV-2 total antibody assay was used to establish seroprevalence in this cohort. Patients provided clinical information including demographics and workplace information. Controls, matched for age and sex to the general Tayside population, were studied for comparison.Results A total of 2062 health and social care workers were recruited for this study. The participants were predominantly female (81.7%) and 95.2% were white. 299 healthcare workers had a positive antibody test (14.5%). 11 out of 231 control sera tested positive (4.8%). Healthcare workers therefore had an increased likelihood of a positive test (odds ratio 3.4 95% CI 1.85-6.16, p<0.0001). Dentists, healthcare assistants and porters were the job roles most likely to test positive. Those working in front-line roles with COVID-19 patients were more likely to test positive (17.4% vs. 13.4%, p=0.02). 97.1% of patients who had previously tested positive for SARS-CoV-2 by RT-PCR had positive antibodies, compared to 11.8% of individuals with a symptomatic illness who had tested negative. Anosmia was the symptom most associated with the presence of detectable antibodies.Conclusion In this study, healthcare workers were three times more likely to test positive for SARS-CoV-2 than the general population. The seroprevalence data in different populations identified in this study will be useful to protect healthcare staff during future waves of the pandemic.

RR:C19 Evidence Scale rating by reviewer:

  • Potentially informative. The main claims made are not strongly justified by the methods and data, but may yield some insight. The results and conclusions of the study may resemble those from the hypothetical ideal study, but there is substantial room for doubt. Decision-makers should consider this evidence only with a thorough understanding of its weaknesses, alongside other evidence and theory. Decision-makers should not consider this actionable, unless the weaknesses are clearly understood and there is other theory and evidence to further support it.

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Review:

The Authors compare SARS-CoV-2 antibody prevalence of health care workers (HCWs) to that of a general population. They report an over 3-fold greater seroprevalence among HCWs. In addition, they find that several persons testing positive for antibodies showed an earlier negative RT-PCR test result.

Below I list my suggestions for improving the manuscript. 

1.    Assess extent of potential HCW response bias

Recruitment of HCWs with knowledge that they would receive an antibody test likely biases the sample towards persons who think they would test positive. This is an important limitation, but one that could be alleviated somewhat if the Authors give the readers a sense of the potential magnitude of this response bias. (i.) Response rates to the survey, (ii.) sociodemographics of non-respondents, and (iii.) RT-PCR data on non- respondent HCWs would assist with assessment of this potential bias. 

2.    Describe in more detail the selection of the control (comparison) population

 The Authors devote scant text to describing the comparison (i.e., non-HCW) population. Also, when they do, they note “randomly selected” but then describe age- and sex- matching. These procedures are inconsistent with each other. How were the clinic- based blood samples retrieved? Would anyone argue that persons getting surgery at NHS Tayside are representative of the broader Scottish population?

Also, if age- and sex- matching were performed, conditional regression models (rather than unconditional logistic regression models) would seem appropriate. Furthermore, the Authors introduce a second control population with even less description (Scottish surveillance data), which makes it very challenging to interpret any odds ratio.

3.    Figure 2: compares OR only within HCWs?

Figure 2 appears to compare SARS-CoV-2 antibody positivity by symptom (yes/no), among only HCWs, since I do not believe that the Authors have symptom data on comparison populations. If this is the case, I am unclear of the utility of p-values for hypotheses that were not stated a priori. At a minimum, for this exploration (and for the exploration about HCW type) I would include a false discovery rate correction for multiple testing. 

Minor points:

•       Data are plural. So Data were analyzed, not “Data was analyzed.”

•       Prevalence is a proportion, not a rate. Avoid the term “seroprevalence rate.”

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