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Research Article
Revised

The relative incidence of COVID-19 in healthcare workers versus non-healthcare workers: evidence from a web-based survey of Facebook users in the United States

[version 2; peer review: 2 approved, 1 approved with reservations]
PUBLISHED 20 Jul 2021
Author details Author details

This article is included in the Coronavirus (COVID-19) collection.

Abstract

Background: Healthcare workers are at the forefront of the COVID-19 pandemic and it is essential to monitor the relative incidence rate of this group, as compared to workers in other occupations. This study aimed to produce estimates of the relative incidence ratio between healthcare workers and workers in non-healthcare occupations.
Methods: Analysis of cross-sectional data from a daily, web-based survey of 1,822,662 Facebook users from September 8, 2020 to October 20, 2020. Participants were Facebook users in the United States aged 18 and above who were tested for COVID-19 because of an employer or school requirement in the past 14 days. The exposure variable was a self-reported history of working in healthcare in the past four weeks and the main outcome was a self-reported positive test for COVID-19.
Results: On October 20, 2020, in the United States, there was a relative COVID-19 incidence ratio of 0.73 (95% UI 0.68 to 0.80) between healthcare workers and workers in non-healthcare occupations.
Conclusions: In fall of 2020, in the United States, healthcare workers likely had a lower COVID-19 incidence rate than workers in non-healthcare occupations.

Keywords

COVID-19, healthcare workers

Revised Amendments from Version 1

In this update, we have corrected two issues in our data analysis, resulting in a substantial change to one sensitivity analysis and minor changes to other results.  We have also substantially moderated the discussion to ensure we keep readers aware of the limitations of our approach and do not over-state the implications our findings.

See the authors' detailed response to the review by Alex Reinhart
See the authors' detailed response to the review by Devan Hawkins and Marcy Goldstein-Gelb
See the authors' detailed response to the review by Tim Driscoll

Introduction

In August, the Peterson-KFF Health System Tracker published a collection of charts showing how healthcare utilization has declined during the COVID-19 pandemic in the United States1, showing that facility discharge volume dropped by over 25% and cancer screening volumes dropped by over 85% from levels in 2019. This decrease is consistent with evidence from other sources2,3, and could be driven by a perceived risk of interacting with workers at health facilities. It is yet to be seen how much this delayed and foregone care will reduce population health. Meanwhile, a Wall Street Journal analysis of Centers for Disease Control and Prevention (CDC) data found that at least 7,400 COVID-19 infections were transmitted in US hospitals in 20204. Access to adequate resources for infection prevention among health care workers (HCWs) remains a topic of urgent importance5.

The existing evidence quantifying the relative COVID-19 incidence rate among HCWs as compared to workers in non-healthcare occupations (non-HCWs) has focused on the first wave of the pandemic, and found that HCWs are at higher risk of COVID69. We hypothesized that by fall of 2020 there was not a substantially elevated rate of COVID-19 infection among HCWs and that HCWs might even have lower incidence rate than non-HCWs, and we analyzed data from a large survey of Facebook users to investigate.

Methods

Study design

We analyzed individual participant data from a large, web-based survey of Facebook users aged 18 and above in the United States (around 300,000 respondents per week). Every day Facebook offered a random sample of US-based users a Qualtrics survey run by the Delphi lab at Carnegie Mellon University who made it rapidly available to other academic researchers10,11. Facebook also provided survey weights to adjust for non-response probability and to match the age and sex distribution at the national level12,13. This sort of survey data has been used previously to perform population based analyses related to COVID-19, though never before at such large scale14,15. Our analysis relied on the responses to two lines of questions: (1) questions about recent work history, worded as, “In the past 4 weeks, did you do any kind of work for pay?” and if so, “[p]lease select the occupational group that best fits the main kind of work you were doing in the last four weeks”; and (2) questions about COVID-19 testing history, worded as, “Have you ever been tested for coronavirus (COVID-19)?”, “[h]ave you been tested for coronavirus (COVID-19) in the last 14 days?”, “[d]id this test find that you had coronavirus (COVID-19)”, and “[d]o any of the following reasons describe why you were tested for coronavirus (COVID-19) in the last 14 days? Please select all that apply.”

We analyzed the six weeks of data from September 8, 2020 to October 20, 2020, which provided more than 80% power to detect a 30% difference between COVID-19 incidence in HCWs and non-HCWs.

Variables

To quantify the relative risk of COVID-19 among healthcare workers (HCWs) versus workers in non-healthcare occupations (non-HCWs), we used the response to the occupational group question as our exposure variable (we coded respondents who selected option “Healthcare practitioners and technicians” or “Healthcare support” as HCWs, and all others, including those with a missing value, as non-HCWs). We identified individuals with COVID-19 as those who reported that they had tested positive for COVID-19 in the last 14 days.

Statistical methods

We calculated the endorsement rate of positive COVID-19 test (ER) for the HCW and non-HCW population as the survey-weighted percent of respondents in either group who reported COVID-19, and calculated the relative COVID-19 incidence ratio (RR) with the equation

   RR = (ER among HCWs) / (ER among non-HCWs).

We quantified the uncertainty in this ratio using non-parametric bootstrap resampling to obtain a 95% uncertainty interval16. To control for confounding due to differential access to COVID-19 testing, we restricted our analysis to only HCWs and non-HCWs who were tested in the last 14 days because their employer or school required it.

As sensitivity analyses, we considered also alternative inclusion criteria and more restrictive subsets of HCWs. The survey provided survey weights that adjust for non-response bias, which we used in our main analysis. However, these weights were designed to represent the national population, and therefore might not represent the HCW population as accurately. As a sensitivity analysis, we repeated our calculation using the unweighted data. To investigate the possibility that workplace testing practices differ between HCW and non-HCW occupational settings, we also repeated our analysis with additional filtering based on the “why you were tested” question. In the main result we used the subset of individuals who responded that they were tested in the last 14 days because of employer/educational requirements, and this question has a “select all that apply” answer type, and also includes “I felt sick” as an option. As a sensitivity analysis, we used only those individuals who were tested because of a workplace requirement and did not feel sick.

Ethical statement

These research activities used no identifiable private information and were therefore exempt from institutional board review.

Results

The survey data contained 43,430 respondents who were tested due to workplace requirements in the time period we focused on, 14,660 HCWs and 28,770 non-HCWs (see Table 1 for demographic details). There were 2,145 respondents who reported a positive test for COVID-19 in the last 14 days (588 among HCWs and 1,557 among non-HCWs).

Table 1. Characteristics of survey respondents.

Non- healthcare workersHealthcare workers
n(%)n(%)
Total 1,699,214100.0123,448100.0
Tested in last 14 days 133,5337.922,59418.3
Test required by work or school 28,7701.714,66011.9
Among those with required test
Male gender 9,30332.32,10614.4
Age in years
18 to 24 3,59512.58185.6
25 to 34 4,99417.32,54417.4
35 to 44 5,14617.93,25522.2
45 to 54 5,17918.03,58724.5
55 to 64 4,22714.73,34522.8
65 to 74 1,3074.59766.7
75 and older 5031.71210.8

Among HCWs with a required test, 588 of 14,660 (4.0%) reported a positive test in the last 14 days, while among non-HCWs with a required test, 1,557 of 28,770 (5.4%) reported a positive test, for a relative COVID-19 incidence ratio of 0.73 (95% UI 0.68 to 0.80) (Table 2).

Table 2. Relative COVID-19 incidence rate (RR) and counts of healthcare workers and non-healthcare workers and their crude counts and rates.

Healthcare workersNon-healthcare workers
TestedPositive%TestedPositive%RR95% UI
14,6605884.028,7701,5575.40.730.68 to 0.80

Our power calculation simulation results showed that 7,000 simulants provide 80% power to reject a null hypothesis that HCWs and non-HCWs have the same RR if, in truth, the RR is 0.7. Since the survey currently collects a weekly volume of around 7,000 individuals who report taking a required COVID-19 test, the simulation results imply that six weeks of data will provide more than sufficient power.

Sensitivity analyses

When we repeated our calculation using the unweighted survey responses to calculate the COVID-19 incidence ratio, we found nearly identical relative incidence ratio of 0.74 (95% UI 0.69 to 0.79).

When we repeated our analysis restricted to only specific subtypes of HCWs, as afforded by the questionnaire, we found a range of risks, usually less than 1.0, with substantially less certainty due to small sample sizes (Table 3).

Table 3. Relative COVID-19 incidence rate (RR) and counts of healthcare workers (HCWs) and non-healthcare workers stratified by worker subtype.

HCW subtypeNumber of non-
subtype HCWs
Number of
subtype HCWs
Relative
risk
Lower
bound
Upper
bound
All HCWs 28,770 14,660 0.730.690.80
Physician or surgeon 43,139 291 2.711.863.60
Registered nurse (including nurse
practitioner)
40,262 3,168 0.660.620.82
Licensed practical or licensed
vocational nurse
41,318 2,112 0.730.600.86
Physician assistant 43,274 156 0.630.331.13
Dentist 43,392 38 0.850.242.22
Any other treating practitioner 43,046 384 0.560.310.81
Pharmacist 43,345 85 0.280.080.72
Any therapist 42,165 1,265 0.510.370.63
Any health technologist or technician 41,841 1,589 1.010.791.17
Veterinarian 43,395 35 0.290.001.28
Nursing assistant or psychiatric aide 41,812 1,618 1.020.801.22
Home health or personal care aide 42,847 583 0.770.521.00
Occupational or physical therapy
assistant or aide
43,350 80 1.470.802.31
Massage therapist 43,426 4 10.160.0013.21
Dental assistant 43,412 18 0.000.000.00
Medical assistant 43,280 150 1.250.641.96
Medical transcriptionist 43,402 28 0.560.001.38
Pharmacy aide 43,413 17 0.000.000.00
Phlebotomist 43,397 33 2.750.634.06
Veterinary assistant 43,422 8 1.740.006.97
Any other healthcare support worker 41,104 2,326 0.550.460.66

When we used only those individuals who were tested because of a workplace requirement and did not feel sick, we obtained a relative risk closer to 1.0. Using only those tested because of a workplace requirement who also did feel sick we still obtained a relative risk substantially smaller than 1.0 (Table 4). Although this finding could suggest that differences in testing patterns between healthcare and other work settings are partially responsible for the different positivity rates among HCWs and non-HCWs, it could also be driven by greater access to COVID-19 testing for confirmation of illness among HCWs experiencing symptoms. The recall period of 14 days provides ample time for an individual to receive a workplace test without symptoms, then develop symptoms, and then receive another test to determine if the symptoms are due to COVID-19, and HCWs might have more opportunity to access such a follow-up test, since they are visiting a healthcare setting for work already.

Table 4. Relative COVID-19 incidence rate (RR) and counts of healthcare workers and non-healthcare workers stratified by those who reported they felt/did not feel sick as an additional reason for getting tested.

Number of
non-HCWs
Number
of HCWs
Relative
risk
Lower
bound
Upper
bound
Test required, did not feel sick 25,236 13,6101.091.011.27
Test required, felt sick 3,534 1,0500.800.690.92

Discussion

This study utilized a population-based approach to examine the relative risk of COVID-19 infection among HCW compared with non-HCW. We founda relative COVID-19 incidence ratio substantially and significantly less than 1.0, which can be cautiously interpreted as a positive result, indicating that infection control measures being taken by HCWs in Fall of 2020 were effective.

Our findings are consistent with the limited other evidence available on the risk of COVID-19 in healthcare facility settings1720, although also contrast with evidence from prior research that has found that HCWs are at higher risk of COVID69. This outbreak and our understanding of it have both changed rapidly in the past, and may do so again, so we will continue to update this information.

Limitations

This work has at least three limitations. First, our results are based on self-reported data from a sample of Facebook users and therefore subject to both recall bias and social desirability bias, and may not be representative of the general population or the HCW population. The questions we relied on did not seem particularly at risk for these biases, although the question “have you been tested for COVID-19 in the last 14 days?” likely included positive responses from individuals who received seroprevalence testing as well as PCR testing, which could also introduce a small amount of bias; using this 14-day recall period as a proxy for incidence of COVID-19 could also introduce a small amount of bias. The impact of nonresponse bias is harder to gauge, however; our sensitivity analysis shows that the survey weights do influence our results. Second, our approach required a large sample size to obtain a sufficiently precise estimate of RR, but this seems safer than including respondents who did not report receiving a required test, as that could introduce confounding. Third, it is possible that there was still uncontrolled confounding due to differential access to tests between HCWs and non-HCWs. Our sensitivity analysis found substantively similar results when restricted only to individuals who had workplace testing when they did not feel sick, but since we have only considered respondents with tests required by their employer or school, this might focus on non-HCW setting with better-than-average infection control policies (for example, they are doing asymptomatic testing) and therefore the relative risk for HCWs might be even lower than our method estimated.

Conclusion

In October, 2020, in the United States the relative infection ratio of HCWs to non-HCWs was lower than 1.0. Infection control remains essential and HCWs must continue to be protected as the COVID-19 pandemic continues, to ensure safety to themselves, their co-workers, and their patients.

Data availability

Underlying data

The underlying data used in this study are available to academic researchers for research purposes from Facebook at: https://www.facebook.com/research-operations/rfp/?title=covid19-symptom-survey-data-access. Conditions of access and instructions for applications can be found at https://dataforgood.fb.com/docs/covid-19-symptom-survey-request-for-data-access/.

Code availability

Reproducibility code available from: https://github.com/aflaxman/covid_hcw_rr

Archived code at time of resubmission: https://doi.org/10.5281/zenodo.427036721.

License: GNU General Public License v3.0

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Version 2
VERSION 2 PUBLISHED 27 Nov 2020
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Flaxman AD, Henning DJ and Duber HC. The relative incidence of COVID-19 in healthcare workers versus non-healthcare workers: evidence from a web-based survey of Facebook users in the United States [version 2; peer review: 2 approved, 1 approved with reservations]. Gates Open Res 2021, 4:174 (https://doi.org/10.12688/gatesopenres.13202.2)
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Comments on this article Comments (0)

Version 2
VERSION 2 PUBLISHED 27 Nov 2020
Comment
Alongside their report, reviewers assign a status to the article:
Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

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