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Introduction
As of July 22, 2020, more than 15 million cases of COVID-19 have been documented worldwide, with nearly 618 000 deaths.
In the UK and the USA, Black, Asian, and minority ethnic communities have been disproportionately affected.
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With ongoing community transmission from asymptomatic individuals, disease burden is expected to rise. As a result, there will be an ongoing need for front-line health-care workers in patient-facing roles. Because this work requires close personal exposure to patients with SARS-CoV-2, front-line health-care workers are at high risk of infection, contributing to further spread.
Initial estimates suggest that front-line health-care workers could account for 10–20% of all diagnoses,
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with some early evidence that people from Black, Asian, and minority ethnic backgrounds are at higher risk.
Guidelines from the UK and the USA recommend mask use for health-care workers caring for people with COVID-19.
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However, global shortages of masks, respirators, face shields, and gowns, caused by surging demand and supply chain disruptions, have led to efforts to conserve PPE through extended use or reuse, and disinfection protocols have been developed, for which scientific consensus on best practice is scarce.
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Evidence before this study
We searched PubMed for articles published between Jan 1 and June 30, 2020, with the terms “covid-19”, “healthcare workers”, and “personal protective equipment”. We did not restrict our search by language or type of publication. The prolonged course of the COVID-19 pandemic, coupled with sustained challenges supplying adequate personal protective equipment (PPE) for front-line health-care workers, have strained global health-care systems in an unprecedented fashion. Despite growing awareness of this problem, there are few studies to inform policy makers on the risk of COVID-19 among health-care workers and the effect of PPE on disease burden. Previous reports of infections in health-care workers are based on cross-sectional data with limited information on individual-level risk factors. Our PubMed search yielded no population-scale investigations.
Added value of this study
We did a prospective observational study of 2 135 190 individuals, comprised of front-line health-care workers and the general community who were voluntary users of the COVID Symptom Study smartphone application (app). From self-reported data obtained via this app, we found that front-line health-care workers had at least a threefold increased risk of COVID-19. Compared with front-line health-care workers who reported adequate availability of PPE, those with inadequate PPE had an increase in risk. However, adequate availability of PPE did not seem to completely reduce risk among health-care workers caring for patients with COVID-19. We also found that Black, Asian, and minority ethnic health-care workers might be disproportionately affected.
Implications of all the available evidence
Front-line health-care workers, particularly those who are from Black, Asian, and minority ethnic backgrounds, could be at substantially greater risk of COVID-19. Health-care systems should ensure adequate availability of PPE and develop additional strategies to protect health-care workers from COVID-19.
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data to inform such efforts are scarce, and particularly so among Black, Asian, and minority ethnic communities. Thus, we did a prospective population-based study using data from a smartphone-based application (app) to investigate the risk of testing positive for COVID-19, the risk of developing symptoms associated with SARS-CoV-2 infection, or both, among individuals in the UK and the USA.
Methods
Study design and participants
COVID Symptom Study (previously known as COVID Symptom Tracker) is a free smartphone app developed by Zoe Global (London, UK) in collaboration with Massachusetts General Hospital (Boston, MA, USA) and King’s College London (London, UK). It offers participants a guided interface to report baseline demographic information and comorbidities, daily information on symptoms, and COVID-19 testing. Participants are encouraged to log daily, even when asymptomatic, for longitudinal collection of incident symptoms and COVID-19 testing results. The app was launched in the UK on March 24, 2020, and the USA on March 29, 2020.
Procedures
Briefly, on first use, participants were asked to provide demographic factors and were questioned separately about a series of COVID-19 risk factors (appendix pp 4–8). At enrolment and with daily reminders, participants were asked if they felt physically normal, and if they reported not feeling well they were asked about their symptoms (appendix p 11). Participants were also asked if they had been tested for COVID-19 and the results (none, negative, pending, or positive). Our primary outcome was a report of a positive COVID-19 test. Follow-up started when participants first reported on the COVID Symptom Study app and continued until a report of a positive COVID-19 test or the time of last data entry, whichever occurred first.
Participants were also asked if they worked in health care and, if yes, whether they had direct patient contact. For our primary analysis, we defined front-line health-care workers as participants who reported direct patient contact. Prespecified secondary analyses among front-line health-care workers investigated PPE availability and contact with patients with COVID-19, as well as the primary site of clinical practice. A post-hoc analysis among front-line health-care workers assessed the effect of race and ethnicity. Beginning March 29, 2020, in an updated version of the app used by 84% of participating health-care workers, we included mandatory questions about availability of PPE for participants who identified as a front-line health-care worker. Among these individuals, we asked whether they cared for patients with suspected or documented SARS-CoV-2 infection and the frequency with which they used PPE (always, sometimes, or never). We asked if they had enough PPE when needed, if they had to reuse PPE, or if they did not have enough because of shortages. We classified PPE as adequate if they never required PPE or if they reported always having the PPE they needed. We classified PPE as inadequate if they reported they did not have enough PPE or if it was not available. We also asked health-care workers to report the site of their patient care (inpatient, nursing home, outpatient, home health, ambulatory clinic, or other).
Statistical analysis
We used Cox proportional hazards modelling stratified by age, date, and country to estimate multivariable-adjusted HRs and 95% CIs. Covariates were selected a priori based on putative risk factors, including sex (male or female), race or ethnic origin (non-Hispanic white, Hispanic or Latinx, Black, Asian, or more than one or other), history of diabetes (yes or no), heart disease (yes or no), lung disease (yes or no), kidney disease (yes or no), current smoking status (yes or no), and body-mass index (17·0–19·9 kg/m2, 20·0–24·9 kg/m2, 25·0–29·9 kg/m2, and ≥30·0 kg/m2). Data imputation replaced no more than 5% of missing values for a given metadatum, with numerical values replaced with the median and categorical variables imputed using the mode.
Briefly, using logistic regression and symptoms preceding testing, we have previously described that loss of smell or taste, fatigue, persistent cough, and loss of appetite predicted COVID-19 positivity with high specificity (appendix p 2). Second, to account for country-specific predictors of obtaining testing, we did separate inverse probability weighting in the UK and the USA as a function of demographic and clinical factors, followed by inverse probability-weighted Cox proportional hazards modelling stratified by age and date with additional adjustment for the covariates used in previous models (appendix p 2). To assess factors associated with PPE adequacy, work in especially high-risk clinical settings, or greater exposure to patients with COVID-19 (including a post-hoc analysis of race and ethnicity), we used multivariable logistic regression models to estimate adjusted odds ratios (ORs) and 95% CIs. Two-sided p values less than 0·05 were considered statistically significant. All analyses were done using R version 3.6.1.
Role of the funding source
Zoe Global developed the app for data collection. The funders had no role in study design, data analysis, data interpretation, or writing of the report. LHN, DAD, MSG, SO, CJS, and ATC had access to raw data. The corresponding author had full access to all data in the study and had final responsibility for the decision to submit for publication.
Results
FigureRisk of testing positive for COVID-19 among front-line health-care workers
(A) Between March 24 and April 23, 2020, considerable disparities were noted in prevalence of a positive COVID-19 test among front-line health-care workers compared with the general community, in both the UK and the USA. (B) Prevalence of a positive COVID-19 test reported by front-line health-care workers in the UK and the USA. Regions in grey did not have sufficient data for analysis. app=COVID-19 Symptom Study smartphone application.
Table 1Baseline characteristics of front-line health-care workers compared with the general community
Data are % or median (IQR). % are calculated based on the total number of participants with available data. Polytomous variables might not add up to 100% because of rounding. Questions about history of cancer, angiotensin-converting enzyme inhibitor use, and smoking status have been asked since launch in the USA and March 29, 2020, in the UK; questions about race and ethnic origin were asked since April 17, 2020, in both the UK and the USA. Percentages within each category are based on the total population responding when the question was first asked.
Table 2Risk of reporting a positive test for COVID-19 among front-line health-care workers compared with the general community
All models were stratified by 5-year age group, calendar date at study entry, and country. Multivariate risk factor models were adjusted for sex (male or female), history of diabetes (yes or no), heart disease (yes or no), lung disease (yes or no), kidney disease (yes or no), current smoking (yes or no), and body-mass index (17·0–19·9 kg/m2, 20·0–24·9 kg/m2, 25·0–29·9 kg/m2, and ≥30 kg/m2). Black, Asian, and minority ethnic was defined among individuals who had race or ethnicity information and did not identify as non-Hispanic white.
Compared with the general community, health-care workers initially free of symptoms had an increased risk of predicted COVID-19 (adjusted HR 2·05, 95% CI 1·99–2·10), which was higher in the UK (2·09, 2·02–2·15) than in the USA (1·31, 1·14–1·51; pdifference
Table 3Risk of reporting a positive test for COVID-19, according to availability of PPE and exposure to patients with COVID-19 among front-line health-care workers (prespecified secondary analysis)
All models were stratified by 5-year age group, calendar date at study entry, and country. Multivariate risk factor models were adjusted for sex (male or female), history of diabetes (yes or no), heart disease (yes or no), lung disease (yes or no), kidney disease (yes or no), current smoking (yes or no), and body-mass index (17·0–19·9 kg/m2, 20·0–24·9 kg/m2, 25·0–29·9 kg/m2, and ≥30·0 kg/m2). PPE=personal protective equipment.
Table 4Risk of reporting PPE inadequacy or reuse among front-line health-care workers, according to race or ethnic origin (post-hoc analysis)
Multivariate risk factor models were adjusted for 5-year age group, sex, and exposure to patients with COVID-19 (none, suspected, and documented). Black, Asian, and minority ethnic was defined among individuals who had race or ethnicity information and did not identify as non-Hispanic white. PPE=personal protective equipment.
Table 5Front-line health-care workers and risk of testing positive for COVID-19, by site of care delivery (prespecified secondary analysis)
Model was stratified by 5-year age group, calendar date at study entry, and country and adjusted for sex (male or female), history of diabetes (yes or no), heart disease (yes or no), lung disease (yes or no), kidney disease (yes or no), current smoking (yes or no), and body-mass index (17·0–19·9 kg/m2, 20·0–24·9 kg/m2, 25·0–29·9 kg/m2, and ≥30·0 kg/m2). Ambulatory clinics include free-standing (non-hospital) primary care or specialty clinics and school-based clinics. PPE=personal protective equipment.
Discussion
Among 2 135 190 people in the UK and USA using the COVID-19 Symptom Study app between March 24 and April 23, 2020, we noted that front-line health-care workers had at least a threefold increased risk of reporting a positive COVID-19 test and predicted COVID-19 infection, compared with the general community, even after accounting for other risk factors. Post-hoc analyses showed that Black, Asian, and minority ethnic health-care workers are at especially high risk of SARS-CoV-2 infection, with at least a fivefold increased risk of COVID-19 compared with the non-Hispanic white general community. Among front-line health-care workers, reuse of PPE or inadequate PPE were each associated with a subsequent increased risk of COVID-19. Although health-care workers caring for patients with COVID-19 who reported inadequate PPE had the highest risk of SARS-CoV-2 infection, increased susceptibility to infection was evident even among those reporting adequate PPE. Front-line health-care workers who worked in inpatient settings (where providers most frequently reported PPE reuse) and nursing homes (where providers most frequently reported inadequate PPE) had the greatest risk. Non-white health-care workers were disproportionately affected by scant PPE adequacy and more likely to work in clinical settings with greater exposure to patients with COVID-19.
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Our results offer individual-level data additionally accounting for workplace risk factors that complement these limited reports by providing a more precise assessment of the magnitude of increased risk among health-care workers during the initial phases of the COVID-19 pandemic. Taken in the context of the requirement for testing to establish a COVID-19 diagnosis, our range of results based on either reporting a positive test for COVID-19 or symptoms predictive of COVID-19 offer several complementary estimates for risk among front-line health-care workers.
The greater risk associated with PPE reuse could be related to either self-contamination during repeated application and removal of PPE or breakdown of materials from extended wear. Of note, during the period of this study, disinfection protocols before PPE reuse were not widely available.
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Thus, results should be not extended to reflect risk of PPE reuse after such disinfection, which has now been implemented in various settings. An assessment of the PPE supply chain and equitable access to PPE should be a part of the deliberate and informed decision making about resource allocation.
or country-specific differences in PPE recommendations for health-care workers or the general public (eg, cloth face coverings).
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Ideally, we would assess risk within a population that has undergone uniform screening. However, the current shortage of PCR-based testing kits does not make such an approach feasible but could justify targeted screening of front-line health-care workers.
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Future studies using serological testing to ascertain SARS-CoV-2 infection will require assessments of test performance and the ability to distinguish recent or active infection from past exposure.
During the severe acute respiratory syndrome epidemic, health-care workers comprised 20–40% of cases,
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and inadequate PPE was associated with increased risk.
The experience with influenza A virus subtype H1N1 reaffirmed the importance of PPE,
with much higher infection rates among health-care workers in dedicated containment units.
By recruiting participants through existing cohorts,
our results provide proof of concept of the feasibility of leveraging existing infrastructure and engaged participants to address a key knowledge gap. Second, we obtained information from participants who did not have a positive COVID-19 test, which offered an opportunity to prospectively assess risk factors with minimal recall bias. Third, our study design recorded initial onset of symptoms, which minimises biases related to capturing only severe cases through hospitalisation records or death reports. Finally, we gathered information on a wide range of known or suspected risk factors for COVID-19 generally not available in existing registries or population-scale surveillance efforts.
This limitation could have resulted in selection bias, although our primary conclusions were robust to several sensitivity and secondary analyses. In future studies, we plan greater targeted outreach of under-represented populations. Our primary outcome was based on the report of a positive COVID-19 test. During the study period, this outcome would generally reflect a positive PCR-based swab, which should be moderately specific, compared with antibody testing, which was not widely available. However, any misclassification of positive testing should be non-differential according to occupation.
In conclusion, we reported increased risk for SARS-CoV-2 infection among front-line health-care workers compared with the general community, using either self-reported data on COVID-19 testing positivity or a symptom-based predictor of positive infection status. This risk was especially high among Black, Asian, and minority ethnic health-care workers and individuals in direct contact with patients with COVID-19 who reported inadequate PPE availability or were required to reuse PPE. Ensuring the adequate allocation of PPE is important to alleviate structural inequities in COVID-19 risk. However, because infection risk was increased even with adequate PPE, our results suggest the need to ensure proper use of PPE and adherence to other infection control measures. Further intervention studies investigating modifiable risk factors for health-care worker-related SARS-CoV-2 infection, ideally accounting for differential exposure according to race and ethnic background and care location, are urgently needed to support our observational findings.
LHN, DAD, MSG, JW, SO, CJS, TDS, and ATC contributed to study concept and design. LHN, DAD, MSG, JW, SO, RD, JC, CJS, TDS, and ATC contributed to acquisition of data. LHN, DAD, MSG, ADJ, C-GG, WM, RSM, DRS, C-HL, SK, and MS contributed to data analysis. LHN, DAD, and ATC contributed to initial drafting of the manuscript. All authors contributed to interpretation of data and critical revision of the report. SO, CJS, TDS, and ATC contributed to study supervision.
JW, RD, and JC are employees of Zoe Global. TDS is a consultant to Zoe Global. DAD and ATC previously served as investigators on a clinical trial of diet and lifestyle using a separate smartphone application that was supported by Zoe Global. All other authors declare no competing interests.
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