Temporal Dynamics of Socioeconomic Inequalities in COVID-19 Outcomes Over the Course of the Pandemic—A Scoping Review

Education and pandemic SARS-CoV-2 infections in the German working population - the mediating role of working from home

OBJECTIVES

SARS-CoV-2 infections were unequally distributed during the pandemic, with those in disadvantaged socioeconomic positions being at higher risk. Little is known about the underlying mechanism of this association. This study assessed to what extent educational differences in SARS-CoV-2 infections were mediated by working from home.

METHODS

We used data of the German working population derived from the seroepidemiological study "Corona Monitoring Nationwide - Wave 2 (RKI-SOEP-2)" (N=6826). Infections were assessed by seropositivity against SARS-CoV-2 antigens and self-reports of previous PCR-confirmed infections from the beginning of the pandemic until study participation (November 2021 - February 2022). The frequency of working from home was assessed between May 2021 and January 2022.We used the Karlson-Holm-Breen (KHB) method to decompose the effect of education on SARS-CoV-2 infections.

RESULTS

Individuals with lower educational attainment had a higher risk for SARS-CoV-2 infection (adjusted prevalence ratio of low versus very high = 1.76, 95% confidence interval 1.08-2.88; P=0.023). Depending on the level of education, between 27% (high education) and 58% (low education) of the differences in infection were mediated by the frequency of working from home.

CONCLUSIONS

Working from home could prevent SARS-CoV-2 infections and contribute to the explanation of socioeconomic inequalities in infection risks. Wherever possible, additional capacities to work remotely, particularly for occupations that require lower educational attainment, should be considered as an important measure of pandemic preparedness. Limitations of this study are the observational cross-sectional design and that the temporal order between infection and working from home remained unclear.

Socioeconomic Inequalities in SARS-CoV-2 Infection and COVID-19 Health Outcomes in Urban Italy During the COVID-19 Vaccine Rollout, January-November 2021

This study analysed the evolution of the association of socioeconomic deprivation (SED) with SARS-CoV-2 infection and COVID-19 outcomes in urban Italy during the vaccine rollout in 2021. We conducted a retrospective cohort analysis between January and November 2021, comprising of 16,044,530 individuals aged ≥ 20 years, by linking national COVID-19 surveillance system data to the Italian SED index calculated at census block level. We estimated incidence rate ratios (IRRs) of infection and severe COVID-19 outcomes by SED tercile relative to the least deprived tercile, over three periods defined as low (0-10%); intermediate (> 10-60%) and high (> 60-74%) vaccination coverage. We found patterns of increasing relative socioeconomic inequalities in infection, hospitalisation and death as COVID-19 vaccination coverage increased. Between the low and high coverage periods, IRRs for the most deprived areas increased from 1.09 (95%CI 1.03-1.15) to 1.28 (95%CI 1.21-1.37) for infection; 1.48 (95%CI 1.36-1.61) to 2.02 (95%CI 1.82-2.25) for hospitalisation and 1.57 (95%CI 1.36-1.80) to 1.89 (95%CI 1.53-2.34) for death. Deprived populations in urban Italy should be considered as vulnerable groups in future pandemic preparedness plans to respond to COVID-19 in particular during mass vaccination roll out phases with gradual lifting of social distancing measures.

Social Inequalities in Long-Term Health Effects After COVID-19-A Scoping Review

Objectives: We aimed to map and synthesize evidence about social inequalities in long-term health effects after COVID-19 (LTHE), often referred to as "long COVID" or "post-COVID-19 conditions." Methods: We conducted a scoping review of peer-reviewed articles by searching the databases Embase and Scopus. According to predefined inclusion criteria, titles/abstracts and full texts were screened for eligibility. Additionally, reference lists of all included studies were hand-searched for eligible studies. This study followed the PRISMA guidelines for scoping reviews. Results: Nineteen articles were included. LTHE were analysed according to ethnicity, education, income, employment and deprivation indices. The studies varied significantly in their definitions of LTHE. Eighty-two analyses showed no statistically significant associations. At least 12 studies had a high risk of type II errors. Only studies associating deprivation indices and long COVID tended to show a higher prevalence of LTHE in deprived areas. Conclusion: Although some studies indicated social inequalities in LTHE, evidence was generally weak and inconclusive. Further studies with larger sample sizes specifically designed to detect social inequalities regarding LTHE are needed to inform future healthcare planning and public health policies.

Assessing readiness for childhood obesity prevention in German municipalities: application of the community readiness model

The World Health Organization has identified childhood obesity as one of the most serious public health problems of the 21st century. Understanding a municipality's readiness to address it is crucial to achieve successful interventions. However, the preparedness of German municipalities to address childhood obesity has not yet been investigated. This study is the first in Germany to apply the community readiness model (CRM) in this context. The purpose was to determine readiness of five municipalities for childhood obesity prevention and to identify factors that influence their readiness. Therefore, 27 semi-structured key informant interviews were conducted. First, the interviews were analysed following the CRM protocol to categorize the municipalities into a readiness level between one and nine. In a second step, a content analysis was carried out for an in-depth interpretation of the readiness scores. The municipalities achieved an average readiness of 3.84, corresponding to the 'Vague Awareness' stage. A lack of prioritization and leadership support, insufficient low-threshold efforts, a lack of knowledge and problem awareness as well as a lack of structures and resources were identified as factors that can determine municipal readiness to prevent childhood obesity. This study not only extends the application of the CRM to childhood obesity in German municipalities but also offers practical implications for professionals in assessing readiness.

Socioeconomic Differences in SARS-CoV-2 Infection and Vaccination in Germany: A Seroepidemiological Study After One Year of COVID-19 Vaccination Campaign

Objective: To evaluate the socioeconomic patterns of SARS-CoV-2 antigen contacts through infection, vaccination or both ("hybrid immunity") after 1 year of vaccination campaign. Methods: Data were derived from the German seroepidemiological Corona Monitoring Nationwide study (RKI-SOEP-2; n = 10,448; November 2021-February 2022). Combining serological and self-report data, we estimated adjusted prevalence ratios (PR) of SARS-CoV-2 infection, COVID-19 vaccination, basic immunization (at least two SARS-CoV-2 antigen contacts through vaccination and/or infection), and three antigen contacts by education and income. Results: Low-education groups had 1.35-times (95% CI 1.01-1.82) the risk of SARS-CoV-2 infection compared to high-education groups. COVID-19 vaccination (at least one dose) and basic immunization decreased with lower education and income. Low-education and low-income groups were less likely to have had at least three antigen contacts (PR low vs. high education: 0.74, 95% CI 0.65-0.84; PR low vs. high income: 0.66, 95% CI 0.57-0.77). Conclusion: The results suggest a lower level of protection against severe COVID-19 for individuals from low and medium socioeconomic groups. Pandemic response and vaccination campaigns should address the specific needs and barriers of these groups.

The Covid-19 pandemic as an accelerator of economic worries and labor-related mental health polarization in Germany? A longitudinal interacted mediation analysis with a difference-in-difference comparison

Objectives

Labor-related mental health polarization refers to exposure to low-paid employment and unemployment decreasing mental health. Previous research identified economic worries as a key mediator. Against this background, the Covid-19 pandemic is often assumed to have accelerated already existing processes and affected vulnerable populations the most. Our study sought to investigate whether the Covid-19 pandemic accelerated the mediation by economic worries between employment type and mental health.

Method

Using the German Socioeconomic Panel (GSOEP) from 2016 onwards, we created a pre-Covid-19 sample (N = 8266) and a per-Covid-19 sample (N = 7294), with each having a t0 wave (2016/2018) and a t1 wave (2018/2020). We applied the mediational g-formula for longitudinal mediation with exposure-mediator (XM) interaction between employment type (X) and economic worries (M). We decomposed the total effect into a direct, indirect, and interacted effect of employment on mental health and provided a difference-in-difference comparison of the effects.

Results

During the Covid-19 pandemic, economic worries increased, and mental health decreased. However, the mediation by economic worries reduced by approx. 18.0% (e.g., from 35.0% to 28.9%). A decreased indirect effect caused the reduction in mediation, while the direct and interacted effect remained rather stable. We also found stark gender differences towards males having a higher total effect but a lower mediated effect during the Covid-19 pandemic.

Conclusion

Our results highlight that mediators competing to economic worries must have emerged during the Covid-19 pandemic. Such mediators could be the risk of infection at the workplace, the possibility of remote work, and gender-specific mediators. Our study is also the first to extend the mediational g-formula with the difference-in-difference approach. It can be used as a blueprint for researchers interested in evaluating the impact of events, such as the Covid-19 pandemic, on preexisting processes.

[Occupational differences of COVID-19 morbidity and mortality in Germany. An analysis of health insurance data from 3.17 million insured persons]

INTRODUCTION

During the COVID-19 pandemic, occupation was assumed to play a central role in the occurrence of infection and disease. For Germany, however, there are only a few studies that analyse occupational differences in risk of COVID-19, COVID-19-associated hospitalisation, and mortality.

METHODS

The study uses longitudinal health insurance data from the research database of the Institute for Applied Health Research (InGef) with information on 3.17 million insured persons aged 18-67 years (1,488,452 women; 1,684,705 men). Outcomes (morbidity, hospitalisation, and mortality) were determined on the basis of submitted COVID-19 diagnoses between 1 January 2020 and 31 December 2021. Occupations were classified according to four groupings of the official German classification of occupations. In addition to cumulative incidences, relative risks (RR) were calculated - separately for men and women.

RESULTS

There is an increased risk of disease in personal service occupations, especially in health care, compared to other occupations (RR for women 1.46; for men 1.30). The same applies to social and cultural service occupations (but only for women) and for manufacturing occupations (only for men). In addition, the risks for hospitalisation and mortality are increased for cleaning occupations and transport and logistics occupations (especially for men). For all three outcomes, the risks are higher in non-managerial occupations and differ by skill level (highest for unskilled jobs and lowest for expert positions).

CONCLUSION

The study provides important findings on work- and gender-related differences in COVID-19 morbidity and mortality in Germany, which indicate starting points for structural infection protection measures.

Socioeconomic disparities and concentration of the spread of the COVID-19 pandemic in the province of Quebec, Canada

BACKGROUND

Recent studies suggest that the risk of SARS-CoV-2 infection may be greater in more densely populated areas and in cities with a higher proportion of persons who are poor, immigrant, or essential workers. This study examines spatial inequalities in SARS-CoV-2 exposure in a health region of the province of Quebec in Canada.

METHODS

The study was conducted on the 1206 Canadian census dissemination areas in the Capitale-Nationale region of the province of Quebec. The observation period was 21 months (March 2020 to November 2021). The number of cases reported daily in each dissemination area was identified from available administrative databases. The magnitude of inequalities was estimated using Gini and Foster-Greer-Thorbecke (FGT) indices. The association between transmission and socioeconomic deprivation was identified based on the concentration of transmission in socially disadvantaged areas and on nonparametric regressions relating the cumulative incidence rate by area to ecological indicators of spatial disadvantage. Quantification of the association between median family income and degree of exposure of dissemination areas was supplemented by an ordered probit multiple regression model.

RESULTS

Spatial disparities were elevated (Gini = 0.265; 95% CI [0.251, 0.279]). The spread was more limited in the less densely populated areas of the Quebec City agglomeration and outlying municipalities. The mean cumulative incidence in the subsample made up of the areas most exposed to the pandemic was 0.093. The spread of the epidemic was concentrated in the most disadvantaged areas, especially in the densely populated areas. Socioeconomic inequality appeared early and increased with each successive pandemic wave. The models showed that areas with economically disadvantaged populations were three times more likely to be among the areas at highest risk for COVID-19 (RR = 3.55; 95% CI [2.02, 5.08]). In contrast, areas with a higher income population (fifth quintile) were two times less likely to be among the most exposed areas (RR = 0.52; 95% CI [0.32, 0.72]).

CONCLUSION

As with the H1N1 pandemics of 1918 and 2009, the SARS-CoV-2 pandemic revealed social vulnerabilities. Further research is needed to explore the various manifestations of social inequality in relation to the pandemic.

Young Adult German Breast Cancer Patients Participating in a Three-Week Inpatient Mother–Child Rehab Program Have High Needs for Supportive Care

A known cut-off problem hampers the interpretation of quality of life (QOL) scores. The purpose of this study was to apply a novel approach for the EORTC QLQ-C30 instrument to identify the proportion of breast cancer (BC) patients in need of supportive care. Changes in QOL during the COVID-19 pandemic were evaluated, as well as changes over time (after treatment termination and up to 4 years later). Data were obtained from a cohort study on young adult BC patients with minor children participating in a mother–child rehab program. Cross-sectional QOL data were collected from 2015 to 2021 (baseline). Follow-up data were available for up to 4 years after diagnosis for a subgroup. The baseline cohort included 853 women (mean age 35 years). More than 50% had a need for supportive care. In the subgroup with follow-up, this proportion remained at a high level up to several years after diagnosis. During the COVID-19 pandemic, changes regarding the proportion with this need were not as high as expected—with the exception of changes on the QLQ-C30 scale ‘role functioning’ (+15%). Even several years after diagnosis, every second BC patient with minor children had a need for supportive care, which is much higher than previously found. Healthcare staff should be aware of this potential need and should address this issue.

Educational inequalities in self-rated health and emotional exhaustion among workers during the COVID-19 pandemic: a longitudinal study

OBJECTIVE

This study aimed to investigate trends in educational inequalities in poor health and emotional exhaustion during the pandemic among workers, and differences in trends between men and women.

METHODS

Five waves (2019-2021) from the longitudinal study 'the Netherlands Working Conditions Survey COVID-19 study' were used (response rates: 32-38%). Generalized logistic mixed models were used to estimate the changes in absolute and relative educational inequalities in poor health and emotional exhaustion for all workers (n = 12,479) and for men and women, separately.

RESULTS

Low and intermediate educated workers reported more often poor health (OR 2.54; 95% CI 1.71-3.77 and OR 2.09; 95% CI 1.68-2.61, respectively) than high educated workers. Intermediate educated women (OR 0.49; 95% CI 0.37-0.64) reported less emotional exhaustion than high educated women, but no differences were observed among men. The prevalence of poor health first decreased across all educational levels until March 2021, and bounced back in November 2021. A similar pattern was found for emotional exhaustion, but for low and intermediate educated workers only. Relative educational inequalities in poor health reduced among men during the pandemic, and absolute differences decreased among men and women by 2.4-2.6%. Relative educational inequalities in emotional exhaustion widened among men only. Absolute differences in emotional exhaustion first increased among both men and women, but narrowed between the last two waves.

DISCUSSION

Socioeconomic inequalities for poor self-rated health remained but narrowed in relative and absolute terms during the pandemic. With regard to emotional exhaustion, socioeconomic inequalities returned to pre-COVID-19 levels at the end of 2021.

Socioeconomic differences in the reduction of face-to-face contacts in the first wave of the COVID-19 pandemic in Germany

BACKGROUND

The COVID-19 pandemic has led to physical distancing measures to control the spread of SARS-CoV-2. Evidence on contact dynamics in different socioeconomic groups is still sparse. This study aimed to investigate the association of socioeconomic status with private and professional contact reductions in the first COVID-19 wave in Germany.

METHODS

Data from two especially affected municipalities were derived from the population-based cross-sectional seroepidemiological CORONA-MONITORING lokal study (data collection May-July 2020). The study sample (n = 3,637) was restricted to working age (18-67 years). We calculated the association of educational and occupational status (low, medium, high) with self-reported private and professional contact reductions with respect to former contact levels in the first wave of the pandemic. Multivariate Poisson regressions were performed to estimate prevalence ratios (PR) adjusted for municipality, age, gender, country of birth, household size, contact levels before physical distancing measures, own infection status, contact to SARS-CoV-2 infected people and working remotely.

RESULTS

The analyses showed significant differences in the initial level of private and professional contacts by educational and occupational status. Less private contact reductions with lower educational status (PR low vs. high = 0,79 [CI = 0.68-0.91], p = 0.002; PR medium vs. high = 0,93 [CI = 0.89-0.97], p = 0.001) and less professional contact reductions with lower educational status (PR low vs. high = 0,87 [CI = 0.70-1.07], p = 0.179; PR medium vs. high = 0,89 [CI = 0.83-0.95], p = 0.001) and lower occupational status (PR low vs. high = 0,62 [CI = 0.55-0.71], p < 0.001; PR medium vs. high = 0,82 [CI = 0.77-0.88], p < 0.001) were observed.

CONCLUSIONS

Our results indicate disadvantages for groups with lower socioeconomic status in private and professional contact reductions in the first wave of the pandemic. This may be associated with the higher risk of infection among individuals in lower socioeconomic groups. Preventive measures that a) adequately explain the importance of contact restrictions with respect to varying living and working conditions and b) facilitate the implementation of these reductions especially in the occupational setting seem necessary to better protect structurally disadvantaged groups during epidemics.

Participation of the adult population in preventive measures for non-communicable diseases during the COVID-19 pandemic in 2020/2021

Background

In 2020/2021, the COVID-19 pandemic and the protective measures associated therewith severely limited the opportunity to participate in prevention and health promotion measures. The article examines the utilisation of the measures and possible factors that are associated with a lower participation during these pandemic years.

Methods

It is based on data acquired between March and August 2021 from the study 'COVID-19 vaccination rate monitoring in Germany' (COVIMO), a cross-sectional telephone survey. The data was used to examine the participation in preventive measures in the last 12 months in terms of sociodemographic factors and to analyse a decreased participation with regard to pandemic-related factors. The analysis sample includes individuals aged 18 years and over (n=3,998).

Results

63% of participants generally did not use these programmes, 7% indicated an unchanged participation, 28% reported having participated in fewer measures, and 2% in more measures. Men reported significantly more often than women that they generally do not participate in prevention and health promotion measures. A relevant pandemic-related factor for decreased participation of men was the less clearly perceived comprehensibility of the regulations against the spread of SARS-CoV-2.

Conclusions

Prevention and health promotion should be part of the contingency planning in epidemically significant situations to prevent a decreased participation and to promote health and gender-related equal opportunities even in a crisis.

Authors' response: Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias

We thank van Tongeren et al for responding to our study on occupational disparities in SARS-CoV-2 infection risks during the first pandemic wave in Germany (1). The authors address the potential for bias resulting from differential testing between occupational groups and propose an alternative analytical strategy for dealing with selective testing. In the following, we want to discuss two aspects of this issue, namely (i) the extent and reasons of differential testing in our cohort and (ii) the advantages and disadvantages of different analytical approaches to study risk factors for SARS-CoV-2 infection. Our study relied on nationwide prospective cohort data including more than 100 000 workers in order to compare the incidence of infections between different occupations and occupational status positions. We found elevated infection risks in personal services and business administration, in essential occupations (including health care) and among people in higher occupational status positions (ie, managers and highly skilled workers) during the first pandemic wave in Germany (2). Van Tongeren's et al main concern is that the correlations found could be affected by a systematic bias because people in healthcare professions get tested more often than employees in other professions. A second argument is that better-off people could be more likely to use testing as they are less affected by direct costs (prices for testing) and the economic hardship associated with a positive test result (eg, loss of earnings in the event of sick leave). We share the authors' view that differential testing must be considered when analysing and interpreting the data. Thus, in our study, we examined the proportion of tests conducted in each occupational group as part of the sensitivity analyses (see supplementary figure S1, accessible at www.sjweh.fi/article/4037). As expected, testing proportions were exceptionally high in medical occupations (due to employer requirements). However, we did not observe systematic differences among non-medical occupations or when categorising by skill-level or managerial responsibility. This might be explained by several reasons. First, SARS-CoV-2 testing was free of charge during the first pandemic wave in Germany, but reporting a risk contact or having symptoms was a necessary condition for testing ( https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html (accessed 5 September 2022). The newspaper article cited by van Tongeren et al is misleading as it refers to a calendar date after our study period. Second, different motivation for testing due to economic hardship in case of a positive test result is an unlikely explanation, because Germany has a universal healthcare system, including paid sick leave and sickness benefits for all workers (3). Self-employed people carry greater financial risks in case of sickness. We therefore included self-employment in the multivariable analyses to address this potential source of bias. While the observed inverse social gradient may be surprising, it actually matches with findings of ecological studies from Germany (4, 5), the United States (6, 7) as well as Spain, Portugal, Sweden, The Netherlands, Israel, and Hong Kong (8), all of which observed higher infection rates in wealthier neighbourhoods during the initial outbreak phase of the pandemic. One possible explanation is the higher mobility of managers and better educated workers, who are more likely to participate in meetings and engage in business travel and holiday trips like skiing. Given the increasing number of studies providing evidence for this hypothesis, we conclude that the inverse social gradient in our study likely reflects different exposure probabilities and is not a result of systematic bias. This also holds true for the elevated infection risks in essential workers, which is actually corroborated by a large body of research (9-11). Regarding differential likelihood of testing, van Tongeren et al state that "[i]t is relatively simple to address this problem by using a test-negative design" (1). As van Tongeren et al describe, this is a case-control approach only including individuals who were tested (without considering those who were not tested). However, the proposed analytical strategy can lead to another (more serious) selection bias if testing proportions and/or testing criteria differ between groups (12). This can be easily illustrated when comparing the results based on a time-incidence design with those obtained by a test-negative design as shown in table 1 (see PDF). Both approaches show similar results in terms of vertical occupational differences. Infection was more common if individuals had a high skill level or had a managerial position, but associations were stronger in the time-incidence design and did not reach statistical significance in the test-negative design (as indicated by the confidence intervals overlapping "1"). Unfortunately, the test-negative approach relies on a strongly reduced sample size and thus results in greater statistical uncertainty and loss of statistical power (13). In contrast, the test-negative design yields a different picture when estimating the association between essential occupation and infection risk: In this analysis, essential workers did not differ from non-essential workers in their chance of being infected with SARS-CoV-2 (the test-negative design even exhibits a lower chance for essential workers). This is rather counter-intuitive and is not in accordance with what we know about the occupational hazards of healthcare workers during the pandemic (14). The main problem is that proportions of positive tests are highly unreliable when testing proportions and/or testing criteria differ between groups. As essential workers were tested more often without being symptomatic (due to employer requirements), a lower proportion of positive tests in this group does not necessarily correspond to a lower risk of infection. Consequently, we are not convinced that the test-negative design should be the 'gold standard' for studying risk factors for SARS-CoV-2 infections (15). Especially problematic is the loss of statistical power (increasing the probability of a type II error) and the low validity of the test-positivity when test criteria and/or test proportions differ between groups. References 1. van Tongeren M, Rhodes S, Pearce N. Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias. Scand J Work Environ Health 2022;48(7):586-587. https://doi.org/10.5271/sjweh.4052. 2. Reuter M, Rigó M, Formazin M, Liebers F, Latza U, Castell S, et al. Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany. Scand J Work Environ Health 2022;48:446-56. https://doi.org/10.5271/sjweh.4037. 3. Busse R, Blümel M, Knieps F, Bärnighausen T. Statutory health insurance in Germany: a health system shaped by 135 years of solidarity, self-governance, and competition. Lancet 2017;390:882-97. https://doi.org/10.1016/S0140-6736(17)31280-1. 4. Wachtler B, Michalski N, Nowossadeck E, Diercke M, Wahrendorf M, Santos-Hövener C, et al. Socioeconomic inequalities in the risk of SARS-CoV-2 infection - First results from an analysis of surveillance data from Germany. J Heal Monit 2020;5:18-29. https://doi.org/10.25646/7057. 5. Plümper T, Neumayer E. The pandemic predominantly hits poor neighbourhoods? SARS-CoV-2 infections and COVID-19 fatalities in German districts. Eur J Public Health 2020;30:1176-80. https://doi.org/10.1093/eurpub/ckaa168. 6. Abedi V, Olulana O, Avula V, Chaudhary D, Khan A, Shahjouei S, et al. Racial, Economic, and Health Inequality and COVID-19 Infection in the United States. J Racial Ethn Heal Disparities 2021;8:732-42. https://doi.org/10.1007/s40615-020-00833-4. 7. Mukherji N. The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase. Rev Reg Stud 2022;52. https://doi.org/10.52324/001c.35255. 8. Beese F, Waldhauer J, Wollgast L, Pförtner T, Wahrendorf M, Haller S, et al. Temporal Dynamics of Socioeconomic Inequalities in COVID-19 Outcomes Over the Course of the Pandemic-A Scoping Review. Int J Public Health 2022;67:1-14. https://doi.org/10.3389/ijph.2022.1605128. 9. Nguyen LH, Drew DA, Graham MS, Joshi AD, Guo C-G, Ma W, et al. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Heal 2020;5:e475-83. https://doi.org/10.1016/S2468-2667(20)30164-X. 10. Chou R, Dana T, Buckley DI, Selph S, Fu R, Totten AM. Epidemiology of and Risk Factors for Coronavirus Infection in Health Care Workers. Ann Intern Med 2020;173:120-36. https://doi.org/10.7326/M20-1632. 11. Stringhini S, Zaballa M-E, Pullen N, de Mestral C, Perez-Saez J, Dumont R, et al. Large variation in anti-SARS-CoV-2 antibody prevalence among essential workers in Geneva, Switzerland. Nat Commun 2021;12:3455. https://doi.org/10.1038/s41467-021-23796-4. 12. Accorsi EK, Qiu X, Rumpler E, Kennedy-Shaffer L, Kahn R, Joshi K, et al. How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19. Eur J Epidemiol 2021;36:179-96. https://doi.org/10.1007/s10654-021-00727-7. 13. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd Editio. New York: Routledge; 2013. https://doi.org/10.4324/9780203771587. 14. The Lancet. The plight of essential workers during the COVID-19 pandemic. Lancet 2020;395:1587. https://doi.org/10.1016/S0140-6736(20)31200-9. 15. Vandenbroucke JP, Brickley EB, Pearce N, Vandenbroucke-Grauls CMJE. The Evolving Usefulness of the Test-negative Design in Studying Risk Factors for COVID-19. 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