Changes in anxiety and depression over the first year of COVID-19 pandemic in Philadelphia, PA: work characteristics and mental health supports.

OBJECTIVE: We investigated the change in anxiety and depression in a general population cohort over the first year of COVID-19 pandemic in relation to work characteristics and mental health support. METHODS: We administered questionnaires to a convenience sample in Greater Philadelphia, USA, in summer of 2020 and a year later. With >60% response rate, 461 people had repeated measurements. RESULTS: Anxiety declined but depression increased in the cohort after a year of COVID-19 pandemic. Perceived increase in support from family and trade unions, stable employment, and professional mental health support were protective. Depression scores worsened mostly in healthcare, higher education, and manufacturing industries. CONCLUSIONS: We observed that while anxiety dissipated over the first year of COVID-19 pandemic, depression worsened, perhaps more so in some industries and where mental health support faltered over time.

The evolution of workplace risk for Covid-19 in Canadian healthcare workers and its relation to vaccination: A nested case-referent study.

BACKGROUND: During the early months of the Covid-19 pandemic, studies demonstrated that healthcare workers (HCWs) were at increased risk of infection. Few modifiable risks were identified. It is largely unknown how these evolved over time. METHODS: A prospective case-referent study was established and nested within a cohort study of Canadian HCWs. Cases of Covid-19, confirmed by polymerase chain reaction, were matched with up to four referents on job, province, gender, and date of first vaccination. Cases and referents completed a questionnaire reporting exposures and experiences in the 21 days before case date. Participants were recruited from October 2020 to March 2022. Workplace factors were examined by mixed-effects logistic regression allowing for competing exposures. A sensitivity analysis was limited to those for whom family/community transmission seemed unlikely. RESULTS: 533 cases were matched with 1697 referents. Among unvaccinated HCWs, the risk of infection was increased if they worked hands-on with patients with Covid-19, on a ward designated for care of infected patients, or handled objects used by infected patients. Sensitivity analysis identified work in residential institutions and geriatric wards as high risk for unvaccinated HCWs. Later, with almost universal HCW vaccination, risk from working with infected patients was much reduced but cases were more likely than referents to report being unable to access an N95 mask or that decontaminated N95 masks were reused. CONCLUSIONS: These results suggest that, after a rocky start, the risks of Covid-19 infection from work in health care are now largely contained in Canada but with need for continued vigilance.

Pride and adversity among nurses and physicians during the pandemic in two US healthcare systems: a mixed methods analysis.

BACKGROUND: Our aims were to examine themes of the most difficult or distressing events reported by healthcare workers during the first wave of COVID-19 pandemic in two US health care systems in order to identify common themes and then to relate them to both behavioral theory and measures of anxiety and depression. METHODS: We conducted a cross-sectional survey of nurses and physicians during the early phases of the COVID-19 pandemic in the US. An emailed recruitment letter was sent, with about half choosing to supply open-ended responses relevant to thematic analysis. We measured symptoms of anxiety and depression separately, captured demographics, and asked two open-ended questions regarding events that were the most difficult or stressful, and reinforced pride. We reported descriptive statistics and coded thematic categories for their continuum "pride" and "distress" the factors related to fostering well-being according to the Self-Determination Theory. RESULTS: Themes that emerged from these narratives were congruent with prediction of Self-Determination theory that autonomy-supportive experiences will foster pride, while autonomy-thwarting experiences will cause distress. Those who reported distressful events were more anxious and depressed compared to those who did not. Among those who reported incidences that reinforced pride in the profession, depression was rarer compared to those who did not. These trends were evident after allowing for medical history and other covariates in logistic regressions. CONCLUSION: Causal claims from our analysis should be made with caution due to the cross-sectional research design. Understanding perceptions of the pandemic by nurses and physicians may help identify and manage sources of distress, and suggest means of mitigating the risk of mental health distress through autonomy-supportive policies.

COVID-19 infection and mental wellness in a Canadian cohort study of healthcare workers

IntroductionHealthcare workers (HCW) working through the pandemic are in the front line for infection, psychological pressure and overwork.ObjectivesTo identify modifiable work factors associated with COVID-19 infection and mental distress, and to assess the effectiveness of provisions to mitigate their impact.MethodsA cohort study of HCWs was set up in the first weeks of the pandemic in Canada. HCWs from British Columbia, Alberta, Ontario, and Quebec completed an online questionnaire in the spring/summer of 2020, and a Phase 2 questionnaire from October 2020. They also provided a blood sample to assess SARS-CoV-2 antibodies. HCWs reporting a COVID-19 infection after the Phase 2 questionnaire were matched on job-type and province to 4 referents for a nested case-referent (C-R) study concentrating on exposures immediately prior to infection. Phase 3 is underway, with a final contact planned for March 2022.Results5135 HCWs completed the Phase 1 questionnaire with 93% (4539/4857) of those eligible completing Phase 2. By March 1st 2021, 157 cases had been confirmed by PCR and a further 10 found positive only on antibody testing (an overall rate of 3.3%). The odds of infection doubled for working one-on-one with known COVID-19 patients. Rates were lower in physicians and nurses, compared to personal support workers, health care aides, and licensed practical nurses. HCWs in a hospital setting had lower rates than those working in the community, where shortages of personal protective equipment were more widespread. High rates of anxiety (on the Hospital Anxiety and Depression Scale) were recorded in both Phase 1 and 2. Only 1 in 4 HCW had used available mental health supports. By May 2021, 100 cases with 389 referents had been recruited to the on-going C-R study.ConclusionInformation collected prospectively has the potential to improve HCWs protection during this and future epidemics.

Experiences of coping with the first wave of COVID-19 epidemic in Philadelphia, PA: Mixed methods analysis of a cross-sectional survey of worries and symptoms of mood disorders.

Our objective was to describe how residents of Philadelphia, Pennsylvania, coped psychologically with the first wave of COVID-19 pandemic. In a cross-sectional design, we aimed to estimate the rates and correlates of anxiety and depression, examine how specific worries correlated with general anxiety and depression, and synthesize themes of "the most difficult experiences" shared by the respondents. We collected data through an on-line survey in a convenience sample of 1,293 adult residents of Philadelphia, PA between April 17 and July 3, 2020, inquiring about symptoms of anxiety and depression (via the Hospital Anxiety and Depression Scale), specific worries, open-ended narratives of "the most difficult experiences" (coded into themes), demographics, perceived sources of support, and general health. Anxiety was evident among 30 to 40% of participants and depression-about 10%. Factor analysis revealed two distinct, yet inter-related clusters of specific worries related to mood disorders: concern about "hardships" and "fear of infection". Regression analyses revealed that anxiety, depression, and fear of infection, but not concern about hardships, worsened over the course of the epidemic. "The most difficult experiences" characterized by loss of income, poor health of self or others, uncertainty, death of a relative or a friend, and struggle accessing food were each associated with some of the measures of worries and mood disorders. Respondents who believed they could rely on support of close personal network fared better psychologically than those who reported relying primarily on government and social services organizations. Thematic analysis revealed complex perceptions of the pandemic by the participants, giving clues to both positive and negative experiences that may have affected how they coped. Despite concerns about external validity, our observations are concordant with emerging evidence of psychological toll of the COVID-19 pandemic and measures employed to mitigate risk of infection.

A Cross-Sectional Survey of the Workplace Factors Contributing to Symptoms of Anxiety and Depression Among Nurses and Physicians During the First Wave of COVID-19 Pandemic in Two US Healthcare Systems.

BACKGROUND: Anxiety and depression among physicians and nurses during the COVID-19 pandemic in the USA are not well described and their modifiable causes are poorly understood. METHODS: We conducted a cross-sectional survey of symptoms of anxiety and depression (Hospital Anxiety and Depression Scale) among physicians and nurses in two US healthcare systems in June through September 2020; participation rate was 5-10%. We described features of work as well as their perceptions and associated concerns in relation to the risk of anxiety and depression, while controlling for health history via regression and path analyses. RESULTS: About a third of 684 nurses and 185 physicians surveyed showed symptoms of anxiety or depression, and the excess of symptoms of mood disorders was particularly prominent in nurses. The belief that one was infected was a dominant correlate of both anxiety and depression. This belief was more associated with history of symptoms of pneumonia than the contact with COVID-19 diagnosed patients. Factors found to be associated with reduced anxiety and depression in this working environment were having confidence in the competent use of and access to personal protective equipment, maintaining usual working hours, being surrounded by colleagues who were both sufficient in numbers and not stressed, and the support of immediate family and religious communities. Involvement in aerosol-generating procedures with infected patients was linked with lower depression in nurses but higher among physicians. Likewise, the setting of recent patient encounters affected risk of anxiety and depression differently for physicians and nurses. CONCLUSIONS: Our findings may help develop mitigation measures and underscore the need to help nurses and physicians bear the psychological burden of the COVID-19 pandemic and similar events in the future.

Effect of Adjustment for Case Misclassification and Infection Date Uncertainty on Estimates of COVID-19 Effective Reproduction Number.

BACKGROUND: Surveillance data captured during the COVID-19 pandemic may not be optimal to inform a public health response, because it is biased by imperfect test accuracy, differential access to testing, and uncertainty in date of infection. METHODS: We downloaded COVID-19 time-series surveillance data from the Colorado Department of Public Health & Environment by report and illness onset dates for 9 March 2020 to 30 September 2020. We used existing Bayesian methods to first adjust for misclassification in testing and surveillance, followed by deconvolution of date of infection. We propagated forward uncertainty from each step corresponding to 10,000 posterior time-series of doubly adjusted epidemic curves. The effective reproduction number (Rt), a parameter of principal interest in tracking the pandemic, gauged the impact of the adjustment on inference. RESULTS: Observed period prevalence was 1.3%; median of the posterior of true (adjusted) prevalence was 1.7% (95% credible interval [CrI]: 1.4%, 1.8%). Sensitivity of surveillance declined over the course of the epidemic from a median of 88.8% (95% CrI: 86.3%, 89.8%) to a median of 60.8% (95% CrI: 60.1%, 62.6%). The mean (minimum, maximum) values of Rt were higher and more variable by report date, 1.12 (0.77, 4.13), compared to those following adjustment, 1.05 (0.89, 1.73). The epidemic curve by report date tended to overestimate Rt early on and be more susceptible to fluctuations in data. CONCLUSION: Adjusting for epidemic curves based on surveillance data is necessary if estimates of missed cases and the effective reproduction number play a role in management of the COVID-19 pandemic.

Symptoms of Anxiety and Depression in Relation to Work Patterns During the First Wave of the COVID-19 Epidemic in Philadelphia PA: A Cross-Sectional Survey.

OBJECTIVE: We investigated whether patterns of work during COVID-19 pandemic altered by effort to contain the outbreak affected anxiety and depression. METHODS: We conducted a cross-sectional online survey of 911 residents of Philadelphia, inquiring about their working lives during early months of the epidemic, symptoms of anxiety and depression, plus demographics, perceived sources of support, and general health. RESULTS: Occupational contact with suspected COVID-19 cases was associated with anxiety. Concerns about return to work, childcare, lack of sick leave, and loss/reduction in work correlated with anxiety and depression, even when there was no evidence of occupational contact with infected persons; patterns differed by sex. CONCLUSIONS: Heightened anxiety and depression during COVID-19 pandemic can be due to widespread disruption of working lives, especially in "non-essential" low-income industries, on par with experience in healthcare.

A Bayesian approach to improving spatial estimates of prevalence of COVID-19 after accounting for misclassification bias in surveillance data in Philadelphia, PA.

Surveillance data obtained by public health agencies for COVID-19 are likely inaccurate due to undercounting and misdiagnosing. Using a Bayesian approach, we sought to reduce bias in the estimates of prevalence of COVID-19 in Philadelphia, PA at the ZIP code level. After evaluating various modeling approaches in a simulation study, we estimated true prevalence by ZIP code with and without conditioning on an area deprivation index (ADI). As of June 10, 2020, in Philadelphia, the observed citywide period prevalence was 1.5%. After accounting for bias in the surveillance data, the median posterior citywide true prevalence was 2.3% when accounting for ADI and 2.1% when not. Overall the median posterior surveillance sensitivity and specificity from the models were similar, about 60% and more than 99%, respectively. Surveillance of COVID-19 in Philadelphia tends to understate discrepancies in burden for the more affected areas, potentially misinforming mitigation priorities.

It can be dangerous to take epidemic curves of COVID-19 at face value.

During an epidemic with a new virus, we depend on modelling to plan the response: but how good are the data? The aim of our work was to better understand the impact of misclassification errors in identification of true cases of COVID-19 on epidemic curves. Data originated from Alberta, Canada (available on 28 May 2020). There is presently no information of sensitivity (Sn) and specificity (Sp) of laboratory tests used in Canada for the causal agent for COVID-19. Therefore, we examined best attainable performance in other jurisdictions and similar viruses. This suggested perfect Sp and Sn 60-95%. We used these values to re-calculate epidemic curves to visualize the potential bias due to imperfect testing. If the sensitivity improved, the observed and adjusted epidemic curves likely fall within 95% confidence intervals of the observed counts. However, bias in shape and peak of the epidemic curves can be pronounced, if sensitivity either degrades or remains poor in the 60-70% range. These issues are minor early in the epidemic, but hundreds of undiagnosed cases are likely later on. It is therefore hazardous to judge progress of the epidemic based on observed epidemic curves unless quality of testing is better understood.

Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: case study of COVID-19 in Alberta, Canada and Philadelphia, USA.

BACKGROUND: Despite widespread use, the accuracy of the diagnostic test for SARS-CoV-2 infection is poorly understood. The aim of our work was to better quantify misclassification errors in identification of true cases of COVID-19 and to study the impact of these errors in epidemic curves using publicly available surveillance data from Alberta, Canada and Philadelphia, USA. METHODS: We examined time-series data of laboratory tests for SARS-CoV-2 viral infection, the causal agent for COVID-19, to try to explore, using a Bayesian approach, the sensitivity and specificity of the diagnostic test. RESULTS: Our analysis revealed that the data were compatible with near-perfect specificity, but it was challenging to gain information about sensitivity. We applied these insights to uncertainty/bias analysis of epidemic curves under the assumptions of both improving and degrading sensitivity. If the sensitivity improved from 60 to 95%, the adjusted epidemic curves likely falls within the 95% confidence intervals of the observed counts. However, bias in the shape and peak of the epidemic curves can be pronounced, if sensitivity either degrades or remains poor in the 60-70% range. In the extreme scenario, hundreds of undiagnosed cases, even among the tested, are possible, potentially leading to further unchecked contagion should these cases not self-isolate. CONCLUSION: The best way to better understand bias in the epidemic curves of COVID-19 due to errors in testing is to empirically evaluate misclassification of diagnosis in clinical settings and apply this knowledge to adjustment of epidemic curves.