Abstract
Background and purpose:
Early on in the COVID-19 pandemic, New York City (NYC) vowed to “keep the subways running” despite the lack of plans in place for protecting the health and well-being of transit workers. This study was designed to assess the impact of employment during the early phase of the pandemic on this essential frontline workforce.
Methods, settings, and study participants:
A convenience sample of members (stratified by job title) of the NYC Transport Workers Union, Local 100, was recruited in August 2020 to participate in an anonymous, cross-sectional, internet-based survey.
Results:
The demographics of the sample participants (N = 645) reflected union membership, ie, 82 percent male, 29 percent Black; 27 percent Hispanic, and 59 percent ≥age 50 years. At the time of the “NYC Pause” (March 22, 2020) when mandatory stay-at-home orders were issued, transit workers had limited worksite protections. Many reported a lack of such basics as face masks (43 percent), hand sanitizer (40 percent), and disposable gloves (34 percent). A high proportion (87 percent) were concerned about getting infected at work. Lack of certain protections was significantly associated with both fear of contagion at work and mental health symptoms. Nearly 24 percent of participants reported a history of COVID-19 infection. Self-reported infection was significantly correlated with lack of certain protections, including respiratory masks (p < 0.001), disposable gloves (p < 0.001), and hand sanitizer (p < 0.001). Infection was also significantly associated with mental health symptoms (p < 0.001). By August 2020, despite participants reporting that many worksite protections were then in place, 72 percent of workers were still fearful for their safety at work, eg, because of potential exposure due to passengers not wearing masks, and risk of verbal abuse and physical assault by passengers angered when asked to wear face masks. Workers who were fearful for their safety at work were more than six times more likely to report mental health symptoms (p < 0.001).
Conclusions:
Lack of worksite protections before “NYC Pause” (March 22, 2020) was significantly associated with self-reported infection, fear, and mental health symptoms in TWU, Local 100 members. To reduce the risk of adverse impacts associated with bioevents in all essential work groups, and across all essential occupational settings, infection control preparedness, early recognition of risk, and implementation of tailored risk reduction strategies are imperative. Pandemic preparedness is fundamental to protecting the health and well-being of essential workers and crucial in controlling the spread of disease in the community. Bioevent preparedness for all essential frontline workgroups will also help reduce occupational health inequities. Workers at risk, regardless of setting, deserve and have the right to equal protections under federal and state law.
Keywords: transit workers, COVID-19 pandemic, Fear, mental health, disaster planning
INTRODUCTION
Critical infrastructure industries remained functional during shelter-in-place/stay-at-home orders throughout the COVID-19 pandemic because of the continued employment of essential workers. Much media and research attention has focused on the role of frontline healthcare workers in providing essential services and the impact this has had on their health and well-being. Far less attention has been paid to the impact of the pandemic on other types of essential workers. Most of our knowledge on the effect of disease bioevents (outbreaks, epidemics, and pandemics) on essential workers comes from pre-COVID-19 studies that focused primarily on healthcare and emergency response personnel. These studies documented rates of willingness to work during bioevents ranging from a low of 35 percent to a high of 80 percent.1–14 Highly skilled emergency room clinicians and emergency medical service workers were the most willing. Less-skilled workers, in roles without direct patient care, were the least willing. Fear of contagion and fear of spread to family were the main drivers of lack of willingness, whereas sense of professional obligation and trust in employers’ preparedness to protect workers were the main facilitators.11,14 Studies have found that even when that trust is well founded and ample and effective control measures are in place, serious adverse outcomes may still result during bioevents, including exposure, infection, and fatalities.15 Risk of exposure and infection have been shown to be related to the intensity of contact with infected patients, implementation and effectiveness of infection control measures, and other occupational risk factors.15,16
Frontline healthcare and emergency response workers at risk of exposure to potentially fatal diseases during bioevents are also at risk of short- and long-term psychosocial and mental health problems. Several studies, including a recent systematic review by Cabarkapa et al., have documented the psychological toll of bioevents, including COVID-19, and noted an increased risk of stress-related disorders, depression, and anxiety in frontline caregivers, with fear a main contributor to stress.17–20
Information on the impact of reporting to work during bioevents is extremely limited, especially for nonclinical essential workers. NYC transit workers, who were suddenly thrust into a frontline work role during COVID-19, are considered “essential” because they are employed in transportation, one of the sixteen critical mass infrastructure sectors considered so vital to US national interest that their “incapacitation or destruction would have a debilitating effect on security, national economic security, national public health or safety, or any combination thereof.”21 In recognition of the vital role mass transit plays in NYC, Mayor De Blasio vowed early on in the pandemic to “keep the subways running”22 even though, at the time, there was limited and/or conflicting worksite safety information provided by the Centers for Disease Control and Prevention (CDC) and the Occupational Safety and Health Administration (OSHA).23,24 Soon after the first few cases of COVID-19 were identified in NYC, infections, hospitalizations, isolation, quarantine, and deaths were reported among transit workers.25,26 Furthermore, unlike frontline healthcare workers who were widely praised as heroes, many transit workers were verbally abused and sometimes stigmatized by riders based on their race or ethnicity, and even physically assaulted by riders angered about being asked to wear face masks.27 Research on the health and mental health impact of the COVID-19 pandemic on non-healthcare essential workers, including transit workers, is exceptionally sparse. The overarching goal of this study was to inform risk reduction strategies, including pandemic planning, for transit and other essential industries.
METHODS
Sample and data collection
In collaboration with our community partner, the Transport Workers Union (TWU), Local 100, a cross-sectional, anonymous survey was conducted in August 2020. A link to the self-administered survey, hosted on an SSL-secured platform, Qualtrics,28 was sent via email by union leadership to a stratified convenience sample (by job type) of roughly 3,000 members of the NYC TWU, Local 100. There are roughly 35,000 NYC transit workers who are members of the TWU, Local 100. The survey was completed by 645 participants over a three-week period.
After review by content experts to refine the survey, the final version included 39 items. Pilot testing indicated that survey completion time ranged from 15 to 20 minutes. Informed consent was obtained prior to the start of the survey. All survey participants were assigned a unique code number and no personal identifying information was collected. No incentives for participation were provided. All study procedures had prior review and exemption by the NYU Office of Human Subjects Protection.
Survey
The survey included questions in four domains: (1) demographic and occupational characteristics and protections at work; (2) history of COVID-19 infection, vaccine intentions (if and when available), and reasons for vaccine hesitancy if no intentions; (3) fear for safety at work; and (4) mental health symptoms. Domain 1 reflects the predictor variables of interest whereas domains 2–4 reflect the outcome variables of interest.
Demographic questions included age, gender, race, ethnicity, marital status, pre-existing health problems, and information about household members. Occupational characteristics included work division, ie, bus or subway, and job title, which were recoded into public- and non-public-facing job categories. Availability of worksite protections was assessed at two points of time, “pre-NYC Pause” (March 2020) and “post-NYC Pause” (measured in August 2020); items included respiratory mask, surgical/cloth mask, face shield/goggles, disposable gloves, hand sanitizer, soap, cleaning/disinfecting products, and Plexiglas protective barriers. Additionally, new safety measures that were put into place after “NYC Pause” were also assessed, such as enhanced cleaning and disinfection of subways and buses and limiting number of passengers to prevent crowding.
Self-reported history of COVID-19 infection was determined by a positive response to any one or more of the following items: positive diagnosis by healthcare professional, positive nasal swab (PCR) test, history of hospitalization for COVID-19 treatment, and positive antibody test for COVID-19. Vaccine intention was measured by a single item; eight response choices (plus “other”) were provided to indicate the reasons for not taking an eventual vaccine.
Fear was measured using a single item: “Are you currently fearful for your safety at work?” Seven possible response choices (plus “other”) were available to describe the sources of fear at work. To measure mental health symptoms, we adapted questions from the General Health Questionnaire (GHQ-4),29 including subscales for anxiety and depression, and added two new items addressing sleep problems and eating problems, for a total of six items.
Statistical methods
To assess the association between the predictor variables (demographic, occupational characteristics, and protections at work) and outcome variables (history of COVID-19 infection, fear, and mental health symptoms; results are shown in Tables 1–4), odds ratios (ORs) and their 95% confidence intervals (CIs) were calculated using logistic regression procedures. Analyses were performed using SPSS 27.030 and STATA MP 16.31
Table 1.
Mental Health Symptoms, Fear, and History of COVID-19 Infection by Demographic Characteristics, NYC Transit Workers, August 2020 (N= 645; % unless noted)
| n (%) | % COVID-19 Infection | OR1 (95% CI2) | % Fear | OR2 (95% CI3) | % MH3 Symptoms | OR2 (95% CI3) | |
|---|---|---|---|---|---|---|---|
| Variables | |||||||
| Pre-Existing Health Problem | |||||||
| Yes | 175 (42.5) | 23.4 | 0.94 (0.60, 1.49) | 76.3 | 1.82 (1.15, 2.88)* | 83.2 | 1.64 (0.99, 2.73) |
| No | 237 (57.5) | 24.5 | 1.00 | 63.9 | 1.00 | 75.1 | 1.00 |
| Age | |||||||
| < 50 | 263 (40.8) | 21.7 | 1.00 | 76.9 | 1.00 | 85.7 | 1.00 |
| ≥ 50 | 382 (59.2) | 25.1 | 1.21 (0.84, 1.76) | 68.0 | 0.64 (0.44, 0.94)* | 75.7 | 0.52 (0.34, 0.80)** |
| Gender | |||||||
| Male | 512 (81.7) | 22.7 | 0.70 (0.44, 1.10) | 69.6 | 0.59 (0.35, 1.00) | 78.5 | 0.65 (0.37, 1.14) |
| Female | 115 (18.3) | 29.6 | 1.00 | 79.4 | 1.00 | 84.8 | 1.00 |
| Race | |||||||
| White | 221 (34.3) | 23.1 | 1.00 | 62.2 | 1.00 | 74.3 | 1.00 |
| Black/African American | 189 (29.3) | 23.8 | 1.04 (0.66, 1.65) | 75.0 | 1.82 (1.16, 2.87)** | 82.9 | 1.67 (1.02, 2.75)* |
| Asian/Native American/Alaska Native/Native Hawaiian/Pacific Islander | 50 (7.8) | 30.0 | 1.43 (0.72, 2.82) | 69.1 | 1.36 (0.66, 2.77) | 83.3 | 1.73 (0.73, 4.13) |
| Multiracial | 8 (1.2) | 12.5 | 0.48 (0.06, 3.96) | 85.7 | 3.65 (0.43, 30.89) | 100.0 | -- |
| Missing/Don’t Know/Refused | 177 (27.4) | 23.2 | 1.00 (0.63, 1.61) | 80.0 | 2.43 (1.50, 3.95)*** | 81.3 | 1.50 (0.92, 2.46) |
| White | 221 (47.2) | 74.3 | 1.00 | 62.2 | 1.00 | 23.1 | 1.00 |
| Non-White | 247 (52.8) | 83.5 | 1.75 (1.10, 2.79)* | 74.2 | 1.75 (1.15, 2.66)** | 24.7 | 1.09 (0.71, 1.67) |
| Hispanic Ethnicity | |||||||
| Yes | 155 (27.0) | 22.6 | 0.92 (0.59, 1.42) | 79.0 | 1.86 (1.17, 2.96)** | 85.4 | 1.71 (1.02, 2.84)* |
| No | 419 (73.0) | 24.1 | 1.00 | 66.9 | 1.00 | 77.5 | 1.00 |
| Marital Status | |||||||
| Married/Cohabitating | 443 (72.7) | 23.7 | 1.00 | 73.0 | 1.00 | 80.8 | 1.00 |
| Not Married/No Partner | 166 (27.3) | 24.7 | 1.06 (0.70, 1.60) | 68.2 | 0.80 (0.53, 1.20) | 76.6 | 0.78 (0.50, 1.21) |
| Household Members | |||||||
| At least one person under 18 years old | 282 (43.7) | 24.8 | 1.11 (0.77, 1.60) | 73.9 | 1.22 (0.84, 1.77) | 84.2 | 1.65 (1.09, 2.49)* |
| At least one person over 60 years old | 210 (32.6) | 19.5 | 0.70 (0.47, 1.05) | 71.2 | 0.98 (0.66, 1.44) | 79.7 | 1.00 (0.65, 1.53) |
| At least one person with chronic health problems | 177 (27.4) | 21.5 | 0.84 (0.55, 1.27) | 85.3 | 2.93 (1.80, 4.78)*** | 87.2 | 2.04 (1.23, 3.39)** |
| 3+ Household Members | 407 (63.6) | 23.3 | 0.96 (0.66, 1.40) | 74.3 | 1.46 (1.00, 2.11)* | 79.9 | 1.00 (0.67, 1.52) |
p < 0.05
p < 0.01
p < 0.001
Unadjusted odds ratio
95% confidence interval
Mental health
Table 4.
Mental Health Symptoms by Work Environment Characteristics, NYC Transit Workers, August 2020 (N= 645; % unless noted)
| n(%) | % MH1 Symptoms | OR2 (95% CI3) | |
|---|---|---|---|
| Variables | |||
| Know Someone who was Infected with COVID-19 | |||
| Yes | 557 (91.2) | 81.7 | 3.07 (1.71, 5.50)*** |
| No | 54 (8.8) | 59.3 | 1.00 |
| History of Home Quarantine/Isolation due to Work Exposure | |||
| Yes | 234 (38.4) | 87.6 | 2.40 (1.52, 3.77)*** |
| No | 375 (61.6) | 74.7 | 1.00 |
| History of COVID-19 Infection | |||
| Yes | 153 (23.7) | 90.1 | 2.82 (1.58, 5.00)*** |
| No | 492 (76.3) | 76.3 | 1.00 |
| Knows Someone who has Died from COVID-19 | |||
| Yes | 465 (76.23) | 83.9 | 2.52 (1.64, 3.86)*** |
| No | 165 (23.77) | 67.4 | 1.00 |
| Work Division | |||
| Bus | 195 (30.2) | 80.4 | 1.00 |
| Subway | 450 (69.8) | 79.4 | 0.94 (0.61, 1.45) |
| Type of Job with Respect to Contact with the Public | |||
| Public facing | 401 (62.4) | 83.6 | 1.79 (1.20, 2.67)** |
| Non-public facing | 242 (37.6) | 74.0 | 1.00 |
| Difficulty Accessing PPE and Other Protections at Work, Before “NYC Pause” (March 22, 2020) | |||
| Respiratory Mask | 342 (53.0) | 88.0 | 3.25 (2.14, 4.92)*** |
| Surgical Mask/Cloth Mask | 277 (43.0) | 89.2 | 3.22 (2.06, 5.05)*** |
| Face shield/Goggles | 199 (30.9) | 90.4 | 3.21 (1.91, 5.41)*** |
| Gloves | 216 (33.5) | 91.2 | 3.72 (2.21, 6.27)*** |
| Hand Sanitizer | 255 (39.5) | 87.8 | 2.53 (1.63, 3.95)*** |
| Soap | 121 (18.8) | 92.5 | 3.77 (1.85, 7.68)*** |
| Cleaning/Disinfecting Products | 190 (29.5) | 92.1 | 4.04 (2.28, 7.15)*** |
| Plexiglas Protective Barriers | 151 (23.4) | 91.4 | 3.38 (1.84, 6.20)*** |
| Difficulty Accessing PPE and Other Protections at Work, After “NYC Pause” (March 22, 2020) | |||
| Respiratory Mask | 129 (20.0) | 94.5 | 5.53 (2.51, 12.17)*** |
| Surgical Mask/Cloth Mask | 70 (10.9) | 92.8 | 3.60 (1.42, 9.15)** |
| Face shield/Goggles | 117 (18.1) | 92.2 | 3.60 (1.77, 7.33)*** |
| Gloves | 95 (14.7) | 95.7 | 6.80 (2.45, 18.90)*** |
| Hand Sanitizer | 93 (14.4) | 92.4 | 3.53 (1.59, 7.85)** |
| Soap | 62 (9.6) | 93.4 | 3.98 (1.41, 11.18)** |
| Cleaning/Disinfecting Products | 120 (18.6) | 93.3 | 4.28 (2.03, 9.04)*** |
| Plexiglas Protective Barriers | 96 (14.9) | 91.6 | 3.15 (1.49, 6.70)** |
| Safety Measures at Work in August 2020 | |||
| Physical barriers to maintain six feet of social distancing | 205 (31.8) | 79.0 | 0.94 (0.62, 1.42) |
| Signage to maintain social distancing and prevent crowding | 386 (59.8) | 76.4 | 0.56 (0.36, 0.86)** |
| Limits on number of passengers to prevent crowding | 88 (13.6) | 77.3 | 0.84 (0.49, 1.45) |
| Enhanced cleaning and disinfection procedures | 374 (58.0) | 76.9 | 0.63 (0.42, 0.97)* |
| Plastic shields/sheeting/barrier to protect against close contact with public | 181 (28.1) | 77.4 | 0.82 (0.54, 1.25) |
| Fear for Safety at Work in August 2020 | |||
| Yes | 407 (71.5) | 89.4 | 6.26 (4.01, 9.76)*** |
| No | 162 (28.5) | 57.5 | 1.00 |
p < 0.05
p < 0.01
p < 0.001
Mental health
Unadjusted odds ratio
95% confidence interval
RESULTS
Sample characteristics
The demographics of the final sample (N = 645) (shown in Table 1) mirrored the demographics of the TWU, Local 100 membership. Participants were predominantly male (82 percent), middle age (median age = 52 years, mode = 55 years, range: 20–75 years), and racially and ethnically diverse (35 percent non-Hispanic White, 29 percent non-Hispanic Black, and 27 percent Hispanic). Most (73 percent) were married or cohabitating and 43 percent reported one or more pre-existing health conditions. Nearly half (44 percent) of the sample had at least one person in the household under the age of 18 years and 27 percent had at least one household member with a chronic disease. A large proportion (64 percent) reported three or more people living in their household.
History of COVID-19 infection was not associated with age, gender, Hispanic ethnicity, pre-existing health condition, or number of people in household. A positive history of COVID-19 infection was not associated with race, even when the race variable was dichotomized (White/non-White, p < 0.01). Only 30 percent of participants intended to receive the COVID-19 vaccine once it became available; 38 percent were not sure and 32 percent said they would not take it. The main reason for not taking it or being unsure was lack of trust in its safety.
History of COVID-19 infection and occupational risk factors
Overall, 24 percent reported a history of COVID-19 infection, generally diagnosed by a healthcare professional (17.9 percent) or confirmed by a positive antibody test (6 percent). As shown in Table 2, most workers (91 percent) reported that they knew someone who had been infected with COVID-19 and 76 percent knew someone who had died. History of quarantine (38 percent) due to a work exposure was associated with self-reported history of COVID-19 infection (p < 0.001) as was knowing someone who had been infected with COVID-19 (p < 0.01). Most (70.0 percent) of the workers were employed in the subway division as opposed to bus (30.0 percent) and 62.4 percent worked in a public-facing job. Job division was not associated with a self-reported history of COVID-19, nor was working in an outward facing job. However, concern about getting infected either at work (87.0 percent) or in the community (68.0 percent) was significantly correlated with self-reported history of COVID-19 infection (p < 0.001).
Table 2.
History of COVID-19 Infection by Work Environment Characteristics, NYC Transit Workers, August 2020 (N= 645; % unless noted)
| n(%) | % COVID-19 Infection | OR1 (95% CI2) | |
|---|---|---|---|
| Variables | |||
| Know Someone who was Infected with COVID-19 | |||
| Yes | 557 (91.2) | 26.6 | 6.15 (1.89, 20.01)** |
| No | 54 (8.8) | 5.6 | 1.00 |
| History of Home Quarantine/Isolation due to Work Exposure | |||
| Yes | 234 (38.4) | 50.0 | 10.36 (6.68, 16.09)*** |
| No | 375 (61.6) | 8.8 | 1.00 |
| Self-reported History of COVID-19 Infection | |||
| Yes | 153 (23.7) | 23.7 | -- |
| No | 492 (76.3) | 76.3 | -- |
| Know Someone who has Died from COVID-19 | |||
| Yes | 465 (76.23) | 25.8 | 1.28 (0.82, 2.00) |
| No | 165 (23.77) | 21.4 | 1.00 |
| Work Division | |||
| Bus | 195 (30.2) | 23.6 | 1.00 |
| Subway | 450 (69.8) | 23.8 | 1.01 (0.68, 1.50) |
| Type of Job with Respect to Contact with the Public | |||
| Public facing | 401 (62.4) | 24.7 | 1.14 (0.78, 1.67) |
| Non-public facing | 242 (37.6) | 22.3 | 1.00 |
| Difficulty Accessing PPE and Other Protections at Work, Before “NYC Pause” (March 22, 2020) | |||
| Respiratory Mask | 342 (53.0) | 29.2 | 1.95 (1.34, 2.84)** |
| Surgical Mask/Cloth Mask | 277 (43.0) | 27.1 | 1.38 (0.96, 1.99) |
| Face shield/Goggles | 199 (30.9) | 28.1 | 1.41 (0.96, 2.06) |
| Gloves | 216 (33.5) | 31.5 | 1.86 (1.28, 2.70)** |
| Hand Sanitizer | 255 (39.5) | 29.8 | 1.73 (1.20, 2.49)** |
| Soap | 121 (18.8) | 28.1 | 1.33 (0.85, 2.08) |
| Cleaning/Disinfecting Products | 190 (29.5) | 31.1 | 1.73 (1.18, 2.53)** |
| Plexiglas Protective Barriers | 151 (23.4) | 29.8 | 1.52 (1.01, 2.28)* |
| Difficulty Accessing PPE and Other Protections at Work, After “NYC Pause” (March 22, 2020) | |||
| Respiratory Mask | 129 (20.0) | 27.1 | 1.26 (0.81, 1.95) |
| Surgical Mask/Cloth Mask | 70 (10.9) | 17.1 | 0.64 (0.33, 1.22) |
| Face shield/Goggles | 117 (18.1) | 30.8 | 1.56 (1.00, 2.43)* |
| Gloves | 95 (14.7) | 24.2 | 1.03 (0.62, 1.72) |
| Hand Sanitizer | 93 (14.4) | 20.4 | 0.80 (0.47, 1.37) |
| Soap | 62 (9.6) | 32.3 | 1.61 (0.91, 2.84) |
| Cleaning/Disinfecting Products | 120 (18.6) | 24.2 | 1.03 (0.65, 1.64) |
| Plexiglas Protective Barriers | 96 (14.9) | 19.8 | 0.76 (0.45, 1.31) |
| Safety Measures at Work in August 2020 | |||
| Physical barriers to maintain six feet of social distancing | 205 (31.8) | 25.9 | 1.19 (0.81, 1.74) |
| Signage to maintain social distancing and prevent crowding | 386 (59.8) | 26.2 | 1.41 (0.97, 2.06) |
| Limits on number of passengers to prevent crowding | 88 (13.6) | 30.7 | 1.51 (0.92, 2.48) |
| Enhanced cleaning and disinfection procedures | 374 (58.0) | 26.2 | 1.39 (0.96, 2.03) |
| Plastic shields/sheeting/barrier to protect against close contact with public | 181 (28.1) | 28.2 | 1.39 (0.94, 2.06) |
| Fear for Safety at Work in August 2020 | |||
| Yes | 407 (71.5) | 26.3 | 1.29 (0.84, 2.00) |
| No | 162 (28.5) | 21.6 | 1.00 |
p < 0.05
p < 0.01
p < 0.001
Unadjusted odds ratio
95% confidence interval
Before the “NYC Pause,” when stay-at-home orders were instituted (March 22, 2020), transit workers reported difficulty in accessing a wide range of personal protective equipment (PPE) and other equipment and supplies; for example, respiratory masks (53 percent), surgical/cloth masks (43 percent), face shields/goggles (31 percent), disposable gloves (34 percent), soap for handwashing (19 percent), cleaning and disinfecting products (30 percent), hand sanitizer (40 percent), and Plexiglas protective barriers (23 percent). As shown in Table 2, difficulty in obtaining certain protective items before “NYC Pause” was associated with self-reported COVID-19 infection, including respiratory masks (p < 0.01), disposable gloves (p < 0.01), hand sanitizer (p < 0.01), cleaning and disinfectant products (p < 0.01), and Plexiglas protective barriers (p < 0.05). After the “NYC Pause” ended, ie, after June 13, 2020, self-reported infection was significantly associated with only a single item: difficulty obtaining face shields/goggles (p < 0.05).
Fear for safety at work
In August 2020, 71.5 percent of participants reported that they were currently fearful for their safety at work; this was related to the following: (1) fear of being attacked when asking riders to wear a mask (46 percent); (2) lack of PPE (43 percent); (3) passengers not wearing masks (42 percent); and (4) fear of being attacked by riders for not enforcing the mask requirements on other, noncompliant riders (38 percent) (data not shown).
As shown in Table 1, fear for safety was significantly correlated with several personal characteristics: history of pre-existing health problems (p < 0.05); age under 50 years (p < 0.05); race (Black/African American) (p < 0.01); Hispanic ethnicity (p < 0.01); someone in household with a chronic health problem (p < 0.001) and sharing household with three or more other household members (p < 0.05).
In Table 3, significant associations with fear were also noted for the following: knowing someone who had been infected with COVID-19 (p < 0.01), history of home quarantine due to work exposure (p < 0.001), knowing someone who had died of COVID-19 (p < 0.01), and job with direct contact with the public (p < 0.01). Fear was not associated with work division (subway vs bus) or history of COVID-19 infection.
Table 3.
Fear for Safety at Work by Work Environment Characteristics, NYC Transit Workers, August 2020 (N= 645; % unless noted)
| n(%) | % Fear | OR1 (95% CI2) | |
|---|---|---|---|
| Variables | |||
| Know Someone who was Infected with COVID-19 | |||
| Yes | 557 (91.2) | 73.4 | 2.24 (1.24, 4.07)** |
| No | 54 (8.8) | 55.1 | 1.00 |
| History of Home Quarantine/Isolation due to Work Exposure | |||
| Yes | 234 (38.4) | 83.5 | 2.78 (1.82, 4.22)*** |
| No | 375 (61.6) | 64.6 | 1.00 |
| History of COVID-19 Infection | |||
| Yes | 153 (23.7) | 75.4 | 1.29 (0.84, 2.00) |
| No | 492 (76.3) | 70.3 | 1.00 |
| Know Someone who has Died from COVID-19 | |||
| Yes | 465 (76.23) | 75.4 | 1.95 (1.30, 2.94)** |
| No | 165 (23.77) | 61.0 | 1.00 |
| Work Division | |||
| Bus | 195 (30.2) | 75.6 | 1.00 |
| Subway | 450 (69.8) | 69.9 | 0.75 (0.49, 1.13) |
| Type of Job with Respect to Contact with the Public | |||
| Public facing | 401 (62.4) | 75.7 | 1.68 (1.16, 2.43)** |
| Non-public facing | 242 (37.6) | 64.9 | 1.00 |
| Difficulty Accessing PPE and Other Protections at Work Before, “NYC Pause” (March 22, 2020) | |||
| Respiratory Mask | 342 (53.0) | 80.0 | 2.79 (1.92, 4.05)*** |
| Surgical Mask/Cloth Mask | 277 (43.0) | 80.0 | 2.29 (1.57, 3.34)*** |
| Face shield/Goggles | 199 (30.9) | 82.3 | 2.42 (1.59, 3.70)*** |
| Gloves | 216 (33.5) | 82.9 | 2.65 (1.75, 4.02)*** |
| Hand Sanitizer | 255 (39.5) | 80.4 | 2.27 (1.55, 3.34)*** |
| Soap | 121 (18.8) | 87.6 | 3.45 (1.94, 6.14)*** |
| Cleaning/Disinfecting Products | 190 (29.5) | 84.7 | 3.00 (1.92, 4.70)*** |
| Plexiglas Protective Barriers | 151 (23.4) | 84.8 | 2.77 (1.70, 4.52)*** |
| Difficulty Accessing PPE and Other Protections at Work, After “NYC Pause” (March 22, 2020) | |||
| Respiratory Mask | 129 (20.0) | 88.3 | 3.77 (2.12, 6.69)*** |
| Surgical Mask/Cloth Mask | 70 (10.9) | 85.7 | 2.63 (1.31, 5.27)** |
| Face shield/Goggles | 117 (18.1) | 87.2 | 3.28 (1.84, 5.83)*** |
| Gloves | 95 (14.7) | 87.4 | 3.20 (1.70, 6.05)*** |
| Hand Sanitizer | 93 (14.4) | 85.0 | 2.55 (1.40, 4.64)** |
| Soap | 62 (9.6) | 83.9 | 2.23 (1.10, 4.50)* |
| Cleaning/Disinfecting Products | 120 (18.6) | 88.3 | 3.72 (2.06, 6.72)*** |
| Plexiglas Protective Barriers | 96 (14.9) | 88.5 | 3.62 (1.88, 6.99)*** |
| Safety Measures at Work in August 2020 | |||
| Physical barriers to maintain six feet of social distancing | 205 (31.8) | 69.1 | 0.83 (0.57, 1.21) |
| Signage to maintain social distancing and prevent crowding | 386 (59.8) | 70.5 | 0.85 (0.58, 1.27) |
| Limits on number of passengers to prevent crowding | 88 (13.6) | 61.4 | 0.58 (0.36, 0.93)* |
| Enhanced cleaning and disinfection procedures | 374 (58.0) | 66.4 | 0.46 (0.30, 0.69)*** |
| Plastic shields/sheeting/barrier to protect against close contact with public | 181 (28.1) | 71.3 | 0.98 (0.66, 1.45) |
| Fear for Safety at Work in August 2020 | |||
| Yes | 407 (71.5) | 71.5 | -- |
| No | 162 (28.5) | 28.5 | -- |
p < 0.05
p < 0.01
p < 0.001
Unadjusted odds ratio
95% confidence interval
With respect to PPE and other supplies, difficulty accessing any of the items listed in Table 3 before the “NYC Pause” was significantly associated with fear (p < 0.001). After the “NYC Pause” ended, and items were more readily available, difficulty accessing any of the items listed was still significantly associated with fear, although in some cases, eg, surgical/cloth mask, hand sanitizer, and soap, to a lesser degree than before NYC Pause. Deep cleaning and disinfection of the subways, which began May 6, 2020, was significantly associated with a decreased risk of fear (p < 0.001). Policies limiting number of passengers to control crowding was also associated with decreased fear (p < 0.05).
Mental health symptoms
New onset mental health symptoms that began soon after the start of the COVID-19 pandemic were frequently reported by the sample; 60 percent reported feeling “nervous, anxious, on-edge, and cannot control worrying;” 15 percent reported feeling “isolated, down, depressed, or hopeless;” 13 percent reported “little interest in doing things with family and friends;” 10 percent could “not stop or control worrying;” 10 percent reported sleep problems; and 2 percent reported eating problems.
As shown in Table 1, personal characteristics were associated with COVID-19-related mental health symptoms. For example, older workers (≥50 years of age) were significantly less likely (p < 0.01) to report new onset mental health symptoms since the COVID-19 pandemic began, and Black and Hispanic participants were more likely to report mental health symptoms (p < 0.05). Reports of mental health symptoms were also more likely if the household included someone 18 years or younger (p < 0.05) or someone with a chronic illness (p < 0.01).
Mental health symptoms were significantly associated with a number of COVID-19 health impact variables, as shown in Table 4. These included knowing someone who had been infected (p < 0.001) or had died from the infection (p < 0.001), history of home quarantine due to work exposure (p < 0.001), and self-reported history of infection (p < 0.001). No significant difference in terms of adverse mental health was noted for bus vs subway work divisions; however, working in a public facing job with direct general public contact was significantly associated with mental health symptoms (p < 0.01).
Difficulty obtaining any of the PPE and other protective equipment and supplies before “NYC Pause” was statistically associated with mental health symptoms (p < 0.001). Difficulty obtaining any of these after “NYC Pause” was also significantly associated with mental health symptoms (see Table 4). Enhanced cleaning and disinfection and signage to maintain social distancing and prevent crowding were associated with decreased risk of mental health symptoms. Participants who feared for their safety were over six times more likely to report mental health symptoms (p < 0.001). Self-reported infection with COVID-19 was also statistically associated with mental health symptoms (p < 0.001).
DISCUSSION
This study estimates the impact of the COVID-19 pandemic on this essential workgroup. Transit workers reported high rates of fear, mental health symptoms, and self-reported infection. During the peak of the pandemic in NYC, when worksite control measures were not yet fully implemented, an estimated 10,000 of the 70,000+ NYC transit workers (35K of whom are members of the TWU, Local 100) were placed in home quarantine, thousands tested positive, hundreds were hospitalized with infection, and, to date, 156 have died.25,26 Our study findings emphasize the serious impact the pandemic has had on this workforce. We did not note an increased risk in non-Whites, which differs from CDC data.32 Racial and ethnic disparities in COVID-19 have been ascribed to both a higher risk of SARS-CoV-2, likely due to increased risk of exposure, and a higher risk for severe COVID-19 disease, likely due to higher prevalence of underlying medical conditions. In our sample, workplace exposure might override the increased risk seen in minority populations.
The rate of self-reported infection in our sample was similar to other NYC first responders and public safety essential work populations. Sami et al.33 found that in a sample (collected in May–June 2020) of nearly 23,000 essential response personnel in NYC, 22.5 percent had SARS-CoV-2 antibodies. Transit workers’ self-reported positive history (24 percent) was somewhat lower than reported rates for emergency medical technicians (38 percent) or paramedics (31 percent), but higher than the rates for police (19 percent) and firefighters (21 percent). The rates reported in Sami et al33 were based on antibody testing and therefore likely to be more accurate compared to self-reports.
We found a significant association between self-reported history of infection and difficulty accessing certain types of PPE, most especially respiratory masks and disposable gloves. In a very large prospective, observational cohort study (with a sample of over 2 million people from the United Kingdom and the United States) with data collected using the COVID Symptom Study app, Nguyen et al.34 found that frontline healthcare workers had at least a threefold increased risk of COVID-19 compared to the general public. They also found that workers with inadequate PPE had an increased risk of infection, and that Black, Asian, and minority ethnic healthcare workers were also disproportionately at greater risk.
Over 70 percent of our sample reported being fearful for their safety at work; a sizable proportion were fearful of contagion spread by passengers, as well as fearful for their personal safety because of aggressive passengers. Fear of passengers was likely exacerbated by well-publicized reports of assaults, including an instance of a passenger deliberately coughing on a bus driver, who shortly thereafter died of COVID-19 infection.35 Fear in our sample was also significantly associated with having household members at increased risk of adverse outcomes associated with infection, such as a household member with a chronic illness. Fear of contagion and fear of spread to family have similarly been shown to be important risk factors for fear and lack of willingness to report to duty during bioevents in samples of frontline healthcare workers.11,14 Fear was also correlated with accessibility of PPE and other work-site protections. While data are exceptionally sparse on this issue in non-healthcare essential workers, in a very recent study of employees of a large medical center, Brand et al. found that nonclinical employees had the highest levels of fear of COVID-19.36
Transit workers in our study, similar to the experience of other essential workers, including healthcare, lacked PPE and other protections during the early peak of the pandemic. This naturally heightened their sense of fear. This may have been further exacerbated for transit and other non-healthcare essential workers because they had little or no access to the expertise of infection control specialists, and limited personal knowledge, training, and experience regarding transmission of potentially lethal infectious diseases. Although transit workers were clearly at risk of exposure, they did not have the same level of preparedness as other essential workers. This is an example of occupational health inequities, and further study is warranted on how best to address these types of workplace disparities with respect to bioevent preparedness.
In our study, difficulty in accessing PPE was also strongly correlated with mental health symptoms. The relationship between workplace contagion, fear, and adverse mental health is well established in frontline healthcare and emergency responder work-groups. For example, studies examining the impact of the 2005 SARS bioevent on the health and well-being of frontline workers similarly found adverse mental health impacts in workers with direct patient contact.19,37 Recently, studies on COVID-19 and mental health impacts in healthcare workers have been published; for example, Lai et al. 38 found strong correlations between the provision of direct frontline healthcare delivery during the COVID-19 pandemic and mental health problems, such as depression and anxiety. In another recent study on psychological distress among US healthcare workers during the COVID-19 pandemic, Young and colleagues found that 33 percent had high levels of clinically meaningful anxiety, 17 percent had moderate to severe depressive symptoms, 14 percent screened positive for post-traumatic stress disorder, and 5 percent had suicidal ideation.39
In our study, fear for safety at work was strongly correlated with mental health symptoms (OR 6.26, p < 0.001) and these were correlated with any aspect related to infection (knowing someone, being quarantined, being infected, family members in household who were at increased risk of adverse outcomes if infected, and self-reported infection). In a study by Lee et al.40 on survivors of SARS infection, an especially troubling finding was that healthcare workers who became SARS patients had an extremely high risk of PTSD (40.7 percent). There is a concern that transit workers who survived COVID-19 might be at risk of adverse long-term mental health outcomes. Therefore, early identification and treatment of workers with symptoms following this or any bioevent or other disaster events is critical to prevent long-term and possibly severe outcomes that are known to occur following disasters.
Unexpected findings in our study included the lack of association between public-facing jobs and history of COVID-19 infection. The public-facing job variable was constructed by combining job titles, which may have inadvertently obscured an association. In any case, during widespread community spread of disease during a pandemic, ascertainment of risk of exposure (community vs. work) may be difficult, especially without rigorous worksite data collection, surveillance, testing, and analysis. Future research is needed on best practices for supporting rapid and efficient conduct of epidemiological investigations in at-risk work settings (and in multiple work settings at the same time) so that focused risk-reduction measures can be swiftly implemented. Federal support is needed to develop and maintain public health and occupational health capabilities in bioevent risk assessment and risk management. The issue is pressing as bioevents are occurring with greater frequency and severity; nearly 100 new and emerging pathogens have been identified in just the past few decades.41
Another intriguing finding was the lack of association between fear and a positive history of COVID-19 infection. Although transit workers who reported a history of COVID-19 infection were significantly more likely to report mental health symptoms compared to uninfected workers, they were no more likely to report fear, perhaps because they had survived their infection and now felt protected. We were not able to explore this issue in greater depth due to sample size and design limitations. Future studies on fear and mental health in this context are warranted.
Finally, results from this study suggest some direction for reducing occupational exposure and occupational health disparities in non-healthcare essential workers. With the advent of COVID-19 vaccine availability since this survey was completed, future studies should focus on vaccine hesitancy as well as the long-term mental health impacts (and effective treatments) associated with employment during potentially lethal bioevents. Studies are needed on other non-healthcare essential workers such as food chain workers (including grocery workers, meat-packing plants, etc.,), delivery workers, pharmacy clerks, and many others. Also, strategic policy research is needed for developing, implementing, and maintaining appropriate pandemic preparedness plans (with worksite-specific infection control measures) for non-healthcare essential work settings. These plans should be required (and updated every three years or more often) for all essential work sectors. Worksite preparedness planning can build trust in both healthcare and non-healthcare essential workgroups and help ensure that the workforce is well protected and thus willing and able to safely continue to provide essential services during any future bioevent.
Limitations
An important limitation in our study was the use of a convenience sample, which limits our ability to generalize these findings to all of NYC transit or to other US transit systems. Our sample did, however, mirror the overall NYC transit worker population characteristics. Another limitation was the cross-sectional design, which precludes our ability to determine temporal associations. This study can, however, generate hypotheses for subsequent studies. Finally, we cannot exclude the possibility that participants may have provided socially desirable responses, even though the survey was anonymous. In spite of these limitations, this study provides new information and a foundation upon which more robust studies can be built.
ACKNOWLEDGMENTS
The authors wish to thank Mr. Tony Utano, President, Transport Workers Union, Local 100; Mr. Earl Phillips, Secretary Treasurer and Health and Safety Director; Mr. Pete Donohue, Director of Press and Media Relations; and Ms. Helen Mahoney, Administrative Assistant to the Secretary Treasurer. The authors also gratefully acknowledge the Transit Workers Union members who participated in this study. Ethical approval: This study received an approval from New York University’s Institutional Review Board (IRB-FY2020-4383).
Contributor Information
Robyn R. Gershon, Department of Epidemiology, New York University School of Global Public Health, New York, New York, New York.
Alexis A. Merdjanoff, Department of Social and Behavioral Sciences, New York University School of Global Public Health, New York, New York.
Gabriella Y. Meltzer, Department of Social and Behavioral Sciences, New York University School of Global Public Health, New York, New York.
Rachael Piltch-Loeb, Division of Policy Translation & Leadership Development, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Associate Research Scientist, Department of Social and Behavioral Sciences, New York University School of Global Public Health, New York, New York.
Jonathan Rosen, AJ Rosen & Associates, Schenectady, New York.
Ezinne M. Nwankwo, Department of Community Health Sciences, University of California Los Angeles Fielding School of Public Health, South Los Angeles, California.
Patty Medina, Department of Epidemiology, New York University School of Global Public Health, New York, New York.
David Vlahov, Yale School of Nursing; Orange; Professor, Department of Epidemiology, Yale School of Public Health, New Haven, Connecticut.
Martin F. Sherman, Department of Psychology, Loyola University Maryland, Baltimore, Maryland.
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