Workforce Serosurveillance to Track Long-term Modifications to COVID-19 Exposure Due to Factors in the Built Environment

The objective of this study is to understand the COVID-19/SARS-CoV-2 disease incidence, prevalence, and trajectory over time, by conducting follow-up antibody testing on employees by first following up with the approximately 5,600 team members who were positive and then extending the invitation to the remaining team members (approximately 65,212).

Aim 1) Follow those who tested positive during prior institutional antibody testing to better understand whether IgG or total antibody measures confer continued immunity; hypothesis 1 is that prior infection will be protective and that restricting testing to prior positives, reduces impact of false positive results due to low prevalence populations. Over a 1.5 year period, testing will be repeated on seropositive individuals in January 2021, May 2021, September of 2021, January 2022, and May 2022.

The results will be to document antibody seropositivity and continued presence of immunity over time. The study investigators will invite those positive Northwell team members to participate in a research study that has the aim of testing for continued presence of antibodies to COVID-19, to understand trends over time.

Aim 2) Continue to document seroconversion rates and distribution of exposure to COVID-19 across the entire remaining workforce; hypothesis 2 is that employees will have lower rates than the general population, even though false positive serology results will be highly dependent upon New York State positive prevalence rates. Over the same 1.5 year period as in Aim 1, testing will be repeated for all workforce participants who previously tested negative and others interested in participating for the first time in May 2021 (or September 2021) and May 2022.

Aim 3) Track any associations between engineering, administrative, and personal protective equipment (PPE) policies across the health system and whether these continue to be protective and adapt to disease/viral behavior over time; hypothesis 3 is that Northwell Health policies are proactive and protective and that co-exposures to environmental factors in the workplace and community are measurable and remediable with respect to their effects on COVID-19 infection rates. The investigators propose to complete three things. First, they will be linking job title, department, and industry codes from participant records, with occupational indices of workplace exposure, such as O*Net. This will create a job or task exposure matrix (JEM) for job groups in the Northwell Health system. This JEM will reflect conventional understanding of job level exposure risk estimates to work stressors that may be physical (e.g., heavy loads), psychosocial (e.g., job demand/control), noise, and chemical (e.g., peracetic acid cleaners). Second, they will link departmental level policy information on personal protective equipment (PPE) for each job/task; administrative policies on work hours for the job and chemicals used for infection control at the unit level; and engineering (ventilation rates) at the building and unit level (e.g., air changes per hour and occupancy limits). This institutional policy information will be gathered from January 2021 to each wave of data collection. Any changes in policy will be documented and the most recent policy will be linked with the job title information. Third, the investigators will integrate community variable census information (at the census tract or zip code level) on neighborhood air quality, poverty rates, language predominance, nativity (US or other), and household density. The study will include travel distance to work and transportation mode.

The investigators anticipate that findings from this work, particularly from Aim 3, have implications that extend to communities across New York State (Northwell Health is the largest employer in New York and its employee residences and work locations span every county). They also believe that this work has broader national and international relevance, as the world continues global efforts to navigate a built environment in which SARS-CoV-2 now exists in a pandemic. The strengths of this study are that it accesses a large population sample of 70,812 people that is diverse and also self-contained, whereby, multiple work, home, and environmental factors can be measured alongside trajectories in COVID-19 prevalence. The population is economically and culturally diverse, even by global standards, and includes Queens County that has recorded some of the highest seropositivity rates to date.