The REACH OUT study is a multi-institutional collaboration funded by the Health Effects Institute to determine if populations who have been chronically exposed to higher levels of air pollution are at greater risk of severe COVID-19 outcomes. The project will involve working with a harmonized repository of electronic health record data from multiple healthcare institutions in NYC that will be linked at the zip code level to city-wide air pollution data and neighborhood-level census variables. The project aims are:

Aim 1: Estimate the combined effect of chronic air pollution and neighborhood-level vulnerability on an individual’s risk of COVID-19 morbidity and mortality and determine if these exposures explain observed racial/ethnic disparities in COVID-19 outcomes.

Aim 2: Calculate excess risk of death due to COVID-19 using all-cause mortality data from the previous 5 years versus the current year and compare differences across neighborhoods with varying levels of chronic air pollution exposure.

This is a paid position which will provide students with the opportunity to use advanced analytic approaches to model high-dimensional data. End-products can include abstracts for conference presentation and journal publications. Students will join the team’s regular research meetings (via Zoom) where they can obtain feedback on works-in-progress.

Selected candidate(s) can receive a stipend directly from the faculty advisor. This is not a guarantee of payment, and the total amount is subject to available funding.

Faculty Advisor

  • Professor: Sandra Albrecht
  • Center/Lab:
  • Location: Epidemiology (Mailman)
  • Dr. Sandra Albrecht is an Assistant Professor of Epidemiology at the Mailman School of Public Health. Her research focuses on the social and environmental determinants of health in marginalized populations with an emphasis on improving access to quality care, and to affordable, healthy food.

Project Timeline

  • Earliest starting date: 9/13/21
  • End date: 8/31/22
  • Number of hours per week of research expected during Fall 2021: ~10
  • Number of hours per week of research expected during Summer 2022: ~20

Candidate requirements

  • Skill sets: Advanced programming skills; experience analyzing electronic health record data, conducting multi-level analyses and using machine learning approaches
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: Yes