Injury, such as falls, motor vehicle crashes, and drug overdose, is a major source of morbidity and mortality. The interaction between injury and disease is complex and mutually causative. For instance, patients with Alzheimer’s Disease or Parkinson’s Disease are known to be at heightened risk of hip fracture from falls and in turn injurious falls among these patients can drastically alter the trajectory of the disease. So far, research on injury-disease interaction has been scant and fragmented. The proposed project is aimed at uncovering the gestalt of the relations between different injuries and different diseases through a data science approach.

Detailed data from approx. 40 million death certificates compiled by the National Center for Health Statistics, Centers of Disease Control and Prevention will be used for this project. On each death certificate, up to 20 diseases and injuries are coded according to the International Classification of Diseases, 10th Version. The student intern will work closely with Dr. Li and his team to map out the relations between injuries and diseases in decedents aged 65 years and older. At least one manuscript based on this study will be published with the student intern being a coauthor. This study will serve as proof of concept for the Human Morome Project, designed to understand the complex relations of all diseases and injuries (over 40000 specific diagnoses recognized by the World Health Organization) in different population groups.

One selected candidate will receive a stipend via the DSI Scholars program. Amount is subject to available funding.

Faculty Advisor

  • Professor Guohua Li
  • Department/School: Anesthesiology/P&S and Epidemiology/MSPH
  • Location: CUMC
  • Dr. Li is the M. Finster Professor and Director of the Center for Injury Epidemiology and Prevention. His research focuses on population health studies that encompass novel epidemiological designs, innovative statistical techniques, and complex data systems.

Project timeline

  • Earliest starting date: 03/01/2019
  • End date: 12/31/2019
  • Number of hours per week of research expected during Spring 2019: ~12
  • Number of hours per week of research expected during Summer 2019: ~28

Candidate requirements

  • Skill sets: Management of large databases and coding for machine learning.
  • Student eligibility (as of Spring 2019): freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Additional comments: especially looking for a candidate who is reliable and being a team player.