Elisa Long is an expert in data analytics and modeling, including statistical and epidemiological analyses. Professor Long develops data-driven mathematical models in the context of healthcare operations management and other healthcare industry topics. She has been retained as an expert witness and has testified in deposition. Professor Long has provided expert testimony responding to an epidemiological model in a pharmaceutical industry matter.
In her research, Professor Long combines epidemiological modeling, economic analysis, and medical decision-making under uncertainty to analyze large and complex data. She uses these tools to assess the value and quality of health interventions, as well as effective allocation of limited resources.
Professor Long has applied a variety of analytical techniques—including machine learning (ML), Markov chain Monte Carlo methods, and queueing models—to predict long-term drug use, forecast infectious disease spread, and tailor the Federal Drug Administration’s (FDA’s) approval process to capture disease severity and other factors. She has also conducted empirical analysis related to patient length-of-stay inside a hospital and COVID-19 transmission among skilled nursing facilities.
Professor Long’s work has been widely published in academic journals and cited by regulatory agencies. The Federal Register cited her research in relation to COVID-19 vaccine mandates for healthcare workers. The Centers for Disease Control (CDC) featured an online tool she developed that enables skilled nursing facilities using shared staff to alert contacts following a COVID-19 outbreak. Professor Long has written for the Washington Post and given numerous talks and presentations, including at the CDC.
At the UCLA Anderson School of Management, Professor Long teaches courses on data and decision-making, healthcare analytics, and sports analytics. She has received numerous awards for excellence in teaching and research. Previously, she served on the faculty at Yale School of Management, teaching probability modeling and statistics, healthcare operations, and decision analysis courses.