Epidemiological models have played an influential role in governments’ responses to the COVID-19 pandemic. Yale SOM’s Edieal Pinker takes a look back at one of the most influential models and argues that such rigorous efforts at understanding the likely course of the disease, while imperfect, are critical to good decision making.
Nicolas Encina ’10 and his colleagues at Ariadne Labs have been demonstrating the potential of a collaborative, multidisciplinary process for designing and scaling simple improvements to healthcare—and also its limits.
With proper precautions, the risk of a day at work, a ride on the bus, or a workout at the gym may be acceptable, write Yale SOM’s Arthur J. Swersey and his co-authors. But that risk compounds dramatically when an activity is repeated day after day.
Yale SOM’s Edward Kaplan used early reports out of Wuhan to evaluate the likely effectiveness of common tactics, such as isolation of patients and quarantine, in keeping the disease from spreading in new regions.
A new study led by Yale SOM’s Arthur J. Swersey, using decision analysis techniques, finds that increasing the number of biopsy needles and using probability modeling to analyze the results can help prevent unnecessary treatment while identifying dangerous cancers.
This month, the Trump administration announced a series of steps to overhaul the kidney transplant system. We asked operations expert Vahideh Manshadi if the changes could make a difference for patients.