Meet Joanna Masel, a WeHealth advisor and Professor of Ecology and Evolutionary Biology at the University of Arizona. Joanna, what is your role at WeHealth?
I head up WeHealth’s research efforts. Our primary goal is to find ways to reduce the amount of virus transmission, while at the same time allowing society to open back up. This means making quarantine and testing recommendations more targeted towards the right people on the right days.
You have been instrumental in the risk assessment model that is incorporated into WeHealth’s exposure notification app. Can you provide an overview of how it works?
We use all the information we can to estimate how likely it is that someone got infected, and hence how important it is for them to quarantine. Many other groups focus on identifying contacts who meet the definition of being within six feet for 15 minutes from someone in an infectious window from two days before symptoms start to whenever they report a diagnosis and are assumed to be in isolation. But it is much more dangerous to be seven feet away from an infectious person for 10 minutes when they are most infectious around the time their symptoms start (an interaction that does not meet this standard definition) than it is to be five feet away for 15 minutes when they are not very infectious five or more days later. We take a holistic approach to total risk assessment. Bluetooth is great for telling us that two people were near each other at all, but the timing and duration of the interaction tell us more about risk than does the exact strength of the Bluetooth signal.
Aspects of how we assessed risk in the early version of the Google/Apple system have now been hard-baked into the second version by Google and Apple. Specifically, we calculate the expected dose of viruses as infectiousness by time, with a weighting for Bluetooth signal.
How do you feel this makes an impact on the spread of COVID-19?
Unlike other algorithms, the WeHealth app catches long exposures that were at more than six feet, and dangerous exposures that happened three days before symptom onset. At the same time, we don’t bother notifying people who are extremely unlikely to be infected after 15 minutes five feet away from a person whose symptoms started more than five days before. So we notify people who really are at risk of having being infected, while letting others get on with their lives.
The WeHealth app also tells people when they have a “low” exposure that is unlikely to lead to infection, and for which they don’t need to quarantine. People like to get feedback about whether their behavior on a given day was risky. We hope this feedback helps them make better decisions.
How do you anticipate this will continue to evolve given the rapidly increasing number of cases U.S. and around the world?
When there are so many cases, we believe that population-wide restrictions need to be tightened. At some point, when a pandemic is out of control, hospitals are over capacity, and everyone is a potential danger to others, then everyone who can needs to stay home. Contact tracing strategies of all kinds are most important when there are fewer cases. Tracing and quarantine focus restrictions on the minority who pose the most risk to others, which allows restrictions to ease up on everyone else. We discuss this in a preprint.
When there are so many cases, we recommend increasing the risk threshold in our app, so that it takes a more serious exposure before someone is singled out for quarantine. Hopefully, when vaccination starts to make a difference and case counts drop, we can lower the risk threshold in our app, and accelerate the process of opening up the economy. Our app is set up to be very regional, so it can have different risk thresholds in different places.