Big Data to help us understand COVID-19
Today's Managing Health Care Costs Number is 3
There's a lot of great "big data" work going on regarding COVID-19, and I'd like to highlight three projects that show how big data can make a real difference.
Most everyone has seen the Johns Hopkins map by now - and the velocity of the spread and deadliness of this virus has helped us see where there is future trouble -and helped motivate us to take public health warnings seriously. Johns Hopkins collects data from multiple sources - and in many instances these data are flawed. We all recognize that the number of cases is understated substantially, since there are many low-level or asymptomatic cases which are not being captured. This also inflates the case fatality rate - as the denominators are way understated. There will be a huge increase in stated cases when testing becomes widely available.
Here was the map on 3/10:
Here is the map two days ago:
Kinsa Health Weather Map (Temperature Monitoring)
Bluetooth-enabled thermometers let us see the progression of this pandemic. Kinsa, which has sells these thermometers, recently reported that fevers were dropping or holding steady in communities that ordered residents to shelter in place or stay at home -with no similar change in communities that recommended 'social distancing' without restricting travel outside the home. The Kinsa data is consistent with emergency department utilization data seen in both New York and Seattle.
Unacast Social Distancing Scoreboard
We can all look at deserted streets outside our homes, and skies empty of planes, and we know that people are traveling less. Unacast has taken deidentified cell phone data to show how much of a decrease in travel distance there is county-by-county. In my county (Middlesex, MA), there is a 55-70% decrease in miles traveled, and a 65-70% decrease in non-essential visits. There are a lot of states with much less physical distancing based on this analysis - and some of them are likely to suffer from much more viral spread over the coming weeks.
It might feel a bit creepy to see how much our phones are tracking our behavior- but they might become an important public health tool going forward. Israel is now using mobile phone records to determine who has been proximate to those who are infectious - and texting the requirement for mandatory self-quarantine based on this data. China used an app which showed red/yellow/green on the mobile phone for risk -and those without green were refused entrance into public places.
Traditional public health contact tracing takes well over a dozen hours per person. Using cell phones is worrisome from a privacy perspective, but might also allow scaling of exposure tracing that would support more targeted quarantine efforts if there is recurrence of spread of COVID-19 after the current shelter in place orders are lifted.
One additional note that’s more clinical:
A Mass Institute of Technology researcher reports that staying six feet away from others might not be enough. I'm not a respiratory droplet scientist- and he is -but I believe the risk from respiratory exposure likely decreases geometrically or exponentially by distance. So six feet is better than five feet - but not as good as 12 feet. The least risk is "nowhere near," which is why "shelter in place" leads to far fewer infections than "physical distancing." This also supports the idea that we should all wear (non-medical) masks if we must be in public – and I suspect we’ll see a change in CDC guidance in the near future.