First:

Contact Tracing of Surfaces Across Time

Another problem with contact tracing apps is they cannot detect contacts across time – nor aerosolized virus and droplets handing in the air.

Some one sits on a bus seat or commuter light rail seat, coughs, putting droplets on the seat and in the air around the seat. Then gets up and leaves. Another person boards and sits in that seat and touches it with their hands. The BLE model is unable to detect this contact. Considering that the NYC subway is now thought to have been a major vector for diseases transmission, this is a serious short coming.

Another example – some one sits at a table at Starbucks, coughs at the table a few times and then leaves. 1 minute later, someone else sits at that table and touches their hands on the table, or just breathes the aerosol or droplet cloud, and later scratches their nose. The contact tracing app cannot detect surface or air contamination scenarios across time. While Starbucks might clean tables frequently, there is no guarantee.

There is no way to solve this problem using a BLE contact algorithm that does not store actual location data – the BLE tracking app only detects instantaneous “moment in time” contacts.

This week the CDC said that may be surface contamination is not a big source of infections so perhaps this is no longer a big factor.

Does it Matter? May be not?

And then perhaps none of this matters. In Utah, where they have traced the source of most Covid-19 patients’ contacts, about 60% were traced to close family contacts that had the disease and about 25% to close social contacts. That’s 85% of all traced contacts. There were not many random connection contacts leading to becoming infected. Originally, China thought about 60% were due to random contacts – but it might be appropriate to extrapolate that – from congested cities where much of the population travels via public transit – to many U.S. states (like Utah) where public transit use may be just 1-2% of the population.

Moving Further Apart Can Increase Signal Strength!

Another interesting problem with BLE-based tracking apps. They rely on the BLE 1 mw discovery process which can send a signal out to about 10 meters. They combine this with the Received Signal Strength Indicator to estimate that a contact is within about 6-7 feet. In a pure “free space” environment, signal strength can approximate distance. But the real world is not a “free space” environment.

First, if the phone is in your left pocket and you stand several feet from another person on your right, whose phone is in their right pocket, the direct path may have lost 20 db of signal strength due to your body blockage. The software thinks the two of you are far apart when you are actually standing next to each other.

Second, in the real world, radio signals do not travel in a straight line from transmitter direct to receiver. Instead, signals reflect off of objects in the environment. Some times the reflected signals arrive at the receiver in a way that increases their apparent strength and in other cases they arrive in a way that decreases their apparent strength. This is known as “multi-path”.

Think of a pond of calm water. Toss in a rock and see how the waves move across the surface. What happens when the waves strike the shore or another rock – they typically reflect or bounce back creating a new wave front. In a complex environment, there are many wave fronts traversing that water. In some places, wave heights may combine momentarily to create a higher wave, while in others they may combine to create a deeper trough.

The effect of this in the Bluetooth contact tracing app scenario is that – and this has been tested in the real world – there are real scenarios where people moving further apart see a stronger received signal strength!

The software erroneously thinks these two people have increased their risk when they are moving further apart!.

The opposite can also occur – as people move closer together, due to multipath, the devices may sense a drop in signal strength and erroneously think there is less risk.

The Need for Controlled Trials

This is why this technology must be tested in the real world before it is rolled out to entire populations. The bottom line assessment is: Does it detect actual contacts we need to worry about – without missing contacts we do need to worry about?

The Gold Standard: Does it result in an actual, measured decrease in the spread of Covid-19 and a reduction in mortality?

To answer those questions requires controlled trials, just as controlled trials are required for the use of hydroxchloroquinine in the treatment of Covid-19.

Some will argue no controlled trial is necessary as the use of the app is harmless. However, if you are periodically placed in 14-day quarantines – unnecessarily – harming your income and mental health, is that truly harmless?

If not tested, deploying smart phone contact tracing apps is a mass population medical experiment without informed consent – which is illegal in the United States. But given we are dealing with public health, laws no longer matter, of course.

Coldstreams