The biggest challenge for these apps going forward is adoption. The more phones that opt-in to the system, the more successfully it can detect how the virus spreads. Apple and Google say that getting the public to trust the apps and opt-in is critical to the effort.
As I explain in detail here, the Apple-Google approach will unlikely have sufficient users to be particularly valuable. If 50% of all smart phone users install the tracking apps, we will have the potential to detect just 16% of close contacts. Is that sufficient to have an impact on the spread of Covid-19?
About 80% of adults have a smart phone. If we assume all 81% have phones capable of running the software (which is not realistic as many people continue to use older phones and may not have compatible Bluetooth Low Energy hardware), then 50% of all users means 40% of adults have the app installed.
The probability of a person having the app is then 0.4. The probability of a 2nd person you meet having the app is also 0.4. The probability that you and a random person you meet both have the app is 0.4 x 0.4 or 16%. Even if all 81% have the app installed, the probability of a detectable contact is at most .81 x .81 or about 65% of the adult population. This does not include children, lowering the contactable percent even more.
Most other countries that have used phone-based contact tracing – so far – have used network-based tracking, not app-based. In network-based tracking, the network tracks the location of all cellular phones – both smart phones and dumb phones with a 100% coverage/participation rate. These systems identify contacts within about a 100 meter radius, which is too broad. But these countries follow up with a robust public health in person contact tracing operation and offer Covid-19 tests so that people are not needlessly placed in 14-day quarantines.
As you can see, the Apple-Google model is unlikely to have sufficient usage to detect many contacts.