“Experts” and public institutions are reluctant to use of geolocation data held by mobile phone operators to backtrack COVID-19 infected people. The reason is that as “the cell-phone mesh is too wide” and GPS is not precise, the data obtained would be unreliable. This fact, according to them, would justify the use of other instruments – and in particular, of “apps” – to be installed more or less mandatory on people’s smartphones.
It is unclear if these “experts” considered that not everyone could or wants to have a “smart” phone. Therefore, more than a few could go around with an old “stupid” but less intrusive mobile phone affecting the overall efficiency of the solution.
Moreover, it is unknown if they considered that the same data their app is going to record, can be acquired independently from Apple and Google. These companies, indeed, own the operating system of the terminal and have full access to its inner working. Of course, these “experts” equip the “apps” with “appropriate security measures”. Still, Android is open source (and I’m curious to know if its source code is “adequately checked”), IOS is not. Apple swears to “be good”, but since we can’t apply Ronald Reagan’s warning (“Trust but verify”), we have to commit to an act of faith.
Are the “unreliability” of GPS and the excessive cell area of the mobile network enough to discard it as an effective tracking tool? Even though this information would not be accurate to the centimetre (although, empirically, anyone who has used Google Maps has a different perception), that doesn’t make it useless.
Of course, if the “experts” expect the BTS data to produce a CSV file with all the information ready to use in a visually appealing presentation, they are just wrong. A similar expectation shows a flawed perception of how telecommunications networks operate and how data are analyzed.
Of course, the more detailed and of good quality the data, the better. Still, what makes the difference is how good the analyst is at making sense of an undifferentiated amount of information.
Gelocalize a patient and match these data with all those belonging to the people he met overtime should not be such a hard task. Perhaps this approach would not work for those who are permanently in the same cell, but it may pay dividends when applied to those who had a high mobility rate.
This just an example, as there are many more creative uses for the personal data available to seek people (potentially) affected by COVID-19. Stil, it is essential to understand that there are no one-fit-all solutions, as the answers depend on the questions asked and the expectations on the results:
- To backtrace, a posteriori, the movements of the last two months of infected people, there is no alternative but to acquire the geolocation data and – for example – those related to the use of credit cards. This solution might not identify 100% of the targets. However, it is a calculated risk,
- to real-time track people, the BTS data should be matched with a map of the gathering places (squares, main streets, shops, etc.). In a “FourSquare style”, people could “check-in” at the place where they leave and at the destination. Rather than focusing on the “app”, why don’t use FourSquare itself?
- finally, to manage “proximity crowding” it might make sense employing a specific software.
Whatever the chosen solution, two aspects matter.
Firstly, as said, there is not a one-fits-all solution. Therefore it is necessary to adopt an integrated approach to a complete infected population mapping, or agree to give up some options to obtain reduced results.
Secondly, using information technology to solve problems does not exempt from working very hard to make the most of it. Only in Mickey Mouse comics, science fiction movies and the Hitchhiker’s Guide to the Galaxy it is possible to “just ask” a computer and get a prompt answer… “42”.