Asynchronous Contact Tracing
Résumé
This document examines the use of IoT technology in contact tracing and introduces the concept of Asynchronous Contact Tracing (ACT). ACT identifies contacts with IoT connected objects that have been contaminated by the SARS-CoV-2 virus and works in synergy with solutions designed for manual contact tracing to identify and alert people who may have been infected by the virus. This shifts the paradigm from synchronously tracing the contacts of the people infected by Covid-19 to asynchronously tracing of contacts of materials (such as infected surfaces, waste water, air conditioning filters, etc.) that are hosting the SARS-CoV-2 virus. This enables people who have come into contact asynchronously with those particular materials to be alerted of a potential Covid-19 contagion, and, at the same time, it signals that one or more persons have been in contact with the material which is now spreading the SARS-CoV-2 virus. This process could be particularly effective, considering that the SARS-CoV-2 virus can survive for a significant time on certain materials. The level of contamination may on the nature of the surface and materials, the concentration of the virus, the ambient temperature, the season of the year, the level of humidity, and exposure to sun light. The period of contamination can span from a few hours to several days. The ACT process uses existing, ready-to-market IoT-based technology and well-established wireless network techniques. The process is not dependent on achieving a certain number of tests, or of people adopting it, in order for the results to be useful. Moreover, it does not require the transmission of any personal information by the user, thus respecting both EU GDPR and public sensibility to personal privacy. This process was inspired by Occam's Razor [5] or the Law of Parsimony (Latin: Lex Parsimoniae), that states that entities and theories useful to solve a problem should not be multiplied unless necessary. On the contrary, simpler entities and theories are preferable to more complex ones because they are easier to test and more likely to be true.
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