JMIR Publications

ABSTRACT

Background:

During the 2020s, there was extensive debate about the possible use of contact tracing (CT) for SARS-CoV-2 pandemic containment, and concerns have been raised about data security and privacy. Little has been said about the effectiveness of CT. In this work, we present a real data analysis of a CT experiment conducted in Italy for eight months involving more than 100,000 users.

Objective:

We discuss the technical and health aspects of a centralized approach. We show the correlation between the acquired contact data and the number of positives to SARS-CoV-2. We analyze CT data to define population behavior, and we show the potential application of real contact tracing data.

Methods:

CT data were collected, analyzed, and evaluated on the basis of the duration, persistence and frequency of contacts over several months of observation. A statistical test was conducted to determine whether there is a correlation between indices of behavior calculated from the data and the number of new infections in the population (new positives).

Results:

We evidence a correlation between a weighted measure of contacts with the new positives to the virus (Pearson coefficient = 0.86), paving the road to a better and more accurate data analysis and spread prediction.

Conclusions:

The data are used to determine the most relevant epidemiological parameters and can be used to develop an agent-based system to simulate the effect of restrictions and vaccinations. Finally, we demonstrated the system's ability to identify the physical locations where the probability of infection is highest. All data collected are available to the scientific community for further analysis.