Convinced that human tracing would be overwhelmed by the nature of the covid19 contagion, epidemiologists, health experts, and computer scientists quickly saw the digitalization of contact tracing as a powerful complement to the traditional method. The efficiency of the solution became, as fast, central to academic and institutional concerns: first because, based on an anonymous but massive detection process, the solution could only be efficient if enough was used, and second because in a virtuous circle, the more citizens would use it, the more it would be legitimate. Netherveless, in their report on 27 contact tracing applications developed in the EU (Prodan & al, 2022), observed that the apps' monitoring remained incomplete and evaluation insufficient to the point where there was no accurate data to conclude. By using an STS approach analyzing both the design process and the citizen experience of the French and the Japanese solutions, we explore the reasons for an announced efficiency assessment failure. We first dwell on the technological and privacy challenges that led many authorities to blindness as to the uses of the application. This investigation highlights the G AFA platform's power and the digital sovereignty issues, all questioning the States' platerfomization ambitions. Second, we focus on what these solutions miss in usage analysis terms. We see how defining usage and "adopter", remained unfinished, probably as it was tough to integrate everyday life, risk perception, and exposure in the algorithms. This paper contributes to an STS approach to measurement in an algorithmic world.