# Evaluating the Effectiveness of COVID-19 Bluetooth-Based Smartphone Contact Tracing Applications
## 3 Smartphone-Based Contact Tracing
### Characterizing Contact Tracing Effectiveness
A straightforward solution could be that governments compel their citizens to use the application. Nevertheless, this approach can be seen in most countries as a restriction of personal freedom and privacy, and is, therefore, not applicable. An alternative is to encourage the population to download (or activate) the application, although, as we have already seen in Singapore, with poor results. Recently, the Apple and Google COVID-19 solution has already been implemented in their latest operating systems versions, so, with a simple firmware update, users can have the contact tracing application; this approach could increase the number of users using the application. Nevertheless, this new facility is disabled by default, meaning that users should proactively opt-in for using the application, penalizing its utilization. The other option could be to have the application activated by default, with the option of opting-out whenever the user wants to. In this case, the user who has concerns about her/his privacy can disable it. Nevertheless, this makes a huge difference, since most people would not opt-out [41]. Therefore, in order to achieve a useful utilization, the only option is to allow users to opt-out. As it will be shown in the experiments, if no other measures are taken, the goal should be a utilization between 75% to 90%, a value that would allow tracing about 56% to 80% of the contacts. An alternative to improve the utilization is to consider a reduced set of the population. Individuals can be forced to use the contact tracing application in some locations (companies, festivals, universities, conferences, etc.) in order to detect the possible contacts only in those defined areas. This way, the utilization of the application for this population subset would be nearly 100%, and so practically all contacts produced in the defined location can be traced. Finally, the last aspect to analyze is the contact tracing speed. It has been shown that, for COVID-19, fast detection and isolation of infected individuals is essential to control new outbreaks. The tracing speed will depend mainly on whether the solution is centralized or decentralized. A centralized solution will be very fast since, when a newly infected individual is detected, health authorities can immediately trace their previous contacts. On the contrary, a decentralized solution will depend on the user's willingness. Firstly, the newly infected citizen should self-report her/his positive using the application. Nevertheless, since self-reporting is prone to false alarms, we assume that health authorities, when individuals are tested as positive, should assure and control that users correctly notify about their positive. Secondly, the previous contacts of this individual should proactively check the application, and then communicate their situation. Therefore, it would take several days to trace all possible contacts, and, furthermore, some of the contacts will be lost. It is clear that a centralized approach is a more effective approach, with tracing times of less than one day. A decentralized approach will suppose a double penalty: it will increase the tracing time, and it will also reduce the number of possible traced contacts. We can measure these penalties: (i) for the increase of tracing time, we consider the average tracing time will be \(TT\), measured in days. In the centralized approach, this value will always be one, which is the unit time used in our model; (ii) for the reduction on the number of traced contacts, we consider the ratio of users checking for their exposure in the application, \(RC\), which depends on the willingness of the users. Note that this value will be one for the centralized approach since the checking is always performed in the centralized servers. Now, based on all the previous parameters, we define two different fractions of the real contacts that can be traced using the application.