# Evaluating the Effectiveness of COVID-19 Bluetooth-Based Smartphone Contact Tracing Applications
## 1 Introduction  
The eruption of COVID-19 has become a severe threat to our society. At present over a million people have died, and more than 20 million have been infected. The social and economic effects of this pandemic are incalculable. International organizations such as the United Nations (UN) and UNICEF have warned about the risks to peace and social cohesion. Furthermore, it has been shown that COVID-19 can exceed the capacities of current health systems, including those with the most resources [1]. Countries dealt with the initial outbreak of COVID-19 in different ways and with very different results. Some countries exhaustively tested all the individuals with symptoms, and when an infected case was detected, their previous contacts were traced. The use of mobility traces has been fundamental to accomplishing this result (see [2]), and COVID-19 could be controlled without taking drastic measures. On the other hand, countries not performing this contact tracing could not control the outbreak, having eventually, no other option than to take extreme measures, such as lockdowns and stringent social distancing. Contact tracing can be considered a more selective isolation measure targeted to the population most likely to have the infection [3]. Nevertheless, as shown with the COVID-19 pandemic, if the basic reproductive number is large and most infected individuals are asymptomatic, contact tracing has to be really efficient and rapid in order to be effective. The so-called digital epidemiology [4] takes advantage of the global penetration of mobile phones to provide a way to track infectious diseases such as COVID-19, and to allow new approaches to deal with epidemics [3]. The FluPhone mobile application, which was developed at Cambridge University, is considered one of the first attempts to estimate infectious contacts by using mobile phones [5]. The idea was to use Bluetooth and other wireless signals to detect physical contacts, and then ask users to report flu-like symptoms for evaluating their risk of infection. For example, the Singaporean government developed and released the TraceTogether mobile application for tracing that also relied on Bluetooth contacts [6]. Other similar proposals are SafePaths [7; 8] and PEPP-PT (Pan-European Privacy-Preserving Proximity Tracing) [9]. Finally, Apple and Google have recently teamed up to develop similar solutions in their smartphone operating systems. Furthermore, by being integrated into the mobile operating systems, it becomes more efficient, and what is more important is that it will reach nearly all smartphone users. Most of the technology of these mobile applications is based on the results of years of research on mobile computing, and singularly on opportunistic networking (usually known as OppNet or opportunist networks) and mobile crowdsensing (MCS). The main idea behind OppNet [10] is to opportunistically exchange messages between nearby devices when establishing some communication link (for example, Bluetooth). As their behavior and dynamics can be comparable to the epidemic spread of messages, the models developed to evaluate opportunistic networks are usually adaptations of known epidemic models [11]. The study of human mobility and their social behavior is also essential for evaluating information dissemination in communication networks [12]. We consider that all this knowledge can help to tackle the spread of infectious diseases too. While the main goal of these previous research works was to increase information dissemination, we now set our primary objective to reducing or avoiding the diffusion of infectious diseases by reusing the various mathematical models and simulation tools previously developed [13; 14; 15; 16]. In a previous work [17], we focused on evaluating how different technologies can be used for contact-tracing, and their impacts on the spread of infectious disease, confirming that Bluetooth is the most efficient technology for these cases. In fact, Bluetooth is being widely adopted in most tracing applications for COVID-19.