Since the beginning of the COVID-19 pandemic, dozens of countries have deployed contact tracing via smartphone apps to employ quarantine for individuals who are at risk of infecting others. The idea behind digital contact tracing is to use smartphone applications to inform people who have been close to infectious people who also use the same application. Data from a handful of nations show mounting evidence that digital contact tracing is useful in keeping the spread of infectious diseases at bay.
Using the toolbox of network science, K. Rizi et al. have investigated the effectiveness of this low-cost intervention method on models that assume more realistic assumptions about human populations. Their model makes it possible to see when and how large an outbreak can happen if a fraction of people adopts the contact tracing apps given several different heterogeneities in the population structure. Importantly, their model includes homophily in the application adoption: the tendency of people who use the application to be more in touch with each other than people who do not use the application. Their results indicate that contact tracing with apps raises the epidemic threshold and reduces the size of the emerging outbreaks. Their results bring this issue to light that digital contact tracing can curb the pandemic even if it is not done perfectly, but its effects are highly nonlinear and strongly dependent on how the connections are structured among application users and others.
K. Rizi, Abbas, et al. “Epidemic spreading and digital contact tracing: Effects of heterogeneous mixing and quarantine failures.”