Digital Herd Immunity and COVID-19

Vir Bannerjee Bulchandani; Saumya Shivam; Sanjay Moudgalya; S L Sondhi

In this paper we contribute to this emerging field of infectious disease control along two axes. First, we present a simple model of the early stages of the spread of COVID-19, which allows us to obtain estimates, as a function of a varying amount of non-symptomatic transmission, of the fraction of the population that needs to participate in a digital contact sharing network in order to prevent new epidemics. Our interest in this question was seeded by the very practical question of whether a country like India can use this technology to achieve epidemic control today. Indeed, India is now launched on this enterprise [11] . While somewhat more complex modeling with various differences from our own became available while we were working on this problem [5, 12] , we feel that our approach has the virtue of making the existence and values of the estimated compliance thresholds transparent. Our estimates for the fraction of the population that needs to own a contact-tracing app to avert a COVID-19 epidemic range from 75% − 95%, depending on the fraction of asymptomatic transmission, θ = 20% − 50%, that takes place. Busy epidemiologists and health officials will find this part of interest.