Probability that an infection like Covid-19 stops without reaching herd immunity, calculated with a stochastic agent-based model

Abstract

AbstractThe spread of an infection is simulated with a stochastic agent-based model. In a certain range of R0 values, the infection either rapidly comes to halt or a large proportion of the population is infected until herd immunity is achieved. Which of these two possibilities actually occurs is random. The probability of each case is determined ‘quasi-empirically’. This stochastic phenomenon may explain unexpected infection trajectories.