This analysis uses a model that incorporates randomness and individual-level variation in transmission (i.e. potential for 'superspreading') to calculate the probability that a given number of independently introduced cases in a new location will eventually lead to a large outbreak. (Source: Lloyd-Smith et al, Nature, 2005). There are two key values to explore: the reproduction number in the new location (i.e. average number of secondary cases generated by a typical infectious individual); and individual-level variation in transmission - do all cases generate similar numbers of secondary cases, or do most generate few and some lots? Infections with more individual-level variation (such as SARS) lead to more fragile initial transmission chains, and hence are overall less likely to spark a large outbreak following an introduced case (although they can lead to rapidly growing outbreaks if by chance transmission does take hold. The random-mixing option in the drop-down menu assumes transmission occurs at random with similar secondary cases from all individuals.

Coronavirus, COVID-19, 2019-nCoV