Microsimulation of SARS-CoV-2 Transmission in Society

The outbreak of the pandemic disease, COVID-19, has shown that the approaches by different countries has resulted in a range of infection rates through their societies. This has arisen from the varying personal behaviour and tactical use of lockdown strategies within each country. We report the use of microsimulation of a simulated community in Australia, using a discrete infection model within a community of residences, places of work and recreation to demonstrate the applicability of this method to both the current pandemic and to infection more generally. Simulations without any societal intervention on infection spread provided base simulations that could be compared with social and societal controls in the future and which were compared with the initial doubling times of country outbreaks across the world. Different population sizes were represented in some simulations and in other simulations the effects of either social distancing or the use of facial masks as personal behaviours was investigated within the community. Good agreement is found between the initial doubling times for several countries and the simulations that suggests that modelling infection as a collection of individual infections provides an alternative to current epidemiological models. The variation of the basic reproductive number, R0, with time and population size, suggests that one of the fundamentals assumptions in SIR type models is wrong, but varies according to the properties of the population being modelled. Investigation of the infection spread shows that the number of super-spreaders varies with the size of the population and occurs through contacts in clubs, supermarkets, schools and theatres where the source of infection is an employee and where there are high numbers of contacts. The simulations of individual control show that the benefits of social distancing or wearing masks is only fully realised where there is considerable compliance within society to these measures.