We began by generating sample populations based on census data from the three years investigated. The datasets that inform our sampling procedure describe local area populations on the order of several hundred people (SA1 in both 2016 and 2011, and Census District in 2006). These datasets provide population (e.g., age, sex, and employment status) and housing (e.g., household size and composition) statistics. These were used as (dependent) probability density functions in the stochastic generation of households and agents, respectively. Additional details of the population generation procedure can be found in the Supplementary Materials. We positioned schools pseudodeterministically based on their postal code as reported by the Australian Curriculum, Assessment and Reporting Authority (ACARA), a noncensus dataset that contains the most complete information available on school enrollment numbers and locations since 2008 (note that we used 2008 school locations and enrollments in place of 2006 data that were not available) (42). We then assigned students to schools based on the proximity rules described in our previous work (31).

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