This topic describes the algorithm used by SynthPops to generate the connections between people in each of the contact layers for a given location in the real world. The fundamental algorithm is the same for homes, schools, and workplaces, but with some variations for each.
The method draws upon the following previously published models to infer high-resolution age-specific contact patterns in different physical settings and locations:
The general idea is to use age-specific contact matrices that describe age mixing patterns for a specific population. By default, SynthPops uses Prem et al.’s (2017) matrices, which project inferred age mixing patterns from the POLYMOD study (Mossong et al. 2008) in Europe to other countries. However, user-specified contact matrices can also be implemented for customizing age mixing patterns for the household, school, and workplace settings (see the social contact data on Zenodo for other empirical contact matrices from survey studies).
The matrices represent the average number of contacts between people for different age bins (the default matrices use 5-year age bins). For example, a household of two individuals is relatively unlikely to consist of a 25-year-old and a 15-year-old, so for the 25-29 year age bin in the household layer, there are a low number of expected contacts with the 15-19 year age bin (c.f., Fig. 2c in Prem et al.).