Human agency and infection rates: implications for social distancing during epidemics

Christopher Bronk Ramsey

Part of the motivation for this theoretical approach are the known limitations in the types of social contact data which underly simulation models, and are required for quantifying networks. In particular, the types of survey data used may under-report chance interactions [4] , and indeed the scale of variation in the length, intensity and closeness of contacts is hard to elicit from such data. The amount of interaction any individual has in a complex modern society will vary over a very wide scale, and probably over a wider scale than contact survey data would suggest. This is partly due to the upper limit on the number of contacts reported, either because the respondent cannot remember them, or because they do not necessarily think they are significant. For the purposes of this model the number of contacts is, in any case, not as significant as total one-one contact time for virus transmission.