Can co-location be used as a proxy for face-to-face contacts?

EPJ Data Science

Table 4 Average similarity between daily networks

	InVS13	InVS15	LH10	LyonSchool	Thiers13
Contact	0.333	0.305	0.351	0.643	0.431
Co-presence	0.415	0.348	0.449	0.806	0.683
Sampling 1	0.361	0.344	0.436	0.749	0.515
Sampling 2	0.388	0.271	0.403	0.175	0.084
Sampling 3	0.286	0.205	0.437	0.042	0.071
Null model	0.022	0.010	0.061	0.046	0.010

For each data set we compute the cosine similarity between the neighbourhoods of each nodes from each daily network, averaged for all nodes and all pairs of daily networks. The neighbourhood of a node n is defined as the vector of the link weights between n and every other nodes (if the link does not exist the weight is set to zero). We compare the values obtained for the contact data, the co-presence data, and for the networks generated by each sampling method of the co-presence data, averaged over 100 realisations for each sampling method. For reference, we also compute as null model the average similarity when links in the contact data are shuffled randomly within each daily network.