title: Efficient detection of contagious outbreaks in massive metropolitan encounter networks.
abstract: Physical contact remains difficult to trace in large metropolitan networks, though it is a key vehicle for the transmission of contagious outbreaks. Co-presence encounters during daily transit use provide us with a city-scale time-resolved physical contact network, consisting of 1 billion contacts among 3 million transit users. Here, we study the advantage that knowledge of such co-presence structures may provide for early detection of contagious outbreaks. We first examine the "friend sensor" scheme--a simple, but universal strategy requiring only local information--and demonstrate that it provides significant early detection of simulated outbreaks. Taking advantage of the full network structure, we then identify advanced "global sensor sets", obtaining substantial early warning times savings over the friends sensor scheme. Individuals with highest number of encounters are the most efficient sensors, with performance comparable to individuals with the highest travel frequency, exploratory behavior and structural centrality. An efficiency balance emerges when testing the dependency on sensor size and evaluating sensor reliability; we find that substantial and reliable lead-time could be attained by monitoring only 0.01% of the population with the highest degree.
authors.affiliation: 1] Future Cities Laboratory, Singapore-ETH Centre for Global Environmental Sustainability (SEC), 138602, Singapore [2] Department of Civil & Environmental Engineering, National University of Singapore, 117576, Singapore [3] Media Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
authors.forename: Lijun
authors.initials: L
authors.lastname: Sun
authors.affiliation: 1] Future Cities Laboratory, Singapore-ETH Centre for Global Environmental Sustainability (SEC), 138602, Singapore [2] Institute for Transport Planning and Systems (IVT), Swiss Federal Institute of Technology, Zürich, 8093, Switzerland.
authors.forename: Kay W
authors.initials: KW
authors.lastname: Axhausen
authors.affiliation: Department of Civil & Environmental Engineering, National University of Singapore, 117576, Singapore.
authors.forename: Der-Horng
authors.initials: DH
authors.lastname: Lee
authors.affiliation: National Information and Communications Technology Australia, University of Melbourne, Victoria 3010, Australia.
authors.forename: Manuel
authors.initials: M
authors.lastname: Cebrian
mesh_terms: D002947:Cities; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D018562:Disease Transmission, Infectious / Q000517:prevention & control* / Q000706:statistics & numerical data; D042241:Early Diagnosis; D005260:Female; D033062:Friends; D006802:Human Activities / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D011157:Population Dynamics; D012944:Social Support