The research of Lijun Sun and colleagues at Singapore's Future Cities Laboratory could yield insight into monitoring a specific group of disease carriers to identify nascent outbreaks early and help prevent epidemics. Such individuals have atypically large numbers of contacts with others and so they spread disease far and wide when they become infected.
These super-spreaders were identified via an analysis of contacts between commuters on Singapore's bus system, as represented by the tapping in/tapping out data from smartcards. The experiment monitored the data over a week to determine whenever individual commuters shared the same bus, how often, for how long, and at what time of day. The resulting commuting patterns were so detailed that they enabled the researchers to model disease proliferation through an actual network.
They built on this experiment to measure the spread of disease by tracking a smaller, more highly connected subset of the population, which was determined to be super-commuters, and thus super-spreaders of infection.
Such individuals are an excellent, low-cost early-warning system, Lijun and colleagues say. They say crowdsourcing could offer one possible method for finding potential super-spreaders to monitor.
From Technology Review
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