A new study from ScienceAdvances finds data on the physical proximity between individuals, derived from anonymized mobile phone geolocation, may enable more accurate predictions of COVID19 case rates than existing mobility metrics.
Public health officials identified travel, social gatherings, workplaces, churches, universities, and recreational sports as contributing to transmission. Nevertheless, on 8 October, the state began phase 3 reopening, permitting 50% capacity in houses of worship capped at 200 people and uncapped outdoor religious gatherings with social distancing and opening indoor dining, hair salons, personal service businesses, and libraries at 75% capacity.
A contact event was computed by using a probabilistic algorithm that computes the likelihood of simultaneous 2-m proximity between pairs of devices across geographic areas. For each device, we identify sets of records where devices were in spatial proximity to one another and stationary.
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