Analyzing the Impact of Covid-19 Control Policies on Campus Occupancy and Mobility via Passive WiFi Sensing
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The outbreak of has resulted in many different policies being enacted across the world to reduce the spread of the virus. These efforts range from increased social awareness and social distancing (Sweden) to full country-wide lockdowns (Singapore, most of Europe, many states in the US). The effectiveness of various policies in containing the spread of the disease is still being studied by researchers. In this paper, using WiFi data collected directly from the infrastructure, we present a detailed analysis of the impact of related policies on the staff and students of three different college campuses. Two of these campuses are in Singapore, while the third is in the Northeastern United States. Our study focuses on two different key metrics, 1) Occupancy, defined as the number of people in a building, on average, in a specific hour, and 2) Mobility, defined as the number of places visited by an individual, on average, in a specific hour. We use these two metrics since they provide a strong indicator of how likely it is for to spread if there is an outbreak. Our results show that online learning, split-team, and other space management policies are effective at lowering Occupancy. However, they do not change the Mobility patterns for individuals who are still moving around. Reducing Mobility requires introducing strict stay-at-home or lockdown orders, but doing so increases Occupancy in residential spaces. We present our results and then discuss the implications of the findings for policymakers.
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