Determining Infectious Disease Positivity Rate Over Interaction Rate Through Analysis of Collocation Data

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Wang, Yiyang
Abowd, Gregory Dominic
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Knowing and understanding the flow of infectious disease within a community is very important, as it can effectively aid community administrations in planning their actions to control the situations. In this study, I investigated the correlation between collocation rate and COVID positivity rate within each building pair using Wifi data and school daily COVID case reports. I used collocation bipartite graphs to generate occupancy features, such as occupancy count and occupancy duration, and then input these features into our correlation model. I then used the COVID positivity rate as the output of the correlation model. Using the model, I am able to find a weak linear correlation between the collocation rate and the COVID positivity rate. The correlation is stronger in places with more students in and out on a daily basis, such as libraries and student centers. Using this insight, the school administration could advise students who visited these places to get tested when there was a COVID outbreak in these areas. A similar approach could also be adopted to investigate the correlation between collocation rate and infectious positivity rate on other types of infectious diseases in the future.
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Undergraduate Thesis
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