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Intelligent network topology based post-pandemic reintroduction policies for offices

COVID-19 has touched almost all facets of modern life. As part of this global shift, many employers have recommended employees work from home in an effort to curb the spread of infection. When organizations bring workers back to the office, the specific policies for personnel reintroduction will shape both productivity and the spread of disease. This study explores the secondary social and energy impacts of potential reintroduction policies. Using a socio-organizational network inferred from an office in Redwood City, California, we define social, epidemic resistance, and energy metrics which are used to compare the character of personnel reintroduction plans. Our notable findings are, first, that the choice of which occupants return has a large effect on modeled network-level epidemic resistance. Second, where the occupants are located can significantly impact overlap in space-use within smaller spatial zones - a concept related to social distancing. In summary, this work is a critical first step in demonstrating the value of intelligent occupant network topology based reintroduction schemes in offices that can minimize: disease spread, socio-organizational disruptions and building energy use impacts.