New outbreak model better predicts COVID-19 hotspots, ISI’s Tony Dahbura, The Hub
Viruses, such as the one that causes COVID-19, spread quickly through large cities because of a complex web of interactions between people taking place in a densely populated area. But how viruses move from person to person in smaller, rural communities is less well understood, resulting in public health and economic decisions that are made on the basis of scant information and overgeneralized modeling.
Developed with the help of Mathias Unberath, an assistant research professor in Computer Science and a member of the Malone Center, along with Lingxin Hao and Emily Agree of the Johns Hopkins Population Center, the new model envisions populations in terms of extremely localized and specific “modules” of people, their dwellings, and shared community spaces such as offices, schools, stores, and restaurants. It takes into account that people interacting with one set of modules may also interact with another, acquiring and spreading infection.