New Model and Tool Incorporating Local Features in Covid-19 Spread

Penn Biostatistics colleague Jing Huang has worked with CHOP collaborators Gregory Tasian and David Rubin, director of PolicyLab, to model incidence data as a function of local characteristics, which may be useful for making future projections.

The approach monitors spread rate as a function of key demographic, local population density, and mobility variables.

Here is a report on the Penn Department of Biostatistics, Epidemiology, and Informatics website.

Here is a link to the results on the CHOP policy lab website


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