Building a Dataset of Coronavirus Transmission Events – Center for Data Innovation

Researchers led by an individual from the London School of Hygiene & Tropical Medicine have released a dataset about the settings that have led to significant clusters of COVID-19 cases. The dataset contains more than 250 transmission events and notes the date, location, if the event was indoors or outdoors, and how many individuals became infected. If an event was indoors, the dataset details the type of building, such as if the building was a dormitory, a processing plant, or a bar. 

Michael McLaughlin is a research analyst at the Center for Data Innovation. He researches and writes about a variety of issues related to information technology and Internet policy, including digital platforms, e-government, and artificial intelligence. Michael graduated from Wake Forest University, where he majored in Communication with Minors in Politics and International Affairs and Journalism. He received his Master’s in Communication at Stanford University, specializing in Data Journalism.