Researchers have developed a computer model that predicts how the novel coronavirus spreads in US cities.
The model looks at three factors that play a role in infection risk: where people go during the day, how long they stay, and how many other people are visiting the same place at the same time.
It found that most cases of the virus occur at ‘superspreader’ sites, such as coffee shops, full-service restaurants and gyms, where people are close together for extended periods of time.
However, limiting capacity in these locations could reduce the number of infections by as much as 75 percent.
The team, from Stanford University School of Engineering, says its model can be used as a tool for officials to determine the tradeoff between new infections and reopening businesses, even at limited capacity.
A computer model from Stanford University found that most COVID-19 infections occur at ‘superspreader’ sites, such