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As the U.S. grapples with the continued spread of the novel coronavirus, two �첥���� professors saydata indicates social distancing is effective in helping to slow infection rate. However, they also found that a state's COVID-19 infection rate increases with the size of its African American population.

According to the researchers, this suggests that the black population of a state is a driver of COVID-19 infection and that they are relatively more vulnerable.

The research uses data from the , which collects testing data across the U.S. and its territories, and the , a survey conducted by the U.S. Department of Labor in 2018 that gauges how much time people in the U.S. spend on various activities during a 24-hour span.

The research quantifies the effect of individual social distancing on the spread of the novel coronavirus with data on individual time spent on activities that would potentially expose them to crowds.

“From a practical perspective, our parameter estimates suggest that if the typical individual in a U.S. state were to spend eight hours away from crowds completely, this would translate into approximately 480,000 less COVID-19 infections across the states,” according to researchers Gregory Price and Eric van Holm of UNO’s Urban Entrepreneurship and Policy Institute.

“Our results suggest that, at least in the United States, social distancing policies are effective in slowing the spread of the novel coronavirus,” the researchers wrote.

The data timeframe is from March 4 through March 27, 2020.  

While the primary interest was the effect of individual social distancing on COVID 19 infections, the research also revealed that the number of state-level COVID 19 infections increases with the percentage of a state’s population that is African American, foreign born, self-employed and living in metropolitan areas or cities, the researchers wrote.

“This suggests that in addition to implementing social distance policies, effective COVID 19 mitigation policies should also consider how the sociodemographic characteristics included in our control covariates are important for the spread of an infectious disease like COVID-19.”