School Closures Could Mean Billions Lost

March 13, 2020
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As you all know, a national emergency has now been declared in the U.S. by the White House. There are unprecedented school closures in several countries and they are quickly mounting here, including in New York State. Given the immediacy of this issue, I updated a 2009 study that my colleagues and I published in PLoS Currents estimating the potential impact of school closures on the U.S. economy and on health care workers.

Adjusting for inflation, our updated analysis finds that a month-long closure of all U.S. K-12 schools and daycare centers could cost more than $50 billion in lost productivity due to absenteeism--employees missing work to stay home with children. This would represent a GDP loss of 0.2%.

Of course, by minimizing contacts, school closures can reduce the total number of infections and delay the epidemic peak, both of which can mitigate the disease and help the health system successfully cope with it.

However, with children out of school, many parents stay home from work – and this absenteeism leads to significant economic costs with wide-ranging implications. For one, closures could exacerbate inequality and hurt low-income families disproportionately, as telecommuting and paid leave are less likely to be available to blue-collar parents.  Additionally, many children from low-income families rely heavily on the two meals a day often provided at school.

Closures could also amplify the epidemic by keeping key health care workers (e.g., nurses) away from their jobs, precisely when they are needed most to respond to an epidemic.

Whether the costs outweigh the benefits depends on several factors still shrouded in uncertainty, including the actual prevalence of the infection, its case fatality rate, the transmission rates by age group, and behavioral responses.

Meanwhile, I thought an evidence-based estimate of the potential costs would be a public service. Hope you agree!

 

 

Dr. Joshua Epstein

Joshua Epstein, PhD
Professor of Epidemiology