How Staying Home From Work Can Spread Disease - Pacific Standard

How Staying Home From Work Can Spread Disease

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For people in essential jobs, calling in sick could put substitute teachers, nurses, and others at risk.

By Nathan Collins


Influenza virus. (Photo: Kat Masback/Flickr)

Most of the time when you’re sick, it makes sense to keep your distance from others—it’s just one more thing that prevents the spread of disease. But in certain cases, staying home may actually result in more people getting sick, according to a paper published today in Nature Physics.

Communicable diseases like the flu spread from person to person, often when one person coughs in close proximity to another, so how the disease spreads depends on the network of who comes into contact with whom. The obvious way to limit the spread of a disease, then, is for sick people to temporarily take themselves out of that network—in other words, to stay home from work so they don’t come into contact with anyone who isn’t already sick.

But for people in careers where it’s common to have someone fill in for a sick worker—teaching or nursing, for example—staying home from work does two things to the network: It removes a sick person, but brings in another healthy person who may now be at greater risk for contracting a disease.

In certain cases, staying home may actually result in more people getting sick.

“Consider the school teacher who is infected with influenza by a student,” complex systems researchers Samuel Scarpino, Antoine Allard, and Laurent Hébert-Dufresne write today in Nature Physics. If that teacher stays home, but infected students do not, a substitute teacher who comes into contact with those students may get sick.

Using a mix of mathematics and computer simulations, Scarpino, Allard, and Hébert-Dufresne show that “relational exchange,” where healthy people fill in for sick ones and thus temporarily inherit their social contacts, can actually spread the epidemic to more people—just before an epidemic peaks, the team calculates, relational exchange leads to an exponential increase in the number of new cases each day.

Meanwhile, getting people to stay home is only really effective when not that many people are sick in the first place; if a substantial portion of students, patients, or co-workers are already sick, an essential employee staying home mostly serves to put the person filling in at risk.

Those results are theoretical, however, so the team next looked for the exponential-growth pattern in 17 years’ worth of influenza tracking data and 19 years’ worth of dengue data. Dengue is important because it’s not transmitted person-to-person, but rather by mosquitoes, which means that relational exchange shouldn’t affect dengue epidemics in the same way as it does influenza. As the researchers predicted, influenza spread exponentially just prior to peak epidemic size in all 17 epidemics, but dengue did so only a few times, most notably in the 1994–95 outbreak in Puerto Rico.

Although the researchers point out a number of technical limitations in their work, the results have a number of important implications, among them the importance of vaccinating substitute teachers (and others in similar roles) to curtail epidemics.

“Finally, methods for forecasting disease spread must include both realistic population structure and salient aspects of human behaviour,” the team writes. “Without these key features, we cannot hope for robust, actionable models for predicting epidemics.”