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Randomized Treatments May Be More Effective at Stopping Disease Outbreaks

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Mathematicians have found that by varying the timing of treatments, doctors may be able to increase the odds that a disease outbreak will die off suddenly.

Herding cats is a cakewalk compared with getting people to take flu vaccine shots in the last weeks of summer—work, school, limited pharmacy hours, beach days and countless other factors conspire to interfere. As a result, vaccinations tend to trickle in over many months. Rather than resisting this tendency, some mathematicians now think that public health officials may one day embrace it. A bit of randomness in treatment schedules may actually help manage a disease outbreak.

This conclusion comes from an analysis of treatment options in infectious disease outbreaks through the lens of complexity theory, which attempts to make sense of systems that are fundamentally unpredictable. Researchers using complexity theory to study disease outbreaks have identified rare instances when the outbreak will die out suddenly. Say, for instance, health workers administer antibiotics to fight an outbreak of bacterial meningitis, causing infections to decline. A classic disease model would suggest that every infected person must be isolated and treated before the disease can die out. But complexity theory shows that occasionally, the disease will die out due to random and unpredictable factors.
 
 

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