Successful public health regimes for COVID-19 push below unity long-term global Rt — the average number of secondary cases caused by an infectious individual. Most assessments use local information. Populations differ in Rt, amongst themselves and over time. We use a SIR model for two populations to make the conceptual point that even if each locality averages Rt < 1, the overall epidemic can still grow, provided these populations have asynchronous variation in transmission, and are coupled by movement of infectious individuals. This emergent effect in pandemic dynamics instantiates “Parrondo’s Paradox,” — an entity comprised of distinct but interacting units can behave qualitatively differently than each part on its own. For effective COVID-19 disease mitigation strategies, it is critical that infectious individuals moving among locations be identified and quarantined. This does not warrant indiscriminate prevention of movement, but rather rational, targeted testing and national coordination.
Competing Interest Statement
The authors have declared no competing interest.
Not applicable (no clinical trials)
This work was funded (via support of postdoctoral salaries) by USDA (award number 2017-67013-26870) as part of the joint USDA-NSF-NIH Ecology and Evolution of Infectious Diseases program, the National Science Foundation (DEB-1655555), and the University of Florida Foundation.
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