Reading the pandemic data

Jeffrey Zacks, professor of psychological & brain sciences in Arts & Sciences


Understanding the spread of coronavirus disease 2019 (COVID-19) requires understanding nonlinear growth. Whereas linear growth is intuitive, nonlinear growth is not. People’s predictions for nonlinear patterns tend to be closer to linear projections, assuming that future growth will be similar to that of the past. For a pandemic, this can lead to dangerous underestimations in the time to reach a critical value.

Most physical phenomena, such as the accumulation of snow or spread of a spill, have linear growth rates or rates that only increase slowly. Exponential growth, in which the rate of growth itself rapidly increases, may be less frequently observed, in part because such growth often quickly ceases after reaching some boundary condition. Pandemics such as COVID-19 grow exponentially, which can challenge understanding. Simulations can help build intuitions about exponential growth.

Read the full piece in Science.

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