With the first COVID-19 epidemic peak behind them, many countries explained the decrease of infection numbers through non-pharmaceutical interventions.

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Phrases like "social distancing" and "flatten the curve" have become part of common vocabulary. Yet some explanations fell short: How could one explain the linear rise of infection curves, which many countries display after the first peak, in contrast to the S-shaped curves, expected from epidemiological models?

In a new paper published in the Proceedings of the National Academy of Sciences, scientists at the Complexity Science Hub Vienna (CSH) offer an explanation for the linear growth of the infection curve.