Using fractional exponents in epidemic models could improve predictions of disease spread

A new class of epidemiological models based on alternative thinking about how contagions propagate, particularly in the early phases of a pandemic, provide a blueprint for more accurate epidemic modeling and improved disease spread predictions and responses, according to a study published recently in Scientific Reports by researchers at the University of California, Irvine and other institutions.

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