The Fractional Epidemics Theory: Managing and Ending an Epidemic
Duclos, T. G.; Reichert, T. A.
Show abstract
Susceptible-infectious-recovered (SIR) models are widely used for estimating the dynamics of epidemics and project that social distancing "flattens the curve", i.e., reduces but delays the peak in daily infections, causing a longer epidemic. Based on these projections, individuals and governments have advocated lifting containment measures such as social distancing to shift the peak forward and limit societal and economic disruption. Paradoxically, the COVID-19 pandemic data exhibits phenomenology opposite to the SIR models projections. Here, we present a new model that replicates the observed phenomenology and quantitates pandemic dynamics with simple and actionable analytical tools for policy makers. Specifically, it offers a prescription of achievable and economically palatable measures for ending an epidemic. One Sentence SummaryThe SIR epidemic models are wrong; a new model offers achievable and economically viable measures for ending an epidemic.
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