Quantification of temporal transmission potential of an infectious disease has been a challenge. Most mathematical models assume that the transmission rate of an infectious disease either does not vary over time or change in fixed pre-determined adhoc ways.

Using a standard mathematical SIR-type epidemic model, Precision’s Anuj Mubayi and co-authors derive analytical estimates of time-dependent transmission rate for an epidemic in terms of either incidence or prevalence, and demonstrate that time-dependent transmission rate estimates can have a large variation, depending on the type of available data and other epidemiological parameters.

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