Modeling improvements promise increased accuracy for epidemic forecasting

Accurate forecasting of epidemic scenarios is critical to implementing effective public health intervention policies. Researchers used dynamical stochastic modeling techniques to reveal that infection and recovery rate fluctuations play a critical role in determining peak times for epidemics. Using a susceptible-infected-recovered epidemic model that incorporates daily fluctuations on control parameters, the study applies probability theory calculations to infection counts at the beginning of an...