A novel sub-epidemic modeling framework for short-term forecasting epidemic waves.

ABSTRACT:

Background

Simple phenomenological growth models can be useful for estimating transmission parameters and forecasting epidemic trajectories. However, most existing phenomenological growth models only support single-peak outbreak dynamics whereas real epidemics often display more complex transmission trajectories.

Methods

We develop and apply a novel sub-epidemic modeling framework that supports a diversity of epidemic trajectories including stable incidence patterns with sustained or damped oscillations to better understand and forecast epidemic outbreaks. We describe how to forecast an epidemic based on the premise that the observed coarse-scale incidence can be decomposed into overlapping sub-epidemics at finer scales. We evaluate our modeling framework using three outbrea

SUBMITTER: Chowell G 

PROVIDER: S-EPMC6704534 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature