id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-330148-yltc6wpv	Lessler, Justin	Trends in the Mechanistic and Dynamic Modeling of Infectious Diseases	2016-07-02		.txt	text/plain	5911	247	34	Uncertainty was largely addressed through scenario-based approaches (e.g., different future epidemic trajectories were presented for different plausible sets of parameters), and for the most part, different aspects of the transmission dynamics were derived from independent studies, with only the growth rate (i.e., doubling time) estimated from incidence data. These recent attempts to quickly characterize the properties of emerging diseases are emblematic of an increasing focus on developing statistical methods, grounded in dynamical models, to estimate key epidemic parameters based on diverse data sources. High-resolution geographic data can gain additional power when paired with mechanistic models that capture changes in disease risk, as in recent analyses that accounted for the effect of birth, natural infection, and vaccine disruptions driving increases in measles susceptibility and epidemic risk in the wake of the Ebola outbreak [63] . The formal statistical integration of population genetic and epidemic models allows us to estimate the critical epidemiological parameters such as the basic reproductive number directly from pathogen sequence data [75] [76] [77] .	./cache/cord-330148-yltc6wpv.txt	./txt/cord-330148-yltc6wpv.txt