title: A Framework for Modeling Emerging Diseases to Inform Management.
abstract: The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.
authors.forename: Robin E
authors.initials: RE
authors.lastname: Russell
authors.forename: Rachel A
authors.initials: RA
authors.lastname: Katz
authors.forename: Katherine L D
authors.initials: KL
authors.lastname: Richgels
authors.forename: Daniel P
authors.initials: DP
authors.lastname: Walsh
authors.forename: Evan H C
authors.initials: EH
authors.lastname: Grant
mesh_terms: D000818:Animals; D000066491:Clinical Decision-Making / Q000379:methods*; D021821:Communicable Diseases, Emerging / Q000453:epidemiology* / Q000517:prevention & control / Q000635:transmission; D003661:Decision Support Techniques; D019468:Disease Management; D006801:Humans; D035501:Uncertainty; D014481:United States / Q000453:epidemiology; D015047:Zoonoses / Q000453:epidemiology* / Q000517:prevention & control / Q000635:transmission
keywords: decision analysis; emerging diseases; infectious diseases; mathematical modelling; model development; one health; predictive modelling; zoonoses; zoonotic diseases