@article{yaylali_ivy_uzsoy_samoff_meyer_maillard_2016, title={Modeling the effect of public health resources and alerting on the dynamics of pertussis spread}, volume={5}, ISSN={["2047-6973"]}, DOI={10.1057/hs.2015.6}, abstractNote={We consider the response of a local health department (LHD) to a pertussis outbreak using a composite discrete event simulation model with a stochastic branching process. The model captures the effect of epidemiologic spread of disease as a function of the health alert levels and the resource availability of the LHD. The primary response mode in the model is contact tracing that is assumed to be a resource-based delay with an iterative tracing policy. The effect of the threshold for initiating contact tracing and its relationship with the resource availability of the LHD is explored. The model parameters associated with contact tracing are estimated using North Carolina (NC), U.S.A. pertussis case data and data from the NC Public Health Information Network. The infectivity parameters are derived from literature. The results suggest that the time to initiate contact tracing significantly affects the magnitude and duration of the outbreak. The resource levels for contact tracing have less significant impact on the outbreak outcomes. However, when the nurse schedule is constrained, that is, if the total hours devoted to contact tracing a week is restricted, the effect of the resource level becomes significant. In fact, some outbreaks could not be controlled within the 1-year time limit of simulation.}, number={2}, journal={HEALTH SYSTEMS}, author={Yaylali, Emine and Ivy, Julie S. and Uzsoy, Reha and Samoff, Erika and Meyer, Anne Marie and Maillard, Jean Marie}, year={2016}, month={Jun}, pages={81–97} }
 @article{yaylali_ivy_taheri_2014, title={Systems Engineering Methods for Enhancing the Value Stream in Public Health Preparedness: The Role of Markov Models, Simulation, and Optimization}, volume={129}, ISSN={["0033-3549"]}, DOI={10.1177/00333549141296s419}, abstractNote={Objectives. Large-scale incidents such as the 2009 H1N1 outbreak, the 2011 European Escherichia coli outbreak, and Hurricane Sandy demonstrate the need for continuous improvement in emergency preparation, alert, and response systems globally. As questions relating to emergency preparedness and response continue to rise to the forefront, the field of industrial and systems engineering (ISE) emerges, as it provides sophisticated techniques that have the ability to model the system, simulate, and optimize complex systems, even under uncertainty. Methods. We applied three ISE techniques—Markov modeling, operations research (OR) or optimization, and computer simulation—to public health emergency preparedness. Results. We present three models developed through a four-year partnership with stakeholders from state and local public health for effectively, efficiently, and appropriately responding to potential public health threats: ( 1) an OR model for optimal alerting in response to a public health event, ( 2) simulation models developed to respond to communicable disease events from the perspective of public health, and ( 3) simulation models for implementing pandemic influenza vaccination clinics representative of clinics in operation for the 2009–2010 H1N1 vaccinations in North Carolina. Conclusions. The methods employed by the ISE discipline offer powerful new insights to understand and improve public health emergency preparedness and response systems. The models can be used by public health practitioners not only to inform their planning decisions but also to provide a quantitative argument to support public health decision making and investment. }, journal={PUBLIC HEALTH REPORTS}, author={Yaylali, Emine and Ivy, Julie Simmons and Taheri, Javad}, year={2014}, pages={145–153} }