Abstract
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.
Original language | English |
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Pages (from-to) | 81-97 |
Number of pages | 17 |
Journal | Health Systems |
Volume | 5 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Jun 2016 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2015, Copyright © 2015, Operational Research Society Ltd.
Funding
The authors would like to acknowledge Dr. Aaron Weldelboe, Assistant Professor, Department of Biostatistics and Epidemiology in the College of Public Health at The University of Oklahoma Health Sciences Center and Travis Worth, former Masters Student in Edwards P. Fitts Department of Industrial and Systems Engineering at North Carolina State University for their contribution to this work. This research was conducted by the North Carolina Preparedness and Emergency Response Research Center (NCPERRC), which is part of the University of North Carolina (UNC) Center for Public Health Preparedness at the UNC at Chapel Hill Gillings School of Global Public Health, and was supported by the Centers for Disease Control and Prevention (CDC) grant #. The contents and views expressed in this article are solely the responsibility of the authors and do not necessarily represent the official views of CDC. The authors would like to acknowledge Dr. Aaron Weldelboe, Assistant Professor, Department of Biostatistics and Epidemiology in the College of Public Health at The University of Oklahoma Health Sciences Center and Travis Worth, former Masters Student in Edwards P. Fitts Department of Industrial and Systems Engineering at North Carolina State University for their contribution to this work. This research was conducted by the North Carolina Preparedness and Emergency Response Research Center (NCPERRC), which is part of the University of North Carolina (UNC) Center for Public Health Preparedness at the UNC at Chapel Hill Gillings School of Global Public Health, and was supported by the Centers for Disease Control and Prevention (CDC) grant #. The contents and views expressed in this article are solely the responsibility of the authors and do not necessarily represent the official views of CDC.
Funders | Funder number |
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Department of Biostatistics and Epidemiology in the College of Public Health | |
Masters Student in Edwards P. Fitts Department of Industrial and Systems Engineering at North Carolina State University | |
Travis Worth | |
Centers for Disease Control and Prevention | |
University of North Carolina | UNC |
University of Oklahoma Health Sciences Center |
Keywords
- contact tracing
- discrete event simulation
- infectious disease modeling
- outbreak management
- pertussis