Modeling the effect of public health resources and alerting on the dynamics of pertussis spread

Emine Yaylali*, Julie S. Ivy, Reha Uzsoy, Erika Samoff, Anne Marie Meyer, Jean Marie Maillard

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

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 languageEnglish
Pages (from-to)81-97
Number of pages17
JournalHealth Systems
Volume5
Issue number2
DOIs
Publication statusPublished - 1 Jun 2016
Externally publishedYes

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.

FundersFunder number
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 CarolinaUNC
University of Oklahoma Health Sciences Center

    Keywords

    • contact tracing
    • discrete event simulation
    • infectious disease modeling
    • outbreak management
    • pertussis

    Fingerprint

    Dive into the research topics of 'Modeling the effect of public health resources and alerting on the dynamics of pertussis spread'. Together they form a unique fingerprint.

    Cite this