The cost of simplifying air travel when modeling disease spread

Public Deposited
Analytics

Downloadable Content

Download PDF
Request Version for Screen Reader
Creator
  • Lessler, J
    • Affiliation: Gillings School of Global Public Health, Department of Epidemiology
    • Other Affiliation: Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
  • Kaufman, J.H
    • Other Affiliation: Health Informatics Research, IBM Almaden Research Center, San Jose, CA, United States
  • Ford, D.A
    • Other Affiliation: Health Informatics Research, IBM Almaden Research Center, San Jose, CA, United States
  • Douglas, J.V
    • Other Affiliation: Health Informatics Research, IBM Almaden Research Center, San Jose, CA, United States
Abstract
  • Background: Air travel plays a key role in the spread of many pathogens. Modeling the long distance spread of infectious disease in these cases requires an air travel model. Highly detailed air transportation models can be over determined and computationally problematic. We compared the predictions of a simplified air transport model with those of a model of all routes and assessed the impact of differences on models of infectious disease. Methodology/Principal Findings: Using U.S. ticket data from 2007, we compared a simplified "pipe" model, in which individuals flow in and out of the air transport system based on the number of arrivals and departures from a given airport, to a fully saturated model where all routes are modeled individually. We also compared the pipe model to a "gravity" model where the probability of travel is scaled by physical distance; the gravity model did not differ significantly from the pipe model. The pipe model roughly approximated actual air travel, but tended to overestimate the number of trips between small airports and underestimate travel between major east and west coast airports. For most routes, the maximum number of false (or missed) introductions of disease is small (<1 per day) but for a few routes this rate is greatly underestimated by the pipe model. Conclusions/Significance: If our interest is in large scale regional and national effects of disease, the simplified pipe model may be adequate. If we are interested in specific effects of interventions on particular air routes or the time for the disease to reach a particular location, a more complex point-to-point model will be more accurate. For many problems a hybrid model that independently models some frequently traveled routes may be the best choice. Regardless of the model used, the effect of simplifications and sensitivity to errors in parameter estimation should be analyzed.
Date of publication
Keyword
DOI
Identifier
Resource type
  • Article
License
  • Attribution 4.0 International
Journal title
  • PLoS ONE
Journal volume
  • 4
Journal issue
  • 2
Language
  • English
Version
  • Publisher
Publisher
  • Public Library of Science

Relations

Parents:

This work has no parents.

In Collection:

Items

Thumbnail Title Date Uploaded Visibility Actions
file details file27.pdf 2024-03-27 Public Download