Skip Navigation LinksSkip Navigation Links
Centers for Disease Control and Prevention
Safer Healthier People
Blue White
Blue White
bottom curve
CDC Home Search Health Topics A-Z spacer spacer
spacer
Blue curve MMWR spacer
spacer
spacer

The content, links, and pdfs are no longer maintained and might be outdated.

  • The content on this page is being archived for historic and reference purposes only.
  • For current, updated information see the MMWR website.

Improving Outbreak Detection by Signal Integration*

Paola Sebastiani,1,2 L. Wang,1,2 K.D. Mandl,2,3 M. Ramoni2,3
1
Boston University, Boston, Massachusetts; 2Center for Biopreparedness at Children's Hospital, Boston, Massachusetts; 3Harvard Medical School, Boston, Massachusetts

Corresponding author: Paola Sebastiani, Department of Biostatistics, Boston University School of Public Health, 715 Albany Street, Boston MA 02118. Telephone: 617-638-5877; Fax: 617-638-6484; E-mail: sebas@bu.edu.

Abstract

Introduction: A critical problem of surveillance systems is the trade-off between true and false detections. Integration of different monitors and information from exogenous sources can increase the true-detection rate by limiting the false-detection rate.

Objective: The authors introduce a probabilistic architecture able to achieve a substantial detection rate while keeping false detections low.

Methods: The architecture is a Bayesian network that encodes probabilistic information through a directed graph. The nodes and arrows represent variables and stochastic dependencies quantified by probability distributions. The integration of two systems for syndromic surveillance at a pediatric and adult hospital is illustrated by using a respiratory illness outbreak (Figure). Empirical evaluations have demonstrated that true and false-alert rates are affected by influenza epidemics, by air quality as measured by pollen level, and by whether the alert day is a holiday. The network integrates the sources of information to compute the probability of an outbreak (given that one or both systems generate alerts) and what is known about the other variables. The probability tables quantifying the network were obtained from data contaminated with different simulated outbreaks. The integrator was validated on 84 simulated outbreaks.

Results and Conclusions: This study indicates that the integration of the two monitoring systems with exogenous information has a 73% true-detection rate with an 8% false-detection rate in limited outbreaks (i.e., an average of four ill persons/day), and 97% true-detection rate with 10% false-detection rate in more substantial outbreaks (i.e., an average of eight ill persons/day).

* This work was supported by the Alfred P. Sloan Foundation (Grant 2002-12-1).

Figure

Figure 1
Return to top.

Use of trade names and commercial sources is for identification only and does not imply endorsement by the U.S. Department of Health and Human Services.


References to non-CDC sites on the Internet are provided as a service to MMWR readers and do not constitute or imply endorsement of these organizations or their programs by CDC or the U.S. Department of Health and Human Services. CDC is not responsible for the content of pages found at these sites. URL addresses listed in MMWR were current as of the date of publication.

Disclaimer   All MMWR HTML versions of articles are electronic conversions from ASCII text into HTML. This conversion may have resulted in character translation or format errors in the HTML version. Users should not rely on this HTML document, but are referred to the electronic PDF version and/or the original MMWR paper copy for the official text, figures, and tables. An original paper copy of this issue can be obtained from the Superintendent of Documents, U.S. Government Printing Office (GPO), Washington, DC 20402-9371; telephone: (202) 512-1800. Contact GPO for current prices.

**Questions or messages regarding errors in formatting should be addressed to mmwrq@cdc.gov.

Page converted: 9/14/2004

HOME  |  ABOUT MMWR  |  MMWR SEARCH  |  DOWNLOADS  |  RSSCONTACT
POLICY  |  DISCLAIMER  |  ACCESSIBILITY

Safer, Healthier People

Morbidity and Mortality Weekly Report
Centers for Disease Control and Prevention
1600 Clifton Rd, MailStop E-90, Atlanta, GA 30333, U.S.A

USA.GovDHHS

Department of Health
and Human Services

This page last reviewed 9/14/2004