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

Using Modified Spatial Scan Statistic to Improve Detection of Disease Outbreak When Exposure Occurs in Workplace --Virginia, 2004

Luiz Duczmal,1 D. Buckeridge2,3
1
Universidade Federal de Minas Gerais, Brazil; 2Veterans Affairs Palo Alto Healthcare System, Palo Alto, California; 3Stanford University, Stanford, California

Corresponding author: Luiz Duczmal, Statistics Department, Universidade Federal de Minas Gerais, Belo Horizonte, MG 31270-901. Telephone: 55-31-3499-5900; Fax: 55-31-3499-5924; E-mail: duczmal@est.ufmg.br.

Disclosure of relationship: The contributors of this report have disclosed that they have no financial interest, relationship, affiliation, or other association with any organization that might represent a conflict of interest. In addition, this report does not contain any discussion of unlabeled use of commercial products or products for investigational use.

Abstract

Introduction: Detecting a disease outbreak is more difficult when the exposure occurs in a workplace but only the patient's home address is available for analysis. In these situations, application of the customary spatial scan statistic designed by Martin Kulldorff does not account for possible differences between home and work addresses, thereby reducing the power of detection.

Objectives: This study examined whether modifying Kulldorff's spatial scan statistic to take into account the movement of persons between home and work can improve detection of disease outbreaks when exposure occurs in the workplace.

Methods: The study region was partitioned into m cells Z(1),. . . ,Z(m). L(k,i) is the proportion of the population living in cell Z(k) that works at cell Z(i). For each cell Z(i), i = 1,. . . ,m, consider the r nearest cells from Z(i), r = 1,. . . ,R as the location of a possible outbreak that occurs during working hours. For each i and each r, build the m zones Y(1),. . . ,Y(m), adjoining successively the residential cells indicating where the workers from the r nearest cells from Z(i) live, in decreasing order of proportion of workers within these cells. The factors L(k,i) are used to compute the observed cases in the residential zones attributable to the contamination from workers at the r nearest neighbors of cell Z(i). This quantity, with the corresponding expected number of cases, is used to build the modified spatial scan statistic, similar to the usual spatial scan statistic. The modified scan statistic is computed m²R times, and the maximum value obtained indicates the most likely pair of outbreak focus and associated residential area found. A Monte Carlo procedure is used to compute the p-value of the most likely pair. The study region consisted of 158 ZIP codes located near Norfolk, Virginia. The following three typical simulated clusters, with their corresponding ZIP codes, are representative of much more extensive simulations: 1) Cluster A: 23601, 23606, 23607, 23661, 23666, 23668, and 23669; 2) Cluster B: 23601, 23602, 23606, 23665, 23666, and 23693; and 3) Cluster C: 23666 and 23669.

Results: Power evaluations of 0.85 (A), 0.70 (B), and 0.53 (C) were obtained by using the modified scan statistic compared with 0.68 (A), 0.52 (B), and 0.42 (C) obtained by using Kulldorff's spatial scan statistic.

Conclusion: Using a modified scan statistic that takes into account the movement of persons between home and work might be a useful complementary tool for the early detection of outbreaks in the workplace. Through simulations, a statistically significant increase in power was observed compared with the usual spatial scan statistic.

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.

Date last reviewed: 8/5/2005

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