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

Luiz Duczmal,¹ D. Buckeridge^2,3
1Universidade 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.

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Date last reviewed: 8/5/2005