Hostname: page-component-8448b6f56d-jr42d Total loading time: 0 Render date: 2024-04-24T10:16:40.442Z Has data issue: false hasContentIssue false
  • English
  • Français

Analyzing Postdisaster Surveillance Data: The Effect of the Statistical Method

Published online by Cambridge University Press:  08 April 2013

Charles DiMaggio ,
Sandro Galea  and
David Abramson
Get access Rights & Permissions [Opens in a new window]

Abstract

Data from existing administrative databases and ongoing surveys or surveillance methods may prove indispensable after mass traumas as a way of providing information that may be useful to emergency planners and practitioners. The analytic approach, however, may affect exposure prevalence estimates and measures of association. We compare Bayesian hierarchical modeling methods to standard survey analytic techniques for survey data collected in the aftermath of a terrorist attack. Estimates for the prevalence of exposure to the terrorist attacks of September 11, 2001, varied by the method chosen. Bayesian hierarchical modeling returned the lowest estimate for exposure prevalence with a credible interval spanning nearly 3 times the range of the confidence intervals (CIs) associated with both unadjusted and survey procedures. Bayesian hierarchical modeling also returned a smaller point estimate for measures of association, although in this instance the credible interval was tighter than that obtained through survey procedures. Bayesian approaches allow a consideration of preexisting assumptions about survey data, and may offer potential advantages, particularly in the uncertain environment of postterrorism and disaster settings. Additional comparative analyses of existing data are necessary to guide our ability to use these techniques in future incidents. (Disaster Med Public Health Preparedness. 2008;2:119–126)

Keywords

Bayesiansurveysurveillancedata
Type
Concepts in Disaster Medicine
Information
Disaster Medicine and Public Health Preparedness , Volume 2 , Issue 2 , June 2008 , pp. 119 - 126
Copyright
Copyright © Society for Disaster Medicine and Public Health, Inc. 2008

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1.Galea, S, Nandi, A, Vlahov, D. The epidemiology of post-traumatic stress disorder after disasters. Epidemiol Rev. 2005; 27: 78–91.Google Scholar
2.Norris, FH, Friedman, MJ, Watson, PJ. 60,000 disaster victims speak: II. Summary and implications of the disaster mental health research. Psychiatry. 2002; 65: 240–260.CrossRefGoogle Scholar
3.Norris, FH, Friedman, MJ, Watson, PJ, et al60,000 disaster victims speak: I. An empirical review of the empirical literature, 1981–2001. Psychiatry. 2002; 65: 207–239.Google Scholar
4.Galea, S, Norris, FH. Public mental health surveillance and monitoring. Norris FH, Galea S, Friedman MJ, Watson PJ, ed. Methods for Disaster Mental Health Research. New York: Guilford Press; 2006 177–194.Google Scholar
5.Noji, EK. Analysis of medical needs during disasters caused by tropical cyclones: anticipated injury patterns. J Trop Med Hyg. 1993; 96: 370–376.Google Scholar
6.Boscarino, JA, Galea, S, Adams, RE, et alMental health service and medication use in New York City after the September 11, 2001, terrorist attack. Psychiatr Serv. 2004; 55: 274–283.Google Scholar
7.Chen, H, Chung, H, Chen, T, et alThe emotional distress in a community after the terrorist attack on the World Trade Center. Community Ment Health J. 2003; 39: 157–165.Google Scholar
8.DiMaggio, C, Galea, S, Madrid, P. SSRI prescription rates after a terrorist attack. Psychiatr Serv. 2006; 57: 1656–1657.CrossRefGoogle ScholarPubMed
9.Dimaggio, C, Galea, S, Richardson, LD. Emergency department visits for behavioral and mental health care after a terrorist attack. Ann Emerg Med. 2006; 50: 327–334.Google Scholar
10.Galea, S, Ahern, J, Resnick, H, et alPsychological sequelae of the September 11 terrorist attacks in New York City. N Engl J Med. 2002; 346: 982–987.Google Scholar
11.Laraque, D, Boscarino, JA, Battista, A, et alReactions and needs of tristate-area pediatricians after the events of September 11th: implications for children's mental health services. Pediatrics. 2004; 113: 1357–1366.Google Scholar
12.Remington, PL, Smith, MY, Williamson, DF, et alDesign, characteristics, and usefulness of state-based behavioral risk factor surveillance: 1981–1987. Public Health Rep. 1988; 103: 366–375.Google Scholar
13.Melnick, TA, Baker, CT, Adams, ML, et alPsychological and emotional effects of the September 11 attacks on the World Trade Center–Connecticut, New Jersey, and New York, 2001. MMWR Morb Mortal Wkly Rep. 2002; 51: 784–786.Google Scholar
14.Centers for Disease Control and Prevention. National Center for Chronic Disease Prevention and Health Promotion. Behavioral Risk Factor Surveillance System. http://www.cdc.gov/brfss. Accessed March 16, 2007.Google Scholar
15.New York State Department of Health. http://www.health.state.ny.us/nysdoh/brfss. Accessed June 4, 2007.Google Scholar
16.SAS 9.1.3. 2006. http://www.sas.com. Accessed May 2, 2008.Google Scholar
17.Greenland, S. Bayesian perspectives for epidemiological research: I. Foundations and basic methods. Int J Epidemiol. 2006; 35: 765–75.CrossRefGoogle ScholarPubMed
18.Lawson, A, Browne, W, Vidal Rodeiro, C. Disease Mapping With WinBUGS and MLWin. New York: John Wiley & Sons; 2003.Google Scholar
19.Baca Baldomero, E, Cabanas Arrate, ML, Perez-Rodriguez, MM, Baca-Garcia, E. Trastornos mentales en las victimas de atentados terroristas y sus familiares [in Spanish]. Med Clin. 2004; 122: 681–685.Google Scholar
20.R 2.2.1. 205. http://www.r-project.org. Accessed September 1, 2006.Google Scholar
21.Noji, EK, Sivertson, KT. Injury prevention in natural disasters: a theoretical framework. Disasters. 1987; 11: 290–296.Google Scholar
22.Bell, W, Dallas, C. Vulnerability of populations and the urban health care systems to nuclear weapon attack—examples from four American cities. Int J Health Geogr. 2007; 6: 5.CrossRefGoogle ScholarPubMed
23.Herman, D, Felton, C, Susser, E. Mental health needs in New York state following the September 11th attacks. J Urban Health. 2002; 79: 322–331.Google Scholar
24.Goldstein, H, Browne, W, Rasbash, J. Partitioning variation in multilevel models. Understanding Stat. 2002; 1: 223–231.CrossRefGoogle Scholar
25.Factor, SH, Wu, Y, Monserrate, J, et alDrug use frequency among street-recruited heroin and cocaine users in Harlem and the Bronx before and after September 11, 2001. J Urban Health. 2002; 79: 404–408.Google Scholar
26.Vlahov, D, Galea, S, Ahern, J, et alSustained increased consumption of cigarettes, alcohol, and marijuana among Manhattan residents after September 11, 2001. Am J Public Health. 2004; 94: 253–254.Google Scholar
27.Vlahov, D, Galea, S, Resnick, H, et alIncreased use of cigarettes, alcohol, and marijuana among Manhattan, New York, residents after the September 11th terrorist attacks. Am J Epidemiol. 2002; 155: 988–996.Google Scholar
28.DiMaggio C, Galea S, Vlahov D. Bayesian hierarchical spatial modeling of substance abuse patterns following a mass trauma: the role of time and place. Subst Use Misuse. 2008. In press.Google Scholar
29.Park D, Gelman A, Bafumi J. State-level opinions from national surveys: post-stratification using hierarchical logistic regression. Paper presented at the Political Methodology Conference. July 18–20, 2002; Seattle, WA.Google Scholar
30.Lewis, RJ. Bayesian modeling and real-world problems. Acad Emerg Med. 2003; 10: 780–782.Google Scholar