Hostname: page-component-78c5997874-94fs2 Total loading time: 0 Render date: 2024-11-18T06:07:22.925Z Has data issue: false hasContentIssue false

Enhancing Local Health Department Disaster Response Capacity with Rapid Community Needs Assessments: Validation of a Computerized Program for Binary Attribute Cluster Sampling

Published online by Cambridge University Press:  28 June 2012

Matthew R. Groenewold*
Affiliation:
Office of Policy Planning and Evaluation, Louisville Metro Health Department, Louisville, Kentucky, USA
*
Matthew R. Groenewold, MSPH, Office of Policy Planning and Evaluation, Louisville Metro Health Department, 400 East Gray Street, PO Box 1704, Louisville, Kentucky 40201 USA E-mail: matt.groenewold@louisvilleky.gov

Abstract

Introduction:

Local health departments are among the first agencies to respond to disasters or other mass emergencies. However, they often lack the ability to handle large-scale events. Plans including locally developed and deployed tools may enhance local response. Simplified cluster sampling methods can be useful in assessing community needs after a sudden-onset, short duration event.

Methods:

Using an adaptation of the methodology used by the World Health Organization Expanded Programme on Immunization (EPI), a Microsoft Access-based application for two-stage cluster sampling of residential addresses in Louisville/Jefferson County Metro, Kentucky was developed. The sampling frame was derived from geographically referenced data on residential addresses and political districts available through the Louisville/Jefferson County Information Consortium (LOJIC). The program randomly selected 30 clusters, defined as election precincts, from within the area of interest, and then, randomly selected 10 residential addresses from each cluster.

The program, called the Rapid Assessment Tools Package (RATP), was tested in terms of accuracy and precision using data on a dichotomous characteristic of residential addresses available from the local tax assessor database. A series of 30 samples were produced and analyzed with respect to their precision and accuracy in estimating the prevalence of the study attribute. Point estimates with 95% confidence intervals were calculated by determining the proportion of the study attribute values in each of the samples and compared with the population proportion. To estimate the design effect, corresponding simple random samples of 300 addresses were taken after each of the 30 cluster samples.

Results:

The sample proportion fell within ±10 absolute percentage points of the true proportion in 80% of the samples. In 93.3% of the samples, the point estimate fell within ±12.5%, and 96.7% fell within ±15%. All of the point estimates fell within ±20% of the true proportion. Estimates of the design effect ranged from 0.926 to 1.436 (mean = 1.157, median = 1.170) for the 30 samples.

Conclusions:

Although prospective evaluation of its performance in field trials or a real emergency is required to confirm its utility, this study suggests that the Rapid Assessment Tools Package, a locally designed and deployed tool, may provide populationbased estimates of community needs or the extent of event-related consequences that are precise enough to serve as the basis for the initial post-event decisions regarding relief efforts.

Type
Original Research
Copyright
Copyright © World Association for Disaster and Emergency Medicine 2006

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

1.Hlady, WG, Quenemoen, LE, Armenia-Cope, RR, Hurt, KJ, Malilay, J, Noji, EK, Wurm, G: Use of a modified cluster sampling method to perform rapid needs assessment after Hurricane Andrew. Ann Emerg Med 1994;23:719725.CrossRefGoogle ScholarPubMed
2.United States Centers for Disease Control and Prevention (CDC): Rapid health needs assessment following Hurricane Andrew–Florida and Louisiana, 1992. MMWR 1992;41:685688.Google Scholar
3.Centers for Disease Control and Prevention: Community needs assessment and morbidity surveillance following an ice storm–Maine, January 1998. MMWR 1998;47:351354.Google Scholar
4.Centers for Disease Control and Prevention: Tropical Storm Allison rapid needs assessment—Houston, Texas, June 2001. MMWR 2002;51:365369.Google Scholar
5.Centers for Disease Control and Prevention: Rapid community health and needs assessments after Hurricanes Isabel and Charley—North Carolina, 2003-2004. MMWR 2004;53:840842.Google Scholar
6.Centers for Disease Control and Prevention: Rapid assessment of the needs and health status of older adults after Hurricane Charley—Charlotte, DeSoto, and Hardee Counties, Florida, August 27–31, 2004. MMWR 2004;53:837840.Google Scholar
7.Malilay, J: Public health assessments in disaster settings: Recommendations for a multidisciplinary approach. Prehosp Disast Med 2000;15(4):167172.CrossRefGoogle ScholarPubMed
8.Centers for Disease Control and Prevention: Community needs assessment of lower Manhattan residents following the World Trade Center attacks—Manhattan, New York City, 2001. MMWR 2002;11 51 Spec No:10–3.Google Scholar
9.Guha-Sapir, D: Rapid assessment of health needs in mass emergencies: Review of current concepts and methods. World Health Stat Q 1991;44:171181.Google Scholar
10.Materia, E, Imoko, J, Berhe, G, Dawuda, C, Omar, MA, Pinto, A, Guerra, R: Rapid surveys in support of district health information systems: An experience from Uganda. East Afr Med J 1995;72:1518.Google ScholarPubMed
11.Frerichs, RR, Tar, KT: Computer-assisted rapid surveys in developing countries. Public Health Rep 1989;104:1423.Google Scholar
12.Mayaud, P, Msuya, W, Todd, J, Kaatano, G, West, B, Begkoyian, G, Grosskurth, H, Mabey, D: STD rapid assessment in Rwandan refugee camps in Tanzania. Genitourin Med 1997;73:3338.Google Scholar
13.Abramson, JH, Abramson, ZH: Survey Methods in Community Medicine: Epidemiological Research, Programme Evaluation, Clinical Trials. 5th ed. Edinburgh: Churchill Livingston, 1999: pp 343354.Google Scholar
14.Goma Epidemiology Group: Public health impact of Rwandan refugee crisis: What happened in Goma, Zaire, in July, 1994? Lancet 1995;345:339344.CrossRefGoogle Scholar
15.Drysdale, S, Howarth, J, Powell, V, Healing, T: The use of cluster sampling to deter mine aid needs in Grozny, Chechnya in 1995. Disasters 2000;24(3):217227.Google Scholar
16.Legetic, B, Jakovljevic, D, Marinkovic, J, Niciforovic, O, Stanisavljevic, D: Health care delivery and the status of the populations' health in the current crisis in former Yugoslavia using World Health Organization Expanded Programme on Immunization-design methodology. Int J Epidemiol 1996;25:341348.CrossRefGoogle Scholar
17.Centers for Disease Control and Prevention: Community needs assessment and morbidity surveillance following an earthquake—Turkey, August 1999. MMWR 1999;48:11471150.Google Scholar
18.Billitier, AJ: Regional emergency preparedness efforts by local health departments in Western New York. J Public Health Management Practice 2003;9(5):394400.Google Scholar
19.Morse, A: Bioterrorism preparedness for local health departments. J Community Health Nurs 2002;19(4):203211.CrossRefGoogle ScholarPubMed
20.Keim, M: Using a community-based approach for prevention and mitigation of national health emergencies. Pac Health Dialog 2002;9(1):9396.Google Scholar
21.Glick, DF, Jerome-D'Emilia, B, Nolan, M, Burke, P: Emergency preparedness: One community's response. Fam Community Health 2004;27(3):266273.CrossRefGoogle ScholarPubMed
22.Bashir, Z, Lafronza, V, Fraser, MR, Brown, CK, Cope, JR: Local and state collaboration for effective preparedness planning. J Public Health Management Practice 2003;9(5):344351.Google Scholar
23.Fraser, MR, Brown, DL: Bioterrorism preparedness and local public health agencies: Building response capacity. Public Health Rep 2000;115:326330.Google Scholar
24. Centers for Disease Control and Prevention: Community study: Rapid Community Needs Assessment using Modified Cluster Sampling Methods. In: Mass Trauma Preparedness and Response: Possible Research Studies, Atlanta.Available at http://www.cdc.gov/masstrauma/research/possible_studies/ community/rapid.htm. Accessed 18 August 2004.Google Scholar
25. Centers for Disease Control and Prevention: Preparedness Research and Response Tools: Mental Health Survey Instrument. In: Emergency Preparedness and Response, Atlanta. Available at: http://www.bt.cdc.gov/masstrauma/mhsurvey-instrument.asp. Accessed 10 March 2005.Google Scholar
26. Louisville/Jefferson County Information Consortium: About LOJIC. In: Louisville/Jefferson County Information Consortium, Louisville. Available at http://www.lojic.org/about/index.htm. Accessed 18 August 2004.Google Scholar
27.Henderson, RH, Sundaresan, T: Cluster sampling to assess immunization coverage: a review of experience with a simplified sampling method. Bull World Health Organ 1982;60:253260.Google ScholarPubMed
28.Armitage, P, Berry, G, Mathews, JNS: Statistical Methods in Medical Research, 4th Ed. Oxford: Blackwell Science, 2002: pp 655656.Google Scholar
29.Lemeshow, S, Robinson, D: Surveys to measure programme coverage and impact: A review of the methodology used by the Expanded Programme on Immunization. World Health Stat Q 1985;38:6575.Google Scholar
30.Bennett, S, Woods, T, Liyanage, WM, Smith, DL: A simplified general method for cluster-sample surveys of health in developing countries. World Health Stat Q 1991;44:98106.Google ScholarPubMed
31.Daniel, WD. Biostatistics: A Foundation for Analysis in the Health Sciences. New York: John Wiley & Sons, Inc., 1999, pp 140–141, 183184.Google Scholar
32.Ruiz, MO, Remmert, D: A local department of public health and the geospatial data infrastructure. J Med Syst 2004;28(4):385395.Google Scholar
33. Kentucky State Data Center and Kentucky Population Research: Louisville Metro Council Districts: Profiles of Child, Family and Demographic Trends. In: Louisville Neighborhood Profiles. Louisville. Available at: http://ksdc.louisville.edu/kpr/MetroCouncilDistricts/councildistricts.html. Accessed 6 April 2005.Google Scholar
34. Kentucky Revised Statutes 117.055(4) (15 July 2002).Google Scholar
35.Katz, J: Sample-size implications for population-based cluster surveys of nutritional status. Am J Clin Nutr 1995;61:155160.CrossRefGoogle ScholarPubMed