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Tuesday, March 18, 2008 - 2:35 PM
50
Geographical Clustering of Nonmedical Exemptions to School Immunization Requirements and Associations with Geographical Clustering of Pertussis
Saad B. Omer, Global Disease Epidemiology and Control Program , International Health, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Room E5537, Baltimore, MD, USA, Kyle S. Enger, Division of Immunization, Michigan Department of Community Health, 201 Townsend St, Lansing, MI, USA, Larry Moulton, Disease Prevention and Control Program, International Health, Johns Hopkins School of Public Health, 615 N. Wolfe Street, Suite 5519, Baltimore, MD, USA, Neal A. Halsey, Division of Disease Control, International Health, Johns Hopkins School of Public Health, 615 N. Wolfe Street, Suite 5515, Baltimore, MD, USA, Shannon Stokley, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, and Daniel A. Salmon, Global Disease Epidemiology and Control Program , International Health, Johns Hopkins School of Public Health, 615 N. Wolfe Street, Suite 5515, Baltimore, MD, USA.
Learning Objectives for this Presentation:
By the end of the presentation participants will be able to appreciate the dynamics and impact of local clustering of vaccine exemptors.
Background:
School immunization requirements are important in controlling vaccine-preventable diseases in the United States. Forty-eight states offer non-medical exemptions to school immunization requirements. Children with exemptions are at increased risk of contracting and transmitting vaccine-preventable diseases. The clustering of non-medical exemptions can impact community risk to vaccine-preventable diseases.
Objectives:
To evaluate spatial clustering of nonmedical exemptions in Michigan and geographical overlap between exemptions clusters and clusters of reported pertussis cases.
Methods:
Spatial analysis of clustering of nonmedical exemptions and pertussis using Scan Statistics.
Results:
Six statistically significant clusters of pertussis cases were identified spanning the following timeframes: 8/93 – 9/93, 8/94 – 2/95, 5/98 – 6/98, 7/00 – 11/00, 4/02, 5/03 – 7/03, and 6/04 – 11/04. It was more likely for census tracts in exemptions clusters to be in pertussis clusters (OR = 3.0; CI, 2.5 – 3.6). The overlap of exemptions clusters and pertussis clusters remained significant after adjusting for population density, proportion minorities, proportion 5 years or younger, and average family size (OR = 3.4; CI, 2.8 – 4.1).
Conclusions:
In addition to monitoring state-level exemption rates, state and local health authorities should be mindful of within-state heterogeneity in exemption rates and should actively follow trends in sub-state level exemption rates.