Enhanced Pertussis Surveillance: A Model for Obtaining High-Quality Surveillance Data

Monday, June 23, 2014: 2:45 PM
109, Nashville Convention Center
Hajime Kamiya , Centers for Disease Control and Prevention, Atlanta, GA
Amanda Faulkner , Centers for Disease Control and Prevention, Atlanta, GA
Lisa Miller , Colorado Department of Public Health and Environment, Denver, CO
Kathy Kudish , Connecticut Department of Public Health, Hartford, CT
Cynthia Kenyon , Minnesota Department of Health, St. Paul, MN
W. David Selvage , New Mexico Department of Health, Santa Fe, NM
Bridget Whitney , New York State Department of Health, Albany, NY
Juventila Liko , Oregon Public Health Division, Portland, OR
Thomas A. Clark , Centers for Disease Control and Prevention, Atlanta, GA
Tami Skoff , Centers for Disease Control and Prevention, Atlanta, GA

BACKGROUND:  Reported pertussis has been increasing in the U.S. since the 1990s with recent epidemic peaks in disease. Furthermore, pertussis epidemiology has changed, with a growing burden of disease among those recently vaccinated. Because of known limitations of National Notifiable Diseases Surveillance System (NNDSS) pertussis surveillance data, Enhanced Pertussis Surveillance (EPS) was established within the Emerging Infections Program Network (EIP) in 2011 to improve surveillance through enhanced case ascertainment, augmented data collection, and isolate collection. The objective of this analysis is to compare EPS to NNDSS data and characterize current U.S. pertussis epidemiology from 2011-2012.

METHODS: Cases that met the Council of State and Territorial Epidemiologists (CSTE) confirmed or probable case definition were identified through routine surveillance in six EPS sites (Colorado, Connecticut, Minnesota, New Mexico, New York and Oregon) in 2011 and 2012. Case-patient demographics, clinical characteristics, outcome, and vaccination history were captured via patient and physician interview on a standardized form.  Available isolates were collected for further laboratory characterization, including susceptibility testing. Overall and age-specific incidence rates were calculated, and the completeness (i.e., proportion of cases with a known response) of key variables was compared between EPS and NNDSS; χ2 was used to compare proportions.

RESULTS: 8,990 pertussis cases were identified through EPS during the study period.  Overall cumulative incidence was 2.4 times higher in EPS (51.5/100,000 versus 21.3/100,000 in NNDSS). While the magnitude of age-specific incidence varied, trends were similar with the highest rates of disease occurring among infants <1 year (NNDSS: 303.1/100,000, EPS: 197.6/100,000), children aged 7-10 (NNDSS: 49.2/100,000, EPS: 122/100,000) and 11-14 year olds (NNDSS: 76.3/100,000, EPS: 231.9/100,000). Primary clinical symptom data (cough, paroxysms, whoop, and posttussive vomiting) were more complete for EPS compared to NNDSS cases (96% vs. 72%, respectively; p<0.01). The greatest differences in data completeness were observed for hospitalization status, outcome, cough onset date , and vaccination dates for children aged <7 years, all of which were >25% more complete among EPS cases. Of 7,351 laboratory-confirmed EPS cases, 354 (4.8%) were culture-confirmed; 86% of which had available isolates. All isolates were susceptible to azithromycin and erythromycin. 

CONCLUSIONS:  Although limited to 6 states, EPS produces high quality surveillance data that are significantly more complete than NNDSS, particularly for important variables such as vaccination history.  EPS data and isolates are essential for monitoring rapidly evolving pertussis epidemiology and molecular changes in the organism, evaluating new and existing vaccination recommendations, and informing future control strategies.