114 Influenza-like Illness Incidence Variation According to Characteristics of Participating Healthcare Practices in the Influenza Incidence Surveillance Project

Tuesday, June 24, 2014: 10:00 AM-10:30 AM
East Exhibit Hall, Nashville Convention Center
Andrea Giorgi , Centers for Disease Control and Prevention, Atlanta, GA
Heather Rubino , Florida Department of Health, Tallahassee, FL
Oluwakemi Oni , Iowa Department of Public Health, Des Moines, IA
Christine Selzer , Los Angeles County Department of Public Health, Los Angeles, CA
Karen Martin , Minnesota Department of Health, Saint Paul, MN
Michelle Feist , North Dakota Department of Health, Bismarck, ND
Steve Di Lonardo , New York City Department of Health and Mental Hygiene, New York City, NY
Lisa McHugh , New Jersey Department of Health and Senior Services, Trenton, NJ
Jose Lojo , Philadelphia Department of Public Health, Philadelphia, PA
Ann Thomas , Oregon Health Authority, Portlant=d, OR
Lesley Brannan , Texas Department of State Health Services, Austin, TX
Katie Kurkjian , Virgina Department of Health, Richmond, VA
Jonathan Temte , University of Wisconsin School of Medicine and Public Health, Madison, WI
Nicole Bryan , CSTE, Atlanta, GA
Lyn Finelli , Centers for Disease Control and Prevention, Atlanta, GA
Ashley Fowlkes , Centers for Disease Control and Prevention, Atlanta, GA

BACKGROUND:   The Influenza Incidence Surveillance Project (IISP) conducts population-based surveillance for outpatient illness through 12 public health departments in the United States.  The network of healthcare practices (HCP) participating in the project consists of HCPs with varying characteristics, locations and communities served.  The present analysis describes the HCPs and evaluates the influence of HCP characteristics on the cumulative incidence of outpatient visits due to influenza-like illness (ILI).

METHODS:   From August 2010 through July 2013, health departments participating in IISP enrolled 4-6 HCPs that had weekly patient volume of approximately 100-150 patients and were able to enumerate or estimate their patient population by age group to be used as the denominator for incidence calculation.  The combination of all HCPs in a surveillance site represented all age groups.  We used linear regression to evaluate HCP characteristics associated with the cumulative incidence of ILI visits during October through May each year, including practice type, location, private or public funding, number of weeks reporting, denominator estimation type, proportion of pediatric patients, and HCP size.

RESULTS:   From 2010-2013, 101 HCPs participated in IISP in 12 sites and served an overall population of 643,113 persons.  Ninety-three percent of IISP HCPs were primary care practices, identified as pediatric, internal, or family medicine, and only 6% were urgent care and 1% student health.  The age distribution of the IISP population was similar to the US, with 26% pediatric and 74% adult; however, 64% of ILI visits were among pediatric patients.  Forty percent of HCPs were located in urban areas, 30% in suburban areas, and 28% in rural areas, and 53% were privately funded.  The cumulative incidence of ILI visits from October through May varied by year: 22 visits per 1000 population in the 2010-11 season, 10 per 1000 in 2011-12 and 23 per 1000 in 2012-13.  The regression model showed that incidence of ILI visits increased significantly with an increasing proportion of pediatric patients (p<0.001) and was dependent upon the surveillance year (p<0.001).  The incidence of ILI visits was marginally higher among rural locations compared with suburban and urban locations (p<0.1).  No other covariates were significant.

CONCLUSIONS:   The IISP is a successful platform for conducting outpatient population-based ILI surveillance through a network of HCPs throughout the country.   Variation in the cumulative incidence of ILI visits among HCPs was influenced by the proportion of ILI visits that were pediatric and the surveillance year, but HCP location may also have an impact.