Do census tract-level demographic and socioeconomic variables predict pertussis rates in New Mexico children less than 12 months of age?
Wednesday, November 6, 2013
: 12:38 p.m. - 12:56 p.m.
During 2011-2012, New Mexico (NM) and the United States experienced pertussis incidence in excess of any time since the 1950s. Children less than 12 months of age are at increased risk for hospitalization and death. NM analyzed 2011-2012 infant (less than 12 months of age) pertussis data to better understand predictors of infection during the current epidemic. Cases were geocoded and assigned to census tract; tract-level incidence rates were calculated. A negative binomial regression model was developed using demographic and socioeconomic variables. The outcome variable was tract-level infant pertussis incidence. Predictor variables included: tract population under age five, Hispanic ethnicity, average household size, median household income, and population in poverty. Sixty-nine NM infant cases were geocoded. Incidence tripled from 2011 to 2012 and increased by a factor of four in Hispanic infants, with a mean 2011-2012 tract-level rate of 118 cases per 100,000 persons. Case average household size was 4.46 persons. The regression model produced very small, non-significant coefficients for all predictor variables. The model pseudo R2 indicated poor model fit. The selected demographic and socioeconomic variables did not significantly predict tract-level infant pertussis incidence. While incidence was higher in Hispanics, tracts with high proportions of Hispanics did not significantly predict higher pertussis rates. Average NM household size was 2.87 persons; however case average household size was nearly double, suggesting that increased rates could be associated with increased numbers of household contacts. An ongoing case-control evaluation of infant pertussis may help identify more useful predictor variables.
Describe the effectiveness of using Census Tract-level demographic and socioeconomic variables to predict pertussis rates.
Keyword(s): Disease Data, Geographic Information Systems
Presenting author's disclosure statement:
Qualified on the content I am responsible for because: I am the Special Studies Coordinator for the New Mexico Emerging Infections Program. I have been examining the use of spatial analysis to create predictive models of disease incidence for several years.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines,
and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed
in my presentation.