Utilizing surveillance data from five sites participating in the Autism and Developmental Disabilities Monitoring Network, we investigated contributions of surveillance subject and census tract population sociodemographic characteristics on variation in autism spectrum disorder ascertainment and prevalence estimates from 2000 to 2008 using ordinal hierarchical models for 2489 tracts. Multivariable analyses showed a significant increase in ascertainment of autism spectrum disorder cases through both school and health sources, the optimal ascertainment scenario, for cases with college-educated mothers (adjusted odds ratio = 1.06, 95% confidence interval = 1.02–1.09). Results from our examination of sociodemographic factors of tract populations from which cases were drawn also showed that after controlling for other covariates, statistical significance remained for associations between optimal ascertainment and percentage of Hispanic residents (adjusted odds ratio = 0.93, 95% confidence interval = 0.88–0.99) and percentage of residents with at least a bachelor’s degree (adjusted odds ratio = 1.06, 95% confidence interval = 1.01–1.11). We identified sociodemographic factors associated with autism spectrum disorder prevalence estimates including race, ethnicity, education, and income. Determining which specific factors influence disparities is complicated; however, it appears that even in the presence of education, racial and ethnic disparities are still apparent. These results suggest disparities in access to autism spectrum disorder assessments and special education for autism spectrum disorder among ethnic groups may impact subsequent surveillance.