The Emergence of Spatial Clustering in Medical Vaccine Exemptions Following California Senate Bill 277, 2015-2018.

Objectives. To understand how the elimination of nonmedical vaccine exemptions through California Senate Bill 277 (SB277) may have resulted in increased spatial clustering of medical exemptions.Methods. We used spatial scan statistics and negative binomial regression models to examine spatial clustering in medical vaccine exemptions in California kindergartens from 2015 to 2018.Results. Spatial clustering of medical exemptions across schools emerged following SB277. Clusters were located in similar geographic areas to previous clusters of nonmedical vaccine exemptions, suggesting a spatial association between high nonmedical exemption prevalence and increasing rates of medical exemptions. Regression results confirmed this positive association at the local level. The sociodemographic characteristics of the neighborhoods in which schools were located explained some, but not all, of the positive spatial associations between exemptions before and after SB277.Conclusions. Elimination of nonmedical vaccine exemptions via SB277 may have prompted some parents to instead seek medical exemptions to required school vaccines. The spatial association of these 2 types of exemptions has implications for maintaining pockets of low vaccine compliance and increased disease transmission.

The disappearing seasonality of autism conceptions in California.

BACKGROUND: Autism incidence and prevalence have increased dramatically in the last two decades. The autism caseload in California increased 600% between 1992 and 2006, yet there is little consensus as to the cause. Studying the seasonality of conceptions of children later diagnosed with autism may yield clues to potential etiological drivers. OBJECTIVE: To assess if the conceptions of children later diagnosed with autism cluster temporally in a systematic manner and whether any pattern of temporal clustering persists over time. METHOD: We searched for seasonality in conceptions of children later diagnosed with autism by applying a one-dimensional scan statistic with adaptive temporal windows on case and control population data from California for 1992 through 2000. We tested for potential confounding effects from known risk factors using logistic regression models. RESULTS: There is a consistent but decreasing seasonal pattern in the risk of conceiving a child later diagnosed with autism in November for the first half of the study period. Temporal clustering of autism conceptions is not an artifact of composition with respect to known risk factors for autism such as socio-economic status. CONCLUSION: There is some evidence of seasonality in the risk of conceiving a child later diagnosed with autism. Searches for environmental factors related to autism should allow for the possibility of risk factors or etiological drivers that are seasonally patterned and that appear and remain salient for a discrete number of years.