Application of Branching Processes to Measles in California

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PROJECT SUMMARY/ABSTRACT Measles, a highly contagious viral illness, was declared eliminated in 2000 in California as a result of a successful vaccination program in the United States. However, measles remains a public health problem in California: Measles outbreaks continue to occur as small clusters, transmission chains, or isolated cases due to introductions from endemic areas. Public health resources totaling approximately $100,000 per case are diverted from other public health programs to monitor outbreaks and investigate contacts of cases. Organized opposition to vaccination, the key component of measles control, remains a significant concern. A large outbreak linked to Disneyland theme parks, in which 131 Californians were infected, made international headlines in early 2015. It was speculated that this unusually large outbreak was due to decreased vaccination rates as a result of opposition to vaccination. In fact, it is not clear why some outbreaks are larger than others. Epidemiologists at the California Department of Public Health have observed that outbreaks of the B3 measles strain tend to be larger than those of other strains. Differences in transmission have been observed for vaccinated and unvaccinated cases and may account for observed heterogeneity in outbreak size. In addition, certain times of year may be more permissive for transmission. The goal of this project is to determine why some outbreaks are larger than others using data on measles cases in California from 2000 to 2015 from the California Department of Public Health, achieved through two specific aims: we aim to determine (aim 1) if there is evidence that the B3 measles strain is more transmissible than other strains, and (aim 2) whether clustering of unvaccinated individuals explains why unexpectedly large measles outbreaks occur. Proposed techniques include branching process theory, which can be used to provide direct estimates of the extent of control, and causal inference to aid in covariate selection. Both maximum likelihood and simulation techniques will be used, along with mixed-effects modeling and parametric bootstrapping. If some strains are more transmissible or if clustering of unvaccinated individuals affects outbreak size, contact investigation strategies could be modified for greater efficiency. In addition, the results could be used to inform vaccination policy nationally. The proposed training plan includes hands-on research experience to execute the proposed aims and fulfill the applicant's dissertation requirement. Training will also include advanced coursework at UCSF and University of California, Berkeley and directed readings with the sponsor (Professor Travis Porco) and co-sponsor (Professor Wayne Enanoria). Additional training and mentorship will come from Dr. Jennifer Zipprich, Epidemiologist at the California Department of Public Health, Immunization Branch, and dissertation committee members, Professor Maria Glymour (UCSF) and Professor Jamie Lloyd-Smith (UCLA).