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    Original Investigation
    Infectious Diseases
    August 21, 2019

    Forecasted Size of Measles Outbreaks Associated With Vaccination Exemptions for Schoolchildren

    Author Affiliations
    • 1Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania
    • 2Texas Pediatric Society, the Texas Chapter of the American Academy of Pediatrics, Austin
    JAMA Netw Open. 2019;2(8):e199768. doi:10.1001/jamanetworkopen.2019.9768
    Key Points español 中文 (chinese)

    Question  What is the expected size of measles outbreaks in Texas at current (ie, 2018) and decreased vaccination rates?

    Findings  In this decision analytical model study of metropolitan statistical areas in Texas, 1 in 20 measles introductions was forecasted to be associated with outbreaks of more than 400 cases in the Austin and Dallas metropolitan areas, according to 1000 simulated outbreaks in each metropolitan area; 64% of cases were forecasted to occur in children for whom a vaccine has been refused and 36% in others (ie, bystanders). Increased vaccine exemptions were forecasted to be associated with increases in the expected size of measles outbreaks.

    Meaning  The 2018 vaccination rates in multiple metropolitan areas may permit large measles outbreaks, which could infect not only vaccine refusers but also other members of the population.


    Importance  Vaccine exemptions, which allow unvaccinated children to attend school, have increased by a factor of 28 since 2003 in Texas. Geographic clustering of unvaccinated children facilitates the spread of measles introductions, but the potential size of outbreaks is unclear.

    Objective  To forecast the range of measles outbreak sizes in each metropolitan area of Texas at 2018 and future reduced school vaccination rates.

    Design, Setting, and Participants  An agent-based decision analytical model using a synthetic population of Texas, derived from the 2010 US Census, was used to simulate measles transmission in the Texas population. Real schools were represented in the simulations, and the 2018 vaccination rate of each real school was applied to a simulated hypothetical equivalent. Single cases of measles were introduced, daily activities and interactions were modeled for each population member, and the number of infections over the course of 9 months was counted for 1000 simulated runs in each Texas metropolitan area.

    Interventions  To determine the outcomes of further decreases in vaccination coverage, additional simulations were performed with vaccination rates reduced by 1% to 10% in schools with populations that are currently undervaccinated.

    Main Outcomes and Measures  Expected distributions of outbreak sizes in each metropolitan area of Texas at 2018 and reduced vaccination rates.

    Results  At 2018 vaccination rates, the median number of cases in large metropolitan areas was typically small, ranging from 1 to 3 cases, which is consistent with outbreaks in Texas 2006 to 2017. However, the upper limit of the distribution of plausible outbreaks (the 95th percentile, associated with 1 in 20 measles introductions) exceeded 400 cases in both the Austin and Dallas metropolitan areas, similar to the largest US outbreaks since measles was eliminated in 2000. Decreases in vaccination rates in schools with undervaccinated populations in 2018 were associated with exponential increases in the potential size of outbreaks: a 5% decrease in vaccination rate was associated with a 40% to 4000% increase in potential outbreak size, depending on the metropolitan area. A mean (SD) of 64% (11%) of cases occurred in students for whom a vaccine had been refused, but a mean (SD) of 36% (11%) occurred in others (ie, bystanders).

    Conclusions and Relevance  This study suggests that vaccination rates in some Texas schools are currently low enough to allow large measles outbreaks. Further decreases are associated with dramatic increases in the probability of large outbreaks. Limiting vaccine exemptions could be associated with a decrease in the risk of large measles outbreaks.