Abstract
BackgroundMeasles cases continue to occur among susceptible individuals despite the elimination of endemic measles transmission in the United States. Clustering of disease susceptibility can threaten herd immunity and impact the likelihood of disease outbreaks in a highly vaccinated population. Previous studies have examined the role of contact tracing to control infectious diseases among clustered populations, but have not explicitly modeled the public health response using an agent-based model.MethodsWe developed an agent-based simulation model of measles transmission using the Framework for Reconstructing Epidemiological Dynamics (FRED) and the Synthetic Population Database maintained by RTI International. The simulation of measles transmission was based on interactions among individuals in different places: households, schools, daycares, workplaces, and neighborhoods. The model simulated different levels of immunity clustering, vaccination coverage, and contact investigations with delays caused by individuals’ behaviors and/or the delay in a health department’s response. We examined the effects of these characteristics on the probability of uncontrolled measles outbreaks and the outbreak size in 365 days after the introduction of one index case into a synthetic population.ResultsWe found that large measles outbreaks can be prevented with contact investigations and moderate contact rates by having (1) a very high vaccination coverage (≥ 95%) with a moderate to low level of immunity clustering (≤ 0.5) for individuals aged less than or equal to 18 years, or (2) a moderate vaccination coverage (85% or 90%) with no immunity clustering for individuals (≤18 years of age), a short intervention delay, and a high probability that a contact can be traced. Without contact investigations, measles outbreaks may be prevented by the highest vaccination coverage with no immunity clustering for individuals (≤18 years of age) with moderate contact rates; but for the highest contact rates, even the highest coverage with no immunity clustering for individuals (≤18 years of age) cannot completely prevent measles outbreaks.ConclusionsThe simulation results demonstrated the importance of vaccination coverage, clustering of immunity, and contact investigations in preventing uncontrolled measles outbreaks.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-015-1766-6) contains supplementary material, which is available to authorized users.
Highlights
Measles cases continue to occur among susceptible individuals despite the elimination of endemic measles transmission in the United States
The agent-based simulation model has two main components: (1) the agentbased simulation model of measles transmission using the Framework for Reconstructing Epidemiological Dynamics (FRED) [14,15], and (2) a synthetic population of individuals adapted from the Synthetic Population Database maintained by RTI International [16]
When the partial rank correlation coefficient (PRCC) is close to zero, the value of the parameter has little relation to the simulation output; when the PRCC is close to +1 or −1, the value of the parameter is highly important in determining the simulation output
Summary
Measles cases continue to occur among susceptible individuals despite the elimination of endemic measles transmission in the United States. Clustering of disease susceptibility can threaten herd immunity and impact the likelihood of disease outbreaks in a highly vaccinated population. Measles cases continue to occur among susceptible individuals despite the elimination of endemic measles transmission in the United States as a result of importation [2,3]. The introduction of one imported measles case into a group or community with a large number of susceptible individuals can yield large outbreaks [4]. Despite high vaccination coverage of a population, clustering of disease susceptibility due to personal beliefs and other exemptions to mandatory childhood vaccination can threaten herd immunity and impact the likelihood of disease outbreaks [7]
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