The role of vaccination coverage, individual behaviors, and the public health response in the control of measles epidemics: an agent-based simulation for California

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.

Missed Opportunities for Measles, Mumps, Rubella Vaccination Among Departing U.S. Adult Travelers Receiving Pretravel Health Consultations

“…Our findings underscore that strategies are needed to improve provider and traveler knowledge of measles as a travel-related illness and to increase pretravel uptake of the MMR vaccine. Improving vaccination rates is particularly important for communities with a higher percentage of nonimmune individuals, since there is a greater risk of transmission events following an index case in these settings (10, 22, 23). …”

The Effect of Contact Investigations and Public Health Interventions in the Control and Prevention of Measles Transmission: A Simulation Study

“…Third, we modeled a public health response to identified cases that involved case and contact investigations with reasonable delays. Fourth, we modeled the use of public health interventions (MMR PEP, IG PEP, and voluntary isolation and quarantine) [22]. Using a synthetic population that contained family structure, household size, age distribution, schools, workplaces, neighborhoods, and population immunity, measles outbreaks were simulated with one infected case introduced into a synthetic population each time.…”

“…Infectious disease transmission is known to occur at higher rates in schools because of the close and sustained contact between students [25][26][27]. In addition, we allowed for the possibility that transmission could occur in daycare settings by adding daycares to the synthetic population based on data from the California Department of Social Services' Community Care License Division (http://www.ccld.ca.gov) [22]. During each simulated day, individuals interacted with other individuals who shared the same locations of social activity.…”

Uses of Agent-Based Modeling for Health Communication: the TELL ME Case Study

“…Over the last forty years, agent-based modeling has become an increasingly popular approach for exploring ideas about the social world (Axelrod, 1997;Epstein & Axtell, 1995;Gilbert & Troitzsch, 2005). While use is in its infancy in public health, there have already been ABMs developed in areas as diverse as epidemiology, illicit drugs and physical activity (Dray et al, 2012;Liu et al, 2015;Yang et al, 2011).…”

“…Over the last forty years, agent-based modeling has become an increasingly popular approach for exploring ideas about the social world (Axelrod, 1997;Epstein & Axtell, 1995;Gilbert & Troitzsch, 2005). While use is in its infancy in public health, there have already been ABMs developed in areas as diverse as epidemiology, illicit drugs and physical activity (Dray et al, 2012;Liu et al, 2015; Yang et al, 2011).ABMs are computer programs that encode important actors (the 'agents'), their behavior, their interaction with each other, interaction with their environment, and any policy interventions. The design of ABMs is typically underpinned by theoretical frameworks and empirical findings from surveys and questionnaires.…”