Understanding the Resurgence of an Eliminated Disease: Spatial, Attitudinal, and Regulatory Factors Underlying Measles Outbreaks in the Post-Elimination Era
Creators: name: Masters, Nina
Publisher: name: My University
Year: 2021
Subjects: subject: vaccine-preventable disease
subject: spatial epidemiology
subject: infectious disease epidemiology
subject: disease dynamics
subject: measles
subject: Public Health
subject: Health Sciences

description: Since the introduction of the highly effective measles-mumps-rubella (MMR) vaccine in 1971, measles incidence has decreased by over 95% globally. In 2012, the Measles and Rubella Initiative set to eliminate measles in five WHO regions by 2020. However, a recent global resurgence of measles amid rising levels of vaccine hesitancy threatens elimination. This dissertation explored three factors that may have contributed to this measles resurgence: spatial clustering of non-vaccination, rising vaccine hesitancy, and policies allowing non-medical exemptions (NMEs). Aim 1 evaluated the consequences of spatial clustering of non-vaccination and the risks posed by using aggregate surveillance estimates to predict outbreaks. This analysis used a spatial dynamic compartmental model, fixing overall vaccination coverage at 95% (the WHO elimination vaccination threshold for measles) and simulating outbreaks across a landscape of non-vaccination clustering motifs. Simulation output revealed that measles outbreaks occurred even at 99% overall vaccination coverage when clustering of non-vaccination was present, calling into question the appropriateness of large-scale herd immunity measures. Aggregation of vaccination data obscured fine-scale clustering and significantly downwardly biased predicted outbreak probability and size, thus underestimating risk. Aim 2 applied the theoretical findings from Aim 1 using school-level kindergarten vaccination data from the Michigan Department of Health and Human Services from 2008-2018. While Aim 1 showed the importance of clustering in driving outbreaks, there is no standard, best practice metric or scale to assess non-vaccination clustering. Across four metrics and four spatial scales, estimates of clustering varied significantly. Measures of exposure performed better than measures of spatial autocorrelation and segregation, both in terms of sensitivity to changing vaccination rates and outbreak-relevant interpretations. All metrics were better able to capture clustering when finer-scaled data were used. Aggregating vaccination data negatively biased estimates of how many students were at-risk of disease, using herd immunity thresholds for measles, mumps, and rubella. Since most public reporting of vaccination rates occurs at the county or state level, these results indicate that such aggregation underestimates the population of at-risk children in Michigan. Aim 3 assessed the impact of regulatory changes on vaccine exemptions; namely Michigan’s 2015 Administrative Rules change requiring parents to attend a vaccine education session at their local health department prior to receiving an NME. This policy had mixed results. While initially the state experienced a 32% decline in the number of exemptions, NMEs returned nearly to pre-policy levels after four years. School type was a significant predictor of NME receipt: compared to public schools, private schools had approximately twice and virtual schools about five times the rate of exemptions. Additionally, philosophical, religious, and medical exemption clusters manifested in distinct geographies. This suggests that if future policy changes affect access to certain types of exemptions in Michigan, they may have a spatially heterogeneous impact. Together, this dissertation illustrates that regulatory policies which permit vaccine-hesitant parents to obtain NMEs for their children result in geographically heterogeneous landscapes of non-vaccination, clustered by sociodemographic and social characteristics. This heterogeneity leads to violations in the assumptions underlying vaccination thresholds set for disease elimination initiatives. Acknowledging such heterogeneity in vaccination patterns, using finer-scale data to identify communities with low vaccination rates, measuring clustering with appropriate and interpretable statistics, and constructing vaccination policies that effectively reduce rates of exemptions are necessary to combat the resurgence of measles and achieve global elimination goals.