Nonvaccinator clusters and measles outbreaks

Local spatial clustering of individuals who are not vaccinated against measles may increase outbreak potential, which may be underestimated by the aggregation of reported vaccination data over large spatial scales, a study suggests. The United States witnessed substantial measles outbreaks in 2019, despite having surpassed the 95% national vaccination coverage recommended by the World Health Organization. Nina Masters, Jon Zelner, and colleagues used computational experiments to explore how measles outbreak occurrence or forecasting at various vaccination levels may be affected by local spatial clustering of nonvaccinated individuals and aggregation of reported vaccination data over large spatial scales. In the presence of clustering, large outbreaks were possible even at 99% overall vaccination coverage, and there was an 89% chance of an outbreak involving five or more people at 95% overall vaccination coverage. Moreover, aggregating vaccination data at the state level or county level could result in underestimation of the predicted risk and size of outbreaks, especially as clustering increases and regardless of the overall vaccination rate. The findings suggest that fine-scale vaccination data should be publicly released and used to create community-level susceptibility maps. Such maps could help effectively plan and implement targeted interventions in high-risk areas to prevent measles outbreaks, according to the authors.

Article #20-11529: "Fine-scale spatial clustering of measles nonvaccination that increases outbreak potential is obscured by aggregated reporting data," by Nina Masters et al.

MEDIA CONTACTS: Jon Zelner, University of Michigan School of Public Health, Ann Arbor, MI; e-mail: jzelner@umich.edu; Nina Masters, University of Michigan School of Public Health, Ann Arbor, MI; tel: 646-354-3687; e-mail: mastersn@umich.edu

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