An agent-based model of school closing in under-vaccinated communities during measles outbreaks. (May 2019)

• Record Type: Journal Article
• Authors: Getz, Wayne M; Carlson, Colin; Dougherty, Eric; Porco, Travis C; Salter, Richard
• Is Part Of: Simulation. Volume 95:Number 5(2019)
• Page Start: 385
• Page End: 393
• Publication Date: 2019-05
• Subjects: Superspreaders -- epidemiological models -- NOVA software platform -- herd immunity -- R-zero; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549717721754
• Languages: English
• ISSNs: 0037-5497

Abstract

The winter 2014–15 measles outbreak in the United States represents a significant crisis in the emergence of a functionally extirpated pathogen. Conclusively linking this outbreak to decreases in the measles, mumps, and rubella (MMR) vaccination rate (driven by anti-vaccine sentiment) is critical to motivating MMR vaccination. We used the NOVA modeling platform to build a stochastic, spatially-structured, individual-based SEIR model of outbreaks, under the assumption thatR 0 ≈ 7 for measles. We show this implies that herd immunity requires vaccination coverage of greater than approximately 85%. We used a network structured version of our NOVA model that involved two communities, one at the relatively low coverage of 85% coverage and one at the higher coverage of 95%, both of which had 400-student schools embedded, as well as students occasionally visiting superspreading sites (e.g., high-density theme parks, and cinemas). These two vaccination coverage levels are within the range of values occurring across Californian counties. Transmission rates at schools and superspreading sites were arbitrarily set to respectively 5 and 15 times the background community rates. Simulations of our model demonstrate that a 'send unvaccinated students home' policy in low coverage counties is extremely effective at shutting down outbreaks of measles.