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<p>Recent measles outbreaks in the USA have emerged despite the availability of the highly effective measles–mumps–rubella (MMR) vaccine. Current surveillance systems rely primarily on telephone surveys with provider verification or school-entry data, methods prone to incompleteness and systematic exclusion of vulnerable populations. Here, to address these limitations, we used a validated digital participatory surveillance platform to collect parental reports of ≥1-dose MMR vaccination among children under 5 years of age. Applying Small Area Estimation methods to generate granular, county-level coverage estimates nationwide, we found substantial geographic variation, including areas with MMR coverage &lt;60%. Analysis of spatial clustering revealed hotspots of undervaccination overlapping closely with recent measles outbreaks, particularly in Texas and New Mexico—where our model estimates substantially lower vaccine coverage than official data. These findings underscore the urgent need for surveillance systems to include more granular and timely data that accurately identify undervaccinated communities, enabling targeted, timely public health interventions.</p>

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Assessing MMR vaccination coverage gaps in US children with digital participatory surveillance

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月15日

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  • Eric Geng Zhou,
  • John S. Brownstein,
  • Benjamin Rader

摘要

Recent measles outbreaks in the USA have emerged despite the availability of the highly effective measles–mumps–rubella (MMR) vaccine. Current surveillance systems rely primarily on telephone surveys with provider verification or school-entry data, methods prone to incompleteness and systematic exclusion of vulnerable populations. Here, to address these limitations, we used a validated digital participatory surveillance platform to collect parental reports of ≥1-dose MMR vaccination among children under 5 years of age. Applying Small Area Estimation methods to generate granular, county-level coverage estimates nationwide, we found substantial geographic variation, including areas with MMR coverage <60%. Analysis of spatial clustering revealed hotspots of undervaccination overlapping closely with recent measles outbreaks, particularly in Texas and New Mexico—where our model estimates substantially lower vaccine coverage than official data. These findings underscore the urgent need for surveillance systems to include more granular and timely data that accurately identify undervaccinated communities, enabling targeted, timely public health interventions.