Spatial clustering of undervaccination amplifies local measles transmission but limits geographic spread: South Carolina, 2025-2026
- 1Clemson University
Abstract
The 2025 measles outbreak in South Carolina, the largest in the United States in over two decades, produced 997 confirmed cases, predominantly among school-aged children in an under-vaccinated community in Spartanburg County. To support the South Carolina Department of Public Health (DPH) measles response, we developed a stochastic agent-based model to forecast outbreak trajectory and evaluate intervention strategies in real time, integrating transmission across three spatial scales and grounded in geocoded households, school enrollment records, and census-derived demographic data. The model predicted a median of 1,020 total infections (90% prediction interval: 840-1,273). Counterfactual simulations without active contact tracing and quarantine projected a median of 2,432 infections (90% prediction interval: 1,867-3,185), approximately 138% more than the model-predicted baseline (1,020 cases). Model fidelity required a highly localized between-school contact structure; broader contact assumptions substantially overpredicted both case counts and geographic spread. Simulated regional introductions confirmed that outbreaks arose only near connected clusters of undervaccination, while well-vaccinated areas remained contained. Model versions deployed prospectively at weeks 9, 17, and 34 of the response informed resource allocation decisions and provided operational evidence for the effectiveness of contact tracing and quarantine strategies. Critically, the model reproduced geographic spread, number of affected schools, and breakthrough infection counts not used in fitting, validating its structural fidelity and establishing a replicable framework for jurisdictions maintaining school-enrollment and vaccination records.
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BibTeX
@misc{pandey2026spatial,
title = {{Spatial clustering of undervaccination amplifies local measles transmission but limits geographic spread: South Carolina, 2025-2026}},
author = {A. Pandey and A. M. Bleichrodt and E. A. Serman and S. H. Tanim and A. I. Bento and L. Rennert},
howpublished = {medRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.21.26363346},
url = {https://www.medrxiv.org/content/10.64898/2026.09.21.26363346v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Spatial clustering of undervaccination amplifies local measles transmission but limits geographic spread: South Carolina, 2025-2026
AU - A. Pandey
AU - A. M. Bleichrodt
AU - E. A. Serman
AU - S. H. Tanim
AU - A. I. Bento
AU - L. Rennert
PY - 2026
DA - 2026/09/21
PB - medRxiv
DO - 10.64898/2026.09.21.26363346
UR - https://www.medrxiv.org/content/10.64898/2026.09.21.26363346v1
AB - The 2025 measles outbreak in South Carolina, the largest in the United States in over two decades, produced 997 confirmed cases, predominantly among school-aged children in an under-vaccinated community in Spartanburg County. To support the South Carolina Department of Public Health (DPH) measles response, we developed a stochastic agent-based model to forecast outbreak trajectory and evaluate intervention strategies in real time, integrating transmission across three spatial scales and grounded in geocoded households, school enrollment records, and census-derived demographic data. The model predicted a median of 1,020 total infections (90% prediction interval: 840-1,273). Counterfactual simulations without active contact tracing and quarantine projected a median of 2,432 infections (90% prediction interval: 1,867-3,185), approximately 138% more than the model-predicted baseline (1,020 cases). Model fidelity required a highly localized between-school contact structure; broader contact assumptions substantially overpredicted both case counts and geographic spread. Simulated regional introductions confirmed that outbreaks arose only near connected clusters of undervaccination, while well-vaccinated areas remained contained. Model versions deployed prospectively at weeks 9, 17, and 34 of the response informed resource allocation decisions and provided operational evidence for the effectiveness of contact tracing and quarantine strategies. Critically, the model reproduced geographic spread, number of affected schools, and breakthrough infection counts not used in fitting, validating its structural fidelity and establishing a replicable framework for jurisdictions maintaining school-enrollment and vaccination records.
ER -