Sequencing-Based Detection of Measles in Wastewater: Texas, January 2025

Measles is a potentially deadly viral infection spread via respiratory droplets from infected individuals. Outbreaks occur when vaccine coverage drops below the threshold of herd, or community, immunity. Using a sequencing-based approach, we report the prospective (January 7, 2025) detection of measles in nucleic acid extracts from 2 wastewater treatment plants in Houston, Texas, with a population of more than 218 000 residents. The sequencing data from 2 samples contained 53 unique reads mapping to 11 different regions of the measles virus genome with a 99.4% match to genotype B3. Importantly, no detections were observed from 821 previous samples from the same city spanning nearly 3 years of monitoring. The findings were confirmed using droplet digital polymerase chain reaction. A concomitant investigation identified 2 unvaccinated measles-positive travelers living within the same sewershed as the wastewater detection event. This work suggests that sequencing-based wastewater analysis is valuable as a comprehensive early detection warning system that facilitates more targeted epidemiological investigation. (<i>Am J Public Health</i>. 2025;115(7):1115-1119. https://doi.org/10.2105/AJPH.2025.308146).

Authors

Institutions

Publication Details

Journal
American Journal of Public Health
Published
2025-05-08
DOI
https://doi.org/10.2105/ajph.2025.308146
Citations
5
Primary Topic
Virology and Viral Diseases
Type
article
Field-Weighted Citation Impact
6.77
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sequencing-Based Detection of Measles in Wastewater: Texas, January 2025

Anil Surathu, Anthony W. Maresso, Kirstin Short, Blake Hanson et al.
5 citations
American Journal of Public Health
Virology and Viral Diseases
6.77
article

Sequencing-Based Detection of Measles in Wastewater: Texas, January 2025

Anil Surathu, Anthony W. Maresso, Kirstin Short, Blake Hanson, Jingjing Wu, Joseph F. Petrosino, Kaavya Domakonda, Eric Boerwinkle, Lauren B. Stadler, Sara J. Javornik Cregeen, Michael J. Tisza, Matthew C. Ross, Jennifer Deegan, Loren Hopkins, Rebecca Schneider, M. Cook
article en
5 citations

Abstract

Measles is a potentially deadly viral infection spread via respiratory droplets from infected individuals. Outbreaks occur when vaccine coverage drops below the threshold of herd, or community, immunity. Using a sequencing-based approach, we report the prospective (January 7, 2025) detection of measles in nucleic acid extracts from 2 wastewater treatment plants in Houston, Texas, with a population of more than 218 000 residents. The sequencing data from 2 samples contained 53 unique reads mapping to 11 different regions of the measles virus genome with a 99.4% match to genotype B3. Importantly, no detections were observed from 821 previous samples from the same city spanning nearly 3 years of monitoring. The findings were confirmed using droplet digital polymerase chain reaction. A concomitant investigation identified 2 unvaccinated measles-positive travelers living within the same sewershed as the wastewater detection event. This work suggests that sequencing-based wastewater analysis is valuable as a comprehensive early detection warning system that facilitates more targeted epidemiological investigation. (<i>Am J Public Health</i>. 2025;115(7):1115-1119. https://doi.org/10.2105/AJPH.2025.308146).

American Journal of Public HealthVol. 115(7)
Baylor College of Medicine (US)
Clean water and sanitation
Openalex Percentile: Top 3%
Virology and Viral Diseases
6.77
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.