Faculty, Staff and Student Publications

Language

English

Publication Date

5-1-2026

Journal

International Journal of Hygiene and Environmental Health

DOI

10.1016/j.ijheh.2026.114790

PMID

41931975

PMCID

PMC13188176

PubMedCentral® Posted Date

5-21-2026

PubMedCentral® Full Text Version

Author MSS

Abstract

Tracking the emergence of new viral variants is critical for epidemic preparedness, but remains challenging because variants typically circulate at low prevalence during the early phase of outbreaks. Here, we present an integrated framework that combines sensitive variant detection in wastewater with quantitative assessment of transmissibility through dynamic epidemic modeling. Using the SARS-CoV-2 Omicron variant as a proof of concept, we developed a novel nested allele-specific RT-qPCR assay (NAS-PCR) that achieved a thousand-fold increase in sensitivity compared with allele-specific RT-qPCR (limit of detection: 0.5 copies/μl). NAS-PCR detected Omicron in wastewater samples from the Greater Boston area starting in September 2021, more than two months before the first reported clinical case in the U.S. To assess transmissibility, we developed a Susceptible-Infected-Viral load model that estimated Omicron’s basic reproduction number (R0) of 2.36~3.09, with robust estimates across variations in susceptible population size and viral shedding rates. This generalizable framework integrates molecular diagnostics, wastewater surveillance, and mechanistic modeling to enable the detection of variants at low prevalence and quantitative assessment of their epidemic potential, thus broadening the wastewater-based surveillance toolkit for early epidemic detection and response.

Keywords

Wastewater, SARS-CoV-2, COVID-19, Humans, Boston, Wastewater surveillance, SARS-CoV-2 Omicron, Variant detection, Nested allele-specific PCR, Basic reproduction number, Epidemic modeling

Published Open-Access

yes

nihms-2172353-f0001.jpg (72 kB)
Graphical Abstract

Included in

Public Health Commons

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.