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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 (R) 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.