We’re pleased to announce the publication of our paper “Inferring the sensitivity of wastewater metagenomic sequencing for early detection of viruses: a statistical modelling study” in the Lancet Microbe. This research builds on early work from the Nucleic Acid Observatory (NAO), first published in August 2023.
At the NAO, our goal is to create early warning systems capable of detecting novel pathogens before they spread widely. Central to this effort is accurately assessing the sensitivity of wastewater metagenomic sequencing (W-MGS) for pathogen detection. Our paper presents a modeling method that gives a quantitative estimate of W-MGS sensitivity.
Specifically, the method involves the following steps:
- Data collection: Analyze untargeted wastewater metagenomic sequencing data to estimate pathogen relative abundance and obtain corresponding prevalence and incidence estimates from academic and public health reports.
- Data integration: Using these data as input, infer the summary statistic RA(1%), defined as the fraction of pathogen sequencing reads observed when the pathogen’s incidence or prevalence is 1%.
- Cost estimation: Use RA(1%) to estimate the required sequencing depth (and its associated cost) to reliably detect a pathogen at a specific stage of an outbreak.
We have already used variants of this method in several related projects:
- Estimating the sensitivity of wastewater metagenomic sequencing using nasal swabs: Combining wastewater and nasal swab sequencing data to infer pathogen prevalence and evaluate the sensitivity of W-MGS.
- Predicting Influenza Abundance in Wastewater Metagenomic Sequencing Data: Extending our method with data from our wastewater sequencing program to predict influenza abundance in wastewater samples.
- Investigating the Sensitivity of Pooled Swab Sampling for Pathogen Early Detection: Assessing the effectiveness of pooled swab sampling combined with metagenomic sequencing to detect pathogens early, based on relative abundance data from individual positive samples.
This research has further informed NAO’s policy-related efforts such as our report Scaling US pathogen detection, which directly relied on RA(1%) estimates to assess the effectiveness of a national sequencing-based biosurveillance system.
Moving forward, we will continue to use this modeling method as we consider how to best extend and improve the NAO’s biosurveillance efforts. If you have questions about the paper, please reach us at info@naobservatory.org.