Inferring the sensitivity of wastewater metagenomic sequencing for pathogen early detection

Detecting novel pathogens at an early stage requires robust early warning that is both sensitive and pathogen-agnostic. Wastewater metagenomic sequencing (W-MGS) could meet these goals, but its sensitivity and financial feasibility depend on the relative abundance of novel pathogen sequences in W-MGS data. Here we collate W-MGS data from a diverse range of studies to characterize the relative abundance of known viruses in wastewater. We then develop a Bayesian statistical model to integrate these data with epidemiological estimates for 13 human-infecting viruses, and use it to estimate the expected relative abundance of different viral pathogens for a given prevalence or incidence in the community. Our results reveal pronounced variation between studies, with estimates differing by one to three orders of magnitude for the same pathogen: for example, the expected relative abundance of SARS-CoV-2 at 1% weekly incidence varied between 10-7 and 10-10. Integrating these estimates with a simple cost model highlights similarly wide inter-study and inter-pathogen variation in the cost of W-MGS-based early detection, with a mean yearly cost estimate of roughly $19,000 for a Norovirus-like pathogen and $2.9 million for a SARS-CoV-2-like pathogen at 1% incidence. The model and parameter estimates presented here represent an important resource for future investigation into the performance of wastewater MGS, and can be extended to incorporate new wastewater datasets as they become available. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement S.L.G., J.T.K., D.P.R., W.J.B., and M.R.M. were funded for this research project by gifts from Open Philanthropy (to SecureBio) and the Musk Foundation (to MIT). S.L.G. was additionally supported through a grant by the Swiss Scholarship Foundation. C.W. was supported by Sir Henry Wellcome Postdoctoral Fellowship, reference 224190/Z/21/Z. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced are available online at and