{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T18:53:11Z","timestamp":1775242391745,"version":"3.50.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1014124","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T00:00:00Z","timestamp":1775174400000}}],"reference-count":86,"publisher":"Public Library of Science (PLoS)","issue":"3","license":[{"start":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T00:00:00Z","timestamp":1774828800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100021154","name":"Amazon Research Awards","doi-asserted-by":"publisher","award":["Fall 2022 CFP"],"award-info":[{"award-number":["Fall 2022 CFP"]}],"id":[{"id":"10.13039\/100021154","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010336","name":"Hellman Foundation","doi-asserted-by":"publisher","award":["Hellman Fellowship"],"award-info":[{"award-number":["Hellman Fellowship"]}],"id":[{"id":"10.13039\/100010336","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100020365","name":"Centers for Disease Control and Prevention Foundation","doi-asserted-by":"publisher","award":["75D30123C17463"],"award-info":[{"award-number":["75D30123C17463"]}],"id":[{"id":"10.13039\/100020365","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Wastewater-based epidemiology (WBE) is a cost-effective, unbiased, and time-efficient tool for public health surveillance. Although widely adopted since the COVID-19 pandemic, WBE remains underutilized in genomic epidemiology, as most tools are limited to lineage-level resolution and focus only on estimating lineage abundances from wastewater sequencing reads. Here, we present WEPP, a pathogen-agnostic pipeline that improves both the resolution and capabilities of WBE analysis. WEPP uses phylogenetic placement of sequencing reads onto mutation-annotated trees (MATs)\u2014daily updated phylogenies of all globally available clinical sequences and their inferred ancestors\u2014to sensitively and precisely identify a subset of haplotypes likely present in a sample. It also reports the abundance of each haplotype and lineage, and flags \u201cunaccounted alleles\u201d\u2014 those found in the sample but not explained by selected haplotypes\u2014that may indicate novel variants. WEPP includes a powerful interactive dashboard for high-resolution visual analysis, allowing users to explore haplotype and lineage abundances, read-to-haplotype mappings, and unaccounted alleles within a global phylogenetic context. Applied to wastewater samples from multiple cities and pathogens, WEPP uncovered biological insights sometimes missed by other tools and enabled new WBE applications previously confined to clinical sequencing, such as identifying (i) intra-lineage haplotype clusters, (ii) multiple cluster introductions in a city, (iii) early haplotype detection up to five weeks before clinical confirmation, (iv) mutations from novel variants, and (v) circulating lineages missed by clinical surveillance. With these capabilities, WEPP can transform wastewater-based epidemiology into a more powerful tool for monitoring and managing infectious disease outbreaks.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1014124","type":"journal-article","created":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T17:28:42Z","timestamp":1774891722000},"page":"e1014124","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["WEPP: Phylogenetic placement achieves near-haplotype resolution in wastewater-based epidemiology"],"prefix":"10.1371","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-9738-900X","authenticated-orcid":true,"given":"Pranav","family":"Gangwar","sequence":"first","affiliation":[]},{"given":"Pratik","family":"Katte","sequence":"additional","affiliation":[]},{"given":"Manu","family":"Bhat","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5600-2900","authenticated-orcid":true,"given":"Yatish","family":"Turakhia","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2026,3,30]]},"reference":[{"key":"pcbi.1014124.ref001","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.coesh.2020.04.006","article-title":"The potential of wastewater-based epidemiology as surveillance and early warning of infectious disease outbreaks","volume":"17","author":"K Mao","year":"2020","journal-title":"Curr Opin Environ Sci 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