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dc.contributor.authorEndo, Norkio
dc.contributor.authorGhaeli, Newsha
dc.contributor.authorDuvallet, Claire
dc.contributor.authorFoppe, Katelyn
dc.contributor.authorErickson, Timothy B
dc.contributor.authorMatus, Mariana
dc.contributor.authorChai, Peter R.
dc.date.accessioned2020-11-06T20:53:41Z
dc.date.available2020-11-06T20:53:41Z
dc.date.issued2020-01
dc.date.submitted2019-12
dc.identifier.issn1556-9039
dc.identifier.issn1937-6995
dc.identifier.urihttps://hdl.handle.net/1721.1/128392
dc.description.abstractIntroduction: Accurate data regarding opioid use, overdose, and treatment is important in guiding community efforts at combating the opioid epidemic. Wastewater-based epidemiology (WBE) is a potential method to quantify community-level trends of opioid exposure beyond overdose data, which is the basis of most existing response efforts. However, most WBE efforts collect parent opioid compounds (e.g., morphine) at wastewater treatment facilities, measuring opioid concentrations across large catchment zones which typically represent an entire municipality. We sought to deploy a robotic sampling device at targeted manholes within a city to semi-quantitatively detect opioid metabolites (e.g., morphine glucuronide) at a sub-city community resolution. Methods: We deployed a robotic wastewater sampling platform at ten residential manholes in an urban municipality in North Carolina, accounting for 44.5% of the total municipal population. Sampling devices comprised a robotic sampling arm with in situ solid phase extraction, and collected hourly samples over 24-hour periods. We used targeted mass spectrometry to detect the presence of a custom panel of opioids, naloxone, and buprenorphine. Results:Ten sampling sites were selected to be a representative survey of the entire municipality by integrating sewer network and demographic GIS data. All eleven metabolites targeted were detected during the program. The average morphine milligram equivalent (MME) across the nine illicit and prescription opioids, as excreted and detected in wastewater, was 49.1 (standard deviation of 31.9) MME/day/1000-people. Codeine was detected most frequently (detection rate of 100%), and buprenorphine was detected least frequently (12%). The presence of naloxone correlated with city data of known overdoses reversed by emergency medical services in the prehospital setting. Conclusion: Wastewater-based epidemiology with smart sewer selection and robotic wastewater collection is feasible to detect the presence of specific opioids, naloxone, methadone, and buprenorphine within a city. These results suggest that wastewater epidemiology could be used to detect patterns of opioid exposure and may ultimately provide information for opioid use disorder (OUD) treatment and harm reduction programs.en_US
dc.publisherSpringer Science and Business Media LLCen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s13181-019-00756-5en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceSpringer USen_US
dc.titleRapid Assessment of Opioid Exposure and Treatment in Cities Through Robotic Collection and Chemical Analysis of Wastewateren_US
dc.typeArticleen_US
dc.identifier.citationEndo, Norkio et al. "Rapid Assessment of Opioid Exposure and Treatment in Cities Through Robotic Collection and Chemical Analysis of Wastewater." Journal of Medical Toxicology 16, 2 (January 2020): 195–203 © 2020 American College of Medical Toxicologyen_US
dc.contributor.departmentKoch Institute for Integrative Cancer Research at MITen_US
dc.relation.journalJournal of Medical Toxicologyen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2020-09-24T21:46:21Z
dc.language.rfc3066en
dc.rights.holderAmerican College of Medical Toxicology
dspace.embargo.termsY
dspace.date.submission2020-09-24T21:46:21Z
mit.journal.volume16en_US
mit.journal.issue2en_US
mit.licensePUBLISHER_POLICY
mit.metadata.statusComplete


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