SARS-CoV-2 Titers in Wastewater Are Higher than Expected from Clinically Confirmed Cases.
- Resource Type
- Academic Journal
- Authors
- Wu F; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Zhang J; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Xiao A; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Gu X; Singapore-MIT Alliance for Research and Technology, National University of Singapore, Singapore.; Campus for Research Excellence and Technological Enterprise, Singapore.; Lee WL; Singapore-MIT Alliance for Research and Technology, National University of Singapore, Singapore.; Campus for Research Excellence and Technological Enterprise, Singapore.; Armas F; Singapore-MIT Alliance for Research and Technology, National University of Singapore, Singapore.; Campus for Research Excellence and Technological Enterprise, Singapore.; Kauffman K; University at Buffalo, The State University of New York, Buffalo, New York, USA.; Hanage W; Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA.; Matus M; Biobot Analytics, Inc., Cambridge, Massachusetts, USA.; Ghaeli N; Biobot Analytics, Inc., Cambridge, Massachusetts, USA.; Endo N; Biobot Analytics, Inc., Cambridge, Massachusetts, USA.; Duvallet C; Biobot Analytics, Inc., Cambridge, Massachusetts, USA.; Poyet M; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Moniz K; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Washburne AD; Selva Analytics, LLC, Bozeman, Montana, USA.; Erickson TB; Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.; Harvard Humanitarian Institute, Cambridge, Massachusetts, USA.; Chai PR; Division of Medical Toxicology, Department of Emergency Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.; The Fenway Institute, Boston, Massachusetts, USA.; The Koch Institute for Integrated Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Thompson J; Singapore Center for Environmental Life Sciences Engineering, Nanyang Technological University, Singapore.; Asian School of the Environment, Nanyang Technological University, Singapore.; Campus for Research Excellence and Technological Enterprise, Singapore.; Alm EJ; Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA ejalm@mit.edu.; Singapore-MIT Alliance for Research and Technology, National University of Singapore, Singapore.; Biobot Analytics, Inc., Cambridge, Massachusetts, USA.; Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.; Campus for Research Excellence and Technological Enterprise, Singapore.; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
- Source
- Publisher: American Society for Microbiology Country of Publication: United States NLM ID: 101680636 Publication Model: Electronic Cited Medium: Print ISSN: 2379-5077 (Print) Linking ISSN: 23795077 NLM ISO Abbreviation: mSystems Subsets: PubMed not MEDLINE
- Subject
- Language
- English
- ISSN
- 2379-5077
Wastewater surveillance represents a complementary approach to clinical surveillance to measure the presence and prevalence of emerging infectious diseases like the novel coronavirus SARS-CoV-2. This innovative data source can improve the precision of epidemiological modeling to understand the penetrance of SARS-CoV-2 in specific vulnerable communities. Here, we tested wastewater collected at a major urban treatment facility in Massachusetts and detected SARS-CoV-2 RNA from the N gene at significant titers (57 to 303 copies per ml of sewage) in the period from 18 to 25 March 2020 using RT-qPCR. We validated detection of SARS-CoV-2 by Sanger sequencing the PCR product from the S gene. Viral titers observed were significantly higher than expected based on clinically confirmed cases in Massachusetts as of 25 March. Our approach is scalable and may be useful in modeling the SARS-CoV-2 pandemic and future outbreaks. IMPORTANCE Wastewater-based surveillance is a promising approach for proactive outbreak monitoring. SARS-CoV-2 is shed in stool early in the clinical course and infects a large asymptomatic population, making it an ideal target for wastewater-based monitoring. In this study, we develop a laboratory protocol to quantify viral titers in raw sewage via qPCR analysis and validate results with sequencing analysis. Our results suggest that the number of positive cases estimated from wastewater viral titers is orders of magnitude greater than the number of confirmed clinical cases and therefore may significantly impact efforts to understand the case fatality rate and progression of disease. These data may help inform decisions surrounding the advancement or scale-back of social distancing and quarantine efforts based on dynamic wastewater catchment-level estimations of prevalence.
(Copyright © 2020 Wu et al.)