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Full-Text Articles in Medicine and Health Sciences
Lineage Abundance Estimation For Sars-Cov-2 In Wastewater Using Transcriptome Quantification Techniques, Jasmijn A. Baaijens, Alessandro Zulli, Isabel M. Ott, Ioanna Nika, Mart J. Van Der Lugt, Mary E. Petrone, Tara Alpert, Joseph R. Fauver, Chaney C. Kalinich, Chantal B. F. Vogels, Mallery I. Breban, Claire Duvallet, Kyle A. Mcelroy, Newsha Ghaeli, Maxim Imakaev, Malaika F. Mckenzie-Bennett, Keith Robison, Alex Plocik, Rebecca Schilling, Martha Pierson, Rebecca Littlefield, Michelle L. Spencer, Birgitte B. Simen, Yale Sars-Cov-2 Genomic Surveillance Initiative, William P. Hanage, Nathan D. Grubaugh, Jordan Peccia, Michael Baym
Lineage Abundance Estimation For Sars-Cov-2 In Wastewater Using Transcriptome Quantification Techniques, Jasmijn A. Baaijens, Alessandro Zulli, Isabel M. Ott, Ioanna Nika, Mart J. Van Der Lugt, Mary E. Petrone, Tara Alpert, Joseph R. Fauver, Chaney C. Kalinich, Chantal B. F. Vogels, Mallery I. Breban, Claire Duvallet, Kyle A. Mcelroy, Newsha Ghaeli, Maxim Imakaev, Malaika F. Mckenzie-Bennett, Keith Robison, Alex Plocik, Rebecca Schilling, Martha Pierson, Rebecca Littlefield, Michelle L. Spencer, Birgitte B. Simen, Yale Sars-Cov-2 Genomic Surveillance Initiative, William P. Hanage, Nathan D. Grubaugh, Jordan Peccia, Michael Baym
Journal Articles: Epidemiology
Effectively monitoring the spread of SARS-CoV-2 mutants is essential to efforts to counter the ongoing pandemic. Predicting lineage abundance from wastewater, however, is technically challenging. We show that by sequencing SARS-CoV-2 RNA in wastewater and applying algorithms initially used for transcriptome quantification, we can estimate lineage abundance in wastewater samples. We find high variability in signal among individual samples, but the overall trends match those observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in mutant prevalence in situations where clinical sequencing is unavailable.
Quantifying The Impact Of Immune History And Variant On Sars-Cov-2 Viral Kinetics And Infection Rebound: A Retrospective Cohort Study, James A. Hay, Stephen M. Kissler, Joseph R. Fauver, Christina Mack, Caroline G. Tai, Radhika M. Samant, Sarah Connolly, Deverick J. Anderson, Gaurav Khullar, Matthew Mackay, Miral Patel, Shannan Kelly, April Manhertz, Isaac Eiter, Daisy Salgado, Tim Baker, Ben Howard, Joel T. Dudley, Christopher E. Mason, Manoj Nair, Yaoxing Huang, John Difiori, David D. Ho, Nathan D. Grubaugh, Yonatan H. Grad
Quantifying The Impact Of Immune History And Variant On Sars-Cov-2 Viral Kinetics And Infection Rebound: A Retrospective Cohort Study, James A. Hay, Stephen M. Kissler, Joseph R. Fauver, Christina Mack, Caroline G. Tai, Radhika M. Samant, Sarah Connolly, Deverick J. Anderson, Gaurav Khullar, Matthew Mackay, Miral Patel, Shannan Kelly, April Manhertz, Isaac Eiter, Daisy Salgado, Tim Baker, Ben Howard, Joel T. Dudley, Christopher E. Mason, Manoj Nair, Yaoxing Huang, John Difiori, David D. Ho, Nathan D. Grubaugh, Yonatan H. Grad
Journal Articles: Epidemiology
BACKGROUND: The combined impact of immunity and SARS-CoV-2 variants on viral kinetics during infections has been unclear.
METHODS: We characterized 1,280 infections from the National Basketball Association occupational health cohort identified between June 2020 and January 2022 using serial RT-qPCR testing. Logistic regression and semi-mechanistic viral RNA kinetics models were used to quantify the effect of age, variant, symptom status, infection history, vaccination status and antibody titer to the founder SARS-CoV-2 strain on the duration of potential infectiousness and overall viral kinetics. The frequency of viral rebounds was quantified under multiple cycle threshold (Ct) value-based definitions.
RESULTS: Among individuals detected …