Kayoko Shioda1, Leslie Barclay1, Sylvia Becker-Dreps2, Filemon Bucardo-Rivera3, Philip J Cooper4, Daniel C Payne1, Jan Vinjé1, Benjamin A Lopman1,5. 1. Division of Viral Diseases, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia. 2. School of Medicine, University of North Carolina at Chapel Hill. 3. Department of Microbiology, National Autonomous University of León, Nicaragua. 4. Facultad de Ciencias Médicas, de la Salud y de la Vida, Universidad Internacional del Ecuador Quito; Institute of Infection and Immunity, St George's University of London, United Kingdom. 5. Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia.
Abstract
BACKGROUND: Real-time reverse-transcriptase polymerase chain reaction (RT-PCR) is the state-of-the-art diagnostic for norovirus. Cycle threshold (Ct), an indicator of viral load, may be associated with symptomatic disease as well as demographic and outbreak characteristics. METHODS: Data on (1) outbreak and sporadic cases and (2) asymptomatic controls in the United States and Latin America were analyzed. With multivariate regression models, we assessed relationships between various factors and Ct values, and we calculated odds ratios (ORs) for the presence of symptoms and attributable fractions of norovirus. Receiver-operating characteristic analysis was performed to define an optimal Ct cutoff to identify disease-causing infections. RESULTS: Cycle threshold values were lower (ie, higher viral loads) among symptomatic cases (model-adjusted mean ± standard error: 25.3 ± 1.2) compared with asymptomatic controls (28.5 ± 1.4). Cycle threshold values were significantly different across age groups, norovirus genogroups, timing of specimen collection, outbreak settings, and transmission modes. Genogroup II (GII) Ct values were associated with presence of symptoms (OR = 1.1), allowing us to estimate that 16% of diarrheal disease was attributable to norovirus. The optimized Ct cutoff led to poor sensitivity and specificity for genogroup I and GII. CONCLUSIONS: Cycle threshold values were associated with host, pathogen, and outbreak factors. Cycle threshold values may not effectively distinguish disease-causing infection for individual patients, but they are useful for epidemiological studies aiming to attribute disease. Published by Oxford University Press on behalf of Infectious Diseases Society of America 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.
BACKGROUND: Real-time reverse-transcriptase polymerase chain reaction (RT-PCR) is the state-of-the-art diagnostic for norovirus. Cycle threshold (Ct), an indicator of viral load, may be associated with symptomatic disease as well as demographic and outbreak characteristics. METHODS: Data on (1) outbreak and sporadic cases and (2) asymptomatic controls in the United States and Latin America were analyzed. With multivariate regression models, we assessed relationships between various factors and Ct values, and we calculated odds ratios (ORs) for the presence of symptoms and attributable fractions of norovirus. Receiver-operating characteristic analysis was performed to define an optimal Ct cutoff to identify disease-causing infections. RESULTS: Cycle threshold values were lower (ie, higher viral loads) among symptomatic cases (model-adjusted mean ± standard error: 25.3 ± 1.2) compared with asymptomatic controls (28.5 ± 1.4). Cycle threshold values were significantly different across age groups, norovirus genogroups, timing of specimen collection, outbreak settings, and transmission modes. Genogroup II (GII) Ct values were associated with presence of symptoms (OR = 1.1), allowing us to estimate that 16% of diarrheal disease was attributable to norovirus. The optimized Ct cutoff led to poor sensitivity and specificity for genogroup I and GII. CONCLUSIONS: Cycle threshold values were associated with host, pathogen, and outbreak factors. Cycle threshold values may not effectively distinguish disease-causing infection for individual patients, but they are useful for epidemiological studies aiming to attribute disease. Published by Oxford University Press on behalf of Infectious Diseases Society of America 2017. This work is written by (a) US Government employee(s) and is in the public domain in the US.
Authors: James A Platts-Mills; Sudhir Babji; Ladaporn Bodhidatta; Jean Gratz; Rashidul Haque; Alexandre Havt; Benjamin Jj McCormick; Monica McGrath; Maribel Paredes Olortegui; Amidou Samie; Sadia Shakoor; Dinesh Mondal; Ila Fn Lima; Dinesh Hariraju; Bishnu B Rayamajhi; Shahida Qureshi; Furqan Kabir; Pablo P Yori; Brenda Mufamadi; Caroline Amour; J Daniel Carreon; Stephanie A Richard; Dennis Lang; Pascal Bessong; Esto Mduma; Tahmeed Ahmed; Aldo Aam Lima; Carl J Mason; Anita Km Zaidi; Zulfiqar A Bhutta; Margaret Kosek; Richard L Guerrant; Michael Gottlieb; Mark Miller; Gagandeep Kang; Eric R Houpt Journal: Lancet Glob Health Date: 2015-07-19 Impact factor: 26.763
Authors: Daniel C Payne; Jan Vinjé; Peter G Szilagyi; Kathryn M Edwards; Mary Allen Staat; Geoffrey A Weinberg; Caroline B Hall; James Chappell; David I Bernstein; Aaron T Curns; Mary Wikswo; S Hannah Shirley; Aron J Hall; Benjamin Lopman; Umesh D Parashar Journal: N Engl J Med Date: 2013-03-21 Impact factor: 91.245
Authors: Robert L Atmar; Antone R Opekun; Mark A Gilger; Mary K Estes; Sue E Crawford; Frederick H Neill; David Y Graham Journal: Emerg Infect Dis Date: 2008-10 Impact factor: 6.883
Authors: Sarah K C Cheung; Kirsty Kwok; Lin-Yao Zhang; Kirran N Mohammad; Grace C Y Lui; Nelson Lee; E Anthony S Nelson; Raymond W M Lai; Ting F Leung; Paul K S Chan; Martin Chi-Wai Chan Journal: Emerg Infect Dis Date: 2019-01 Impact factor: 6.883
Authors: Brian McKay; Mark Ebell; Wesley Zane Billings; Ariella Perry Dale; Ye Shen; Andreas Handel Journal: Open Forum Infect Dis Date: 2020-10-16 Impact factor: 3.835
Authors: Natasha Halasa; Bhinnata Piya; Laura S Stewart; Herdi Rahman; Daniel C Payne; Amy Woron; Linda Thomas; Lisha Constantine-Renna; Katie Garman; Rendie McHenry; James Chappell; Andrew J Spieker; Christopher Fonnesbeck; Einas Batarseh; Lubna Hamdan; Mary E Wikswo; Umesh Parashar; Michael D Bowen; Jan Vinjé; Aron J Hall; John R Dunn Journal: Clin Infect Dis Date: 2021-02-16 Impact factor: 9.079
Authors: Martin Chi-Wai Chan; Sarah K C Cheung; Kirran N Mohammad; Jenny C M Chan; Mary K Estes; Paul K S Chan Journal: Emerg Infect Dis Date: 2019-09 Impact factor: 6.883