Jodell E. Linder, PhD, David C

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Human rhinovirus C: Age, season, and lower respiratory illness over the past 3 decades Jodell E. Linder, PhD, David C. Kraft, BS, Yassir Mohamed, MS, Zengqi Lu, MS, Luke Heil, BS, Sharon Tollefson, BA, Benjamin R. Saville, PhD, Peter F. Wright, MD, John V. Williams, MD, E. Kathryn Miller, MD, MPH Journal of Allergy and Clinical Immunology Volume 131, Issue 1, Pages 69-77.e6 (January 2013) DOI: 10.1016/j.jaci.2012.09.033 Copyright © 2012 American Academy of Allergy, Asthma & Immunology Terms and Conditions

Fig 1 Age and month are significantly correlated with HRV infection. A, HRV is more common in younger children in fall and spring months. Winter, solid line; spring, dashed line; summer, gray dot; fall, gray dash/dot. Graph shown for white males. B, In September, children had a 2.47-fold increased risk of positive HRV diagnosis than in July. Lines represent modeled negative binomial regression. Journal of Allergy and Clinical Immunology 2013 131, 69-77.e6DOI: (10.1016/j.jaci.2012.09.033) Copyright © 2012 American Academy of Allergy, Asthma & Immunology Terms and Conditions

Fig 2 Older females in the winter months were more likely to present with HRV-C. A, Age and season predicted HRV species (shown for white males). The negative binomial regression modeled here predicts that HRV-C is more common with increasing age. B, Sex was also a significant factor in the likelihood of HRV-C (shown for 11.2-month-old white child in the fall). Journal of Allergy and Clinical Immunology 2013 131, 69-77.e6DOI: (10.1016/j.jaci.2012.09.033) Copyright © 2012 American Academy of Allergy, Asthma & Immunology Terms and Conditions

Fig 3 HRV-A rate varies from year to year. HRV-A fluctuated significantly over the years; recently, there was more HRV-A present in children with respiratory illness. Lines represent the negative binomial regression model based on the data. Journal of Allergy and Clinical Immunology 2013 131, 69-77.e6DOI: (10.1016/j.jaci.2012.09.033) Copyright © 2012 American Academy of Allergy, Asthma & Immunology Terms and Conditions

Fig 4 LRI diagnosis is more often associated with HRV-C and URI with HRV-A. Percentage of patients diagnosed with infection type: LRI (bronchiolitis, croup, pneumonia, and asthma) and URI (coryza, pharyngitis, and acute otitis media). White bars represent HRV-C, and gray bars represent HRV-A. Journal of Allergy and Clinical Immunology 2013 131, 69-77.e6DOI: (10.1016/j.jaci.2012.09.033) Copyright © 2012 American Academy of Allergy, Asthma & Immunology Terms and Conditions

Fig 5 Phylogenetic tree of HRV species depicting HRV species and URI (red circle) or LRI (blue square) diagnosis. Grouping URI and LRI diagnoses suggests that HRV species is associated with certain clinical phenotypes (or respiratory disease severity). Novel sequences are designated by “VU” followed by the sample number, and sequences matching published HRV strains are marked as HRV followed by the strain number. Journal of Allergy and Clinical Immunology 2013 131, 69-77.e6DOI: (10.1016/j.jaci.2012.09.033) Copyright © 2012 American Academy of Allergy, Asthma & Immunology Terms and Conditions

Fig E1 Number of samples analyzed for HRV by year. Black bars indicate the number of positive samples. Journal of Allergy and Clinical Immunology 2013 131, 69-77.e6DOI: (10.1016/j.jaci.2012.09.033) Copyright © 2012 American Academy of Allergy, Asthma & Immunology Terms and Conditions

Fig E2 The probability of HMPV varies significantly over month and year. Lines represent negative binomial regression model based on data. Journal of Allergy and Clinical Immunology 2013 131, 69-77.e6DOI: (10.1016/j.jaci.2012.09.033) Copyright © 2012 American Academy of Allergy, Asthma & Immunology Terms and Conditions

Fig E3 The probability of parainfluenza virus varies significantly over month and year. January and February were least likely to be associated with positive PIV. Lines represent negative binomial regression model based on data. Journal of Allergy and Clinical Immunology 2013 131, 69-77.e6DOI: (10.1016/j.jaci.2012.09.033) Copyright © 2012 American Academy of Allergy, Asthma & Immunology Terms and Conditions

Fig E4 The probability of RSV infection varies by month. December, January, and February were more likely to be associated with virus detection. Lines represent negative binomial regression model based on data. Journal of Allergy and Clinical Immunology 2013 131, 69-77.e6DOI: (10.1016/j.jaci.2012.09.033) Copyright © 2012 American Academy of Allergy, Asthma & Immunology Terms and Conditions

Fig E5 The probability of influenza varies by month. Because of low sample size, data were binned into 2-month intervals. January/February was most likely to be associated with positive influenza diagnosis. Lines represent negative binomial regression model based on data. Journal of Allergy and Clinical Immunology 2013 131, 69-77.e6DOI: (10.1016/j.jaci.2012.09.033) Copyright © 2012 American Academy of Allergy, Asthma & Immunology Terms and Conditions

Fig E6 The probability of adenovirus varies by both month and year. September was least likely to be associated with adenovirus, and May was most often associated with adenovirus. Lines represent negative binomial regression model based on data. Journal of Allergy and Clinical Immunology 2013 131, 69-77.e6DOI: (10.1016/j.jaci.2012.09.033) Copyright © 2012 American Academy of Allergy, Asthma & Immunology Terms and Conditions