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Perofsky AC, Huddleston J, Hansen C, Barnes JR, Rowe T, Xu X, Kondor R, Wentworth DE, Lewis N, Whittaker L, Ermetal B, Harvey R, Galiano M, Daniels RS, McCauley JW, Fujisaki S, Nakamura K, Kishida N, Watanabe S, Hasegawa H, Sullivan SG, Barr IG, Subbarao K, Krammer F, Bedford T, Viboud C. Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.10.02.23296453. [PMID: 37873362 PMCID: PMC10593063 DOI: 10.1101/2023.10.02.23296453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection dynamics, presumably via heterosubtypic cross-immunity.
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Affiliation(s)
- Amanda C Perofsky
- Fogarty International Center, National Institutes of Health, United States
- Brotman Baty Institute for Precision Medicine, University of Washington, United States
| | - John Huddleston
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, United States
| | - Chelsea Hansen
- Fogarty International Center, National Institutes of Health, United States
- Brotman Baty Institute for Precision Medicine, University of Washington, United States
| | - John R Barnes
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), United States
| | - Thomas Rowe
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), United States
| | - Xiyan Xu
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), United States
| | - Rebecca Kondor
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), United States
| | - David E Wentworth
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), United States
| | - Nicola Lewis
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - Lynne Whittaker
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - Burcu Ermetal
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - Ruth Harvey
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - Monica Galiano
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - Rodney Stuart Daniels
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - John W McCauley
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - Seiichiro Fujisaki
- Influenza Virus Research Center, National Institute of Infectious Diseases, Japan
| | - Kazuya Nakamura
- Influenza Virus Research Center, National Institute of Infectious Diseases, Japan
| | - Noriko Kishida
- Influenza Virus Research Center, National Institute of Infectious Diseases, Japan
| | - Shinji Watanabe
- Influenza Virus Research Center, National Institute of Infectious Diseases, Japan
| | - Hideki Hasegawa
- Influenza Virus Research Center, National Institute of Infectious Diseases, Japan
| | - Sheena G Sullivan
- WHO Collaborating Centre for Reference and Research on Influenza, The Peter Doherty Institute for Infection and Immunity, Department of Microbiology and Immunology, The University of Melbourne, The Peter Doherty Institute for Infection and Immunity, Australia
| | - Ian G Barr
- WHO Collaborating Centre for Reference and Research on Influenza, The Peter Doherty Institute for Infection and Immunity, Department of Microbiology and Immunology, The University of Melbourne, The Peter Doherty Institute for Infection and Immunity, Australia
| | - Kanta Subbarao
- WHO Collaborating Centre for Reference and Research on Influenza, The Peter Doherty Institute for Infection and Immunity, Department of Microbiology and Immunology, The University of Melbourne, The Peter Doherty Institute for Infection and Immunity, Australia
| | - Florian Krammer
- Center for Vaccine Research and Pandemic Preparedness (C-VaRPP), Icahn School of Medicine at Mount Sinai, United States
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, United States
| | - Trevor Bedford
- Brotman Baty Institute for Precision Medicine, University of Washington, United States
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, United States
- Department of Genome Sciences, University of Washington, United States
- Howard Hughes Medical Institute, Seattle, United States
| | - Cécile Viboud
- Fogarty International Center, National Institutes of Health, United States
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Movva N, Suh M, Bylsma LC, Fryzek JP, Nelson CB. Systematic Literature Review of Respiratory Syncytial Virus Laboratory Testing Practices and Incidence in United States Infants and Children <5 Years of Age. J Infect Dis 2022; 226:S213-S224. [PMID: 35968874 PMCID: PMC9377029 DOI: 10.1093/infdis/jiac203] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Background Respiratory syncytial virus (RSV) can cause serious illness in those aged <5 years in the United States, but uncertainty remains around which populations receive RSV testing. We conducted a systematic literature review of RSV testing patterns in studies published from 2000 to 2021. Methods Studies of RSV, medically attended RSV lower respiratory tract infections (LRTIs), and bronchiolitis were identified using standard methodology. Outcomes were clinical decisions to test for RSV, testing frequency, and testing incidence proportions in inpatient (IP), emergency department (ED), outpatient (OP), and urgent care settings. Results Eighty good-/fair-quality studies, which reported data from the period 1988–2020, were identified. Twenty-seven described the clinical decision to test, which varied across and within settings. Two studies reported RSV testing frequency for multiple settings, with higher testing proportions in IP (n = 2, range: 83%–85%, 1996–2009) compared with ED (n = 1, 25%, 2006–2009) and OP (n = 2, 15%–25%, 1996–2009). Higher RSV testing incidence proportions were observed among LRTI infant populations in the ED (n = 1, 74%, 2007–2008) and OP (n = 2, 54%–69%, 1995–2008). Incidence proportions in LRTI populations were not consistently higher in the IP setting (n = 13). Across studies and time, there was heterogeneity in RSV testing patterns, which may reflect varying detection methods, populations, locations, time periods, and healthcare settings. Conclusions Not all infants and children with LRTI are tested for RSV, highlighting underestimation of RSV burden across all settings.
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Affiliation(s)
- Naimisha Movva
- EpidStrategies, a Division of ToxStrategies, Rockville, Maryland, USA
| | - Mina Suh
- EpidStrategies, a Division of ToxStrategies, Rockville, Maryland, USA
| | - Lauren C Bylsma
- EpidStrategies, a Division of ToxStrategies, Rockville, Maryland, USA
| | - Jon P Fryzek
- EpidStrategies, a Division of ToxStrategies, Rockville, Maryland, USA
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DeJonge PM, Monto AS, Malosh RE, Petrie JG, Segaloff HE, McSpadden E, Cheng C, Bazzi L, Callear A, Johnson E, Truscon R, Martin ET. Distinct influenza surveillance networks and their agreement in recording regional influenza circulation: Experience from Southeast Michigan. Influenza Other Respir Viruses 2021; 16:521-531. [PMID: 34821476 PMCID: PMC8983886 DOI: 10.1111/irv.12944] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 11/07/2021] [Indexed: 01/22/2023] Open
Abstract
INTRODUCTION In Southeast Michigan, active surveillance studies monitor influenza activity in hospitals, ambulatory clinics, and community households. Across five respiratory seasons, we assessed the contribution of data from each of the three networks towards improving our overall understanding of regional influenza circulation. METHODS All three networks used case definitions for acute respiratory illness (ARI) and molecularly tested for influenza from research-collected respiratory specimens. Age- and network-stratified epidemic curves were created for influenza A and B. We compared stratified epidemic curves visually and by centering at seasonal midpoints. RESULTS Across all seasons (from 2014/2015 through 2018/2019), epidemic curves from each of the three networks were comparable in terms of both timing and magnitude. Small discrepancies in epidemics recorded by each network support previous conclusions about broader characteristics of particular influenza seasons. CONCLUSION Influenza surveillance systems based in hospital, ambulatory clinic, and community household settings appear to provide largely similar information regarding regional epidemic activity. Together, multiple levels of influenza surveillance provide a detailed view of regional influenza epidemics, but a single surveillance system-regardless of population subgroup monitored-appears to be sufficient in providing vital information regarding community influenza epidemics.
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Affiliation(s)
- Peter M DeJonge
- Michigan Influenza Center, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Arnold S Monto
- Michigan Influenza Center, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Ryan E Malosh
- Michigan Influenza Center, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Joshua G Petrie
- Michigan Influenza Center, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Hannah E Segaloff
- Michigan Influenza Center, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Erin McSpadden
- Michigan Influenza Center, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Caroline Cheng
- Michigan Influenza Center, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Latifa Bazzi
- Michigan Influenza Center, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Amy Callear
- Michigan Influenza Center, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Emileigh Johnson
- Michigan Influenza Center, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Rachel Truscon
- Michigan Influenza Center, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Emily T Martin
- Michigan Influenza Center, Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
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Schuster JE. Can't Touch This: A Novel Method of Contactless Respiratory Surveillance during a Novel Time. Clin Infect Dis 2020; 73:e4419-e4420. [PMID: 33242068 DOI: 10.1093/cid/ciaa1766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Indexed: 11/12/2022] Open
Affiliation(s)
- Jennifer E Schuster
- Division of Pediatric Infectious Diseases, Children's Mercy Kansas City; Kansas City, MO, USA
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Stewart RJ, Rossow J, Eckel S, Bidol S, Ballew G, Signs K, Conover JT, Burns E, Bresee JS, Fry AM, Olsen SJ, Biggerstaff M. Text-Based Illness Monitoring for Detection of Novel Influenza A Virus Infections During an Influenza A (H3N2)v Virus Outbreak in Michigan, 2016: Surveillance and Survey. JMIR Public Health Surveill 2019; 5:e10842. [PMID: 31025948 PMCID: PMC6658270 DOI: 10.2196/10842] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Revised: 11/13/2018] [Accepted: 12/20/2018] [Indexed: 01/23/2023] Open
Abstract
Background Rapid reporting of human infections with novel influenza A viruses accelerates detection of viruses with pandemic potential and implementation of an effective public health response. After detection of human infections with influenza A (H3N2) variant (H3N2v) viruses associated with agricultural fairs during August 2016, the Michigan Department of Health and Human Services worked with the US Centers for Disease Control and Prevention (CDC) to identify infections with variant influenza viruses using a text-based illness monitoring system. Objective To enhance detection of influenza infections using text-based monitoring and evaluate the feasibility and acceptability of the system for use in future outbreaks of novel influenza viruses. Methods During an outbreak of H3N2v virus infections among agricultural fair attendees, we deployed a text-illness monitoring (TIM) system to conduct active illness surveillance among households of youth who exhibited swine at fairs. We selected all fairs with suspected H3N2v virus infections. For fairs without suspected infections, we selected only those fairs that met predefined criteria. Eligible respondents were identified and recruited through email outreach and/or on-site meetings at fairs. During the fairs and for 10 days after selected fairs, enrolled households received daily, automated text-messages inquiring about illness; reports of illness were investigated by local health departments. To understand the feasibility and acceptability of the system, we monitored enrollment and trends in participation and distributed a Web-based survey to households of exhibitors from five fairs. Results Among an estimated 500 households with a member who exhibited swine at one of nine selected fairs, representatives of 87 (17.4%) households were enrolled, representing 392 household members. Among fairs that were ongoing when the TIM system was deployed, the number of respondents peaked at 54 on the third day of the fair and then steadily declined throughout the rest of the monitoring period; 19 out of 87 household representatives (22%) responded through the end of the 10-day monitoring period. We detected 2 H3N2v virus infections using the TIM system, which represents 17% (2/12) of all H3N2v virus infections detected during this outbreak in Michigan. Of the 70 survey respondents, 16 (23%) had participated in the TIM system. A total of 73% (11/15) participated because it was recommended by fair coordinators and 80% (12/15) said they would participate again. Conclusions Using a text-message system, we monitored for illness among a large number of individuals and households and detected H3N2v virus infections through active surveillance. Text-based illness monitoring systems are useful for detecting novel influenza virus infections when active monitoring is necessary. Participant retention and testing of persons reporting illness are critical elements for system improvement.
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Affiliation(s)
- Rebekah J Stewart
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States.,Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - John Rossow
- Epidemiology Elective Program, Division of Scientific Education and Professional Development, Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, United States.,College of Veterinary Medicine, University of Georgia, Athens, GA, United States
| | - Seth Eckel
- Michigan Department of Health and Human Services, Lansing, MI, United States
| | - Sally Bidol
- Michigan Department of Health and Human Services, Lansing, MI, United States
| | - Grant Ballew
- Compliant Campaign, Scottsdale, AZ, United States
| | - Kimberly Signs
- Michigan Department of Health and Human Services, Lansing, MI, United States
| | | | - Erin Burns
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Joseph S Bresee
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Alicia M Fry
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Sonja J Olsen
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Matthew Biggerstaff
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
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Russell KE, Fowlkes A, Stockwell MS, Vargas CY, Saiman L, Larson EL, LaRussa P, Di Lonardo S, Popowich M, St. George K, Steffens A, Reed C. Comparison of outpatient medically attended and community-level influenza-like illness-New York City, 2013-2015. Influenza Other Respir Viruses 2018; 12:336-343. [PMID: 29350791 PMCID: PMC5907822 DOI: 10.1111/irv.12540] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/12/2017] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Surveillance of influenza-like illness (ILI) in the United States is primarily conducted through medical settings despite a significant burden of non-medically attended ILI. OBJECTIVES To assess consistency between surveillance for respiratory viruses in outpatient and community settings using ILI surveillance from the Centers for Disease Control and Prevention Influenza Incidence Surveillance Project (IISP) and the Mobile Surveillance for Acute Respiratory Infections (ARI) and Influenza-Like Illness in the Community (MoSAIC) Study. METHODS The Influenza Incidence Surveillance Project conducts ILI surveillance in 3 primary care clinics in New York City, and MoSAIC conducts community-based ILI/ARI surveillance through text messaging among a cohort of New York City residents. Both systems obtain respiratory specimens from participants with ILI/ARI and test for multiple pathogens. We conducted a retrospective review of ILI cases in IISP and MoSAIC from January 2013 to May 2015 with descriptive analyses of clinical and laboratory data. RESULTS Five-hundred twelve MoSAIC and 669 IISP participants met an ILI criteria (fever with cough or sore throat) and were included. Forty percent of MoSAIC participants sought care; the majority primary care. Pathogens were detected in 63% of MoSAIC and 70% of IISP cases. The relative distribution of influenza and other respiratory viruses detected was similar; however, there were statistically significant differences in the frequency that were not explained by care seeking. CONCLUSIONS Outpatient and community-based surveillance in the one found similar timing and relative distribution of respiratory viruses, but community surveillance in a single neighborhood may not fully capture the variations in ILI etiology that occur more broadly.
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Affiliation(s)
- Kate E. Russell
- Epidemic Intelligence ServiceCenters for Disease Control and PreventionAtlantaGAUSA
- Influenza DivisionNational Center for Immunization and Respiratory DiseasesCenters for Disease Control and PreventionAtlantaGAUSA
| | - Ashley Fowlkes
- Influenza DivisionNational Center for Immunization and Respiratory DiseasesCenters for Disease Control and PreventionAtlantaGAUSA
| | - Melissa S. Stockwell
- Columbia University Medical CenterNew YorkNYUSA
- NewYork‐Presbyterian HospitalNew YorkNYUSA
| | | | - Lisa Saiman
- Columbia University Medical CenterNew YorkNYUSA
- NewYork‐Presbyterian HospitalNew YorkNYUSA
| | | | | | - Steve Di Lonardo
- New York City Department of Health and Mental HygieneNew YorkNYUSA
| | | | | | - Andrea Steffens
- Influenza DivisionNational Center for Immunization and Respiratory DiseasesCenters for Disease Control and PreventionAtlantaGAUSA
| | - Carrie Reed
- Influenza DivisionNational Center for Immunization and Respiratory DiseasesCenters for Disease Control and PreventionAtlantaGAUSA
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