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Stafford E, Dimitrov D, Trinidad SB, Matrajt L. Evaluating equity-promoting interventions to prevent race-based inequities in influenza outcomes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.20.24307635. [PMID: 39040204 PMCID: PMC11261914 DOI: 10.1101/2024.05.20.24307635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
Importance Seasonal influenza hospitalizations pose a considerable burden in the United States, with BIPOC (Black, Indigenous, and other People of Color) communities being disproportionately affected. Objective To determine and quantify the effects of different types of mitigation strategies on inequities in influenza outcomes (symptomatic infections and hospitalizations). Design In this simulation study, we fit a race-stratified agent-based model of influenza transmission to demographic and hospitalization data of the United States. Participants We consider five racial-ethnic groups: non-Hispanic White persons, non- Hispanic Black persons, non-Hispanic Asian persons, non-Hispanic American Indian or Alaska Native persons, and Hispanic or Latino persons. Setting We tested five idealized equity-promoting interventions to determine their effectiveness in reducing inequity in influenza outcomes. The interventions assumed (i) equalized vaccination rates, (ii) equalized comorbidities, (iii) work-risk distribution proportional to the distribution of the population, (iv) reduced work contacts for all, or (v) a combination of equalizing vaccination rates and comorbidities and reducing work contacts. Main Outcomes and Measures Reduction in symptomatic or hospitalization risk ratios, defined as the ratio of the number of symptomatic infections (hospitalizations respectively) in each age- and racial-ethnic group and their corresponding white counterpart. We also evaluated the reduction in the absolute mean number of symptomatic infections or hospitalizations in each age- and racial-ethnic group compared to the fitted scenario (baseline). Results Our analysis suggests that symptomatic infections were equalized and reduced (by up to 17% in BIPOC adults aged 18-49) by strategies reducing work contacts or equalizing vaccination rates. Reducing comorbidities resulted in significant decreases in hospitalizations, with a reduction of over 40% in BIPOC groups. All tested interventions reduced the inequity in influenza hospitalizations in all racial-ethnic groups, but interventions reducing comorbidities in marginalized populations were the most effective. Notably, these interventions resulted in better outcomes across all racial-ethnic groups, not only those prioritized by the interventions. Conclusions and Relevance In this simulation modeling study, equalizing vaccination rates and reducing number of work contacts (which are relatively simple strategies to implement) reduced the both the inequity in hospitalizations and the absolute number of symptomatic infections and hospitalizations in all age and racial-ethnic groups.
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Affiliation(s)
- Erin Stafford
- Department of Applied Mathematics, University of Washington, Seattle, WA, USA
- Current address: Department of Public Health and Clinical Medicine, Umeå University, Umeå, SE
| | - Dobromir Dimitrov
- Department of Applied Mathematics, University of Washington, Seattle, WA, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Susan Brown Trinidad
- Department of Bioethics and Humanities, University of Washington, Seattle, WA, USA
| | - Laura Matrajt
- Department of Applied Mathematics, University of Washington, Seattle, WA, USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
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Hoy G, Cortier T, Maier HE, Kuan G, Lopez R, Sanchez N, Ojeda S, Plazaola M, Stadlbauer D, Shotwell A, Balmaseda A, Krammer F, Cauchemez S, Gordon A. Anti-Neuraminidase Antibodies Reduce the Susceptibility to and Infectivity of Influenza A/H3N2 Virus. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.14.24308936. [PMID: 38946969 PMCID: PMC11213101 DOI: 10.1101/2024.06.14.24308936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Immune responses against neuraminidase (NA) are of great interest for developing more robust influenza vaccines, but the role of anti-NA antibodies on influenza infectivity has not been established. We conducted household transmission studies in Managua, Nicaragua to examine the impact of anti-NA antibodies on influenza A/H3N2 susceptibility and infectivity. Analyzing these data with mathematical models capturing household transmission dynamics and their drivers, we estimated that having higher preexisting antibody levels against the hemagglutinin (HA) head, HA stalk, and NA was associated with reduced susceptibility to infection (relative susceptibility 0.67, 95% Credible Interval [CrI] 0.50-0.92 for HA head; 0.59, 95% CrI 0.42-0.82 for HA stalk; and 0.56, 95% CrI 0.40-0.77 for NA). Only anti-NA antibodies were associated with reduced infectivity (relative infectivity 0.36, 95% CrI 0.23-0.55). These benefits from anti-NA immunity were observed even among individuals with preexisting anti-HA immunity. These results suggest that influenza vaccines designed to elicit NA immunity in addition to hemagglutinin immunity may not only contribute to protection against infection but reduce infectivity of vaccinated individuals upon infection.
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Hay JA, Zhu H, Jiang CQ, Kwok KO, Shen R, Kucharski A, Yang B, Read JM, Lessler J, Cummings DAT, Riley S. Reconstructed influenza A/H3N2 infection histories reveal variation in incidence and antibody dynamics over the life course. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.18.24304371. [PMID: 38562868 PMCID: PMC10984066 DOI: 10.1101/2024.03.18.24304371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Humans experience many influenza infections over their lives, resulting in complex and varied immunological histories. Although experimental and quantitative analyses have improved our understanding of the immunological processes defining an individual's antibody repertoire, how these within-host processes are linked to population-level influenza epidemiology remains unclear. Here, we used a multi-level mathematical model to jointly infer antibody dynamics and individual-level lifetime influenza A/H3N2 infection histories for 1,130 individuals in Guangzhou, China, using 67,683 haemagglutination inhibition (HI) assay measurements against 20 A/H3N2 strains from repeat serum samples collected between 2009 and 2015. These estimated infection histories allowed us to reconstruct historical seasonal influenza patterns and to investigate how influenza incidence varies over time, space and age in this population. We estimated median annual influenza infection rates to be approximately 18% from 1968 to 2015, but with substantial variation between years. 88% of individuals were estimated to have been infected at least once during the study period (2009-2015), and 20% were estimated to have three or more infections in that time. We inferred decreasing infection rates with increasing age, and found that annual attack rates were highly correlated across all locations, regardless of their distance, suggesting that age has a stronger impact than fine-scale spatial effects in determining an individual's antibody profile. Finally, we reconstructed each individual's expected antibody profile over their lifetime and inferred an age-stratified relationship between probability of infection and HI titre. Our analyses show how multi-strain serological panels provide rich information on long term, epidemiological trends, within-host processes and immunity when analyzed using appropriate inference methods, and adds to our understanding of the life course epidemiology of influenza A/H3N2.
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Affiliation(s)
- James A. Hay
- Pandemic Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- MRC Centre for Global Infectious Disease Analysis, Imperial College London
| | - Huachen Zhu
- Guangdong-Hong Kong Joint Laboratory of Emerging Infectious Diseases/MOE Joint Laboratory for International Collaboration in Virology and Emerging Infectious Diseases, Joint Institute of Virology (Shantou University/The University of Hong Kong), Shantou University, Shantou, China
- State Key Laboratory of Emerging Infectious Diseases / World Health Organization Influenza Reference Laboratory, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- 5EKIH (Gewuzhikang) Pathogen Research Institute, Guangdong, China
| | | | - Kin On Kwok
- The Jockey Club School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Stanley Ho Centre for Emerging Infectious Diseases, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Asia-Pacific Studies, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Ruiyin Shen
- Guangzhou No.12 Hospital, Guangzhou, Guangdong, China
| | - Adam Kucharski
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, United Kingdom
| | - Bingyi Yang
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Jonathan M. Read
- Centre for Health Informatics Computing and Statistics, Lancaster University, Lancaster, United Kingdom
| | - Justin Lessler
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United States
- Department of Epidemiology, UNC Gillings School of Global Public Health, Chapel Hill, United States
- UNC Carolina Population Center, Chapel Hill, United States
| | - Derek A. T. Cummings
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, United States
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Imperial College London
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4
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Zhang L, Duan W, Ma C, Zhang J, Sun Y, Ma J, Wang Y, Zhang D, Wang Q, Liu J, Liu M. An Intense Out-of-Season Rebound of Influenza Activity After the Relaxation of Coronavirus Disease 2019 Restrictions in Beijing, China. Open Forum Infect Dis 2024; 11:ofae163. [PMID: 38585185 PMCID: PMC10995958 DOI: 10.1093/ofid/ofae163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 03/19/2024] [Indexed: 04/09/2024] Open
Abstract
Background The aim of this study was to investigate the changes of epidemic characteristics of influenza activity pre- and post-coronavirus disease 2019 (COVID-19) in Beijing, China. Methods Epidemiologic data were collected from the influenza surveillance system in Beijing. We compared epidemic intensity, epidemic onset and duration, and influenza transmissibility during the 2022-2023 season with pre-COVID-19 seasons from 2014 to 2020. Results The overall incidence rate of influenza in the 2022-2023 season was significantly higher than that of the pre-COVID-19 period, with the record-high level of epidemic intensity in Beijing. The onset and duration of the influenza epidemic period in 2022-2023 season was notably later and shorter than that of the 2014-2020 seasons. Maximum daily instantaneous reproduction number (Rt) of the 2022-2023 season (Rt = 2.31) was much higher than that of the pre-COVID-19 period (Rt = 1.49). The incidence of influenza A(H1N1) and A(H3N2) were the highest among children aged 0-4 years and 5-14 years, respectively, in the 2022-2023 season. Conclusions A late, intense, and short-term peak influenza activity was observed in the 2022-2023 season in Beijing. Children <15 years old were impacted the most by the interruption of influenza circulation during the COVID-19 pandemic. Maintaining continuous surveillance and developing targeted public health strategies of influenza is necessary.
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Affiliation(s)
- Li Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Wei Duan
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Chunna Ma
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Jiaojiao Zhang
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Ying Sun
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Jiaxin Ma
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Yingying Wang
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Daitao Zhang
- Institute for Infectious Disease and Endemic Disease Control, Beijing Center for Disease Prevention and Control, Beijing, China
| | - Quanyi Wang
- Center Office, Beijing Center for Disease Prevention and Control, Beijing, China
- Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Jue Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Min Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
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5
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Mettelman RC, Souquette A, Van de Velde LA, Vegesana K, Allen EK, Kackos CM, Trifkovic S, DeBeauchamp J, Wilson TL, St James DG, Menon SS, Wood T, Jelley L, Webby RJ, Huang QS, Thomas PG. Baseline innate and T cell populations are correlates of protection against symptomatic influenza virus infection independent of serology. Nat Immunol 2023; 24:1511-1526. [PMID: 37592015 PMCID: PMC10566627 DOI: 10.1038/s41590-023-01590-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 07/13/2023] [Indexed: 08/19/2023]
Abstract
Evidence suggests that innate and adaptive cellular responses mediate resistance to the influenza virus and confer protection after vaccination. However, few studies have resolved the contribution of cellular responses within the context of preexisting antibody titers. Here, we measured the peripheral immune profiles of 206 vaccinated or unvaccinated adults to determine how baseline variations in the cellular and humoral immune compartments contribute independently or synergistically to the risk of developing symptomatic influenza. Protection correlated with diverse and polyfunctional CD4+ and CD8+ T, circulating T follicular helper, T helper type 17, myeloid dendritic and CD16+ natural killer (NK) cell subsets. Conversely, increased susceptibility was predominantly attributed to nonspecific inflammatory populations, including γδ T cells and activated CD16- NK cells, as well as TNFα+ single-cytokine-producing CD8+ T cells. Multivariate and predictive modeling indicated that cellular subsets (1) work synergistically with humoral immunity to confer protection, (2) improve model performance over demographic and serologic factors alone and (3) comprise the most important predictive covariates. Together, these results demonstrate that preinfection peripheral cell composition improves the prediction of symptomatic influenza susceptibility over vaccination, demographics or serology alone.
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Affiliation(s)
- Robert C Mettelman
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Aisha Souquette
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Lee-Ann Van de Velde
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Kasi Vegesana
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - E Kaitlynn Allen
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Christina M Kackos
- Department of Host-Microbe Interactions, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Sanja Trifkovic
- Department of Host-Microbe Interactions, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Jennifer DeBeauchamp
- Department of Host-Microbe Interactions, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Taylor L Wilson
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
- Department of Microbiology, Immunology and Biochemistry, College of Graduate Health Sciences, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Deryn G St James
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
- Department of Microbiology, Immunology and Biochemistry, College of Graduate Health Sciences, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Smrithi S Menon
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Timothy Wood
- Institute of Environmental Science and Research Limited (ESR), Wallaceville Science Centre, Upper Hutt, New Zealand
| | - Lauren Jelley
- Institute of Environmental Science and Research Limited (ESR), Wallaceville Science Centre, Upper Hutt, New Zealand
| | - Richard J Webby
- Department of Host-Microbe Interactions, St. Jude Children's Research Hospital, Memphis, TN, USA.
| | - Q Sue Huang
- Institute of Environmental Science and Research Limited (ESR), Wallaceville Science Centre, Upper Hutt, New Zealand.
| | - Paul G Thomas
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN, USA.
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6
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Daulagala P, Mann BR, Leung K, Lau EHY, Yung L, Lei R, Nizami SIN, Wu JT, Chiu SS, Daniels RS, Wu NC, Wentworth D, Peiris M, Yen HL. Imprinted Anti-Hemagglutinin and Anti-Neuraminidase Antibody Responses after Childhood Infections of A(H1N1) and A(H1N1)pdm09 Influenza Viruses. mBio 2023; 14:e0008423. [PMID: 37070986 PMCID: PMC10294682 DOI: 10.1128/mbio.00084-23] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 03/29/2023] [Indexed: 04/19/2023] Open
Abstract
Immune imprinting is a driver known to shape the anti-hemagglutinin (HA) antibody landscape of individuals born within the same birth cohort. With the HA and neuraminidase (NA) proteins evolving at different rates under immune selection pressures, anti-HA and anti-NA antibody responses since childhood influenza virus infections have not been evaluated in parallel at the individual level. This is partly due to the limited knowledge of changes in NA antigenicity, as seasonal influenza vaccines have focused on generating neutralizing anti-HA antibodies against HA antigenic variants. Here, we systematically characterized the NA antigenic variants of seasonal A(H1N1) viruses from 1977 to 1991 and completed the antigenic profile of N1 NAs from 1977 to 2015. We identified that NA proteins of A/USSR/90/77, A/Singapore/06/86, and A/Texas/36/91 were antigenically distinct and mapped N386K as a key determinant of the NA antigenic change from A/USSR/90/77 to A/Singapore/06/86. With comprehensive panels of HA and NA antigenic variants of A(H1N1) and A(H1N1)pdm09 viruses, we determined hemagglutinin inhibition (HI) and neuraminidase inhibition (NI) antibodies from 130 subjects born between 1950 and 2015. Age-dependent imprinting was observed for both anti-HA and anti-NA antibodies, with the peak HI and NI titers predominantly detected from subjects at 4 to 12 years old during the year of initial virus isolation, except the age-independent anti-HA antibody response against A(H1N1)pdm09 viruses. More participants possessed antibodies that reacted to multiple antigenically distinct NA proteins than those with antibodies that reacted to multiple antigenically distinct HA proteins. Our results support the need to include NA proteins in seasonal influenza vaccine preparations. IMPORTANCE Seasonal influenza vaccines have aimed to generate neutralizing anti-HA antibodies for protection since licensure. More recently, anti-NA antibodies have been established as an additional correlate of protection. While HA and NA antigenic changes occurred discordantly, the anti-HA and anti-NA antibody profiles have rarely been analyzed in parallel at the individual level, due to the limited knowledge on NA antigenic changes. By characterizing NA antigenic changes of A(H1N1) viruses, we determined the anti-HA and anti-NA antibody landscape against antigenically distinct A(H1N1) and A(H1N1)pdm09 viruses using sera of 130 subjects born between 1950 and 2015. We observed age-dependent imprinting of both anti-HA and anti-NA antibodies against strains circulated during the first decade of life. A total of 67.7% (88/130) and 90% (117/130) of participants developed cross-reactive antibodies to multiple HA and NA antigens at titers ≥1:40. With slower NA antigenic changes and cross-reactive anti-NA antibody responses, including NA protein in influenza vaccine preparation may enhance vaccine efficacy.
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Affiliation(s)
- Pavithra Daulagala
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - Brian R. Mann
- WHO Collaborating Center for Surveillance, Epidemiology and Control of Influenza, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Kathy Leung
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong SAR, China
- University of Hong Kong, Shenzhen Hospital, Shenzhen, China
| | - Eric H. Y. Lau
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong SAR, China
| | - Louise Yung
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - Ruipeng Lei
- Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Sarea I. N. Nizami
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - Joseph T. Wu
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
- Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong SAR, China
| | - Susan S. Chiu
- Department of Paediatrics and Adolescent Medicine, Queen Mary Hospital and Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
| | - Rodney S. Daniels
- Francis Crick Institute, Crick Worldwide Influenza Centre, WHO Collaborating Centre for Reference and Research on Influenza, London, UK
| | - Nicholas C. Wu
- Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - David Wentworth
- WHO Collaborating Center for Surveillance, Epidemiology and Control of Influenza, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Malik Peiris
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
- Centre for Immunology and Infection (C2I), Hong Kong Science Park, Hong Kong SAR, China
| | - Hui-Ling Yen
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
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7
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Most ZM, Nyquist AC, Radonovich LJ, Rodriguez-Barradas MC, Price CS, Simberkoff MS, Bessesen MT, Cummings DAT, Rattigan SM, Warren-Gash C, Gaydos CA, Gibert CL, Gorse GJ, Perl TM. Preschool-Aged Household Contacts as a Risk Factor for Viral Respiratory Infections in Healthcare Personnel. Open Forum Infect Dis 2023; 10:ofad057. [PMID: 36824623 PMCID: PMC9942663 DOI: 10.1093/ofid/ofad057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 02/03/2023] [Indexed: 02/11/2023] Open
Abstract
Background Viral respiratory infections (VRIs) are common and are occupational risks for healthcare personnel (HCP). VRIs can also be acquired at home and other settings among HCPs. We sought to determine if preschool-aged household contacts are a risk factor for VRIs among HCPs working in outpatient settings. Methods We conducted a secondary analysis of data from a cluster randomized trial at 7 medical centers in the United States over 4 influenza seasons from 2011-2012 to 2014-2015. Adult HCPs who routinely came within 6 feet of patients with respiratory infections were included. Participants were tested for respiratory viruses whenever symptomatic and at 2 random times each season when asymptomatic. The exposure of interest was the number of household contacts 0-5 years old (preschool-aged) at the beginning of each HCP-season. The primary outcome was the rate of polymerase chain reaction-detected VRIs, regardless of symptoms. The VRI incidence rate ratio (IRR) was calculated using a mixed-effects Poisson regression model that accounted for clustering at the clinic level. Results Among the 4476 HCP-seasons, most HCPs were female (85.4%) and between 30 and 49 years of age (54.6%). The overall VRI rate was 2.04 per 100 person-weeks. In the adjusted analysis, HCPs having 1 (IRR, 1.22 [95% confidence interval {CI}, 1.05-1.43]) and ≥2 (IRR, 1.35 [95% CI, 1.09-1.67]) preschool-aged household contacts had higher VRI rates than those with zero preschool-aged household contacts. Conclusions Preschool-aged household contacts are a risk factor for developing VRIs among HCPs working in outpatient settings.
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Affiliation(s)
- Zachary M Most
- Pediatric Infectious Diseases Program, Children’s Health System of Texas, Dallas, Texas, USA
- Division of Infectious Disease, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Ann-Christine Nyquist
- Department of Infectious Disease, Children’s Hospital Colorado, Aurora, Colorado, USA
- Division of Infectious Diseases, Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Lewis J Radonovich
- Respiratory Health Division, National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention, Morgantown, West Virginia, USA
| | - Maria C Rodriguez-Barradas
- Infectious Diseases Section, Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA
- Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Connie Savor Price
- Division of Infectious Diseases, University of Colorado School of Medicine, Aurora, Colorado, USA
- Infectious Disease Department, Denver Health Medical Center, Denver, Colorado, USA
| | - Michael S Simberkoff
- Department of Medicine, Veterans Affairs New York Harbor Healthcare System, New York, New York, USA
- Division of Infectious Diseases, New York University Grossman School of Medicine, New York, New York, USA
| | - Mary T Bessesen
- Division of Infectious Diseases, University of Colorado School of Medicine, Aurora, Colorado, USA
- Medical Service/Infectious Disease, Veterans Affairs Eastern Colorado Healthcare System, Aurora, Colorado, USA
| | - Derek A T Cummings
- Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Susan M Rattigan
- Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - Charlotte Warren-Gash
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Charlotte A Gaydos
- Department of Medicine and Division of Infectious Diseases, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Cynthia L Gibert
- Medical Service/Infectious Disease, Veterans Affairs Medical Center, Washington, District of Columbia, USA
- Department of Medicine, George Washington University School of Medical and Health Sciences, Washington, District of Columbia, USA
| | - Geoffrey J Gorse
- Division of Infectious Diseases, Allergy and Immunology, Saint Louis University School of Medicine, St Louis, Missouri, USA
| | - Trish M Perl
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Division of Infectious Diseases and Geographic Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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8
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Jiang Y, Lin YF, Shi S, Chen D, Shu Y. Effects of baloxavir and oseltamivir antiviral therapy on the transmission of seasonal influenza in China: A mathematical modeling analysis. J Med Virol 2022; 94:5425-5433. [PMID: 35770453 DOI: 10.1002/jmv.27969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 04/30/2022] [Accepted: 06/28/2022] [Indexed: 12/15/2022]
Abstract
New antiviral influenza treatments can effectively alleviate illness while reducing viral shedding. However, how such effects can translate into lower population infections of seasonal influenza in China remains unknown. To shed light on the public health impacts of novel antiviral agents for influenza, we constructed a dynamic transmission model to simulate the seasonal influenza epidemics in China. Two antivirus treatments, baloxavir and oseltamivir, were evaluated by estimating their impacts on the incidences of influenza infection in a single flu season. In the base-case analysis of a 10% antiviral treatment uptake rate, 2760 and 3420 per 10 000 persons contracted influenza under the treatment of baloxavir and oseltamivir, respectively. These incidence rates amounted to an 18.90% relative risk reduction (RRR) of infection associated with baloxavir in relation to oseltamivir. The corresponding RRR was 82.16% when the antiviral treatment uptake rate was increased to 35%. In addition, the peak of the prevalence of infected individuals per 10 000 persons under the baloxavir treatment was 177 (range: 93-274) fewer than that of oseltamivir. Our analyses suggest that the baloxavir treatment strategy reduces the incidence of influenza in China compared with oseltamivir in the setting of a seasonal flu epidemic. Also, increasing the uptake rate of antiviral treatment can potentially prevent millions of infections during a single flu season.
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Affiliation(s)
- Yawen Jiang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China
| | - Yi-Fan Lin
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China
| | - Si Shi
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China
| | - Daqin Chen
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China
| | - Yuelong Shu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, China
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9
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Wu S, Ross TM, Carlock MA, Ghedin E, Choi H, Vogel C. Evaluation of determinants of the serological response to the quadrivalent split-inactivated influenza vaccine. Mol Syst Biol 2022; 18:e10724. [PMID: 35514207 PMCID: PMC9073386 DOI: 10.15252/msb.202110724] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 04/11/2022] [Accepted: 04/12/2022] [Indexed: 12/20/2022] Open
Abstract
The seasonal influenza vaccine is only effective in half of the vaccinated population. To identify determinants of vaccine efficacy, we used data from > 1,300 vaccination events to predict the response to vaccination measured as seroconversion as well as hemagglutination inhibition (HAI) titer levels one year after. We evaluated the predictive capabilities of age, body mass index (BMI), sex, race, comorbidities, vaccination history, and baseline HAI titers, as well as vaccination month and vaccine dose in multiple linear regression models. The models predicted the categorical response for > 75% of the cases in all subsets with one exception. Prior vaccination, baseline titer level, and age were the major determinants of seroconversion, all of which had negative effects. Further, we identified a gender effect in older participants and an effect of vaccination month. BMI had a surprisingly small effect, likely due to its correlation with age. Comorbidities, vaccine dose, and race had negligible effects. Our models can generate a new seroconversion score that is corrected for the impact of these factors which can facilitate future biomarker identification.
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Affiliation(s)
- Shaohuan Wu
- Center for Genomics and Systems BiologyNew York UniversityNYUSA
| | - Ted M Ross
- Department of Infectious DiseasesCollege of Veterinary MedicineUniversity of GeorgiaAthensGAUSA
- Center for Vaccines and ImmunologyUniversity of GeorgiaAthensGAUSA
| | - Michael A Carlock
- Department of Infectious DiseasesCollege of Veterinary MedicineUniversity of GeorgiaAthensGAUSA
- Center for Vaccines and ImmunologyUniversity of GeorgiaAthensGAUSA
| | - Elodie Ghedin
- Center for Genomics and Systems BiologyNew York UniversityNYUSA
- Systems Genomics SectionLaboratory of Parasitic DiseasesNIAID, NIHBethesdaMDUSA
| | - Hyungwon Choi
- Department of MedicineYong Loo Lin School of MedicineNational University of SingaporeSingapore CitySingapore
| | - Christine Vogel
- Center for Genomics and Systems BiologyNew York UniversityNYUSA
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10
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Ge J, Lin X, Guo J, Liu L, Li Z, Lan Y, Liu L, Guo J, Lu J, Huang W, Xin L, Wang D, Qin K, Xu C, Zhou J. The Antibody Response Against Neuraminidase in Human Influenza A (H3N2) Virus Infections During 2018/2019 Flu Season: Focusing on the Epitopes of 329- N-Glycosylation and E344 in N2. Front Microbiol 2022; 13:845088. [PMID: 35387078 PMCID: PMC8978628 DOI: 10.3389/fmicb.2022.845088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 02/10/2022] [Indexed: 11/13/2022] Open
Abstract
Seasonal influenza A (H3N2) virus has been a concern since its first introduction in humans in 1968. Accumulating antigenic changes in viral hemagglutinin (HA), particularly recent cocirculations of multiple HA genetic clades, allow H3N2 virus evade into humans annually. From 2010, the binding of neuraminidase (NA) to sialic acid made the traditional assay for HA inhibition antibodies (Abs) unsuitable for antigenicity characterization. Here, we investigated the serum anti-NA response in a cohort with a seroconversion of microneutralizing (MN) Abs targeting the circulating strain, A/Singapore/INFIMH-16-0019/2016 (H3N2, 3C.2a1)-like, a virus during 2018/2019 flu seasons. We discovered that MN Ab titers show no difference between children and adults. Nevertheless, higher titers of Abs with NA activity inhibition (NI) activity of 129 and seroconversion rate of 68.42% are presented in children aged 7-17 years (n = 19) and 73.47 and 41.17% in adults aged 21-59 years (n = 17), respectively. The MN Abs generated in children display direct correlations with HA- and NA-binding Abs or NI Abs. The NI activity exhibited cross-reactivity to N2 of H3N2 viruses of 2007 and 2013, commonly with 329-N-glycosylation and E344 in N2, a characteristic of earlier 3C.2a H3N2 virus in 2014. The percentage of such viruses pronouncedly decreased and was even replaced by those dominant H3N2 viruses with E344K and 329 non-glycosylation, which have a significantly low activity to the tested antisera. Our findings suggest that NI assay is a testable assay applied in H3N2 infection in children, and the antigenic drift of current N2 should be considered for vaccine selection.
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Affiliation(s)
- Jing Ge
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Xiaojing Lin
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Jinlei Guo
- The Disease Control and Prevention of Qinhuai District, Nanjing, China
| | - Ling Liu
- Qinhuai District Center for Disease Control and Prevention, Nanjing, China
| | - Zi Li
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Yu Lan
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Liqi Liu
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Junfeng Guo
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Jian Lu
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Weijuan Huang
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Li Xin
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Dayan Wang
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Kun Qin
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Cuiling Xu
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Jianfang Zhou
- Key Laboratory for Medical Virology, National Health, and Family Planning Commission, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
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11
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Song S, Li Q, Shen L, Sun M, Yang Z, Wang N, Liu J, Liu K, Shao Z. From Outbreak to Near Disappearance: How Did Non-pharmaceutical Interventions Against COVID-19 Affect the Transmission of Influenza Virus? Front Public Health 2022; 10:863522. [PMID: 35425738 PMCID: PMC9001955 DOI: 10.3389/fpubh.2022.863522] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Accepted: 03/02/2022] [Indexed: 11/13/2022] Open
Abstract
Influenza shares the same putative transmission pathway with coronavirus disease 2019 (COVID-19), and causes tremendous morbidity and mortality annually globally. Since the transmission of COVID-19 in China, a series of non-pharmaceutical interventions (NPIs) against to the disease have been implemented to contain its transmission. Based on the surveillance data of influenza, Search Engine Index, and meteorological factors from 2011 to 2021 in Xi'an, and the different level of emergence responses for COVID-19 from 2020 to 2021, Bayesian Structural Time Series model and interrupted time series analysis were applied to quantitatively assess the impact of NPIs in sequent phases with different intensities, and to estimate the reduction of influenza infections. From 2011 to 2021, a total of 197,528 confirmed cases of influenza were reported in Xi'an, and the incidence of influenza continuously increased from 2011 to 2019, especially, in 2019-2020, when the incidence was up to 975.90 per 100,000 persons; however, it showed a sharp reduction of 97.68% in 2020-2021, and of 87.22% in 2021, comparing with 2019-2020. The highest impact on reduction of influenza was observed in the phase of strict implementation of NPIs with an inclusion probability of 0.54. The weekly influenza incidence was reduced by 95.45%, and an approximate reduction of 210,100 (95% CI: 125,100-329,500) influenza infections was found during the post-COVID-19 period. The reduction exhibited significant variations in the geographical, population, and temporal distribution. Our findings demonstrated that NPIs against COVID-19 had a long-term impact on the reduction of influenza transmission.
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Affiliation(s)
- Shuxuan Song
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, China
| | - Qian Li
- Department of Infectious Disease Control and Prevention, Xi'an Center for Disease Prevention and Control, Xi'an, China
| | - Li Shen
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
| | - Minghao Sun
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
| | - Zurong Yang
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, China
| | - Nuoya Wang
- School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China
| | - Jifeng Liu
- Department of Infectious Disease Control and Prevention, Xi'an Center for Disease Prevention and Control, Xi'an, China
| | - Kun Liu
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, China
| | - Zhongjun Shao
- Department of Epidemiology, Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment, School of Public Health, Air Force Medical University, Xi'an, China
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12
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Reynolds D, Vazquez Guillamet C, Day A, Borcherding N, Vazquez Guillamet R, Choreño-Parra JA, House SL, O'Halloran JA, Zúñiga J, Ellebedy AH, Byers DE, Mudd PA. Comprehensive Immunologic Evaluation of Bronchoalveolar Lavage Samples from Human Patients with Moderate and Severe Seasonal Influenza and Severe COVID-19. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2021; 207:1229-1238. [PMID: 34348975 PMCID: PMC8387368 DOI: 10.4049/jimmunol.2100294] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 07/01/2021] [Indexed: 12/15/2022]
Abstract
Infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) or seasonal influenza may lead to respiratory failure requiring intubation and mechanical ventilation. The pathophysiology of this respiratory failure is attributed to local immune dysregulation, but how the immune response to viral infection in the lower airways of the human lung differs between individuals with respiratory failure and those without is not well understood. We used quantitative multiparameter flow cytometry and multiplex cytokine assays to evaluate matched blood and bronchoalveolar lavage (BAL) samples from control human subjects, subjects with symptomatic seasonal influenza who did not have respiratory failure, and subjects with severe seasonal influenza or SARS-CoV-2 infection with respiratory failure. We find that severe cases are associated with an influx of nonclassical monocytes, activated T cells, and plasmablast B cells into the lower airways. Cytokine concentrations were not elevated in the lower airways of moderate influenza patients compared with controls; however, 28 of 35 measured cytokines were significantly elevated in severe influenza, severe SARS-CoV-2 infection, or both. We noted the largest elevations in IL-6, IP-10, MCP-1, and IL-8. IL-1 family cytokines and RANTES were higher in severe influenza infection than severe SARS-CoV-2 infection. Interestingly, only the concentration of IP-10-correlated between blood and BAL during severe infection. Our results demonstrate inflammatory immune dysregulation in the lower airways during severe viral pneumonia that is distinct from lower airway responses seen in human patients with symptomatic, but not severe, illness and suggest that measurement of blood IP-10 concentration may predict this unique dysregulation.
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Affiliation(s)
- Daniel Reynolds
- Division of Pulmonology and Critical Care, Department of Medicine, Washington University School of Medicine, Saint Louis, MO
| | - Cristina Vazquez Guillamet
- Division of Pulmonology and Critical Care, Department of Medicine, Washington University School of Medicine, Saint Louis, MO
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, Saint Louis, MO
| | - Aaron Day
- Department of Emergency Medicine, Washington University School of Medicine, Saint Louis, MO
| | - Nicholas Borcherding
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO
| | - Rodrigo Vazquez Guillamet
- Division of Pulmonology and Critical Care, Department of Medicine, Washington University School of Medicine, Saint Louis, MO
| | - José Alberto Choreño-Parra
- Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, México City, México
- Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México City, México
| | - Stacey L House
- Department of Emergency Medicine, Washington University School of Medicine, Saint Louis, MO
| | - Jane A O'Halloran
- Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, Saint Louis, MO
| | - Joaquín Zúñiga
- Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, México City, México
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, México City, México; and
| | - Ali H Ellebedy
- Department of Pathology and Immunology, Washington University School of Medicine, Saint Louis, MO
- Bursky Center for Human Immunology and Immunotherapy Program, Washington University School of Medicine, Saint Louis, MO
| | - Derek E Byers
- Division of Pulmonology and Critical Care, Department of Medicine, Washington University School of Medicine, Saint Louis, MO
| | - Philip A Mudd
- Department of Emergency Medicine, Washington University School of Medicine, Saint Louis, MO;
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13
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Lin X, Lin F, Liang T, Ducatez MF, Zanin M, Wong SS. Antibody Responsiveness to Influenza: What Drives It? Viruses 2021; 13:v13071400. [PMID: 34372607 PMCID: PMC8310379 DOI: 10.3390/v13071400] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 07/02/2021] [Accepted: 07/03/2021] [Indexed: 02/06/2023] Open
Abstract
The induction of a specific antibody response has long been accepted as a serological hallmark of recent infection or antigen exposure. Much of our understanding of the influenza antibody response has been derived from studying antibodies that target the hemagglutinin (HA) protein. However, growing evidence points to limitations associated with this approach. In this review, we aim to highlight the issue of antibody non-responsiveness after influenza virus infection and vaccination. We will then provide an overview of the major factors known to influence antibody responsiveness to influenza after infection and vaccination. We discuss the biological factors such as age, sex, influence of prior immunity, genetics, and some chronic infections that may affect the induction of influenza antibody responses. We also discuss the technical factors, such as assay choices, strain variations, and viral properties that may influence the sensitivity of the assays used to measure influenza antibodies. Understanding these factors will hopefully provide a more comprehensive picture of what influenza immunogenicity and protection means, which will be important in our effort to improve influenza vaccines.
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Affiliation(s)
- Xia Lin
- State Key Laboratory of Respiratory Diseases, Guangzhou Medical University, 195 Dongfengxi Rd, Guangzhou 510182, China; (X.L.); (F.L.); (T.L.); (M.Z.)
| | - Fangmei Lin
- State Key Laboratory of Respiratory Diseases, Guangzhou Medical University, 195 Dongfengxi Rd, Guangzhou 510182, China; (X.L.); (F.L.); (T.L.); (M.Z.)
| | - Tingting Liang
- State Key Laboratory of Respiratory Diseases, Guangzhou Medical University, 195 Dongfengxi Rd, Guangzhou 510182, China; (X.L.); (F.L.); (T.L.); (M.Z.)
| | | | - Mark Zanin
- State Key Laboratory of Respiratory Diseases, Guangzhou Medical University, 195 Dongfengxi Rd, Guangzhou 510182, China; (X.L.); (F.L.); (T.L.); (M.Z.)
- School of Public Health, The University of Hong Kong, Hong Kong, China
| | - Sook-San Wong
- State Key Laboratory of Respiratory Diseases, Guangzhou Medical University, 195 Dongfengxi Rd, Guangzhou 510182, China; (X.L.); (F.L.); (T.L.); (M.Z.)
- School of Public Health, The University of Hong Kong, Hong Kong, China
- Correspondence: ; Tel.: +86-178-2584-6078
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14
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Vieira MC, Donato CM, Arevalo P, Rimmelzwaan GF, Wood T, Lopez L, Huang QS, Dhanasekaran V, Koelle K, Cobey S. Lineage-specific protection and immune imprinting shape the age distributions of influenza B cases. Nat Commun 2021; 12:4313. [PMID: 34262041 PMCID: PMC8280188 DOI: 10.1038/s41467-021-24566-y] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 06/22/2021] [Indexed: 02/06/2023] Open
Abstract
How a history of influenza virus infections contributes to protection is not fully understood, but such protection might explain the contrasting age distributions of cases of the two lineages of influenza B, B/Victoria and B/Yamagata. Fitting a statistical model to those distributions using surveillance data from New Zealand, we found they could be explained by historical changes in lineage frequencies combined with cross-protection between strains of the same lineage. We found additional protection against B/Yamagata in people for whom it was their first influenza B infection, similar to the immune imprinting observed in influenza A. While the data were not informative about B/Victoria imprinting, B/Yamagata imprinting could explain the fewer B/Yamagata than B/Victoria cases in cohorts born in the 1990s and the bimodal age distribution of B/Yamagata cases. Longitudinal studies can test if these forms of protection inferred from historical data extend to more recent strains and other populations.
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Affiliation(s)
- Marcos C Vieira
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA.
| | - Celeste M Donato
- Enteric Diseases Group, Murdoch Children's Research Institute, Parkville, VIC, Australia
- Department of Paediatrics, The University of Melbourne, Parkville, VIC, Australia
| | - Philip Arevalo
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA
| | - Guus F Rimmelzwaan
- Research Center for Emerging Infections and Zoonoses, University of Veterinary Medicine Hannover, Hannover, Germany
| | - Timothy Wood
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Liza Lopez
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Q Sue Huang
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Vijaykrishna Dhanasekaran
- Department of Microbiology, Biomedicine Discovery Institute, Monash University, Melbourne, VIC, Australia
| | - Katia Koelle
- Department of Biology, Emory University, Atlanta, GA, USA
| | - Sarah Cobey
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA.
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15
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Cohen C, Kleynhans J, Moyes J, McMorrow ML, Treurnicht FK, Hellferscee O, Mathunjwa A, von Gottberg A, Wolter N, Martinson NA, Kahn K, Lebina L, Mothlaoleng K, Wafawanaka F, Gómez-Olivé FX, Mkhencele T, Mathee A, Piketh S, Language B, Tempia S. Asymptomatic transmission and high community burden of seasonal influenza in an urban and a rural community in South Africa, 2017-18 (PHIRST): a population cohort study. Lancet Glob Health 2021; 9:e863-e874. [PMID: 34019838 PMCID: PMC8262603 DOI: 10.1016/s2214-109x(21)00141-8] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 02/23/2021] [Accepted: 02/26/2021] [Indexed: 12/17/2022]
Abstract
BACKGROUND Data on influenza community burden and transmission are important to plan interventions especially in resource-limited settings. However, data are limited, particularly from low-income and middle-income countries. We aimed to evaluate the community burden and transmission of influenza in a rural and an urban setting in South Africa. METHODS In this prospective cohort study approximately 50 households were selected sequentially from both a rural setting (Agincourt, Mpumalanga Province, South Africa; with a health and sociodemographic surveillance system) and an urban setting (Klerksdorp, Northwest Province, South Africa; using global positioning system data), enrolled, and followed up for 10 months in 2017 and 2018. Different households were enrolled in each year. Households of more than two individuals in which 80% or more of the occupants agreed to participate were included in the study. Nasopharyngeal swabs were collected twice per week from participating household members irrespective of symptoms and tested for influenza using real-time RT-PCR. The primary outcome was the incidence of influenza infection, defined as the number of real-time RT-PCR-positive episodes divided by the person-time under observation. Household cumulative infection risk (HCIR) was defined as the number of subsequent infections within a household following influenza introduction. FINDINGS 81 430 nasopharyngeal samples were collected from 1116 participants in 225 households (follow-up rate 88%). 917 (1%) tested positive for influenza; 178 (79%) of 225 households had one or more influenza-positive individual. The incidence of influenza infection was 43·6 (95% CI 39·8-47·7) per 100 person-seasons. 69 (17%) of 408 individuals who had one influenza infection had a repeat influenza infection during the same season. The incidence (67·4 per 100 person-seasons) and proportion with repeat infections (22 [23%] of 97 children) were highest in children younger than 5 years and decreased with increasing age (p<0·0001). Overall, 268 (56%) of 478 infections were symptomatic and 66 (14%) of 478 infections were medically attended. The overall HCIR was 10% (109 of 1088 exposed household members infected [95% CI 9-13%). Transmission (HCIR) from index cases was highest in participants aged 1-4 years (16%; 40 of 252 exposed household members) and individuals with two or more symptoms (17%; 68 of 396 exposed household members). Individuals with asymptomatic influenza transmitted infection to 29 (6%) of 509 household contacts. HIV infection, affecting 167 (16%) of 1075 individuals, was not associated with increased incidence or HCIR. INTERPRETATION Approximately half of influenza infections were symptomatic, with asymptomatic individuals transmitting influenza to 6% of household contacts. This suggests that strategies, such as quarantine and isolation, might be ineffective to control influenza. Vaccination of children, with the aim of reducing influenza transmission might be effective in African settings given the young population and high influenza burden. FUNDING US Centers for Disease Control and Prevention.
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Affiliation(s)
- Cheryl Cohen
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Public Health, University of the Witwatersrand, Johannesburg, South Africa.
| | - Jackie Kleynhans
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Jocelyn Moyes
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Meredith L McMorrow
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA; Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa
| | - Florette K Treurnicht
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Orienka Hellferscee
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Pathology, University of the Witwatersrand, Johannesburg, South Africa
| | - Azwifarwi Mathunjwa
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Anne von Gottberg
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Pathology, University of the Witwatersrand, Johannesburg, South Africa
| | - Nicole Wolter
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa; School of Pathology, University of the Witwatersrand, Johannesburg, South Africa
| | - Neil A Martinson
- Perinatal HIV Research Unit, South African Medical Research Council, Soweto Matlosana Collaborating Centre for HIV/AIDS and Tuberculosis, University of the Witwatersrand, Johannesburg, South Africa; Department of Science and Technology, National Research Foundations, Centre of Excellence for Biomedical Tuberculosis Research, University of the Witwatersrand, Johannesburg, South Africa; Center for Tuberculosis Research, Johns Hopkins University, Baltimore, MD, USA
| | - Kathleen Kahn
- South African Medical Research Council Rural Public Health and Health Transitions Research Unit (Agincourt), University of the Witwatersrand, Johannesburg, South Africa
| | - Limakatso Lebina
- Perinatal HIV Research Unit, South African Medical Research Council, Soweto Matlosana Collaborating Centre for HIV/AIDS and Tuberculosis, University of the Witwatersrand, Johannesburg, South Africa
| | - Katlego Mothlaoleng
- Perinatal HIV Research Unit, South African Medical Research Council, Soweto Matlosana Collaborating Centre for HIV/AIDS and Tuberculosis, University of the Witwatersrand, Johannesburg, South Africa
| | - Floidy Wafawanaka
- South African Medical Research Council Rural Public Health and Health Transitions Research Unit (Agincourt), University of the Witwatersrand, Johannesburg, South Africa
| | - Francesc Xavier Gómez-Olivé
- South African Medical Research Council Rural Public Health and Health Transitions Research Unit (Agincourt), University of the Witwatersrand, Johannesburg, South Africa
| | - Thulisa Mkhencele
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Angela Mathee
- Environment and Health Research Unit, South African Medical Research Council, Johannesburg, South Africa
| | - Stuart Piketh
- Unit for Environmental Science and Management, Climatology Research Group, North-West University, Potchefstroom, South Africa
| | - Brigitte Language
- Unit for Environmental Science and Management, Climatology Research Group, North-West University, Potchefstroom, South Africa
| | - Stefano Tempia
- School of Public Health, University of the Witwatersrand, Johannesburg, South Africa; Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA; Influenza Program, Centers for Disease Control and Prevention, Pretoria, South Africa; MassGenics, Duluth, GA, USA
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16
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Leung VKY, Fox A, Carolan LA, Aban M, Laurie KL, Druce J, Deng YM, Slavin MA, Marshall C, Sullivan SG. Impact of prior vaccination on antibody response and influenza-like illness among Australian healthcare workers after influenza vaccination in 2016. Vaccine 2021; 39:3270-3278. [PMID: 33985853 DOI: 10.1016/j.vaccine.2021.04.036] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 04/15/2021] [Accepted: 04/19/2021] [Indexed: 12/19/2022]
Abstract
BACKGROUND Epidemiological studies suggest that influenza vaccine effectiveness decreases with repeated administration. We examined antibody responses to influenza vaccination among healthcare workers (HCWs) by prior vaccination history and determined the incidence of influenza infection. METHODS HCWs were vaccinated with the 2016 Southern Hemisphere quadrivalent influenza vaccine. Serum samples were collected pre-vaccination, 21-28 days and 7 months post-vaccination. Influenza antibody titres were measured at each time-point using the haemagglutination inhibition (HI) assay. Immunogenicity was compared by prior vaccination history. RESULTS A total of 157 HCWs completed the study. The majority were frequently vaccinated, with only 5 reporting no prior vaccinations since 2011. Rises in titres for all vaccine strains among vaccine-naïve HCWs were significantly greater than rises observed for HCWs who received between 1 and 5 prior vaccinations (p < 0.001, respectively). Post-vaccination GMTs against influenza A but not B strains decreased as the number of prior vaccinations increased from 1 to 5. There was a significant decline in GMTs post-season for both B lineages. Sixty five (41%) HCWs reported at least one influenza-like illness episode, with 6 (4%) identified as influenza positive. CONCLUSIONS Varying serological responses to influenza vaccination were observed among HCWs by prior vaccination history, with vaccine-naïve HCWs demonstrating greater post-vaccination responses against A(H3N2).
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Affiliation(s)
- Vivian K Y Leung
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Annette Fox
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia; Department of Microbiology and Immunology, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia; Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Louise A Carolan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Malet Aban
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Karen L Laurie
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Julian Druce
- Victorian Infectious Disease Reference Laboratory, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Yi-Mo Deng
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Monica A Slavin
- Victorian Infectious Disease Service, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia; Department of Infectious Diseases, Peter MacCallum Cancer Centre, Melbourne, Australia; National Centre for Infections in Cancer, Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Australia
| | - Caroline Marshall
- Victorian Infectious Disease Service, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia; Infection Prevention and Surveillance Service, Royal Melbourne Hospital, Melbourne, Australia; Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Sheena G Sullivan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia; Fielding School of Public Health, University of California, Los Angeles, USA; Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Australia.
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17
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Mettelman RC, Thomas PG. Human Susceptibility to Influenza Infection and Severe Disease. Cold Spring Harb Perspect Med 2021; 11:cshperspect.a038711. [PMID: 31964647 PMCID: PMC8091954 DOI: 10.1101/cshperspect.a038711] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Influenza viruses are a persistent threat to global human health. Increased susceptibility to infection and the risk factors associated with progression to severe influenza-related disease are determined by a multitude of viral, host, and environmental conditions. Decades of epidemiologic research have broadly defined high-risk groups, while new genomic association studies have identified specific host factors impacting an individual's response to influenza. Here, we review and highlight both human susceptibility to influenza infection and the conditions that lead to severe influenza disease.
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Affiliation(s)
- Robert C Mettelman
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Paul G Thomas
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
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18
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Tokars JI, Patel MM, Foppa IM, Reed C, Fry AM, Ferdinands JM. Waning of Measured Influenza Vaccine Effectiveness Over Time: The Potential Contribution of Leaky Vaccine Effect. Clin Infect Dis 2021; 71:e633-e641. [PMID: 32227109 DOI: 10.1093/cid/ciaa340] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Accepted: 03/26/2020] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Several observational studies have shown decreases in measured influenza vaccine effectiveness (mVE) during influenza seasons. One study found decreases of 6-11%/month during the 2011-2012 to 2014-2015 seasons. These findings could indicate waning immunity but could also occur if vaccine effectiveness is stable and vaccine provides partial protection in all vaccinees ("leaky") rather than complete protection in a subset of vaccinees. Since it is unknown whether influenza vaccine is leaky, we simulated the 2011-2012 to 2014-2015 influenza seasons to estimate the potential contribution of leaky vaccine effect to the observed decline in mVE. METHODS We used available data to estimate daily numbers of vaccinations and infections with A/H1N1, A/H3N2, and B viruses. We assumed that vaccine effect was leaky, calculated mVE as 1 minus the Mantel-Haenszel relative risk of vaccine on incident cases, and determined the mean mVE change per 30 days since vaccination. Because change in mVE was highly dependent on infection rates, we performed simulations using low (15%) and high (31%) total (including symptomatic and asymptomatic) seasonal infection rates. RESULTS For the low infection rate, decreases (absolute) in mVE per 30 days after vaccination were 2% for A/H1N1 and 1% for A/H3N2and B viruses. For the high infection rate, decreases were 5% for A/H1N1, 4% for A/H3, and 3% for B viruses. CONCLUSIONS The leaky vaccine bias could account for some, but probably not all, of the observed intraseasonal decreases in mVE. These results underscore the need for strategies to deal with intraseasonal vaccine effectiveness decline.
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Affiliation(s)
- Jerome I Tokars
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Manish M Patel
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Ivo M Foppa
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.,Battelle, Atlanta, Georgia, USA
| | - Carrie Reed
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Alicia M Fry
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jill M Ferdinands
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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19
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Wong SS, Oshansky CM, Guo XZJ, Ralston J, Wood T, Reynolds GE, Seeds R, Jelley L, Waite B, Jeevan T, Zanin M, Widdowson MA, Huang QS, Thomas PG, Webby RJ. Activated CD4 + T cells and CD14 hiCD16 + monocytes correlate with antibody response following influenza virus infection in humans. CELL REPORTS MEDICINE 2021; 2:100237. [PMID: 33948570 PMCID: PMC8080109 DOI: 10.1016/j.xcrm.2021.100237] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 01/25/2021] [Accepted: 03/10/2021] [Indexed: 12/19/2022]
Abstract
The failure to mount an antibody response following viral infection or seroconversion failure is a largely underappreciated and poorly understood phenomenon. Here, we identified immunologic markers associated with robust antibody responses after influenza virus infection in two independent human cohorts, SHIVERS and FLU09, based in Auckland, New Zealand and Memphis, Tennessee, USA, respectively. In the SHIVERS cohort, seroconversion significantly associates with (1) hospitalization, (2) greater numbers of proliferating, activated CD4+ T cells, but not CD8+ T cells, in the periphery during the acute phase of illness, and (3) fewer inflammatory monocytes (CD14hiCD16+) by convalescence. In the FLU09 cohort, fewer CD14hiCD16+ monocytes during early illness in the nasal mucosa were also associated with the generation of influenza-specific mucosal immunoglobulin A (IgA) and IgG antibodies. Our study demonstrates that seroconversion failure after infection is a definable immunological phenomenon, associated with quantifiable cellular markers that can be used to improve diagnostics, vaccine efficacy, and epidemiologic efforts. Post-infection seroconversion is associated with severity of influenza virus infection Seroconverters have early proliferation and activation of CD4+ T cells CD8+ T cells are unaffected CD14hiCD16+ monocytes in the blood and nasal mucosa is associated with antibody response
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Affiliation(s)
- Sook-San Wong
- State Key Laboratory for Respiratory Diseases, Guangzhou Medical University, 151 Dongfengxi Road, Yuexiu District, Guangzhou 510000, China.,Department of Infectious Diseases, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.,School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong SAR, China
| | - Christine M Oshansky
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.,Biomedical Advanced Research and Development Authority (BARDA), Office of the Assistant Secretary for Preparedness and Response (ASPR), US Department of Health and Human Services (DHHS), 200 C Street, SW, Washington, DC 20201, USA
| | - Xi-Zhi J Guo
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.,Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN 38163, USA.,Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02115, USA
| | - Jacqui Ralston
- Institute for Environmental Science and Research, NCBID Wallaceville, 66 Ward Street, Upper Hutt 5018, New Zealand
| | - Timothy Wood
- Institute for Environmental Science and Research, NCBID Wallaceville, 66 Ward Street, Upper Hutt 5018, New Zealand
| | - Gary E Reynolds
- Immunisation Advisory Centre, University of Auckland, Auckland, New Zealand
| | - Ruth Seeds
- Institute for Environmental Science and Research, NCBID Wallaceville, 66 Ward Street, Upper Hutt 5018, New Zealand.,Minsitry for Primary Industries, 66 Ward Street, Upper Hutt 5140, New Zealand
| | - Lauren Jelley
- Institute for Environmental Science and Research, NCBID Wallaceville, 66 Ward Street, Upper Hutt 5018, New Zealand
| | - Ben Waite
- Institute for Environmental Science and Research, NCBID Wallaceville, 66 Ward Street, Upper Hutt 5018, New Zealand
| | - Trushar Jeevan
- Department of Infectious Diseases, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Mark Zanin
- State Key Laboratory for Respiratory Diseases, Guangzhou Medical University, 151 Dongfengxi Road, Yuexiu District, Guangzhou 510000, China.,Department of Infectious Diseases, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.,School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong SAR, China
| | - Marc-Alain Widdowson
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA 30333, USA.,Institute of Tropical Medicine (ITM), Nationalestraat 155, 2000 Antwerp, Belgium
| | - Q Sue Huang
- Institute for Environmental Science and Research, NCBID Wallaceville, 66 Ward Street, Upper Hutt 5018, New Zealand
| | - Paul G Thomas
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA.,Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Richard J Webby
- Department of Infectious Diseases, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
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20
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Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand. Nat Commun 2021; 12:1001. [PMID: 33579926 PMCID: PMC7881137 DOI: 10.1038/s41467-021-21157-9] [Citation(s) in RCA: 240] [Impact Index Per Article: 80.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Accepted: 01/13/2021] [Indexed: 02/08/2023] Open
Abstract
Stringent nonpharmaceutical interventions (NPIs) such as lockdowns and border closures are not currently recommended for pandemic influenza control. New Zealand used these NPIs to eliminate coronavirus disease 2019 during its first wave. Using multiple surveillance systems, we observed a parallel and unprecedented reduction of influenza and other respiratory viral infections in 2020. This finding supports the use of these NPIs for controlling pandemic influenza and other severe respiratory viral threats. New Zealand has been relatively successful in controlling COVID-19 due to implementation of strict non-pharmaceutical interventions. Here, the authors demonstrate a striking decline in reports of influenza and other non-influenza respiratory pathogens over winter months in which the interventions have been in place.
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21
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Huang QS, Wood T, Jelley L, Jennings T, Jefferies S, Daniells K, Nesdale A, Dowell T, Turner N, Campbell-Stokes P, Balm M, Dobinson HC, Grant CC, James S, Aminisani N, Ralston J, Gunn W, Bocacao J, Danielewicz J, Moncrieff T, McNeill A, Lopez L, Waite B, Kiedrzynski T, Schrader H, Gray R, Cook K, Currin D, Engelbrecht C, Tapurau W, Emmerton L, Martin M, Baker MG, Taylor S, Trenholme A, Wong C, Lawrence S, McArthur C, Stanley A, Roberts S, Ranama F, Bennett J, Mansell C, Dilcher M, Werno A, Grant J, van der Linden A, Youngblood B, Thomas PG, Webby RJ. Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2020:2020.11.11.20228692. [PMID: 33200149 PMCID: PMC7668762 DOI: 10.1101/2020.11.11.20228692] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Stringent nonpharmaceutical interventions (NPIs) such as lockdowns and border closures are not currently recommended for pandemic influenza control. New Zealand used these NPIs to eliminate coronavirus disease 2019 during its first wave. Using multiple surveillance systems, we observed a parallel and unprecedented reduction of influenza and other respiratory viral infections in 2020. This finding supports the use of these NPIs for controlling pandemic influenza and other severe respiratory viral threats.
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Affiliation(s)
- Q Sue Huang
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Tim Wood
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Lauren Jelley
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Tineke Jennings
- Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand
| | - Sarah Jefferies
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Karen Daniells
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Annette Nesdale
- Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand
| | - Tony Dowell
- University of Otago, School of Medicine in Wellington, Wellington, New Zealand
| | | | | | - Michelle Balm
- Capital Coast District Health Board, Wellington, New Zealand
| | | | | | - Shelley James
- Capital Coast District Health Board, Wellington, New Zealand
| | - Nayyereh Aminisani
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Jacqui Ralston
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Wendy Gunn
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Judy Bocacao
- Institute of Environmental Science and Research, Wellington, New Zealand
| | | | - Tessa Moncrieff
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Andrea McNeill
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Liza Lopez
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Ben Waite
- Institute of Environmental Science and Research, Wellington, New Zealand
| | | | - Hannah Schrader
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Rebekah Gray
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Kayla Cook
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Danielle Currin
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Chaune Engelbrecht
- Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand
| | - Whitney Tapurau
- Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand
| | - Leigh Emmerton
- Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand
| | - Maxine Martin
- Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand
| | - Michael G Baker
- University of Otago, School of Medicine in Wellington, Wellington, New Zealand
| | - Susan Taylor
- Counties Manukau District Health Board, Auckland, New Zealand
| | | | - Conroy Wong
- Counties Manukau District Health Board, Auckland, New Zealand
| | | | | | | | - Sally Roberts
- Auckland District Health Board, Auckland, New Zealand
| | | | - Jenny Bennett
- Waikato District Health Board, Hamilton, New Zealand
| | - Chris Mansell
- Waikato District Health Board, Hamilton, New Zealand
| | - Meik Dilcher
- Canterbury District Health Board, Christchurch, New Zealand
| | - Anja Werno
- Canterbury District Health Board, Christchurch, New Zealand
| | | | | | - Ben Youngblood
- WHO Collaborating Centre, St Jude Children's Research Hospital, Memphis, USA
| | - Paul G Thomas
- WHO Collaborating Centre, St Jude Children's Research Hospital, Memphis, USA
| | - Richard J Webby
- WHO Collaborating Centre, St Jude Children's Research Hospital, Memphis, USA
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22
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Affiliation(s)
- Michael G Baker
- University of Otago, Wellington, 23 Mein Street, Newtown, Wellington 6021, New Zealand
| | - Nick Wilson
- University of Otago, Wellington, 23 Mein Street, Newtown, Wellington 6021, New Zealand
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23
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Araujo KLRD, Aquino ÉCD, Silva LLSD, Ternes YMF. Factors associated with Severe Acute Respiratory Syndrome in a Brazilian central region. CIENCIA & SAUDE COLETIVA 2020; 25:4121-4130. [PMID: 33027348 DOI: 10.1590/1413-812320202510.2.26802020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2020] [Accepted: 08/10/2020] [Indexed: 11/22/2022] Open
Abstract
Severe Acute Respiratory Infection (SARI) is a notifiable syndrome that must be investigated. This study aimed to analyze the epidemiological profile and factors associated with SARI-related hospitalization and deaths reported in Goiás. Retrospective cohort study, with data from the investigation files of the Notifiable Diseases Information System's Influenza Web. Multivariate analysis methods were employed to verify the association between exposure variables with the outcomes of ICU admission and death. A total of 4,832 SARI cases were reported in Goiás from 2013 to 2018. The primary etiological diagnosis was Influenza A (22.3%) with the predominant subtype A (H1N1pdm09), followed by the Respiratory Syncytial Virus. A total of 34.6% of the patients required ICU admission, and 19% died. A longer time to start treatment with antivirals was associated with a higher likelihood to have an ICU admission, while a previous non-vaccination against Influenza, longer time to start treatment, and older age were associated with a higher likelihood to suffer death. The study showed a high frequency of respiratory diseases caused by the Influenza virus in Goiás and that the severity of the syndrome, characterized by ICU admission and deaths, is associated with the start of antiviral treatment vaccine status, and patient's age.
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Affiliation(s)
- Kamilla Lelis Rodrigues de Araujo
- Programa de Pós-Graduação em Assistência e Avaliação em Saúde, Universidade Federal de Goiás (UFG). Av. Rúda Quadra 41A, Lote 10, Vila Brasília. 74905-760 Aparecida de Goiânia GO Brasil.
| | - Érika Carvalho de Aquino
- Instituto de Patologia Tropical e Saúde Pública, Departamento de Saúde Coletiva, UFG. Goiânia GO Brasil
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24
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Turner JS, Lei T, Schmitz AJ, Day A, Choreño-Parra JA, Jiménez-Alvarez L, Cruz-Lagunas A, House SL, Zúñiga J, Ellebedy AH, Mudd PA. Impaired Cellular Immune Responses During the First Week of Severe Acute Influenza Infection. J Infect Dis 2020; 222:1235-1244. [PMID: 32369589 PMCID: PMC7768688 DOI: 10.1093/infdis/jiaa226] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 04/27/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Cellular immune responses are not well characterized during the initial days of acute symptomatic influenza infection. METHODS We developed a prospective cohort of human subjects with confirmed influenza illness of varying severity who presented within a week after symptom onset. We characterized lymphocyte and monocyte populations as well as antigen-specific CD8+ T-cell and B-cell responses from peripheral blood mononuclear cells using flow cytometry and enzyme-linked immunospot assays. RESULTS We recruited 68 influenza-infected individuals on average 3.5 days after the onset of symptoms. Three patients required mechanical ventilation. Influenza-specific CD8+ T-cell responses expanded before the appearance of plasmablast B cells. However, the influenza-specific CD8+ T-cell response was lower in infected subjects than responses seen in uninfected control subjects. Circulating populations of inflammatory monocytes were increased in most subjects compared with healthy controls. Inflammatory monocytes were significantly reduced in the 3 subjects requiring mechanical ventilation. Inflammatory monocytes were also reduced in a separate validation cohort of mechanically ventilated patients. CONCLUSIONS Antigen-specific CD8+ T cells respond early during acute influenza infection at magnitudes that are lower than responses seen in uninfected individuals. Circulating inflammatory monocytes increase during acute illness and low absolute numbers are associated with very severe disease.
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Affiliation(s)
- Jackson S Turner
- Department of Pathology and Immunology, Washington University School of Medicine in St Louis, St Louis, Missouri, USA
| | - Tingting Lei
- Department of Pathology and Immunology, Washington University School of Medicine in St Louis, St Louis, Missouri, USA
| | - Aaron J Schmitz
- Department of Pathology and Immunology, Washington University School of Medicine in St Louis, St Louis, Missouri, USA
| | - Aaron Day
- Department of Emergency Medicine, Washington University School of Medicine in St Louis, St Louis, Missouri, USA
| | - José Alberto Choreño-Parra
- Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City, Mexico
- Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, Mexico City, Mexico
| | - Luis Jiménez-Alvarez
- Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City, Mexico
| | - Alfredo Cruz-Lagunas
- Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City, Mexico
| | - Stacey L House
- Department of Emergency Medicine, Washington University School of Medicine in St Louis, St Louis, Missouri, USA
| | - Joaquín Zúñiga
- Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City, Mexico
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Mexico City, Mexico
| | - Ali H Ellebedy
- Department of Pathology and Immunology, Washington University School of Medicine in St Louis, St Louis, Missouri, USA
| | - Philip A Mudd
- Department of Emergency Medicine, Washington University School of Medicine in St Louis, St Louis, Missouri, USA
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25
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Arevalo P, McLean HQ, Belongia EA, Cobey S. Earliest infections predict the age distribution of seasonal influenza A cases. eLife 2020; 9:e50060. [PMID: 32633233 PMCID: PMC7367686 DOI: 10.7554/elife.50060] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2019] [Accepted: 06/29/2020] [Indexed: 12/02/2022] Open
Abstract
Seasonal variation in the age distribution of influenza A cases suggests that factors other than age shape susceptibility to medically attended infection. We ask whether these differences can be partly explained by protection conferred by childhood influenza infection, which has lasting impacts on immune responses to influenza and protection against new influenza A subtypes (phenomena known as original antigenic sin and immune imprinting). Fitting a statistical model to data from studies of influenza vaccine effectiveness (VE), we find that primary infection appears to reduce the risk of medically attended infection with that subtype throughout life. This effect is stronger for H1N1 compared to H3N2. Additionally, we find evidence that VE varies with both age and birth year, suggesting that VE is sensitive to early exposures. Our findings may improve estimates of age-specific risk and VE in similarly vaccinated populations and thus improve forecasting and vaccination strategies to combat seasonal influenza.
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Affiliation(s)
- Philip Arevalo
- Department of Ecology and Evolutionary Biology, University of ChicagoChicagoUnited States
| | - Huong Q McLean
- Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research InstituteMarshfieldUnited States
| | - Edward A Belongia
- Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research InstituteMarshfieldUnited States
| | - Sarah Cobey
- Department of Ecology and Evolutionary Biology, University of ChicagoChicagoUnited States
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26
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Wraith S, Nachbagauer R, Balmaseda A, Stadlbauer D, Ojeda S, Rajabhathor A, Lopez R, Guglia AF, Sanchez N, Amanat F, Gresh L, Kuan G, Krammer F, Gordon A. Antibody responses to influenza A(H1N1)pdm infection. Vaccine 2020; 38:4221-4225. [PMID: 32389495 PMCID: PMC7707244 DOI: 10.1016/j.vaccine.2020.04.069] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 03/28/2020] [Accepted: 04/26/2020] [Indexed: 11/20/2022]
Abstract
We investigated humoral immune response to influenza A(H1N1)pdm infection and found 32 (22%) of the infected individuals identified by PCR failed to produce a ≥ 4-fold hemagglutinin inhibition assay (HAI) response; a subset of 18 (56%) produced an alternate antibody response (against full-length HA, HA stalk, or neuraminidase). These individuals had lower pre-existing HAI antibody titers and showed a pattern of milder illness. An additional subset of 14 (44%) did not produce an alternate antibody response, had higher pre-existing antibody titers against full-length & stalk HA, and were less sick. These findings demonstrate that some individuals mount an alternate antibody response to influenza infection. In order to design more broadly protective influenza vaccines it may be useful to target these alternate sites. These findings support that there are influenza cases currently being missed by solely implementing HAI assays, resulting in an underestimation of the global burden of influenza infection.
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Affiliation(s)
- Steph Wraith
- Department of Epidemiology, School of Public Health, University of Michigan, USA
| | - Raffael Nachbagauer
- Centers of Excellence for Influenza Research and Surveillance (CEIRS), USA; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Research on Influenza Pathogenesis (CRIP), New York, NY, USA
| | - Angel Balmaseda
- Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua; Sustainable Sciences Institute, Managua, Nicaragua
| | - Daniel Stadlbauer
- Centers of Excellence for Influenza Research and Surveillance (CEIRS), USA; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Research on Influenza Pathogenesis (CRIP), New York, NY, USA
| | - Sergio Ojeda
- Sustainable Sciences Institute, Managua, Nicaragua; Centro de Salud Sócrates Flores Vivas, Ministry of Health, Managua, Nicaragua
| | - Arvind Rajabhathor
- Centers of Excellence for Influenza Research and Surveillance (CEIRS), USA; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Research on Influenza Pathogenesis (CRIP), New York, NY, USA
| | - Roger Lopez
- Laboratorio Nacional de Virología, Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua; Sustainable Sciences Institute, Managua, Nicaragua
| | - Andrea F Guglia
- Centers of Excellence for Influenza Research and Surveillance (CEIRS), USA; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Research on Influenza Pathogenesis (CRIP), New York, NY, USA
| | - Nery Sanchez
- Sustainable Sciences Institute, Managua, Nicaragua; Centro de Salud Sócrates Flores Vivas, Ministry of Health, Managua, Nicaragua
| | - Fatima Amanat
- Centers of Excellence for Influenza Research and Surveillance (CEIRS), USA; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Research on Influenza Pathogenesis (CRIP), New York, NY, USA
| | - Lionel Gresh
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Guillermina Kuan
- Sustainable Sciences Institute, Managua, Nicaragua; Centro de Salud Sócrates Flores Vivas, Ministry of Health, Managua, Nicaragua
| | - Florian Krammer
- Centers of Excellence for Influenza Research and Surveillance (CEIRS), USA; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Center for Research on Influenza Pathogenesis (CRIP), New York, NY, USA.
| | - Aubree Gordon
- Department of Epidemiology, School of Public Health, University of Michigan, USA; St. Jude Center of Excellence for Influenza Research and Surveillance, Memphis, TN, USA; Centers of Excellence for Influenza Research and Surveillance (CEIRS), USA.
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27
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Yang W, Lau EHY, Cowling BJ. Dynamic interactions of influenza viruses in Hong Kong during 1998-2018. PLoS Comput Biol 2020; 16:e1007989. [PMID: 32542015 PMCID: PMC7316359 DOI: 10.1371/journal.pcbi.1007989] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 06/25/2020] [Accepted: 05/27/2020] [Indexed: 11/19/2022] Open
Abstract
Influenza epidemics cause substantial morbidity and mortality every year worldwide. Currently, two influenza A subtypes, A(H1N1) and A(H3N2), and type B viruses co-circulate in humans and infection with one type/subtype could provide cross-protection against the others. However, it remains unclear how such ecologic competition via cross-immunity and antigenic mutations that allow immune escape impact influenza epidemic dynamics at the population level. Here we develop a comprehensive model-inference system and apply it to study the evolutionary and epidemiological dynamics of the three influenza types/subtypes in Hong Kong, a city of global public health significance for influenza epidemic and pandemic control. Utilizing long-term influenza surveillance data since 1998, we are able to estimate the strength of cross-immunity between each virus-pairs, the timing and frequency of punctuated changes in population immunity in response to antigenic mutations in influenza viruses, and key epidemiological parameters over the last 20 years including the 2009 pandemic. We find evidence of cross-immunity in all types/subtypes, with strongest cross-immunity from A(H1N1) against A(H3N2). Our results also suggest that A(H3N2) may undergo antigenic mutations in both summers and winters and thus monitoring the virus in both seasons may be important for vaccine development. Overall, our study reveals intricate epidemiological interactions and underscores the importance of simultaneous monitoring of population immunity, incidence rates, and viral genetic and antigenic changes.
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Affiliation(s)
- Wan Yang
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, United States of America
| | - Eric H. Y. Lau
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, the University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Benjamin J. Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, the University of Hong Kong, Hong Kong Special Administrative Region, China
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28
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Hay JA, Minter A, Ainslie KEC, Lessler J, Yang B, Cummings DAT, Kucharski AJ, Riley S. An open source tool to infer epidemiological and immunological dynamics from serological data: serosolver. PLoS Comput Biol 2020; 16:e1007840. [PMID: 32365062 PMCID: PMC7241836 DOI: 10.1371/journal.pcbi.1007840] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 05/21/2020] [Accepted: 04/01/2020] [Indexed: 11/19/2022] Open
Abstract
We present a flexible, open source R package designed to obtain biological and epidemiological insights from serological datasets. Characterising past exposures for multi-strain pathogens poses a specific statistical challenge: observed antibody responses measured in serological assays depend on multiple unobserved prior infections that produce cross-reactive antibody responses. We provide a general modelling framework to jointly infer infection histories and describe immune responses generated by these infections using antibody titres against current and historical strains. We do this by linking latent infection dynamics with a mechanistic model of antibody kinetics that generates expected antibody titres over time. Our aim is to provide a flexible package to identify infection histories that can be applied to a range of pathogens. We present two case studies to illustrate how our model can infer key immunological parameters, such as antibody titre boosting, waning and cross-reaction, as well as latent epidemiological processes such as attack rates and age-stratified infection risk.
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Affiliation(s)
- James A. Hay
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Amanda Minter
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Kylie E. C. Ainslie
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Justin Lessler
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Bingyi Yang
- Department of Biology, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Derek A. T. Cummings
- Department of Biology, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Adam J. Kucharski
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Steven Riley
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
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29
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Buckrell S, Coleman BL, McNeil SA, Katz K, Muller MP, Simor A, Loeb M, Powis J, Kuster SP, Di Bella JM, Coleman KKL, Drews SJ, Kohler P, McGeer A. Sources of viral respiratory infections in Canadian acute care hospital healthcare personnel. J Hosp Infect 2020; 104:513-521. [PMID: 31954763 PMCID: PMC7172118 DOI: 10.1016/j.jhin.2020.01.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 01/09/2020] [Indexed: 12/17/2022]
Abstract
BACKGROUND Viral respiratory illnesses are common causes of outbreaks and can be fatal to some patients. AIM To investigate the association between laboratory-confirmed viral respiratory infections and potential sources of exposure during the previous 7 days. METHODS In this nested case-control analysis, healthcare personnel from nine Canadian hospitals who developed acute respiratory illnesses during the winters of 2010/11-2013/14 submitted swabs that were tested for viral pathogens. Associated illness diaries and the weekly diaries of non-ill participants provided information on contact with people displaying symptoms of acute respiratory illness in the previous week. Conditional logistic regression assessed the association between cases, who were matched by study week and site with controls with no respiratory symptoms. FINDINGS There were 814 laboratory-confirmed viral respiratory illnesses. The adjusted odds ratio (aOR) of a viral illness was higher for healthcare personnel reporting exposures to ill household members [7.0, 95% confidence interval (CI) 5.4-9.1], co-workers (3.4, 95% CI 2.4-4.7) or other social contacts (5.1, 95% CI 3.6-7.1). Exposures to patients with respiratory illness were not associated with infection (aOR 0.9, 95% CI 0.7-1.2); however, healthcare personnel with direct patient contact did have higher odds (aOR 1.3, 95% CI 1.1-1.6). The aORs for exposure and for direct patient contact were similar for illnesses caused by influenza. CONCLUSION Community and co-worker contacts are important sources of viral respiratory illness in healthcare personnel, while exposure to patients with recognized respiratory infections is not associated. The comparatively low risk associated with direct patient contact may reflect transmission related to asymptomatic patients or unrecognized infections.
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Affiliation(s)
- S Buckrell
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - B L Coleman
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada; Sinai Health System, Toronto, ON, Canada.
| | - S A McNeil
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre, and Nova Scotia Health Authority, Halifax, NS, Canada
| | - K Katz
- North York General Hospital and Sunnybrook Health Sciences Centre, Toronto, ON, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - M P Muller
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada; Unity Health, Toronto, ON, Canada
| | - A Simor
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada; Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - M Loeb
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - J Powis
- Toronto East Health Network, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - S P Kuster
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital and University of Zurich, Zürich, Switzerland
| | | | - K K L Coleman
- Sinai Health System, Toronto, ON, Canada; Parkwood Institute, London Health Sciences Centre, London, ON, Canada
| | - S J Drews
- Canadian Blood Services, Edmonton, AB, Canada; Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB, Canada
| | - P Kohler
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital, St. Gallen, Switzerland
| | - A McGeer
- Sinai Health System, Toronto, ON, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
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30
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Wong SS, Waite B, Ralston J, Wood T, Reynolds GE, Seeds R, Newbern EC, Thompson MG, Huang QS, Webby RJ. Hemagglutinin and Neuraminidase Antibodies Are Induced in an Age- and Subtype-Dependent Manner after Influenza Virus Infection. J Virol 2020; 94:e01385-19. [PMID: 31941786 PMCID: PMC7081922 DOI: 10.1128/jvi.01385-19] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 12/19/2019] [Indexed: 12/26/2022] Open
Abstract
Despite evidence that antibodies targeting the influenza virus neuraminidase (NA) protein can be protective and are broadly cross-reactive, the immune response to NA during infection is poorly understood compared to the response to hemagglutinin (HA) protein. As such, we compared the antibody profile to HA and NA in two naturally infected human cohorts in Auckland, New Zealand: (i) a serosurvey cohort, consisting of pre- and post-influenza season sera from PCR-confirmed influenza cases (n = 50), and (ii) an immunology cohort, consisting of paired sera collected after PCR-confirmation of infection (n = 94). The induction of both HA and NA antibodies in these cohorts was influenced by age and subtype. Seroconversion to HA was more frequent in those <20 years old (yo) for influenza A (serosurvey, P = 0.01; immunology, P = 0.02) but not influenza B virus infection. Seroconversion to NA was not influenced by age or virus type. Adults ≥20 yo infected with influenza A viruses were more likely to show NA-only seroconversion compared to children (56% versus 14% [5 to 19 yo] and 0% [0 to 4 yo], respectively). Conversely, children infected with influenza B viruses were more likely than adults to show NA-only seroconversion (88% [0 to 4 yo] and 75% [5 to 19 yo] versus 40% [≥20 yo]). These data indicate a potential role for immunological memory in the dynamics of HA and NA antibody responses. A better mechanistic understanding of this phenomenon will be critical for any future vaccines aimed at eliciting NA immunity.IMPORTANCE Data on the immunologic responses to neuraminidase (NA) is lacking compared to what is available on hemagglutinin (HA) responses, despite growing evidence that NA immunity can be protective and broadly cross-reactive. Understanding these NA responses during natural infection is key to exploiting these properties for improving influenza vaccines. Using two community-acquired influenza cohorts, we showed that the induction of both HA and NA antibodies after infection is influenced by age and subtypes. Such response dynamics suggest the influence of immunological memory, and understanding how this process is regulated will be critical to any vaccine effort targeting NA immunity.
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Affiliation(s)
- Sook-San Wong
- State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, People’s Republic of China
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong SAR, People’s Republic of China
- Department of Infectious Diseases, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - Ben Waite
- Institute of Environmental Science and Research, Ltd., NCBID–Wallaceville, Wallaceville, New Zealand
| | - Jacqui Ralston
- Institute of Environmental Science and Research, Ltd., NCBID–Wallaceville, Wallaceville, New Zealand
| | - Tim Wood
- Institute of Environmental Science and Research, Ltd., NCBID–Wallaceville, Wallaceville, New Zealand
| | - G. Edwin Reynolds
- Immunisation Advisory Centre (IMAC), University Services, University of Auckland, Auckland, New Zealand
| | - Ruth Seeds
- Institute of Environmental Science and Research, Ltd., NCBID–Wallaceville, Wallaceville, New Zealand
| | - E. Claire Newbern
- Institute of Environmental Science and Research, Ltd., NCBID–Wallaceville, Wallaceville, New Zealand
| | - Mark G. Thompson
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Q. Sue Huang
- Institute of Environmental Science and Research, Ltd., NCBID–Wallaceville, Wallaceville, New Zealand
| | - Richard J. Webby
- Department of Infectious Diseases, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
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31
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Robertson AH, Mahic M, Savic M, Tunheim G, Hungnes O, Trogstad L, Lipkin WI, Mjaaland S. Detection of anti-NS1 antibodies after pandemic influenza exposure: Evaluation of a serological method for distinguishing H1N1pdm09 infected from vaccinated cases. Influenza Other Respir Viruses 2020; 14:294-301. [PMID: 31955522 PMCID: PMC7182603 DOI: 10.1111/irv.12712] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 12/05/2019] [Accepted: 12/08/2019] [Indexed: 12/26/2022] Open
Abstract
Background Reliable exposure information is crucial for assessing health outcomes of influenza infection and vaccination. Current serological methods are unable to distinguish between anti‐hemagglutinin (HA) antibodies induced by infection or vaccination. Objectives We aimed to explore an alternative method for differentiating influenza infection and vaccination. Methods Sera from animals inoculated with influenza viruses or purified H1N1pdm09 HA were obtained. Human samples were selected from a pregnancy cohort established during the 2009 H1N1 pandemic. Unvaccinated, laboratory‐confirmed cases (N = 18), vaccinated cases without influenza‐like‐illness (N = 18) and uninfected, unvaccinated controls (N = 18) were identified based on exposure data from questionnaires, national registries and maternal hemagglutination inhibition (HI) titres at delivery. Animal and human samples were tested for antibodies against the non‐structural protein 1 (NS1) and HA from H1N1pdm09, using a Luciferase Immunoprecipitation System (LIPS). Results Anti‐NS1 H1N1pdm09 antibodies were detected in sera from experimentally infected, but not from vaccinated, animals. Anti‐HA H1N1pdm09 antibodies were detectable after either of these exposures. In human samples, 28% of individuals with laboratory‐confirmed influenza were seropositive for H1N1pdm09 NS1, whereas vaccinated cases and controls were seronegative. There was a trend for H1N1pdm09 NS1 seropositive cases reporting more severe and longer duration of symptomatic illness than seronegative cases. Anti‐HA H1N1pdm09 antibodies were detected in all cases and in 61% of controls. Conclusions The LIPS method could differentiate between sera from experimentally infected and vaccinated animals. However, in human samples obtained more than 6 months after the pandemic, LIPS was specific, but not sufficiently sensitive for ascertaining cases by exposure.
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Affiliation(s)
- Anna Hayman Robertson
- Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Milada Mahic
- Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway.,Center for Infection and Immunity, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Miloje Savic
- Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Gro Tunheim
- Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway.,KG Jebsen Center for Influenza Vaccine Research, Oslo, Norway
| | - Olav Hungnes
- Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway.,WHO National Influenza Centre, Oslo, Norway
| | - Lill Trogstad
- Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Walter Ian Lipkin
- Center for Infection and Immunity, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Siri Mjaaland
- Division of Infection Control and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway.,Center for Infection and Immunity, Mailman School of Public Health, Columbia University, New York, NY, USA.,KG Jebsen Center for Influenza Vaccine Research, Oslo, Norway
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32
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Potter BI, Kondor R, Hadfield J, Huddleston J, Barnes J, Rowe T, Guo L, Xu X, Neher RA, Bedford T, Wentworth DE. Evolution and rapid spread of a reassortant A(H3N2) virus that predominated the 2017-2018 influenza season. Virus Evol 2019; 5:vez046. [PMID: 33282337 DOI: 10.1093/ve/vez046] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The 2017-2018 North American influenza season caused more hospitalizations and deaths than any year since the 2009 H1N1 pandemic. The majority of recorded influenza infections were caused by A(H3N2) viruses, with most of the virus's North American diversity falling into the A2 clade. Within A2, we observe a subclade which we call A2/re that rose to comprise almost 70 per cent of A(H3N2) viruses circulating in North America by early 2018. Unlike most fast-growing clades, however, A2/re contains no amino acid substitutions in the hemagglutinin (HA) segment. Moreover, hemagglutination inhibition assays did not suggest substantial antigenic differences between A2/re viruses and viruses sampled during the 2016-2017 season. Rather, we observe that the A2/re clade was the result of a reassortment event that occurred in late 2016 or early 2017 and involved the combination of the HA and PB1 segments of an A2 virus with neuraminidase (NA) and other segments a virus from the clade A1b. The success of this clade shows the need for antigenic analysis that targets NA in addition to HA. Our results illustrate the potential for non-HA drivers of viral success and necessitate the need for more thorough tracking of full viral genomes to better understand the dynamics of influenza epidemics.
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Affiliation(s)
- Barney I Potter
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
| | - Rebecca Kondor
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), 1600 Clifton Road, Atlanta, GA 30333, USA
| | - James Hadfield
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
| | - John Huddleston
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA.,Molecular and Cellular Biology Program, University of Washington, 4109 E Stevens Way NE, Seattle, WA 98105, USA
| | - John Barnes
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), 1600 Clifton Road, Atlanta, GA 30333, USA
| | - Thomas Rowe
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), 1600 Clifton Road, Atlanta, GA 30333, USA
| | - Lizheng Guo
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), 1600 Clifton Road, Atlanta, GA 30333, USA
| | - Xiyan Xu
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), 1600 Clifton Road, Atlanta, GA 30333, USA
| | - Richard A Neher
- Biozentrum, University of Basel, Klingelbergstrasse 70, 4056 Basel, Switzerland.,SIB Swiss Institute of Bioinformatics, Klingelbergstrasse 70, 4056 Basel, Switzerland
| | - Trevor Bedford
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
| | - 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), 1600 Clifton Road, Atlanta, GA 30333, USA
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33
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Gostic KM, Bridge R, Brady S, Viboud C, Worobey M, Lloyd-Smith JO. Childhood immune imprinting to influenza A shapes birth year-specific risk during seasonal H1N1 and H3N2 epidemics. PLoS Pathog 2019; 15:e1008109. [PMID: 31856206 PMCID: PMC6922319 DOI: 10.1371/journal.ppat.1008109] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 09/25/2019] [Indexed: 11/25/2022] Open
Abstract
Across decades of co-circulation in humans, influenza A subtypes H1N1 and H3N2 have caused seasonal epidemics characterized by different age distributions of cases and mortality. H3N2 causes the majority of severe, clinically attended cases in high-risk elderly cohorts, and the majority of overall deaths, whereas H1N1 causes fewer deaths overall, and cases shifted towards young and middle-aged adults. These contrasting age profiles may result from differences in childhood imprinting to H1N1 and H3N2 or from differences in evolutionary rate between subtypes. Here we analyze a large epidemiological surveillance dataset to test whether childhood immune imprinting shapes seasonal influenza epidemiology, and if so, whether it acts primarily via homosubtypic immune memory or via broader, heterosubtypic memory. We also test the impact of evolutionary differences between influenza subtypes on age distributions of cases. Likelihood-based model comparison shows that narrow, within-subtype imprinting shapes seasonal influenza risk alongside age-specific risk factors. The data do not support a strong effect of evolutionary rate, or of broadly protective imprinting that acts across subtypes. Our findings emphasize that childhood exposures can imprint a lifelong immunological bias toward particular influenza subtypes, and that these cohort-specific biases shape epidemic age distributions. As a consequence, newer and less "senior" antibody responses acquired later in life do not provide the same strength of protection as responses imprinted in childhood. Finally, we project that the relatively low mortality burden of H1N1 may increase in the coming decades, as cohorts that lack H1N1-specific imprinting eventually reach old age.
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Affiliation(s)
- Katelyn M. Gostic
- Dept. of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Rebecca Bridge
- Arizona Department of Health Services, Phoenix, Arizona, United States of America
| | - Shane Brady
- Arizona Department of Health Services, Phoenix, Arizona, United States of America
| | - Cécile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Michael Worobey
- Dept. of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, United States of America
| | - James O. Lloyd-Smith
- Dept. of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, United States of America
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
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34
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Predicting Seasonal Influenza Based on SARIMA Model, in Mainland China from 2005 to 2018. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16234760. [PMID: 31783697 PMCID: PMC6926639 DOI: 10.3390/ijerph16234760] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Revised: 11/24/2019] [Accepted: 11/25/2019] [Indexed: 11/17/2022]
Abstract
Seasonal influenza is one of the mandatorily monitored infectious diseases, in China. Making full use of the influenza surveillance data helps to predict seasonal influenza. In this study, a seasonal autoregressive integrated moving average (SARIMA) model was used to predict the influenza changes by analyzing monthly data of influenza incidence from January 2005 to December 2018, in China. The inter-annual incidence rate fluctuated from 2.76 to 55.07 per 100,000 individuals. The SARIMA (1, 0, 0) × (0, 1, 1) 12 model predicted that the influenza incidence in 2018 was similar to that of previous years, and it fitted the seasonal fluctuation. The relative errors between actual values and predicted values fluctuated from 0.0010 to 0.0137, which indicated that the predicted values matched the actual values well. This study demonstrated that the SARIMA model could effectively make short-term predictions of seasonal influenza.
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35
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Tempia S, Walaza S, Moyes J, Cohen AL, McMorrow ML, Treurnicht FK, Hellferscee O, Wolter N, von Gottberg A, Nguweneza A, McAnerney JM, Dawood H, Variava E, Madhi SA, Cohen C. Quantifying How Different Clinical Presentations, Levels of Severity, and Healthcare Attendance Shape the Burden of Influenza-associated Illness: A Modeling Study From South Africa. Clin Infect Dis 2019; 69:1036-1048. [PMID: 30508065 PMCID: PMC7804385 DOI: 10.1093/cid/ciy1017] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2018] [Accepted: 11/29/2018] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Burden estimates of medically and nonmedically attended influenza-associated illness across syndromes and levels of severity are lacking. METHODS We estimated the national burden of medically and nonmedically attended influenza-associated illness among individuals with different clinical presentations (all-respiratory, all-circulatory, and nonrespiratory/noncirculatory) and levels of severity (mild, fatal, and severe, nonfatal) using a combination of case-based (from laboratory-confirmed influenza surveillance) and ecological studies, as well as data from healthcare utilization surveys in South Africa during 2013-2015. In addition, we compared estimates of medically attended influenza-associated respiratory illness, obtained from case-based and ecological studies. Rates were reported per 100 000 individuals in the population. RESULTS The estimated mean annual number of influenza-associated illness episodes was 10 737 847 (19.8% of 54 096 705 inhabitants). Of these episodes, 10 598 138 (98.7%) were mild, 128 173 (1.2%) were severe, nonfatal, and 11 536 (0.1%) were fatal. There were 2 718 140 (25.6%) mild, 56 226 (43.9%) severe, nonfatal, and 4945 (42.8%) medically attended should be after fatal episodes. Influenza-associated respiratory illness accounted for 99.2% (10 576 146) of any mild, 65.5% (83 941) of any severe, nonfatal, and 33.7% (3893) of any fatal illnesses. Ecological and case-based estimates of medically attended, influenza-associated, respiratory mild (rates: ecological, 1778.8, vs case-based, 1703.3; difference, 4.4%), severe, nonfatal (rates: ecological, 88.6, vs case-based, 75.3; difference, 15.0%), and fatal (rates: ecological, 3.8, vs case-based, 3.5; difference, 8.4%) illnesses were similar. CONCLUSIONS There was a substantial burden of influenza-associated symptomatic illness, including severe, nonfatal and fatal illnesses, and a large proportion was nonmedically attended. Estimates, including only influenza-associated respiratory illness, substantially underestimated influenza-associated, severe, nonfatal and fatal illnesses. Ecological and case-based estimates were found to be similar for the compared categories.
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Affiliation(s)
- Stefano Tempia
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
- Influenza Program, Centers for Disease Control and Prevention, Pretoria
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Sibongile Walaza
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Jocelyn Moyes
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Adam L Cohen
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
- Global Immunization Monitoring and Surveillance Team, Expanded Programme on Immunization, Department of Immunization, Vaccines and Biological, World Health Organization, Geneva, Switzerland
| | - Meredith L McMorrow
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia
- Influenza Program, Centers for Disease Control and Prevention, Pretoria
| | - Florette K Treurnicht
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Orienka Hellferscee
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Nicole Wolter
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Anne von Gottberg
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Arthemon Nguweneza
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Johanna M McAnerney
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Halima Dawood
- Department of Medicine, Pietermaritzburg Metropolitan Hospital, South Africa
- Caprisa, University of KwaZulu-Natal, Pietermaritzburg, South Africa
| | - Ebrahim Variava
- Department of Medicine, Klerksdorp-Tshepong Hospital Complex, South Africa
- Department of Medicine, Faculty of Health Sciences, South Africa
- Perinatal Human Immunodeficiency Virus Research Unit, South Africa
| | - Shabir A Madhi
- Medical Research Council, Respiratory and Meningeal Pathogens Research Unit, South Africa
- Department of Science and Technology/National Research Foundation: Vaccine Preventable Diseases, University of the Witwatersrand, Johannesburg, South Africa
| | - Cheryl Cohen
- Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
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Karunarathna HMTK, Perera RAPM, Fang VJ, Yen HL, Cowling BJ, Peiris M. Serum anti-neuraminidase antibody responses in human influenza A(H1N1)pdm09 virus infections. Emerg Microbes Infect 2019; 8:404-412. [PMID: 30898033 PMCID: PMC6455630 DOI: 10.1080/22221751.2019.1572433] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Haemagglutination inhibition (HAI) antibody titres are a correlate of protection for influenza virus infection, but several studies have also demonstrated the protective role of anti-neuraminidase (anti-NA) antibodies. However, there is limited data on anti-NA antibody responses in naturally occurring human influenza. We investigated anti-NA antibody responses to pandemic N1 and seasonal N1 in 18 RT-PCR-confirmed patients with naturally acquired pandemic influenza A (H1N1) 2009 disease detected as part of a prospective community study of influenza. There were increases in neuraminidase inhibition (NAI) antibody titres to both pandemic and seasonal N1 antigens, with greater fold increases in those who had low levels of anti-pandemic N1 titres in acute sera. Of 18 patients with pandemic H1N1 infection, fourfold increases in antibody were observed by HAI in 11 (61%) patients, by anti-pandemic N1 inhibition in 13 (72%) or either in 15 of them (83%). Prior seasonal H1N1 virus infections had elicited cross-reactive anti-pandemic N1 antibody titres in some people prior to the emergence of the 2009 pandemic H1N1 virus. Antibody responses to the anti-N1 pandemic 2009 virus and cross-reactive responses to anti-seasonal N1 antibody were seen in influenza A pandemic 2009 infections. NAI antibodies can complement HAI antibody in sero-diagnosis and sero-epidemiology.
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Affiliation(s)
- Herath M T K Karunarathna
- a WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine , The University of Hong Kong , Hong Kong , Hong Kong SAR, People's Republic of China.,b Department of Veterinary Public Health and Pharmacology, Faculty of Veterinary Medicine and Animal Science , University of Peradeniya , Peradeniya , Sri Lanka
| | - Ranawaka A P M Perera
- a WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine , The University of Hong Kong , Hong Kong , Hong Kong SAR, People's Republic of China
| | - Vicky J Fang
- a WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine , The University of Hong Kong , Hong Kong , Hong Kong SAR, People's Republic of China
| | - Hui-Ling Yen
- a WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine , The University of Hong Kong , Hong Kong , Hong Kong SAR, People's Republic of China
| | - Benjamin John Cowling
- a WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine , The University of Hong Kong , Hong Kong , Hong Kong SAR, People's Republic of China
| | - Malik Peiris
- a WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine , The University of Hong Kong , Hong Kong , Hong Kong SAR, People's Republic of China
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