1
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Janson A, Gracy S, Paré PE, Sandberg H, Johansson KH. Competitive networked bi-virus spread: Existence of coexistence equilibria. Math Biosci 2024:109286. [PMID: 39214449 DOI: 10.1016/j.mbs.2024.109286] [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: 04/26/2024] [Revised: 07/11/2024] [Accepted: 08/26/2024] [Indexed: 09/04/2024]
Abstract
The paper studies multi-competitive continuous-time epidemic processes. We consider the setting where two viruses are simultaneously prevalent, and the spread occurs due to individual-to-individual interaction. In such a setting, an individual is either not affected by any of the viruses, or infected by one and exactly one of the two viruses. One of the equilibrium points is the coexistence equilibrium, i.e., multiple viruses simultaneously infect separate fractions of the population. We provide a sufficient condition for the existence of a coexistence equilibrium. We identify a condition such that for certain pairs of spread matrices either every coexistence equilibrium lies on a line that is locally exponentially attractive, or there is no coexistence equilibrium. We then provide a condition that, for certain pairs of spread matrices, rules out the possibility of the existence of a coexistence equilibrium, and, as a consequence, establishes global asymptotic convergence to the endemic equilibrium of the dominant virus. Finally, we provide a mitigation strategy that employs one virus to ensure that the other virus is eradicated. The theoretical results are illustrated using simulations.
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Affiliation(s)
- Axel Janson
- Division of Decision and Control Systems, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, and Digital Futures, Stockholm, Sweden.
| | - Sebin Gracy
- Department of Electrical Engineering and Computer Science, South Dakota School of Mines and Technology, SD, USA.
| | - Philip E Paré
- School of Electrical and Computer Engineering, Purdue University, IN, USA.
| | - Henrik Sandberg
- Division of Decision and Control Systems, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, and Digital Futures, Stockholm, Sweden.
| | - Karl Henrik Johansson
- Division of Decision and Control Systems, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, and Digital Futures, Stockholm, Sweden.
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2
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Noffel Z, Dobrovolny HM. Modeling the bystander effect during viral coinfection. J Theor Biol 2024; 594:111928. [PMID: 39168369 DOI: 10.1016/j.jtbi.2024.111928] [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: 06/08/2024] [Revised: 08/07/2024] [Accepted: 08/15/2024] [Indexed: 08/23/2024]
Abstract
Viral coinfections are responsible for a significant portion of cases of patients hospitalized with influenza-like illness. As our awareness of viral coinfections has increased, researchers have started to experimentally examine some of the virus-virus interactions underlying these infections. One mechanism of interaction between viruses is through the innate immune response. This seems to occur primarily through the interferon response, which generates an antiviral state in nearby uninfected cells, a phenomenon know as the bystander effect. Here, we develop a mathematical model of two viruses interacting through the bystander effect. We find that when the rate of removal of cells to the protected state is high, growth of the first virus is suppressed, while the second virus enjoys sole access to the protected cells, enhancing its growth. Conversely, growth of the second virus can be fully suppressed if its ability to infect the protected cells is limited.
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Affiliation(s)
- Zakarya Noffel
- University of Texas at Austin, Department of Computer Science, Asutin, TX, United States
| | - Hana M Dobrovolny
- Texas Christian University, Department of Physics & Astronomy, Fort Worth, 76129, TX, United States.
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3
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Li K, Hamrin J, Weinberger DM, Pitzer VE. Unraveling the Role of Viral Interference in Disrupting Biennial RSV Epidemics in Northern Stockholm. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.09.24310749. [PMID: 39148838 PMCID: PMC11326348 DOI: 10.1101/2024.08.09.24310749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Respiratory syncytial virus (RSV) primarily impacts infants and older adults, with seasonal winter outbreaks in temperate countries. Biennial cycles of RSV activity have also been identified in Northern Europe and some states in the United States. Delayed RSV activity was reported worldwide during the 2009 influenza pandemic, and a disrupted biennial pattern of RSV activity was observed in northern Stockholm following the pandemic. Biennial patterns shifted to early/large outbreaks in even-numbered years and late/small outbreaks in odd-numbered years. However, the mechanisms underpinning this change in pattern remain unknown. In this work, we constructed an age-stratified mechanistic model to explicitly test three factors that could lead to the change in RSV transmission dynamics: 1) birth rates, 2) temperatures, and 3) viral interference. By fitting the model to weekly RSV admission data over a 20-year period and comparing different models, we found that viral interference from influenza was the only mechanism that explained the shifted biennial pattern. Our work demonstrates the complex interplay between different respiratory viruses, providing evidence that supports the presence of interactions between the H1N1 pandemic influenza virus and RSV at the population level, with implications for future public health interventions.
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Affiliation(s)
- Ke Li
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Johan Hamrin
- Astrid Lindgren Children’s Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Daniel M. Weinberger
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Virginia E. Pitzer
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
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4
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Chin T, Foxman EF, Watkins TA, Lipsitch M. Considerations for viral co-infection studies in human populations. mBio 2024; 15:e0065824. [PMID: 38847531 PMCID: PMC11253623 DOI: 10.1128/mbio.00658-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2024] Open
Abstract
When respiratory viruses co-circulate in a population, individuals may be infected with multiple pathogens and experience possible virus-virus interactions, where concurrent or recent prior infection with one virus affects the infection process of another virus. While experimental studies have provided convincing evidence for within-host mechanisms of virus-virus interactions, evaluating evidence for viral interference or potentiation using population-level data has proven more difficult. Recent studies have quantified the prevalence of co-detections using populations drawn from clinical settings. Here, we focus on selection bias issues associated with this study design. We provide a quantitative account of the conditions under which selection bias arises in these studies, review previous attempts to address this bias, and propose unbiased study designs with sample size estimates needed to ascertain viral interference. We show that selection bias is expected in cross-sectional co-detection prevalence studies conducted in clinical settings, except under a strict set of assumptions regarding the relative probabilities of being included in a study limited to individuals with clinical disease under different viral states. Population-wide studies that collect samples from participants irrespective of their clinical status would meanwhile require large sample sizes to be sufficiently powered to detect viral interference, suggesting that a study's timing, inclusion criteria, and the expected magnitude of interference are instrumental in determining feasibility.
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Affiliation(s)
- Taylor Chin
- Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Ellen F. Foxman
- Department of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Timothy A. Watkins
- Department of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Immunobiology, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Marc Lipsitch
- Center for Communicable Disease Dynamics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
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5
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Hamid S, Grajeda L, de Leon O, Lopez M, Maldonado H, Gomez A, Lopman B, Clasen T, McCracken J. Variability in the Timing of Respiratory Syncytial Virus Epidemics in Guatemala, 2008-2018. Influenza Other Respir Viruses 2024; 18:e13334. [PMID: 38980961 PMCID: PMC11232890 DOI: 10.1111/irv.13334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2024] [Revised: 05/12/2024] [Accepted: 05/19/2024] [Indexed: 07/11/2024] Open
Abstract
BACKGROUND The description of local seasonality patterns in respiratory syncytial virus (RSV) incidence is important to guide the timing of administration of RSV immunization products. METHODS We characterized RSV seasonality in Guatemala using the moving epidemic method (MEM) with absolute counts of RSV-associated acute respiratory infections (ARI) from hospital surveillance in Santa Rosa and Quetzaltenango departments of Guatemala. RESULTS From Week 17 of 2008 through Week 16 of 2018, 8487 ARI cases tested positive for RSV by rRT-PCR. Season onsets varied up to 5 months; early seasons starting in late May to early August and finishing in September to November were most common, but late seasons starting in October to November and finishing in March to April were also observed. Both epidemic patterns had similar durations ranging from 4 to 6 months. Epidemic thresholds (the levels of virus activity that signal the onset and end of a seasonal epidemic) calculated prospectively using previous seasons' data captured between 70% and 99% of annual RSV detections. Onset weeks differed by 2-10 weeks, and offset weeks differed by 2-16 weeks between the two surveillance sites. CONCLUSIONS Variability in the timing of seasonal RSV epidemics in Guatemala demonstrates the difficulty in precisely predicting the timing of seasonal RSV epidemics based on onset weeks from past seasons and suggests that maximal reduction in RSV disease burden would be achieved through year-round vaccination and immunoprophylaxis administration to at-risk infants.
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Affiliation(s)
- Sarah Hamid
- Department of Epidemiology, Rollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
| | - Laura M. Grajeda
- Centro de Estudios en SaludUniversidad del Valle de GuatemalaGuatemala CityGuatemala
- Global Health Institute, College of Public HealthUniversity of GeorgiaAthensGeorgiaUSA
| | - Oscar de Leon
- Department of Epidemiology, Rollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
- Centro de Estudios en SaludUniversidad del Valle de GuatemalaGuatemala CityGuatemala
- Gangarosa Department of Environmental Health, Rollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
| | - Maria Renee Lopez
- Centro de Estudios en SaludUniversidad del Valle de GuatemalaGuatemala CityGuatemala
| | - Herberth Maldonado
- Centro de Estudios en SaludUniversidad del Valle de GuatemalaGuatemala CityGuatemala
| | - Ana Beatriz Gomez
- Centro de Estudios en SaludUniversidad del Valle de GuatemalaGuatemala CityGuatemala
| | - Benjamin Lopman
- Department of Epidemiology, Rollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
| | - Thomas F. Clasen
- Department of Epidemiology, Rollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
- Gangarosa Department of Environmental Health, Rollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
| | - John P. McCracken
- Centro de Estudios en SaludUniversidad del Valle de GuatemalaGuatemala CityGuatemala
- Global Health Institute, College of Public HealthUniversity of GeorgiaAthensGeorgiaUSA
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6
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Wu H, Zhou HY, Zheng H, Wu A. Towards Understanding and Identification of Human Viral Co-Infections. Viruses 2024; 16:673. [PMID: 38793555 PMCID: PMC11126107 DOI: 10.3390/v16050673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 04/19/2024] [Accepted: 04/24/2024] [Indexed: 05/26/2024] Open
Abstract
Viral co-infections, in which a host is infected with multiple viruses simultaneously, are common in the human population. Human viral co-infections can lead to complex interactions between the viruses and the host immune system, affecting the clinical outcome and posing challenges for treatment. Understanding the types, mechanisms, impacts, and identification methods of human viral co-infections is crucial for the prevention and control of viral diseases. In this review, we first introduce the significance of studying human viral co-infections and summarize the current research progress and gaps in this field. We then classify human viral co-infections into four types based on the pathogenic properties and species of the viruses involved. Next, we discuss the molecular mechanisms of viral co-infections, focusing on virus-virus interactions, host immune responses, and clinical manifestations. We also summarize the experimental and computational methods for the identification of viral co-infections, emphasizing the latest advances in high-throughput sequencing and bioinformatics approaches. Finally, we highlight the challenges and future directions in human viral co-infection research, aiming to provide new insights and strategies for the prevention, control, diagnosis, and treatment of viral diseases. This review provides a comprehensive overview of the current knowledge and future perspectives on human viral co-infections and underscores the need for interdisciplinary collaboration to address this complex and important topic.
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Affiliation(s)
- Hui Wu
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 211100, China;
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
| | - Hang-Yu Zhou
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
| | - Heng Zheng
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 211100, China;
| | - Aiping Wu
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China
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7
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Babawale PI, Guerrero-Plata A. Respiratory Viral Coinfections: Insights into Epidemiology, Immune Response, Pathology, and Clinical Outcomes. Pathogens 2024; 13:316. [PMID: 38668271 PMCID: PMC11053695 DOI: 10.3390/pathogens13040316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 04/06/2024] [Accepted: 04/11/2024] [Indexed: 04/29/2024] Open
Abstract
Respiratory viral coinfections are a global public health threat that poses an economic burden on individuals, families, and healthcare infrastructure. Viruses may coinfect and interact synergistically or antagonistically, or their coinfection may not affect their replication rate. These interactions are specific to different virus combinations, which underlines the importance of understanding the mechanisms behind these differential viral interactions and the need for novel diagnostic methods to accurately identify multiple viruses causing a disease in a patient to avoid misdiagnosis. This review examines epidemiological patterns, pathology manifestations, and the immune response modulation of different respiratory viral combinations that occur during coinfections using different experimental models to better understand the dynamics respiratory viral coinfection takes in driving disease outcomes and severity, which is crucial to guide the development of prevention and treatment strategies.
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Affiliation(s)
| | - Antonieta Guerrero-Plata
- Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70803, USA;
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8
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Xu D, Chen Z, Zhu G. Change of epidemiological characteristics of four respiratory viral infections in children before and during COVID-19 pandemic. Infect Dis Now 2024; 54:104858. [PMID: 38309644 DOI: 10.1016/j.idnow.2024.104858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 12/18/2023] [Accepted: 01/29/2024] [Indexed: 02/05/2024]
Abstract
OBJECTIVES Viruses are the main infectious agents of acute respiratory infections (ARIs) in children. We aim to describe the changes in epidemic characteristics of viral ARIs in outpatient children before and during the COVID-19 pandemic. PATIENTS AND METHODS From 2017 to 2022, the results of viral detection in oral pharyngeal swabs in 479,236 children with ARIs in the outpatient department of Children's Hospital, Zhejiang University School of Medicine, were retrospectively analyzed. Viral antigens, including adenovirus (ADV), influenza A (FLUA), influenza B (FLUB) and respiratory syncytial virus (RSV) were detected by the colloidal gold method. RESULTS The median age was 3.4 (1.6-5.6) years. Among all the children, 159,895 cases (33.4 %) were positive for at least one virus. The total positive rate for ADV, FLUA and FLUB during the pandemic period was lower than during the pre-pandemic period in every season (pre-pandemic period vs. pandemic period11.7 % vs. 4.7 %, 13.9 % vs. 9.2 %, 7.0 % vs. 5.2 %, respectively, with overall p value < 0.001). However, the positive rate fir RSV was not significantly different between the pre-pandemic period and the pandemic period (5.6 % vs. 5.8 %, p = 0.117). Atypical timing of RSV (summer-autumn 2021) and FLUA (summer 2022) was noted. CONCLUSIONS Public health interventions for different pathogens are maximally effective. While positive rates for ADV, FLUA and FLUB decreased during the COVID-19 pandemic period, positive rates for RSV remained similar. In RSV and FLUA, off-season outbreaks were observed. Measures need to be taken to protect children from possible infection surges due to immunity debt having accrued over the last three years.
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Affiliation(s)
- Dan Xu
- Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, 3333, Binsheng Road, Hangzhou, Zhejiang Province, China
| | - Zhimin Chen
- Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, 3333, Binsheng Road, Hangzhou, Zhejiang Province, China
| | - Guohong Zhu
- Department of Pulmonology, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, 3333, Binsheng Road, Hangzhou, Zhejiang Province, China.
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9
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Li K, Thindwa D, Weinberger DM, Pitzer VE. The role of viral interference in shaping RSV epidemics following the 2009 H1N1 influenza pandemic. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.25.24303336. [PMID: 38464193 PMCID: PMC10925368 DOI: 10.1101/2024.02.25.24303336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Respiratory syncytial virus (RSV) primarily affects infants, young children, and older adults, with seasonal outbreaks in the United States (US) peaking around December or January. Despite the limited implementation of non-pharmaceutical interventions, disrupted RSV activity was observed in different countries following the 2009 influenza pandemic, suggesting possible viral interference from influenza. Although interactions between the influenza A/H1N1 pandemic virus and RSV have been demonstrated at an individual level, it remains unclear whether the disruption of RSV activity at the population level can be attributed to viral interference. In this work, we first evaluated changes in the timing and intensity of RSV activity across 10 regions of the US in the years following the 2009 influenza pandemic using dynamic time warping. We observed a reduction in RSV activity following the pandemic, which was associated with intensity of influenza activity in the region. We then developed an age-stratified, two-pathogen model to examine various hypotheses regarding viral interference mechanisms. Based on our model estimates, we identified three mechanisms through which influenza infections could interfere with RSV: 1) reducing susceptibility to RSV coinfection; 2) shortening the RSV infectious period in coinfected individuals; and 3) reducing RSV infectivity in coinfection. Our study offers statistical support for the occurrence of atypical RSV seasons following the 2009 influenza pandemic. Our work also offers new insights into the mechanisms of viral interference that contribute to disruptions in RSV epidemics and provides a model-fitting framework that enables the analysis of new surveillance data for studying viral interference at the population level.
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Affiliation(s)
- Ke Li
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Deus Thindwa
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Daniel M Weinberger
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Virginia E Pitzer
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
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10
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Heimonen J, Chow EJ, Wang Y, Hughes JP, Rogers J, Emanuels A, O’Hanlon J, Han PD, Wolf CR, Logue JK, Ogokeh CE, Rolfes MA, Uyeki TM, Starita L, Englund JA, Chu HY. Risk of Subsequent Respiratory Virus Detection After Primary Virus Detection in a Community Household Study-King County, Washington, 2019-2021. J Infect Dis 2024; 229:422-431. [PMID: 37531658 PMCID: PMC10873185 DOI: 10.1093/infdis/jiad305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 07/19/2023] [Accepted: 07/31/2023] [Indexed: 08/04/2023] Open
Abstract
BACKGROUND The epidemiology of respiratory viral infections is complex. How infection with one respiratory virus affects risk of subsequent infection with the same or another respiratory virus is not well described. METHODS From October 2019 to June 2021, enrolled households completed active surveillance for acute respiratory illness (ARI), and participants with ARI self-collected nasal swab specimens; after April 2020, participants with ARI or laboratory-confirmed severe acute respiratory syndrome coronavirus 2 and their household members self-collected nasal swab specimens. Specimens were tested using multiplex reverse-transcription polymerase chain reaction for respiratory viruses. A Cox regression model with a time-dependent covariate examined risk of subsequent detections following a specific primary viral detection. RESULTS Rhinovirus was the most frequently detected pathogen in study specimens (406 [9.5%]). Among 51 participants with multiple viral detections, rhinovirus to seasonal coronavirus (8 [14.8%]) was the most common viral detection pairing. Relative to no primary detection, there was a 1.03-2.06-fold increase in risk of subsequent virus detection in the 90 days after primary detection; risk varied by primary virus: human parainfluenza virus, rhinovirus, and respiratory syncytial virus were statistically significant. CONCLUSIONS Primary virus detection was associated with higher risk of subsequent virus detection within the first 90 days after primary detection.
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Affiliation(s)
- Jessica Heimonen
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Eric J Chow
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
- Prevention Division, Public Health—Seattle & King County, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Yongzhe Wang
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - James P Hughes
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Julia Rogers
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Anne Emanuels
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Jessica O’Hanlon
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Peter D Han
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
| | - Caitlin R Wolf
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Jennifer K Logue
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Constance E Ogokeh
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- Military and Health Research Foundation, Laurel, Maryland, USA
| | - Melissa A Rolfes
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Timothy M Uyeki
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Lea Starita
- Brotman Baty Institute for Precision Medicine, Seattle, Washington, USA
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - Janet A Englund
- Division of Pediatric Infectious Diseases, Seattle Children's Research Institute, Seattle, Washington, USA
- Department of Pediatrics, University of Washington, Seattle, Washington, USA
| | - Helen Y Chu
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
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11
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Eales O, Plank MJ, Cowling BJ, Howden BP, Kucharski AJ, Sullivan SG, Vandemaele K, Viboud C, Riley S, McCaw JM, Shearer FM. Key Challenges for Respiratory Virus Surveillance while Transitioning out of Acute Phase of COVID-19 Pandemic. Emerg Infect Dis 2024; 30:e230768. [PMID: 38190760 PMCID: PMC10826770 DOI: 10.3201/eid3002.230768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2024] Open
Abstract
To support the ongoing management of viral respiratory diseases while transitioning out of the acute phase of the COVID-19 pandemic, many countries are moving toward an integrated model of surveillance for SARS-CoV-2, influenza virus, and other respiratory pathogens. Although many surveillance approaches catalyzed by the COVID-19 pandemic provide novel epidemiologic insight, continuing them as implemented during the pandemic is unlikely to be feasible for nonemergency surveillance, and many have already been scaled back. Furthermore, given anticipated cocirculation of SARS-CoV-2 and influenza virus, surveillance activities in place before the pandemic require review and adjustment to ensure their ongoing value for public health. In this report, we highlight key challenges for the development of integrated models of surveillance. We discuss the relative strengths and limitations of different surveillance practices and studies as well as their contribution to epidemiologic assessment, forecasting, and public health decision-making.
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12
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Feng Y, Wen S, Xue S, Hou M, Jin Y. Potential co-infection of influenza A, influenza B, respiratory syncytial virus, and Chlamydia pneumoniae: a case report with literature review. Front Med (Lausanne) 2024; 10:1325482. [PMID: 38259842 PMCID: PMC10800736 DOI: 10.3389/fmed.2023.1325482] [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: 10/31/2023] [Accepted: 12/15/2023] [Indexed: 01/24/2024] Open
Abstract
The occurrence of a co-infection involving four distinct respiratory pathogens could be underestimated. Here, we report the case of a 72-year-old woman who presented to a community hospital with a cough productive of sputum as her main clinical manifestation. Antibody detection of common respiratory pathogens revealed potential co-infection with influenza A, influenza B, respiratory syncytial virus, and Chlamydia pneumoniae. We treated her with 75 mg oseltamivir phosphate administered orally twice daily for 5 days, 0.5 g azithromycin administered orally for 5 days, and 0.3 g acetylcysteine aerosol inhaled twice daily for 3 days. The patient showed a favorable outcome on the eighth day after early diagnosis and treatment. Since co-infection with these four pathogens is rare, we performed an extensive PubMed search of similar cases and carried out a systematic review to analyze the epidemiology, clinical manifestations, transmission route, susceptible population, and outcomes of these four different pathogens. Our report highlights the importance for general practitioners to be vigilant about the possibility of mixed infections when a patient presents with respiratory symptoms. Although these symptoms may be mild, early diagnosis and timely treatment could improve outcomes. Additionally, further research is warranted to explore the potential influence of SARS-CoV-2 infection on the co-occurrence of multiple respiratory pathogens.
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Affiliation(s)
| | | | | | | | - Ying Jin
- Huangpu District Dapuqiao Community Health Center, Shanghai, China
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13
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Matera L, Manti S, Petrarca L, Pierangeli A, Conti MG, Mancino E, Leonardi S, Midulla F, Nenna R. An overview on viral interference during SARS-CoV-2 pandemic. Front Pediatr 2023; 11:1308105. [PMID: 38178911 PMCID: PMC10764478 DOI: 10.3389/fped.2023.1308105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 12/07/2023] [Indexed: 01/06/2024] Open
Abstract
Respiratory viruses represent the most frequent cause of mortality, morbidity and high healthcare costs for emergency visits and hospitalization in the pediatric age. Respiratory viruses can circulate simultaneously and can potentially infect the same host, determining different types of interactions, the so-called viral interference. The role of viral interference has assumed great importance since December 2019, when the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) came on the scene. The aim of this narrative review is to present our perspective regarding research in respiratory virus interference and discuss recent advances on the topic because, following SARS-CoV-2 restrictions mitigation, we are experimenting the co-circulation of respiratory viruses along with SARS-CoV-2. This scenario is raising many concerns about possible virus-virus interactions, both positive and negative, and the clinical, diagnostic and therapeutic management of these coinfections. Moreover, we cannot rule out that also climatic conditions and social behaviours are involved. Thus, this situation can lead to different population epidemic dynamics, including changes in the age of the targeted population, disease course and severity, highlighting the need for prospective epidemiologic studies and mathematical modelling able to predict the timing and magnitude of epidemics caused by SARS-CoV-2/seasonal respiratory virus interactions in order to adjust better public health interventions.
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Affiliation(s)
- Luigi Matera
- Department of Maternal Infantile and Urological Sciences, Sapienza University of Rome, Rome, Italy
| | - Sara Manti
- Department of Human and Pediatric Pathology, Pediatric Unit, G. Martino Hospital, University of Messina, Messina, Italy
| | - Laura Petrarca
- Department of Maternal Infantile and Urological Sciences, Sapienza University of Rome, Rome, Italy
| | - Alessandra Pierangeli
- Laboratory of Virology, Department of Molecular Medicine, Affiliated to Istituto Pasteur Italia, Sapienza University of Rome, Rome, Italy
| | - Maria Giulia Conti
- Department of Maternal Infantile and Urological Sciences, Sapienza University of Rome, Rome, Italy
| | - Enrica Mancino
- Department of Maternal Infantile and Urological Sciences, Sapienza University of Rome, Rome, Italy
| | - Salvatore Leonardi
- Pediatric Respiratory Unit, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy
| | - Fabio Midulla
- Department of Maternal Infantile and Urological Sciences, Sapienza University of Rome, Rome, Italy
| | - Raffaella Nenna
- Department of Maternal Infantile and Urological Sciences, Sapienza University of Rome, Rome, Italy
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Mochan E, Sego TJ. Mathematical Modeling of the Lethal Synergism of Coinfecting Pathogens in Respiratory Viral Infections: A Review. Microorganisms 2023; 11:2974. [PMID: 38138118 PMCID: PMC10745501 DOI: 10.3390/microorganisms11122974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 12/05/2023] [Accepted: 12/08/2023] [Indexed: 12/24/2023] Open
Abstract
Influenza A virus (IAV) infections represent a substantial global health challenge and are often accompanied by coinfections involving secondary viruses or bacteria, resulting in increased morbidity and mortality. The clinical impact of coinfections remains poorly understood, with conflicting findings regarding fatality. Isolating the impact of each pathogen and mechanisms of pathogen synergy during coinfections is challenging and further complicated by host and pathogen variability and experimental conditions. Factors such as cytokine dysregulation, immune cell function alterations, mucociliary dysfunction, and changes to the respiratory tract epithelium have been identified as contributors to increased lethality. The relative significance of these factors depends on variables such as pathogen types, infection timing, sequence, and inoculum size. Mathematical biological modeling can play a pivotal role in shedding light on the mechanisms of coinfections. Mathematical modeling enables the quantification of aspects of the intra-host immune response that are difficult to assess experimentally. In this narrative review, we highlight important mechanisms of IAV coinfection with bacterial and viral pathogens and survey mathematical models of coinfection and the insights gained from them. We discuss current challenges and limitations facing coinfection modeling, as well as current trends and future directions toward a complete understanding of coinfection using mathematical modeling and computer simulation.
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Affiliation(s)
- Ericka Mochan
- Department of Computational and Chemical Sciences, Carlow University, Pittsburgh, PA 15213, USA
| | - T. J. Sego
- Department of Medicine, University of Florida, Gainesville, FL 32611, USA;
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15
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Wan L, Li L, Zhang H, Liu C, Li R, Wu X, Chen J. The changing pattern of common respiratory viruses among children from 2018 to 2021 in Wuhan, China. Arch Virol 2023; 168:291. [PMID: 37962775 PMCID: PMC10645662 DOI: 10.1007/s00705-023-05891-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 08/18/2023] [Indexed: 11/15/2023]
Abstract
BACKGROUND Acute respiratory infections in children are a global public health challenge. Owing to the coronavirus disease (COVID-19) pandemic, non-pharmaceutical interventions, including patient isolation, social distancing, hand washing, and mask wearing, have been widely implemented, impacting the transmission of common respiratory viruses. The aim of this study was to clarify the epidemiological features of respiratory viruses in children less than 14 years of age in Wuhan before and after COVID-19. METHODS Respiratory specimens were collected from patients aged < 14 years at two hospitals in Wuhan, China, from January 2018 to December 2021. Seven respiratory viruses were identified using an immunofluorescence assay. Pathogen profiles and seasonality were analysed. RESULTS The number of visits and virus detection rate decreased dramatically after February 2020. The respiratory virus detection rate peaked in January and December and decreased dramatically in February and August. The detection rate was lower in 2021 than in 2018 and 2019. Respiratory syncytial virus (RSV) was identified as the leading pathogen in children aged < 1 year and 1-4 years before and after the COVID-19 pandemic. In children aged 5-14 years, influenza virus was detected at the highest rate before, and RSV after, the COVID-19 pandemic. RSV was the most common virus in coinfections. CONCLUSIONS This study revealed the epidemiological patterns of common respiratory viruses from 2018 to 2021. The spectrum of pathogens involved in paediatric respiratory infections had partly changed. Non-pharmaceutical interventions resulted in fewer opportunities for the spread of common viruses but also in an "immunity debt" that could have negative consequences when the pandemic is under control in Wuhan.
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Affiliation(s)
- Lu Wan
- Department of Pulmonary and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Liangyu Li
- Department of Pulmonary and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Haiyue Zhang
- Department of Pulmonary and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Chan Liu
- Department of Pulmonary and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Ruiyun Li
- Department of Pulmonary and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, Hubei, China
| | - Xiaojun Wu
- Department of Pulmonary and Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, Hubei, China.
| | - Jianjun Chen
- CAS Key Laboratory of Special Pathogens, Center for Biosafety Mega Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, Hubei, China.
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16
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Lampros A, Talla C, Diarra M, Tall B, Sagne S, Diallo MK, Diop B, Oumar I, Dia N, Sall AA, Barry MA, Loucoubar C. Shifting Patterns of Influenza Circulation during the COVID-19 Pandemic, Senegal. Emerg Infect Dis 2023; 29:1808-1817. [PMID: 37610149 PMCID: PMC10461650 DOI: 10.3201/eid2909.230307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/24/2023] Open
Abstract
Historically low levels of seasonal influenza circulation were reported during the first years of the COVID-19 pandemic and were mainly attributed to implementation of nonpharmaceutical interventions. In tropical regions, influenza's seasonality differs largely, and data on this topic are scarce. We analyzed data from Senegal's sentinel syndromic surveillance network before and after the start of the COVID-19 pandemic to assess changes in influenza circulation. We found that influenza shows year-round circulation in Senegal and has 2 distinct epidemic peaks: during January-March and during the rainy season in August-October. During 2021-2022, the expected January-March influenza peak completely disappeared, corresponding to periods of active SARS-CoV-2 circulation. We noted an unexpected influenza epidemic peak during May-July 2022. The observed reciprocal circulation of SARS-CoV-2 and influenza suggests that factors such as viral interference might be at play and should be further investigated in tropical settings.
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Affiliation(s)
- Alexandre Lampros
- Hôpital Européen Georges Pompidou, Paris, France (A. Lampros)
- Institut Pasteur de Dakar, Dakar, Senegal (A. Lampros, C. Talla, M. Diarra, B. Tall, S. Sagne, M. Korka Diallo, N. Dia, A.A. Sall, M.A. Barry, C. Loucoubar)
- Government of Senegal Ministry of Health and Social Action, Dakar (A. Lampros, B. Diop)
- World Health Organization, Dakar (A. Lampros, I. Oumar)
| | - Cheikh Talla
- Hôpital Européen Georges Pompidou, Paris, France (A. Lampros)
- Institut Pasteur de Dakar, Dakar, Senegal (A. Lampros, C. Talla, M. Diarra, B. Tall, S. Sagne, M. Korka Diallo, N. Dia, A.A. Sall, M.A. Barry, C. Loucoubar)
- Government of Senegal Ministry of Health and Social Action, Dakar (A. Lampros, B. Diop)
- World Health Organization, Dakar (A. Lampros, I. Oumar)
| | - Maryam Diarra
- Hôpital Européen Georges Pompidou, Paris, France (A. Lampros)
- Institut Pasteur de Dakar, Dakar, Senegal (A. Lampros, C. Talla, M. Diarra, B. Tall, S. Sagne, M. Korka Diallo, N. Dia, A.A. Sall, M.A. Barry, C. Loucoubar)
- Government of Senegal Ministry of Health and Social Action, Dakar (A. Lampros, B. Diop)
- World Health Organization, Dakar (A. Lampros, I. Oumar)
| | - Billo Tall
- Hôpital Européen Georges Pompidou, Paris, France (A. Lampros)
- Institut Pasteur de Dakar, Dakar, Senegal (A. Lampros, C. Talla, M. Diarra, B. Tall, S. Sagne, M. Korka Diallo, N. Dia, A.A. Sall, M.A. Barry, C. Loucoubar)
- Government of Senegal Ministry of Health and Social Action, Dakar (A. Lampros, B. Diop)
- World Health Organization, Dakar (A. Lampros, I. Oumar)
| | - Samba Sagne
- Hôpital Européen Georges Pompidou, Paris, France (A. Lampros)
- Institut Pasteur de Dakar, Dakar, Senegal (A. Lampros, C. Talla, M. Diarra, B. Tall, S. Sagne, M. Korka Diallo, N. Dia, A.A. Sall, M.A. Barry, C. Loucoubar)
- Government of Senegal Ministry of Health and Social Action, Dakar (A. Lampros, B. Diop)
- World Health Organization, Dakar (A. Lampros, I. Oumar)
| | - Mamadou Korka Diallo
- Hôpital Européen Georges Pompidou, Paris, France (A. Lampros)
- Institut Pasteur de Dakar, Dakar, Senegal (A. Lampros, C. Talla, M. Diarra, B. Tall, S. Sagne, M. Korka Diallo, N. Dia, A.A. Sall, M.A. Barry, C. Loucoubar)
- Government of Senegal Ministry of Health and Social Action, Dakar (A. Lampros, B. Diop)
- World Health Organization, Dakar (A. Lampros, I. Oumar)
| | - Boly Diop
- Hôpital Européen Georges Pompidou, Paris, France (A. Lampros)
- Institut Pasteur de Dakar, Dakar, Senegal (A. Lampros, C. Talla, M. Diarra, B. Tall, S. Sagne, M. Korka Diallo, N. Dia, A.A. Sall, M.A. Barry, C. Loucoubar)
- Government of Senegal Ministry of Health and Social Action, Dakar (A. Lampros, B. Diop)
- World Health Organization, Dakar (A. Lampros, I. Oumar)
| | - Ibrahim Oumar
- Hôpital Européen Georges Pompidou, Paris, France (A. Lampros)
- Institut Pasteur de Dakar, Dakar, Senegal (A. Lampros, C. Talla, M. Diarra, B. Tall, S. Sagne, M. Korka Diallo, N. Dia, A.A. Sall, M.A. Barry, C. Loucoubar)
- Government of Senegal Ministry of Health and Social Action, Dakar (A. Lampros, B. Diop)
- World Health Organization, Dakar (A. Lampros, I. Oumar)
| | - Ndongo Dia
- Hôpital Européen Georges Pompidou, Paris, France (A. Lampros)
- Institut Pasteur de Dakar, Dakar, Senegal (A. Lampros, C. Talla, M. Diarra, B. Tall, S. Sagne, M. Korka Diallo, N. Dia, A.A. Sall, M.A. Barry, C. Loucoubar)
- Government of Senegal Ministry of Health and Social Action, Dakar (A. Lampros, B. Diop)
- World Health Organization, Dakar (A. Lampros, I. Oumar)
| | - Amadou Alpha Sall
- Hôpital Européen Georges Pompidou, Paris, France (A. Lampros)
- Institut Pasteur de Dakar, Dakar, Senegal (A. Lampros, C. Talla, M. Diarra, B. Tall, S. Sagne, M. Korka Diallo, N. Dia, A.A. Sall, M.A. Barry, C. Loucoubar)
- Government of Senegal Ministry of Health and Social Action, Dakar (A. Lampros, B. Diop)
- World Health Organization, Dakar (A. Lampros, I. Oumar)
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Zhang L, Xiao Y, Xiang Z, Chen L, Wang Y, Wang X, Dong X, Ren L, Wang J. Statistical Analysis of Common Respiratory Viruses Reveals the Binary of Virus-Virus Interaction. Microbiol Spectr 2023; 11:e0001923. [PMID: 37378522 PMCID: PMC10433823 DOI: 10.1128/spectrum.00019-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 06/09/2023] [Indexed: 06/29/2023] Open
Abstract
Respiratory viruses may interfere with each other and affect the epidemic trend of the virus. However, the understanding of the interactions between respiratory viruses at the population level is still very limited. We here conducted a prospective laboratory-based etiological study by enrolling 14,426 patients suffered from acute respiratory infection (ARI) in Beijing, China during 2005 to 2015. All 18 respiratory viruses were simultaneously tested for each nasal and throat swabs collected from enrolled patients using molecular tests. The virus correlations were quantitatively evaluated, and the respiratory viruses could be divided into two panels according to the positive and negative correlations. One included influenza viruses (IFVs) A, B, and respiratory syncytial virus (RSV), while the other included human parainfluenza viruses (HPIVs) 1/3, 2/4, adenovirus (Adv), human metapneumovirus (hMPV), and enterovirus (including rhinovirus, named picoRNA), α and β human coronaviruses (HCoVs). The viruses were positive-correlated in each panel, while negative-correlated between panels. After adjusting the confounding factors by vector autoregressive model, positive interaction between IFV-A and RSV and negative interaction between IFV-A and picoRNA are still be observed. The asynchronous interference of IFV-A significantly delayed the peak of β human coronaviruses epidemic. The binary property of the respiratory virus interactions provides new insights into the viral epidemic dynamics in human population, facilitating the development of infectious disease control and prevention strategies. IMPORTANCE Systematic quantitative assessment of the interactions between different respiratory viruses is pivotal for the prevention of infectious diseases and the development of vaccine strategies. Our data showed stable interactions among respiratory viruses at human population level, which are season irrelevant. Respiratory viruses could be divided into two panels according to their positive and negative correlations. One included influenza virus and respiratory syncytial virus, while the other included other common respiratory viruses. It showed negative correlations between the two panels. The asynchronous interference between influenza virus and β human coronaviruses significantly delayed the peak of β human coronaviruses epidemic. The binary property of the viruses indicated transient immunity induced by one kind of virus would play role on subsequent infection, which provides important data for the development of epidemic surveillance strategies.
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Affiliation(s)
- Lulu Zhang
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
| | - Yan Xiao
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
- Key Laboratory of Respiratory Disease Pathogenomics, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Zichun Xiang
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
| | - Lan Chen
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
| | - Ying Wang
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
| | - Xinming Wang
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
| | - Xiaojing Dong
- Santa Clara University, Santa Clara, California, USA
| | - Lili Ren
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
- Key Laboratory of Respiratory Disease Pathogenomics, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
| | - Jianwei Wang
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, People’s Republic of China
- Key Laboratory of Respiratory Disease Pathogenomics, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People’s Republic of China
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Cao R, Du Y, Tong J, Xia D, Song Q, Xia Z, Liu M, Du H, Han J, Gao C. Influence of COVID-19 pandemic on the virus spectrum in children with respiratory infection in Xuzhou, China: a long-term active surveillance study from 2015 to 2021. BMC Infect Dis 2023; 23:467. [PMID: 37442963 DOI: 10.1186/s12879-023-08247-3] [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: 01/31/2023] [Accepted: 04/12/2023] [Indexed: 07/15/2023] Open
Abstract
BACKGROUND To investigate the impact of the coronavirus disease 2019 (COVID-19) outbreak on the prevalence of respiratory viruses among pediatric patients with acute respiratory infections in Xuzhou from 2015-2021. METHODS Severe acute respiratory infection (SARI) cases in hospitalized children were collected from 2015-2021 in Xuzhou, China. Influenza virus(IFV), respiratory syncytial virus (RSV), human parainfluenza virus type 3(hPIV-3), human rhinovirus (hRV), human adenovirus(hAdV), human coronavirus(hCoV) were detected by real-time fluorescence polymerase chain reaction(RT-qPCR), and the results were statistically analyzed by SPSS 23.0 software. RESULTS A total of 1663 samples with SARI were collected from 2015-2021, with a male-to-female ratio of 1.67:1 and a total virus detection rate of 38.5% (641/1663). The total detection rate of respiratory viruses decreased from 46.2% (2015-2019) to 36% (2020-2021) under the control measures for COVID-19 (P < 0.01). The three viruses with the highest detection rates changed from hRV, RSV, and hPIV-3 to hRV, RSV, and hCoV. The epidemic trend of hPIV-3 and hAdV was upside down before and after control measures(P < 0.01); however, the epidemic trend of RV and RSV had not changed from 2015 to 2021(P > 0.05). After the control measures, the detection rate of hPIV-3 decreased in all age groups, and the detection rate of hCoV increased in all except the 1 ~ 3 years old group. CONCLUSIONS Implementing control measures for COVID-19 outbreak curbed the spread of respiratory viruses among children as a whole. However, the epidemic of RV and RSV was not affected by the COVID-19 control policy.
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Affiliation(s)
- Rundong Cao
- Center for Viral Resource, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, 102206, China
| | - Yangguang Du
- Xuzhou Center for Disease Control and Prevention, Xuzhou, 221002, China
| | - Jing Tong
- Xuzhou Center for Disease Control and Prevention, Xuzhou, 221002, China
| | - Dong Xia
- Center for Viral Resource, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, 102206, China
| | - Qinqin Song
- Center for Viral Resource, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, 102206, China
| | - Zhiqiang Xia
- Center for Viral Resource, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, 102206, China
| | - Mi Liu
- Center for Viral Resource, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, 102206, China
| | - Haijun Du
- Center for Viral Resource, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, 102206, China
| | - Jun Han
- Center for Viral Resource, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, 102206, China.
| | - Chen Gao
- Center for Viral Resource, Chinese Center for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, 102206, China.
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19
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Yang MC, Su YT, Chen PH, Tsai CC, Lin TI, Wu JR. Changing patterns of infectious diseases in children during the COVID-19 pandemic. Front Cell Infect Microbiol 2023; 13:1200617. [PMID: 37457965 PMCID: PMC10339349 DOI: 10.3389/fcimb.2023.1200617] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 06/19/2023] [Indexed: 07/18/2023] Open
Abstract
Each infectious disease has had its own epidemic pattern and seasonality for decades. However, public health mitigation measures during the coronavirus disease 2019 (COVID-19) pandemic have resulted in changing epidemic patterns of infectious diseases. Stringent measures resulted in low incidences of various infectious diseases during the outbreak of COVID-19, including influenza, respiratory syncytial virus, pneumococcus, enterovirus, and parainfluenza. Owing to the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and subsequent immunity development, decreasing virulence of SARS-CoV-2, and worldwide immunization against SARS-CoV-2 in children beyond 6 months of age, mitigation measures are lifted country by country. Consequently, the immunity debt to infectious respiratory viruses other than SARS-CoV-2 contributed to the "off-season," "see-saw," and "upsurge" patterns of various infectious diseases in children. Moreover, apart from the persistence of SARS-CoV-2, the coexistence of other circulating viruses or bacterial outbreaks may lead to twindemics or tripledemics during the following years. Therefore, it is necessary to maintain hand hygiene and immunization policies against various pathogens to alleviate the ongoing impact of infectious diseases on children.
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Affiliation(s)
- Ming-Chun Yang
- Department of Pediatrics, E-DA Hospital, I-Shou University, Kaohsiung, Taiwan
- School of Medicine, College of Medicine, I-Shou University, Kaohsiung, Taiwan
| | - Yu-Tsun Su
- Department of Pediatrics, E-DA Hospital, I-Shou University, Kaohsiung, Taiwan
- School of Medicine for International Students, College of Medicine, I-Shou University, Kaohsiung, Taiwan
| | - Ping-Hong Chen
- Department of Pediatrics, E-DA Hospital, I-Shou University, Kaohsiung, Taiwan
| | - Ching-Chung Tsai
- Department of Pediatrics, E-DA Hospital, I-Shou University, Kaohsiung, Taiwan
- School of Medicine for International Students, College of Medicine, I-Shou University, Kaohsiung, Taiwan
| | - Ting-I Lin
- Department of Pediatrics, E-DA Hospital, I-Shou University, Kaohsiung, Taiwan
| | - Jiunn-Ren Wu
- Department of Pediatrics, E-DA Hospital, I-Shou University, Kaohsiung, Taiwan
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Pinky L, DeAguero JR, Remien CH, Smith AM. How Interactions during Viral-Viral Coinfection Can Shape Infection Kinetics. Viruses 2023; 15:1303. [PMID: 37376603 PMCID: PMC10301061 DOI: 10.3390/v15061303] [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: 04/19/2023] [Revised: 05/29/2023] [Accepted: 05/30/2023] [Indexed: 06/29/2023] Open
Abstract
Respiratory viral infections are a leading global cause of disease with multiple viruses detected in 20-30% of cases, and several viruses simultaneously circulating. Some infections with unique viral copathogens result in reduced pathogenicity, while other viral pairings can worsen disease. The mechanisms driving these dichotomous outcomes are likely variable and have only begun to be examined in the laboratory and clinic. To better understand viral-viral coinfections and predict potential mechanisms that result in distinct disease outcomes, we first systematically fit mathematical models to viral load data from ferrets infected with respiratory syncytial virus (RSV), followed by influenza A virus (IAV) after 3 days. The results suggest that IAV reduced the rate of RSV production, while RSV reduced the rate of IAV infected cell clearance. We then explored the realm of possible dynamics for scenarios that had not been examined experimentally, including a different infection order, coinfection timing, interaction mechanisms, and viral pairings. IAV coinfection with rhinovirus (RV) or SARS-CoV-2 (CoV2) was examined by using human viral load data from single infections together with murine weight-loss data from IAV-RV, RV-IAV, and IAV-CoV2 coinfections to guide the interpretation of the model results. Similar to the results with RSV-IAV coinfection, this analysis shows that the increased disease severity observed during murine IAV-RV or IAV-CoV2 coinfection was likely due to the slower clearance of IAV-infected cells by the other viruses. The improved outcome when IAV followed RV, on the other hand, could be replicated when the rate of RV infected cell clearance was reduced by IAV. Simulating viral-viral coinfections in this way provides new insights about how viral-viral interactions can regulate disease severity during coinfection and yields testable hypotheses ripe for experimental evaluation.
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Affiliation(s)
- Lubna Pinky
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Joseph R. DeAguero
- Bioinformatics and Computational Biology Program, University of Idaho, Moscow, ID 83844, USA
| | - Christopher H. Remien
- Department of Mathematics and Statistical Science, University of Idaho, Moscow, ID 83844, USA
| | - Amber M. Smith
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38163, USA
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Pinky L, DeAguero JR, Remien CH, Smith AM. How Interactions During Viral-Viral Coinfection Can Shape Infection Kinetics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.05.535744. [PMID: 37066297 PMCID: PMC10104040 DOI: 10.1101/2023.04.05.535744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Respiratory virus infections are a leading cause of disease worldwide with multiple viruses detected in 20-30% of cases and several viruses simultaneously circulating. Some infections with viral copathogens have been shown to result in reduced pathogenicity while other virus pairings can worsen disease. The mechanisms driving these dichotomous outcomes are likely variable and have only begun to be examined in the laboratory and clinic. To better understand viral-viral coinfections and predict potential mechanisms that result in distinct disease outcomes, we first systematically fit mathematical models to viral load data from ferrets infected with respiratory syncytial virus (RSV) followed by influenza A virus (IAV) after 3 days. The results suggested that IAV reduced the rate of RSV production while RSV reduced the rate of IAV infected cell clearance. We then explored the realm of possible dynamics for scenarios not examined experimentally, including different infection order, coinfection timing, interaction mechanisms, and viral pairings. IAV coinfection with rhinovirus (RV) or SARS-CoV-2 (CoV2) was examined by using human viral load data from single infections together with murine weight loss data from IAV-RV, RV-IAV, and IAV-CoV2 coinfections to guide the interpretation of the model results. Similar to the results with RSV-IAV coinfection, this analysis showed that the increased disease severity observed during murine IAV-RV or IAV-CoV2 coinfection was likely due to slower clearance of IAV infected cells by the other viruses. On the contrary, the improved outcome when IAV followed RV could be replicated when the rate of RV infected cell clearance was reduced by IAV. Simulating viral-viral coinfections in this way provides new insights about how viral-viral interactions can regulate disease severity during coinfection and yields testable hypotheses ripe for experimental evaluation.
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Fine SR, Bazzi LA, Callear AP, Petrie JG, Malosh RE, Foster‐Tucker JE, Smith M, Ibiebele J, McDermott A, Rolfes MA, Monto AS, Martin ET. Respiratory virus circulation during the first year of the COVID-19 pandemic in the Household Influenza Vaccine Evaluation (HIVE) cohort. Influenza Other Respir Viruses 2023; 17:e13106. [PMID: 36875204 PMCID: PMC9975790 DOI: 10.1111/irv.13106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 01/10/2023] [Indexed: 03/06/2023] Open
Abstract
Background The annual reappearance of respiratory viruses has been recognized for decades. COVID-19 mitigation measures taken during the pandemic were targeted at respiratory transmission and broadly impacted the burden of acute respiratory illnesses (ARIs). Methods We used the longitudinal Household Influenza Vaccine Evaluation (HIVE) cohort in southeast Michigan to characterize the circulation of respiratory viruses from March 1, 2020, to June 30, 2021, using RT-PCR of respiratory specimens collected at illness onset. Participants were surveyed twice during the study period, and SARS-CoV-2 antibodies were measured in serum by electrochemiluminescence immunoassay. Incidence rates of ARI reports and virus detections were compared between the study period and a preceding pre-pandemic period of similar duration. Results Overall, 437 participants reported a total of 772 ARIs; 42.6% had respiratory viruses detected. Rhinoviruses were the most frequent virus, but seasonal coronaviruses, excluding SARS-CoV-2, were also common. Illness reports and percent positivity were lowest from May to August 2020, when mitigation measures were most stringent. Seropositivity for SARS-CoV-2 was 5.3% in summer 2020 and increased to 11.3% in spring 2021. The incidence rate of total reported ARIs for the study period was 50% lower (95% CI: 0.5, 0.6; p < 0.001) than the incidence rate from a pre-pandemic comparison period (March 1, 2016, to June 30, 2017). Conclusions The burden of ARI in the HIVE cohort during the COVID-19 pandemic fluctuated, with declines occurring concurrently with the widespread use of public health measures. Rhinovirus and seasonal coronaviruses continued to circulate even when influenza and SARS-CoV-2 circulation was low.
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Affiliation(s)
- Sydney R. Fine
- Department of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
| | - Latifa A. Bazzi
- Department of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
- Present address:
Northwestern UniversityEvanstonIllinoisUSA
| | - Amy P. Callear
- Department of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
| | - Joshua G. Petrie
- Department of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
- Present address:
Marshfield Clinic Research InstituteMarshfieldWisconsinUSA
| | - Ryan E. Malosh
- Department of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
- Present address:
Michigan Department of Health and Human ServicesLansingMichiganUSA
| | | | - Matthew Smith
- Department of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
| | - Jessica Ibiebele
- Department of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
| | - Adrian McDermott
- Vaccine Research CenterNational Institute of Allergy and Infectious Diseases, National Institutes of HealthBethesdaMarylandUSA
| | - Melissa A. Rolfes
- Influenza DivisionCenters for Disease Control and PreventionAtlantaGeorgiaUSA
| | - Arnold S. Monto
- Department of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
| | - Emily T. Martin
- Department of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
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Wong A, Barrero Guevara LA, Goult E, Briga M, Kramer SC, Kovacevic A, Opatowski L, Domenech de Cellès M. The interactions of SARS-CoV-2 with cocirculating pathogens: Epidemiological implications and current knowledge gaps. PLoS Pathog 2023; 19:e1011167. [PMID: 36888684 PMCID: PMC9994710 DOI: 10.1371/journal.ppat.1011167] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023] Open
Abstract
Despite the availability of effective vaccines, the persistence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) suggests that cocirculation with other pathogens and resulting multiepidemics (of, for example, COVID-19 and influenza) may become increasingly frequent. To better forecast and control the risk of such multiepidemics, it is essential to elucidate the potential interactions of SARS-CoV-2 with other pathogens; these interactions, however, remain poorly defined. Here, we aimed to review the current body of evidence about SARS-CoV-2 interactions. Our review is structured in four parts. To study pathogen interactions in a systematic and comprehensive way, we first developed a general framework to capture their major components: sign (either negative for antagonistic interactions or positive for synergistic interactions), strength (i.e., magnitude of the interaction), symmetry (describing whether the interaction depends on the order of infection of interacting pathogens), duration (describing whether the interaction is short-lived or long-lived), and mechanism (e.g., whether interaction modifies susceptibility to infection, transmissibility of infection, or severity of disease). Second, we reviewed the experimental evidence from animal models about SARS-CoV-2 interactions. Of the 14 studies identified, 11 focused on the outcomes of coinfection with nonattenuated influenza A viruses (IAVs), and 3 with other pathogens. The 11 studies on IAV used different designs and animal models (ferrets, hamsters, and mice) but generally demonstrated that coinfection increased disease severity compared with either monoinfection. By contrast, the effect of coinfection on the viral load of either virus was variable and inconsistent across studies. Third, we reviewed the epidemiological evidence about SARS-CoV-2 interactions in human populations. Although numerous studies were identified, only a few were specifically designed to infer interaction, and many were prone to multiple biases, including confounding. Nevertheless, their results suggested that influenza and pneumococcal conjugate vaccinations were associated with a reduced risk of SARS-CoV-2 infection. Finally, fourth, we formulated simple transmission models of SARS-CoV-2 cocirculation with an epidemic viral pathogen or an endemic bacterial pathogen, showing how they can naturally incorporate the proposed framework. More generally, we argue that such models, when designed with an integrative and multidisciplinary perspective, will be invaluable tools to resolve the substantial uncertainties that remain about SARS-CoV-2 interactions.
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Affiliation(s)
- Anabelle Wong
- Infectious Disease Epidemiology group, Max Planck Institute for Infection Biology, Berlin, Germany
- Institute of Public Health, Charité–Universitätsmedizin Berlin, Berlin, Germany
| | - Laura Andrea Barrero Guevara
- Infectious Disease Epidemiology group, Max Planck Institute for Infection Biology, Berlin, Germany
- Institute of Public Health, Charité–Universitätsmedizin Berlin, Berlin, Germany
| | - Elizabeth Goult
- Infectious Disease Epidemiology group, Max Planck Institute for Infection Biology, Berlin, Germany
| | - Michael Briga
- Infectious Disease Epidemiology group, Max Planck Institute for Infection Biology, Berlin, Germany
| | - Sarah C. Kramer
- Infectious Disease Epidemiology group, Max Planck Institute for Infection Biology, Berlin, Germany
| | - Aleksandra Kovacevic
- Epidemiology and Modelling of Antibiotic Evasion, Institut Pasteur, Université Paris Cité, Paris, France
- Anti-infective Evasion and Pharmacoepidemiology Team, CESP, Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, INSERM U1018 Montigny-le-Bretonneux, France
| | - Lulla Opatowski
- Epidemiology and Modelling of Antibiotic Evasion, Institut Pasteur, Université Paris Cité, Paris, France
- Anti-infective Evasion and Pharmacoepidemiology Team, CESP, Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, INSERM U1018 Montigny-le-Bretonneux, France
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Sharp decline in rates of community respiratory viral detection among patients at the National Institutes of Health Clinical Center during the coronavirus disease 2019 (COVID-19) pandemic. Infect Control Hosp Epidemiol 2023; 44:62-67. [PMID: 35177161 PMCID: PMC9021590 DOI: 10.1017/ice.2022.31] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
OBJECTIVES To analyze the frequency and rates of community respiratory virus infections detected in patients at the National Institutes of Health Clinical Center (NIHCC) between January 2015 and March 2021, comparing the trends before and during the coronavirus disease 2019 (COVID-19) pandemic. METHODS We conducted a retrospective study comparing frequency and rates of community respiratory viruses detected in NIHCC patients between January 2015 and March 2021. Test results from nasopharyngeal swabs and washes, bronchoalveolar lavages, and bronchial washes were included in this study. Results from viral-challenge studies and repeated positives were excluded. A quantitative data analysis was completed using cross tabulations. Comparisons were performed using mixed models, applying the Dunnett correction for multiplicity. RESULTS Frequency of all respiratory pathogens declined from an annual range of 0.88%-1.97% between January 2015 and March 2020 to 0.29% between April 2020 and March 2021. Individual viral pathogens declined sharply in frequency during the same period, with no cases of influenza A/B orparainfluenza and 1 case of respiratory syncytial virus (RSV). Rhino/enterovirusdetection continued, but with a substantially lower frequency of 4.27% between April 2020 and March 2021, compared with an annual range of 8.65%-18.28% between January 2015 and March 2020. CONCLUSIONS The decrease in viral respiratory infections detected in NIHCC patients during the pandemic was likely due to the layered COVID-19 prevention and mitigation measures implemented in the community and the hospital. Hospitals should consider continuing the use of nonpharmaceutical interventions in the future to prevent nosocomial transmission of respiratory viruses during times of high community viral load.
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25
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Dee K, Schultz V, Haney J, Bissett LA, Magill C, Murcia PR. Influenza A and respiratory syncytial virus trigger a cellular response that blocks severe acute respiratory syndrome virus 2 infection in the respiratory tract. J Infect Dis 2022:6957417. [PMID: 36550077 DOI: 10.1093/infdis/jiac494] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 12/16/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Multiple viruses cocirculate and contribute to the burden of respiratory disease. Virus-virus interactions can decrease susceptibility to infection and this interference can have an epidemiological impact. As humans are normally exposed to a community of cocirculating respiratory viruses, experimental coinfection studies are necessary to understand the disease mechanisms of multi-pathogen systems. We aimed to characterize interactions within the respiratory tract between severe acute respiratory syndrome virus 2 (SARS-CoV-2) and two major respiratory viruses: influenza A virus (IAV), and respiratory syncytial virus (RSV). METHODS We performed single infections and coinfections with SARS-CoV-2 combined with IAV or RSV in cultures of human bronchial epithelial cells. We combined microscopy with quantification of viral replication in the presence or absence of an innate immune inhibitor to determine changes in virus-induced pathology, virus spread, and virus replication. RESULTS SARS-CoV-2 replication is inhibited by both IAV and RSV. This inhibition is dependent on a functional antiviral response and the level of inhibition is proportional to the timing of secondary viral infection. CONCLUSIONS Infections by other respiratory viruses might provide transient resistance to SARS-CoV-2. It would therefore be expected that the incidence of COVID-19 may decrease during periods of high circulation of IAV and RSV.Virus-virus interactions impact the infection dynamics of respiratory viruses at multiple levels, from cells to populations. Using three-dimensional cultures of airway epithelium, we showed that SARS-CoV-2 replication is impaired in coinfections with either influenza A or respiratory syncytial virus.
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Affiliation(s)
- Kieran Dee
- MRC-University of Glasgow Centre for Virus Research. Glasgow, G61 1QH, United Kingdom
| | - Verena Schultz
- MRC-University of Glasgow Centre for Virus Research. Glasgow, G61 1QH, United Kingdom
| | - Joanne Haney
- MRC-University of Glasgow Centre for Virus Research. Glasgow, G61 1QH, United Kingdom
| | - Laura A Bissett
- MRC-University of Glasgow Centre for Virus Research. Glasgow, G61 1QH, United Kingdom
| | - Callum Magill
- MRC-University of Glasgow Centre for Virus Research. Glasgow, G61 1QH, United Kingdom
| | - Pablo R Murcia
- MRC-University of Glasgow Centre for Virus Research. Glasgow, G61 1QH, United Kingdom
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Fine SR, Bazzi LA, Callear AP, Petrie JG, Malosh RE, Tucker JE, Smith M, Ibiebele J, McDermott A, Rolfes MA, Monto AS, Martin ET. Respiratory Virus Circulation during the First Year of the COVID-19 Pandemic in the Household Influenza Vaccine Evaluation (HIVE) Cohort. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.12.08.22283268. [PMID: 36523413 PMCID: PMC9753789 DOI: 10.1101/2022.12.08.22283268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background The annual reappearance of respiratory viruses has been recognized for decades. The onset of the COVID-19 pandemic altered typical respiratory virus transmission patterns. COVID-19 mitigation measures taken during the pandemic were targeted at SARS-CoV-2 respiratory transmission and thus broadly impacted the burden of acute respiratory illnesses (ARIs), in general. Methods We used the longitudinal Household Influenza Vaccine Evaluation (HIVE) cohort of households in southeast Michigan to characterize mitigation strategy adherence, respiratory illness burden, and the circulation of 15 respiratory viruses during the COVID-19 pandemic determined by RT-PCR of respiratory specimens collected at illness onset. Study participants were surveyed twice during the study period (March 1, 2020, to June 30, 2021), and serologic specimens were collected for antibody measurement by electrochemiluminescence immunoassay. Incidence rates of ARI reports and virus detections were calculated and compared using incidence rate ratios for the study period and a pre-pandemic period of similar length. Results Overall, 437 participants reported a total of 772 ARIs and 329 specimens (42.6%) had respiratory viruses detected. Rhinoviruses were the most frequently detected organism, but seasonal coronaviruses-excluding SARS-CoV-2-were also common. Illness reports and percent positivity were lowest from May to August 2020, when mitigation measures were most stringent. Study participants were more adherent to mitigation measures in the first survey compared with the second survey. Supplemental serology surveillance identified 5.3% seropositivity for SARS-CoV-2 in summer 2020; 3.0% between fall 2020 and winter 2021; and 11.3% in spring 2021. Compared to a pre-pandemic period of similar length, the incidence rate of total reported ARIs for the study period was 50% lower (95% CI: 0.5, 0.6; p<0.001) than the incidence rate from March 1, 2016, to June 30, 2017. Conclusions The burden of ARI in the HIVE cohort during the COVID-19 pandemic fluctuated, with declines occurring concurrently with the widespread use of public health measures. It is notable, however, that rhinovirus and seasonal coronaviruses continued to circulate even as influenza and SARS-CoV-2 circulation was low.
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27
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Geng Y, Hao Y, Xu X, Huang R, He F, Ni J, Zhan J, Chen Y, Hu F, Wu C. Clinical features and viral etiology of acute respiratory infection in an outpatient fever clinic during COVID-19 pandemic in a tertiary hospital in Nanjing, China. J Clin Lab Anal 2022; 36:e24778. [PMID: 36447425 PMCID: PMC9756996 DOI: 10.1002/jcla.24778] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 10/27/2022] [Accepted: 11/08/2022] [Indexed: 12/10/2023] Open
Abstract
BACKGROUND Clinical feature and viral etiology for acute respiratory infection (ARI) in the community was unknown during coronavirus disease 2019 (COVID-19) pandemic. OBJECTIVE In a retrospective study, we aimed to characterize the clinical feature and etiology for the ARI patients admitted to the outpatient fever clinic in Nanjing Drum Tower Hospital between November 2020 and March 2021. METHODS Fifteen common respiratory pathogens were tested using pharyngeal swabs by multiplex reverse transcriptase-polymerase chain reaction assays. RESULTS Of the 242 patients, 56 (23%) were tested positive for at least one viral agent. The predominant viruses included human rhinovirus (HRV) (5.4%), parainfluenza virus type III (PIV-III) (5.0%), and human coronavirus-NL63 (HCoV-NL63) (3.7%). Cough, sputum, nasal obstruction, and rhinorrhea were the most prevalent symptoms in patients with viral infection. Elderly and the patients with underlying diseases were susceptible to pneumonia accompanied with sputum and chest oppression. Three (5.4%) patients in virus infection group, whereas 31 (16.7%) in non-viral infection group (p = 0.033), were empirically prescribed with antiviral agents. Among 149 patients who received antibiotic therapy, 30 (20.1%) patients were later identified with viral infection. CONCLUSION Our study indicated the importance of accurate diagnosis of ARI, especially during the COVID-19 pandemic, which might facilitate appropriate clinical treatment.
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Affiliation(s)
- Yu Geng
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western MedicineNanjing University of Chinese MedicineNanjingChina
| | - Yingying Hao
- Department of Intensive Care UnitsNanjing Drum Tower Hospital, Nanjing University Medical SchoolNanjingChina
| | - Xiaoming Xu
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western MedicineNanjing University of Chinese MedicineNanjingChina
| | - Rui Huang
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western MedicineNanjing University of Chinese MedicineNanjingChina
| | - Fei He
- Department of Emergency MedicineNanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical SchoolNanjingChina
| | - Jun Ni
- Department of Laboratory MedicineNanjing Drum Tower Hospital Clinical College of Jiangsu University, Jiangsu UniversityNanjingChina
| | - Jie Zhan
- Department of Infectious DiseasesNanjing Drum Tower Hospital, Clinical College of Nanjing Medical UniversityNanjingJiangsuChina
| | - Yuxin Chen
- Department of Laboratory MedicineNanjing Drum Tower Hospital Clinical College of Jiangsu University, Jiangsu UniversityNanjingChina
| | - FengHua Hu
- Department of Laboratory MedicineNanjing Drum Tower Hospital Clinical College of Jiangsu University, Jiangsu UniversityNanjingChina
| | - Chao Wu
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western MedicineNanjing University of Chinese MedicineNanjingChina
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Cui A, Xie Z, Xu J, Hu K, Zhu R, Li Z, Li Y, Sun L, Xiang X, Xu B, Zhang R, Gao Z, Zhang Y, Xu W. Comparative analysis of the clinical and epidemiological characteristics of human influenza virus versus human respiratory syncytial virus versus human metapneumovirus infection in nine provinces of China during 2009-2021. J Med Virol 2022; 94:5894-5903. [PMID: 35981880 DOI: 10.1002/jmv.28073] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 07/29/2022] [Accepted: 08/16/2022] [Indexed: 01/06/2023]
Abstract
A comparative analysis of confirmed cases of human influenza virus (HIFV), human respiratory syncytial virus (HRSV), and human metapneumovirus (HMPV) was conducted to describe their clinical and epidemiological characteristics. During 2009-2021, active surveillance of acute respiratory infections (ARIs) was performed in nine provinces of China. Clinical and epidemiological information and laboratory testing results of HIFV, HRSV, and HMPV were analyzed. Among 11591 ARI patients, the single-infection rates of HIFV, HRSV, and HMPV were 15.00%, 9.59%, and 2.24%, respectively; the coinfection rate of these three viruses was 0.64%. HIFV infection was mainly in adults aged 15-59 years, accounting for 39.10%. HRSV and HMPV infections were mainly in children under 5 years old, accounting for 87.13% and 83.46%, respectively. Patients with HRSV infection were younger than HMPV. HRSV and HMPV had high similarities in clinical manifestations, presenting with lower respiratory symptoms. HIFV mainly presented with an upper respiratory infection. The epidemic peak of HRSV was earlier than that of HIFV, and that of HMPV was later than those of HRSV and HFIV. A total of 85.14% of coinfection cases were children under 5 years old. Coinfection might increase the risk of pneumonia in HIFV cases. During 2020-2021, the positive rates and seasonal patterns of these three viruses changed due to the impact of the COVID-19 pandemic. Certain clinical and epidemiological features were observed in HIFV, HRSV, and HMPV infections, which could be beneficial for guiding clinical diagnosis, treatment, and prevention of these three viruses in China.
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Affiliation(s)
- Aili Cui
- NHC Key Laboratory of Medical Virology and Viral Diseases, Chinese Centers for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Zhibo Xie
- NHC Key Laboratory of Medical Virology and Viral Diseases, Chinese Centers for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Jing Xu
- Viral Disease Department, Shaanxi Center for Disease Control and Prevention, Xi'an, China
| | - Kongxin Hu
- Institute of Health Inspection and Quarantine, Chinese Academy of Inspection and Quarantine, Beijing, China
| | - Runan Zhu
- Department of Virology, Beijing Key Laboratory of Pediatric Virology, Capital Institute of Pediatrics, Beijing, China
| | - Zhong Li
- Department of Viral Diseases, Shandong Center for Disease Control and Prevention, Institute for Communicable Disease Control and Prevention, Jinan, China
| | - Yan Li
- Hebei Center for Disease Control and Prevention, Institute for Prevention and Control of Viral Diseases, Shijiazhuang, China
| | - Liwei Sun
- Precision Medicine Research Center, Children's Hospital of Changchun, Changchun, China
| | - Xingyu Xiang
- Microbiological Examination Department, Hunan Center for Disease Control and Prevention, Changsha, China
| | - Baoping Xu
- Respiratory Department, Research Unit of Critical Infection in Children, China National Clinical Research Center of Respiratory Diseases, National Center for Children's Health, Beijing Children's Hospital, Chinese Academy of Medical Sciences, Capital Medical University, Beijing, China
| | - Rongbo Zhang
- Department of Immunology, School of Medicine, Anhui University of Science and Technology, Huainan, China
| | - Zhenguo Gao
- Xinjiang Uyghur Autonomous Region Center for Disease Control and Prevention, Institute for Infectious Disease Prevention and Treatment, Wulumuqi, China
| | - Yan Zhang
- NHC Key Laboratory of Medical Virology and Viral Diseases, Chinese Centers for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
| | - Wenbo Xu
- NHC Key Laboratory of Medical Virology and Viral Diseases, Chinese Centers for Disease Control and Prevention, National Institute for Viral Disease Control and Prevention, Beijing, China
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Qiu W, Zheng C, Huang S, Zhang Y, Chen Z. Epidemiological Trend of RSV Infection Before and During COVID-19 Pandemic: A Three-Year Consecutive Study in China. Infect Drug Resist 2022; 15:6829-6837. [PMID: 36465809 PMCID: PMC9717604 DOI: 10.2147/idr.s388231] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 11/18/2022] [Indexed: 07/22/2023] Open
Abstract
OBJECTIVE This study aimed to explore the epidemiological trend and clinical characteristics of respiratory syncytial virus (RSV) infection among inpatient children with lower respiratory tract infection (LRTI) before and during the coronavirus disease 2019 (COVID-19) pandemic. METHODS A retrospective study of inpatients with LRTI was conducted at the Department of Pulmonology, The Children's Hospital, Zhejiang University School of Medicine (Hangzhou, China) from January 2019 to December 2021. All respiratory specimens were tested for common respiratory pathogens. The clinical data in children with RSV-induced LRTI in the past three years were collected and analyzed. RESULTS A total of 11,290 patients were enrolled, and RSV positive cases were 402 (7.6%), 288 (9.6%), 415 (13.8%) in 2019, 2020, 2021, respectively, with a significant statistical difference of the RSV positive rate among the three groups (p < 0.001). Most patients were under 2-year old, especially under 1-year old, and the median age of patients was 4 months, 5 months, 6 months in 2019, 2020, 2021, respectively, with a tendency to increase in age. In terms of the seasonal distribution, most patients of LRTI with RSV infection were admitted in winter, while in 2021 compared with in 2019, the cases significantly reduced in winter and increased in autumn. From 2019 to 2021, there was an increase in autumn trend year by year. CONCLUSION RSV infection was still an important cause of hospitalization in children with LRTI after the outbreak of COVID-19, and its proportion increased gradually. LRTI caused by RSV is still more common in infants under 1-year old, but there is a trend of increasing in older children. What deserves the attention of pediatricians and Center for Disease Control is that the incidence of RSV infection continues to rise in autumn, and the difference in seasonal distribution is narrowed.
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Affiliation(s)
- Weiling Qiu
- Department of Pulmonology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children’s Regional Medical Center, Hangzhou, Zhejiang, People’s Republic of China
| | - Chen Zheng
- Department of Pulmonology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children’s Regional Medical Center, Hangzhou, Zhejiang, People’s Republic of China
| | - Shumin Huang
- Department of Pulmonology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children’s Regional Medical Center, Hangzhou, Zhejiang, People’s Republic of China
| | - Yuanyuan Zhang
- Department of Pulmonology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children’s Regional Medical Center, Hangzhou, Zhejiang, People’s Republic of China
| | - Zhimin Chen
- Department of Pulmonology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children’s Regional Medical Center, Hangzhou, Zhejiang, People’s Republic of China
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30
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Respiratory Syncytial Virus Protects Bystander Cells against Influenza A Virus Infection by Triggering Secretion of Type I and Type III Interferons. J Virol 2022; 96:e0134122. [DOI: 10.1128/jvi.01341-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Influenza A virus (IAV) and respiratory syncytial virus (RSV) are common recurrent respiratory infectants that show a relatively high coincidence. We demonstrated that preinfection with RSV partitions the cell population into a subpopulation susceptible to subsequent infection with IAV and an IAV-proof subpopulation.
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Smith M, Kubale J, Kuan G, Ojeda S, Vydiswaran N, Sanchez N, Gresh L, Latta K, Lopez R, Patel M, Balmaseda A, Gordon A. Respiratory Syncytial Virus Incidence and Severity in a Community-Based Prospective Cohort of Children Aged 0-14 Years. Open Forum Infect Dis 2022; 9:ofac598. [PMID: 36447616 PMCID: PMC9697591 DOI: 10.1093/ofid/ofac598] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 11/01/2022] [Indexed: 01/08/2024] Open
Abstract
BACKGROUND Respiratory syncytial virus (RSV) is a substantial source of severe illnesses including acute lower respiratory infections (ALRIs) like pneumonia. However, its burden in older children remains less well understood. METHODS Using a community-based prospective cohort, we assessed the burden of symptomatic reverse-transcription polymerase chain reaction-confirmed RSV among Nicaraguan children aged 0-14 years from 2011 to 2016. ALRI was defined as physician diagnosis of pneumonia, bronchiolitis, bronchitis, or bronchial hyperreactivity. RESULTS Between 2011 and 2016, 2575 children participated in the cohort. Of these, 630 (24.5%) had at least 1 episode of symptomatic RSV and 194 (7.5%) had multiple episodes. Subtype was identified in 571 (69.3%) episodes with 408 (71.5%) RSV-A, 157 (27.5%) RSV-B, and 6 (1%) positive for both. Children aged <2 years displayed the highest incidence of symptomatic RSV, with 269.3 cases per 1000 person-years (95% confidence interval [CI], 242.1-299.5). Beyond 2 years, incidence (95% CI) of symptomatic RSV decreased rapidly: 145.6 (129.9-163.1), 37.9 (31.9-45.0), and 19.3 (14.9-25.0) cases per 1000 person-years among children aged 2-4, 5-9, and 10-14 years, respectively. Incidence of RSV-associated ALRI was highest in children aged <2 years (85.95 per 1000 person-years [95% CI, 71.30-103.61]): 2.1, 9.5, and 17.3 times that of participants aged 2-4, 5-9, and 10-14 years, respectively. Children <2 years old were significantly more likely to have an RSV-associated hospitalization (P < .001). CONCLUSIONS There is a substantial burden of symptomatic and severe RSV in children. While older children did present with RSV, the rates of symptomatic and severe RSV decreased by as much as 95% beyond age 5.
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Affiliation(s)
- Matthew Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - John Kubale
- ICPSR, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, USA
| | - Guillermina Kuan
- Health Center Sócrates Flores Vivas, Ministry of Health, Managua, Nicaragua
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Sergio Ojeda
- Health Center Sócrates Flores Vivas, Ministry of Health, Managua, Nicaragua
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Nivea Vydiswaran
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Nery Sanchez
- Health Center Sócrates Flores Vivas, Ministry of Health, Managua, Nicaragua
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Lionel Gresh
- Sustainable Sciences Institute, Managua, Nicaragua
| | - Krista Latta
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Roger Lopez
- Sustainable Sciences Institute, Managua, Nicaragua
- Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua
| | - May Patel
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Angel Balmaseda
- Sustainable Sciences Institute, Managua, Nicaragua
- Centro Nacional de Diagnóstico y Referencia, Ministry of Health, Managua, Nicaragua
| | - Aubree Gordon
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
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Klitting R, Kafetzopoulou LE, Thiery W, Dudas G, Gryseels S, Kotamarthi A, Vrancken B, Gangavarapu K, Momoh M, Sandi JD, Goba A, Alhasan F, Grant DS, Okogbenin S, Ogbaini-Emovo E, Garry RF, Smither AR, Zeller M, Pauthner MG, McGraw M, Hughes LD, Duraffour S, Günther S, Suchard MA, Lemey P, Andersen KG, Dellicour S. Predicting the evolution of the Lassa virus endemic area and population at risk over the next decades. Nat Commun 2022; 13:5596. [PMID: 36167835 PMCID: PMC9515147 DOI: 10.1038/s41467-022-33112-3] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 09/02/2022] [Indexed: 01/27/2023] Open
Abstract
Lassa fever is a severe viral hemorrhagic fever caused by a zoonotic virus that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate and land use changes could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence using ecological niche modelling, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. Based on projections of climate, land use, and population changes, we find that regions in Central and East Africa will likely become suitable for Lassa virus over the next decades and estimate that the total population living in ecological conditions that are suitable for Lassa virus circulation may drastically increase by 2070. By analysing geotagged viral genomes using spatially-explicit phylogeography and simulating virus dispersal, we find that in the event of Lassa virus being introduced into a new suitable region, its spread might remain spatially limited over the first decades.
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Affiliation(s)
- Raphaëlle Klitting
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, 92037, USA.
| | - Liana E. Kafetzopoulou
- grid.5596.f0000 0001 0668 7884Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven - University of Leuven, Leuven, Belgium ,grid.424065.10000 0001 0701 3136Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany
| | - Wim Thiery
- grid.8767.e0000 0001 2290 8069Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel, Brussels, Belgium
| | - Gytis Dudas
- grid.6441.70000 0001 2243 2806Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania
| | - Sophie Gryseels
- grid.5284.b0000 0001 0790 3681Evolutionary Ecology group, Department of Biology, University of Antwerp, 2610 Antwerp, Belgium ,grid.20478.390000 0001 2171 9581Vertebrate group, Directorate Taxonomy and Phylogeny, Royal Belgian Institute of Natural Sciences, 1000 Brussels, Belgium
| | - Anjali Kotamarthi
- grid.214007.00000000122199231Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037 USA
| | - Bram Vrancken
- grid.5596.f0000 0001 0668 7884Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven - University of Leuven, Leuven, Belgium
| | - Karthik Gangavarapu
- grid.214007.00000000122199231Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037 USA
| | - Mambu Momoh
- grid.442296.f0000 0001 2290 9707Eastern Technical University of Sierra Leone, Kenema, Sierra Leone ,grid.463455.50000 0004 1799 2069Viral Hemorrhagic Fever Program, Kenema Government Hospital, Ministry of Health and Sanitation, Kenema, Sierra Leone
| | - John Demby Sandi
- grid.463455.50000 0004 1799 2069Viral Hemorrhagic Fever Program, Kenema Government Hospital, Ministry of Health and Sanitation, Kenema, Sierra Leone
| | - Augustine Goba
- grid.463455.50000 0004 1799 2069Viral Hemorrhagic Fever Program, Kenema Government Hospital, Ministry of Health and Sanitation, Kenema, Sierra Leone
| | - Foday Alhasan
- grid.463455.50000 0004 1799 2069Viral Hemorrhagic Fever Program, Kenema Government Hospital, Ministry of Health and Sanitation, Kenema, Sierra Leone
| | - Donald S. Grant
- grid.463455.50000 0004 1799 2069Viral Hemorrhagic Fever Program, Kenema Government Hospital, Ministry of Health and Sanitation, Kenema, Sierra Leone ,grid.442296.f0000 0001 2290 9707College of Medicine and Allied Health Sciences, University of Sierra Leone, Kenema, Sierra Leone
| | - Sylvanus Okogbenin
- grid.508091.5Irrua Specialist Teaching Hospital, Irrua, Nigeria ,grid.411357.50000 0000 9018 355XFaculty of Clinical Sciences, College of Medicine, Ambrose Alli University, Ekpoma, Nigeria
| | | | - Robert F. Garry
- grid.265219.b0000 0001 2217 8588Department of Microbiology and Immunology, Tulane University, School of Medicine, New Orleans, LA 70112 USA ,grid.505518.c0000 0004 5901 1919Zalgen Labs, LCC, Frederick, MD 21703 USA ,grid.475149.aGlobal Virus Network (GVN), Baltimore, MD 21201 USA
| | - Allison R. Smither
- grid.265219.b0000 0001 2217 8588Department of Microbiology and Immunology, Tulane University, School of Medicine, New Orleans, LA 70112 USA
| | - Mark Zeller
- grid.214007.00000000122199231Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037 USA
| | - Matthias G. Pauthner
- grid.214007.00000000122199231Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037 USA
| | - Michelle McGraw
- grid.214007.00000000122199231Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037 USA
| | - Laura D. Hughes
- grid.214007.00000000122199231Department of Integrative, Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037 USA
| | - Sophie Duraffour
- grid.424065.10000 0001 0701 3136Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany ,grid.452463.2German Center for Infection Research (DZIF), Partner site Hamburg–Lübeck–Borstel–Riems, Hamburg, Germany
| | - Stephan Günther
- grid.424065.10000 0001 0701 3136Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany ,grid.452463.2German Center for Infection Research (DZIF), Partner site Hamburg–Lübeck–Borstel–Riems, Hamburg, Germany
| | - Marc A. Suchard
- grid.19006.3e0000 0000 9632 6718Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Biostatistics, Fielding School of Public Health, University of California, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA USA
| | - Philippe Lemey
- grid.5596.f0000 0001 0668 7884Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven - University of Leuven, Leuven, Belgium
| | - Kristian G. Andersen
- grid.214007.00000000122199231Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA 92037 USA ,grid.214007.00000000122199231Scripps Research Translational Institute, La Jolla, CA 92037 USA
| | - Simon Dellicour
- Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory for Clinical and Epidemiological Virology, KU Leuven - University of Leuven, Leuven, Belgium. .,Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, CP160/12 50, av. FD Roosevelt, 1050, Bruxelles, Belgium.
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Jones RP, Ponomarenko A. Roles for Pathogen Interference in Influenza Vaccination, with Implications to Vaccine Effectiveness (VE) and Attribution of Influenza Deaths. Infect Dis Rep 2022; 14:710-758. [PMID: 36286197 PMCID: PMC9602062 DOI: 10.3390/idr14050076] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 09/15/2022] [Accepted: 09/15/2022] [Indexed: 08/29/2023] Open
Abstract
Pathogen interference is the ability of one pathogen to alter the course and clinical outcomes of infection by another. With up to 3000 species of human pathogens the potential combinations are vast. These combinations operate within further immune complexity induced by infection with multiple persistent pathogens, and by the role which the human microbiome plays in maintaining health, immune function, and resistance to infection. All the above are further complicated by malnutrition in children and the elderly. Influenza vaccination offers a measure of protection for elderly individuals subsequently infected with influenza. However, all vaccines induce both specific and non-specific effects. The specific effects involve stimulation of humoral and cellular immunity, while the nonspecific effects are far more nuanced including changes in gene expression patterns and production of small RNAs which contribute to pathogen interference. Little is known about the outcomes of vaccinated elderly not subsequently infected with influenza but infected with multiple other non-influenza winter pathogens. In this review we propose that in certain years the specific antigen mix in the seasonal influenza vaccine inadvertently increases the risk of infection from other non-influenza pathogens. The possibility that vaccination could upset the pathogen balance, and that the timing of vaccination relative to the pathogen balance was critical to success, was proposed in 2010 but was seemingly ignored. Persons vaccinated early in the winter are more likely to experience higher pathogen interference. Implications to the estimation of vaccine effectiveness and influenza deaths are discussed.
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Affiliation(s)
- Rodney P Jones
- Healthcare Analysis and Forecasting, Wantage OX12 0NE, UK
| | - Andrey Ponomarenko
- Department of Biophysics, Informatics and Medical Instrumentation, Odessa National Medical University, Valikhovsky Lane 2, 65082 Odessa, Ukraine
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34
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Takashima MD, Grimwood K, Sly PD, Lambert SB, Ware RS. Interference between rhinovirus and other RNA respiratory viruses in the first 2-years of life: A longitudinal community-based birth cohort study. J Clin Virol 2022; 155:105249. [PMID: 35939878 DOI: 10.1016/j.jcv.2022.105249] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 07/27/2022] [Accepted: 07/30/2022] [Indexed: 10/16/2022]
Abstract
BACKGROUND Cross-sectional studies report negative associations between rhinovirus and other RNA respiratory viruses. However, longitudinal studies with frequent, serial sampling are needed to identify the directionality of this relationship and its nature. OBJECTIVE To investigate the association between rhinovirus and other RNA respiratory viruses detected 1-week apart. METHODS The Observational Research in Childhood Infectious Diseases cohort study was conducted in Brisbane, Australia (2010-2014). Parents collected nasal swabs weekly from birth until age 2-years. Swabs were analysed by real-time polymerase chain reaction. The association between new rhinovirus detections and five other RNA viruses (influenza, respiratory syncytial virus, parainfluenza viruses, seasonal human coronaviruses, and human metapneumovirus) in paired swabs 1-week apart were investigated. RESULTS Overall, 157 children provided 8,101 swabs, from which 4,672 paired swabs 1-week apart were analysed. New rhinovirus detections were negatively associated with new pooled RNA respiratory virus detections 1-week later (adjusted odds ratio (aOR) 0.48; 95% confidence interval (CI): 0.13-0.83), as were pooled RNA virus detections with new rhinovirus detections the following week (aOR 0.34; 95%CI: 0.09-0.60). At the individual species level, rhinovirus had the strongest negative association with new seasonal human coronavirus detections in the subsequent week (aOR 0.34; 95%CI: 0.120.95) and respiratory syncytial virus had the strongest negative association with rhinovirus 1-week later (aOR 0.21; 95%CI: 0.050.88). CONCLUSION A strong, negative bidirectional association was observed between rhinovirus and other RNA viruses in a longitudinal study of a community-based cohort of young Australian children. This suggests within-host interference between RNA respiratory viruses.
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Affiliation(s)
- Mari D Takashima
- Menzies Health Institute Queensland and School of Medicine and Dentistry, Griffith University, Gold Coast 4222, Queensland, Australia.
| | - Keith Grimwood
- Menzies Health Institute Queensland and School of Medicine and Dentistry, Griffith University, Gold Coast 4222, Queensland, Australia; Departments of Infectious Diseases and Paediatrics, Gold Coast Health, Gold Coast 4215, Queensland, Australia
| | - Peter D Sly
- Children's Health and Environment Program, Child Health Research Centre, The University of Queensland, South Brisbane 4101, Queensland, Australia; Australian Infectious Diseases Research Centre, The University of Queensland, St Lucia 4072, Queensland, Australia
| | - Stephen B Lambert
- UQ Centre for Clinical Research, The University of Queensland, Herston 4006, Queensland, Australia; National Centre for Immunisation Research and Surveillance, Westmead 2145, New South Wales, Australia
| | - Robert S Ware
- Menzies Health Institute Queensland and School of Medicine and Dentistry, Griffith University, Gold Coast 4222, Queensland, Australia
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35
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Chan KF, Duarte JDG, Ostrouska S, Behren A. γδ T Cells in the Tumor Microenvironment-Interactions With Other Immune Cells. Front Immunol 2022; 13:894315. [PMID: 35880177 PMCID: PMC9307934 DOI: 10.3389/fimmu.2022.894315] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Accepted: 06/15/2022] [Indexed: 01/02/2023] Open
Abstract
A growing number of studies have shown that γδ T cells play a pivotal role in mediating the clearance of tumors and pathogen-infected cells with their potent cytotoxic, cytolytic, and unique immune-modulating functions. Unlike the more abundant αβ T cells, γδ T cells can recognize a broad range of tumors and infected cells without the requirement of antigen presentation via major histocompatibility complex (MHC) molecules. Our group has recently demonstrated parts of the mechanisms of T-cell receptor (TCR)-dependent activation of Vγ9Vδ2+ T cells by tumors following the presentation of phosphoantigens, intermediates of the mevalonate pathway. This process is mediated through the B7 immunoglobulin family-like butyrophilin 2A1 (BTN2A1) and BTN3A1 complexes. Such recognition results in activation, a robust immunosurveillance process, and elicits rapid γδ T-cell immune responses. These include targeted cell killing, and the ability to produce copious quantities of cytokines and chemokines to exert immune-modulating properties and to interact with other immune cells. This immune cell network includes αβ T cells, B cells, dendritic cells, macrophages, monocytes, natural killer cells, and neutrophils, hence heavily influencing the outcome of immune responses. This key role in orchestrating immune cells and their natural tropism for tumor microenvironment makes γδ T cells an attractive target for cancer immunotherapy. Here, we review the current understanding of these important interactions and highlight the implications of the crosstalk between γδ T cells and other immune cells in the context of anti-tumor immunity.
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Affiliation(s)
- Kok Fei Chan
- Olivia Newton-John Cancer Research Institute, and School of Cancer Medicine, La Trobe University, Heidelberg, VIC, Australia
| | - Jessica Da Gama Duarte
- Olivia Newton-John Cancer Research Institute, and School of Cancer Medicine, La Trobe University, Heidelberg, VIC, Australia
| | - Simone Ostrouska
- Olivia Newton-John Cancer Research Institute, and School of Cancer Medicine, La Trobe University, Heidelberg, VIC, Australia
| | - Andreas Behren
- Olivia Newton-John Cancer Research Institute, and School of Cancer Medicine, La Trobe University, Heidelberg, VIC, Australia
- Department of Medicine, University of Melbourne, Parkville, VIC, Australia
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36
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Nazareno AL, Muscatello DJ, Turner RM, Wood JG, Moore HC, Newall AT. Modelled estimates of hospitalisations attributable to respiratory syncytial virus and influenza in Australia, 2009-2017. Influenza Other Respir Viruses 2022; 16:1082-1090. [PMID: 35775106 PMCID: PMC9530581 DOI: 10.1111/irv.13003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Revised: 03/30/2022] [Accepted: 04/17/2022] [Indexed: 11/30/2022] Open
Abstract
Background Respiratory syncytial virus (RSV) and influenza are important causes of disease in children and adults. In Australia, information on the burden of RSV in adults is particularly limited. Methods We used time series analysis to estimate respiratory, acute respiratory infection, pneumonia and influenza, and bronchiolitis hospitalisations attributable to RSV and influenza in Australia during 2009 through 2017. RSV and influenza‐coded hospitalisations in <5‐year‐olds were used as proxies for relative weekly viral activity. Results From 2009 to 2017, the estimated all‐age average annual rates of respiratory hospitalisations attributable to RSV and seasonal influenza (excluding 2009) were 54.8 (95% confidence interval [CI]: 20.1, 88.8) and 87.8 (95% CI: 74.5, 97.7) per 100,000, respectively. The highest estimated average annual RSV‐attributable respiratory hospitalisation rate per 100,000 was 464.2 (95% CI: 285.9, 641.2) in <5‐year‐olds. For seasonal influenza, it was 521.6 (95% CI: 420.9, 600.0) in persons aged ≥75 years. In ≥75‐year‐olds, modelled estimates were approximately eight and two times the coded estimates for RSV and seasonal influenza, respectively. Conclusions RSV and influenza are major causes of hospitalisation in young children and older adults in Australia, with morbidity underestimated by hospital diagnosis codes.
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Affiliation(s)
- Allen L Nazareno
- School of Population Health, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia.,Institute of Mathematical Sciences and Physics, College of Arts and Sciences, University of the Philippines Los Baños, Laguna, Philippines
| | - David J Muscatello
- School of Population Health, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Robin M Turner
- Biostatistics Centre, Division of Health Sciences, University of Otago, Dunedin, New Zealand
| | - James G Wood
- School of Population Health, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
| | - Hannah C Moore
- Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, Perth, Western Australia, Australia
| | - Anthony T Newall
- School of Population Health, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia
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37
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Seo SU, Seong BL. Prospects on Repurposing a Live Attenuated Vaccine for the Control of Unrelated Infections. Front Immunol 2022; 13:877845. [PMID: 35651619 PMCID: PMC9149153 DOI: 10.3389/fimmu.2022.877845] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Accepted: 03/31/2022] [Indexed: 12/03/2022] Open
Abstract
Live vaccines use attenuated microbes to acquire immunity against pathogens in a safe way. As live attenuated vaccines (LAVs) still maintain infectivity, the vaccination stimulates diverse immune responses by mimicking natural infection. Induction of pathogen-specific antibodies or cell-mediated cytotoxicity provides means of specific protection, but LAV can also elicit unintended off-target effects, termed non-specific effects. Such mechanisms as short-lived genetic interference and non-specific innate immune response or long-lasting trained immunity and heterologous immunity allow LAVs to develop resistance to subsequent microbial infections. Based on their safety and potential for interference, LAVs may be considered as an alternative for immediate mitigation and control of unexpected pandemic outbreaks before pathogen-specific therapeutic and prophylactic measures are deployed.
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Affiliation(s)
- Sang-Uk Seo
- Department of Microbiology, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Baik-Lin Seong
- Department of Microbiology, Yonsei University College of Medicine, Seoul, South Korea.,Vaccine Innovative Technology ALliance (VITAL)-Korea, Yonsei University, Seoul, South Korea
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38
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Dai Y, Zhong J, Lan Y. Virus-virus interactions of febrile respiratory syndrome among patients in China based on surveillance data from February 2011 to December 2020. J Med Virol 2022; 94:4369-4377. [PMID: 35514049 DOI: 10.1002/jmv.27833] [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: 12/29/2021] [Revised: 04/17/2022] [Accepted: 05/02/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND The burden of acute respiratory infections is still considerable, and virus-virus interactions may affect their epidemics, but previous evidence is inconclusive. OBJECTIVE To quantitatively investigate the interactions among respiratory viruses at both the population and individual levels. METHODS Cases tested for influenza virus (IV), respiratory syncytial virus (RSV), human parainfluenza virus (PIV), human Adenovirus (AdV), human coronavirus (CoV), human bocavirus (BoV) and rhinoviruses (RV) were collected from the pathogen surveillance for febrile respiratory syndrome (FRS) in China from February 2011 to December 2020. We used spearman's rank correlation coefficients and binary logistic regression models to analyze the interactions between any two of the viruses at the population and individual levels, respectively. RESULTS Among 120,237 cases, 4.5% were co-infected with two or more viruses. Correlation coefficients showed 7 virus pairs were positively correlated, namely: IV and RSV, PIV and AdV, PIV and CoV, PIV and BoV, PIV and RV, AdV and BoV, CoV and RV. Regression models showed except for the negative interaction between IV and RV (OR=0.70, 95%CI: 0.61-0.81), all other virus pairs had positive interactions. CONCLUSION Most of the respiratory viruses interact positively, while IV and RV interact negatively. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Yucen Dai
- Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China, 610041
| | - Jiao Zhong
- Department of Occupational and Environmental Medicine, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China, 610041.,Department of Osteoporosis, West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China, 610041
| | - Yajia Lan
- Department of Occupational and Environmental Medicine, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China, 610041
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Treatment of Respiratory Viral Coinfections. EPIDEMIOLGIA (BASEL, SWITZERLAND) 2022; 3:81-96. [PMID: 36417269 PMCID: PMC9620919 DOI: 10.3390/epidemiologia3010008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 01/18/2022] [Accepted: 02/01/2022] [Indexed: 12/14/2022]
Abstract
With the advent of rapid multiplex PCR, physicians have been able to test for multiple viral pathogens when a patient presents with influenza-like illness. This has led to the discovery that many respiratory infections are caused by more than one virus. Antiviral treatment of viral coinfections can be complex because treatment of one virus will affect the time course of the other virus. Since effective antivirals are only available for some respiratory viruses, careful consideration needs to be given on the effect treating one virus will have on the dynamics of the other virus, which might not have available antiviral treatment. In this study, we use mathematical models of viral coinfections to assess the effect of antiviral treatment on coinfections. We examine the effect of the mechanism of action, relative growth rates of the viruses, and the assumptions underlying the interaction of the viruses. We find that high antiviral efficacy is needed to suppress both infections. If high doses of both antivirals are not achieved, then we run the risk of lengthening the duration of coinfection or even of allowing a suppressed virus to replicate to higher viral titers.
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40
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Influenza A(H1N1)pdm09 Virus but Not Respiratory Syncytial Virus Interferes with SARS-CoV-2 Replication during Sequential Infections in Human Nasal Epithelial Cells. Viruses 2022; 14:v14020395. [PMID: 35215988 PMCID: PMC8879759 DOI: 10.3390/v14020395] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 02/11/2022] [Accepted: 02/13/2022] [Indexed: 12/17/2022] Open
Abstract
The types of interactions between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory viruses are not well-characterized due to the low number of co-infection cases described since the onset of the pandemic. We have evaluated the interactions between SARS-CoV-2 (D614G mutant) and influenza A(H1N1)pdm09 or respiratory syncytial virus (RSV) in the nasal human airway epithelium (HAE) infected simultaneously or sequentially (24 h apart) with virus combinations. The replication kinetics of each virus were determined by RT-qPCR at different post-infection times. Our results showed that during simultaneous infection, SARS-CoV-2 interferes with RSV-A2 but not with A(H1N1)pdm09 replication. The prior infection of nasal HAE with SARS-CoV-2 reduces the replication kinetics of both respiratory viruses. SARS-CoV-2 replication is decreased by a prior infection with A(H1N1)pdm09 but not with RSV-A2. The pretreatment of nasal HAE with BX795, a TANK-binding kinase 1 inhibitor, partially alleviates the reduced replication of SARS-CoV-2 or influenza A(H1N1)pdm09 during sequential infection with both virus combinations. Thus, a prior infection of nasal HAE with SARS-CoV-2 interferes with the replication kinetics of A(H1N1)pdm09 and RSV-A2, whereas only A(H1N1)pdm09 reduces the subsequent infection with SARS-CoV-2. The mechanism involved in the viral interference between SARS-CoV-2 and A(H1N1)pdm09 is mediated by the production of interferon.
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Burstein R, Althouse BM, Adler A, Akullian A, Brandstetter E, Cho S, Emanuels A, Fay K, Gamboa L, Han P, Huden K, Ilcisin M, Izzo M, Jackson ML, Kim AE, Kimball L, Lacombe K, Lee J, Logue JK, Rogers J, Chung E, Sibley TR, Van Raay K, Wenger E, Wolf CR, Boeckh M, Chu H, Duchin J, Rieder M, Shendure J, Starita LM, Viboud C, Bedford T, Englund JA, Famulare M. Interactions among 17 respiratory pathogens: a cross-sectional study using clinical and community surveillance data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.02.04.22270474. [PMID: 35169816 PMCID: PMC8845514 DOI: 10.1101/2022.02.04.22270474] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Background Co-circulating respiratory pathogens can interfere with or promote each other, leading to important effects on disease epidemiology. Estimating the magnitude of pathogen-pathogen interactions from clinical specimens is challenging because sampling from symptomatic individuals can create biased estimates. Methods We conducted an observational, cross-sectional study using samples collected by the Seattle Flu Study between 11 November 2018 and 20 August 2021. Samples that tested positive via RT-qPCR for at least one of 17 potential respiratory pathogens were included in this study. Semi-quantitative cycle threshold (Ct) values were used to measure pathogen load. Differences in pathogen load between monoinfected and coinfected samples were assessed using linear regression adjusting for age, season, and recruitment channel. Results 21,686 samples were positive for at least one potential pathogen. Most prevalent were rhinovirus (33·5%), Streptococcus pneumoniae (SPn, 29·0%), SARS-CoV-2 (13.8%) and influenza A/H1N1 (9·6%). 140 potential pathogen pairs were included for analysis, and 56 (40%) pairs yielded significant Ct differences (p < 0.01) between monoinfected and co-infected samples. We observed no virus-virus pairs showing evidence of significant facilitating interactions, and found significant viral load decrease among 37 of 108 (34%) assessed pairs. Samples positive with SPn and a virus were consistently associated with increased SPn load. Conclusions Viral load data can be used to overcome sampling bias in studies of pathogen-pathogen interactions. When applied to respiratory pathogens, we found evidence of viral-SPn facilitation and several examples of viral-viral interference. Multipathogen surveillance is a cost-efficient data collection approach, with added clinical and epidemiological informational value over single-pathogen testing, but requires careful analysis to mitigate selection bias.
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Affiliation(s)
- Roy Burstein
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| | - Benjamin M. Althouse
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
- Department of Biology, New Mexico State University, Las Cruces, NM
| | - Amanda Adler
- Seattle Children’s Research Institute, Seattle WA USA
| | - Adam Akullian
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| | | | - Shari Cho
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Anne Emanuels
- Department of Medicine, University of Washington, Seattle WA USA
| | - Kairsten Fay
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | - Luis Gamboa
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Peter Han
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Kristen Huden
- Department of Medicine, University of Washington, Seattle WA USA
| | - Misja Ilcisin
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | - Mandy Izzo
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| | | | - Ashley E. Kim
- Department of Medicine, University of Washington, Seattle WA USA
| | - Louise Kimball
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | | | - Jover Lee
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | | | - Julia Rogers
- Department of Medicine, University of Washington, Seattle WA USA
| | - Erin Chung
- Department of Pediatrics, University of Washington, Seattle Children’s Hospital, Seattle
| | - Thomas R. Sibley
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | | | - Edward Wenger
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
| | - Caitlin R. Wolf
- Department of Medicine, University of Washington, Seattle WA USA
| | - Michael Boeckh
- Department of Medicine, University of Washington, Seattle WA USA
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | - Helen Chu
- Department of Medicine, University of Washington, Seattle WA USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
| | - Jeff Duchin
- Department of Medicine, University of Washington, Seattle WA USA
- Public Health Seattle & King County, Seattle WA USA
| | - Mark Rieder
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Jay Shendure
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
- Department of Genome Sciences, University of Washington, Seattle WA USA
- Howard Hughes Medical Institute, Seattle WA USA
| | - Lea M. Starita
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
- Department of Genome Sciences, University of Washington, Seattle WA USA
| | - Cecile Viboud
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| | - Trevor Bedford
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle WA USA
- Howard Hughes Medical Institute, Seattle WA USA
| | - Janet A. Englund
- Seattle Children’s Research Institute, Seattle WA USA
- Brotman Baty Institute for Precision Medicine, Seattle WA USA
| | - Michael Famulare
- Institute for Disease Modeling, Bill & Melinda Gates Foundation, Seattle WA USA
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Abstract
Multiple respiratory viruses can concurrently or sequentially infect the respiratory tract and lead to virus‒virus interactions. Infection by a first virus could enhance or reduce infection and replication of a second virus, resulting in positive (additive or synergistic) or negative (antagonistic) interaction. The concept of viral interference has been demonstrated at the cellular, host, and population levels. The mechanisms involved in viral interference have been evaluated in differentiated airway epithelial cells and in animal models susceptible to the respiratory viruses of interest. A likely mechanism is the interferon response that could confer a temporary nonspecific immunity to the host. During the coronavirus disease pandemic, nonpharmacologic interventions have prevented the circulation of most respiratory viruses. Once the sanitary restrictions are lifted, circulation of seasonal respiratory viruses is expected to resume and will offer the opportunity to study their interactions, notably with severe acute respiratory syndrome coronavirus 2.
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Domenech de Cellès M, Goult E, Casalegno JS, Kramer SC. The pitfalls of inferring virus-virus interactions from co-detection prevalence data: application to influenza and SARS-CoV-2. Proc Biol Sci 2022; 289:20212358. [PMID: 35016540 PMCID: PMC8753173 DOI: 10.1098/rspb.2021.2358] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 12/06/2021] [Indexed: 12/15/2022] Open
Abstract
There is growing experimental evidence that many respiratory viruses-including influenza and SARS-CoV-2-can interact, such that their epidemiological dynamics may not be independent. To assess these interactions, standard statistical tests of independence suggest that the prevalence ratio-defined as the ratio of co-infection prevalence to the product of single-infection prevalences-should equal unity for non-interacting pathogens. As a result, earlier epidemiological studies aimed to estimate the prevalence ratio from co-detection prevalence data, under the assumption that deviations from unity implied interaction. To examine the validity of this assumption, we designed a simulation study that built on a broadly applicable epidemiological model of co-circulation of two emerging or seasonal respiratory viruses. By focusing on the pair influenza-SARS-CoV-2, we first demonstrate that the prevalence ratio systematically underestimates the strength of interaction, and can even misclassify antagonistic or synergistic interactions that persist after clearance of infection. In a global sensitivity analysis, we further identify properties of viral infection-such as a high reproduction number or a short infectious period-that blur the interaction inferred from the prevalence ratio. Altogether, our results suggest that ecological or epidemiological studies based on co-detection prevalence data provide a poor guide to assess interactions among respiratory viruses.
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Affiliation(s)
- Matthieu Domenech de Cellès
- Max Planck Institute for Infection Biology, Infectious Disease Epidemiology group, Charitéplatz 1, Campus Charité Mitte, 10117 Berlin, Germany
| | - Elizabeth Goult
- Max Planck Institute for Infection Biology, Infectious Disease Epidemiology group, Charitéplatz 1, Campus Charité Mitte, 10117 Berlin, Germany
| | - Jean-Sebastien Casalegno
- Laboratoire de Virologie des HCL, IAI, CNR des virus à transmission respiratoire (dont la grippe) Hôpital de la Croix-Rousse F-69317, Lyon cedex 04, France
- Virpath, Centre International de Recherche en Infectiologie (CIRI), Université de Lyon Inserm U1111, CNRS UMR 5308, ENS de Lyon, UCBL F-69372, Lyon cedex 08, France
| | - Sarah C. Kramer
- Max Planck Institute for Infection Biology, Infectious Disease Epidemiology group, Charitéplatz 1, Campus Charité Mitte, 10117 Berlin, Germany
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Kim YI, Yu KM, Koh JY, Kim EH, Kim SM, Kim EJ, Casel MAB, Rollon R, Jang SG, Song MS, Park SJ, Jeong HW, Kim EG, Lee OJ, Kim YD, Choi Y, Lee SA, Choi YJ, Park SH, Jung JU, Choi YK. Age-dependent pathogenic characteristics of SARS-CoV-2 infection in ferrets. Nat Commun 2022; 13:21. [PMID: 35013229 PMCID: PMC8748994 DOI: 10.1038/s41467-021-27717-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 12/03/2021] [Indexed: 12/15/2022] Open
Abstract
While the seroprevalence of SARS-CoV-2 in healthy people does not differ significantly among age groups, those aged 65 years or older exhibit strikingly higher COVID-19 mortality compared to younger individuals. To further understand differing COVID-19 manifestations in patients of different ages, three age groups of ferrets are infected with SARS-CoV-2. Although SARS-CoV-2 is isolated from all ferrets regardless of age, aged ferrets (≥3 years old) show higher viral loads, longer nasal virus shedding, and more severe lung inflammatory cell infiltration, and clinical symptoms compared to juvenile (≤6 months) and young adult (1–2 years) groups. Furthermore, direct contact ferrets co-housed with the virus-infected aged group shed more virus than direct-contact ferrets co-housed with virus-infected juvenile or young adult ferrets. Transcriptome analysis of aged ferret lungs reveals strong enrichment of gene sets related to type I interferon, activated T cells, and M1 macrophage responses, mimicking the gene expression profile of severe COVID-19 patients. Thus, SARS-CoV-2-infected aged ferrets highly recapitulate COVID-19 patients with severe symptoms and are useful for understanding age-associated infection, transmission, and pathogenesis of SARS-CoV-2. Here, Kim et al. characterize SARS-CoV-2 infection in juvenile, young, and old aged ferrets to provide a further understanding of differences in COVID-19 severity in humans at different ages. Aged ferrets have higher viral loads, shed virus longer, and mimic the transcriptomic profile of severely infected patients.
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Affiliation(s)
- Young-Il Kim
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea.,Zoonotic Infectious Diseases Research Center, Chungbuk National University, Cheongju, Korea.,Center for Study of Emerging and Re-emerging Viruses, Korea Virus Research Institute, Institute for Basic Science (IBS), Daejeon, 34126, Republic of Korea
| | - Kwang-Min Yu
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea.,Zoonotic Infectious Diseases Research Center, Chungbuk National University, Cheongju, Korea
| | - June-Young Koh
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Eun-Ha Kim
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea.,Zoonotic Infectious Diseases Research Center, Chungbuk National University, Cheongju, Korea
| | - Se-Mi Kim
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea.,Zoonotic Infectious Diseases Research Center, Chungbuk National University, Cheongju, Korea.,Center for Study of Emerging and Re-emerging Viruses, Korea Virus Research Institute, Institute for Basic Science (IBS), Daejeon, 34126, Republic of Korea
| | - Eun Ji Kim
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea.,Zoonotic Infectious Diseases Research Center, Chungbuk National University, Cheongju, Korea
| | - Mark Anthony B Casel
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea.,Zoonotic Infectious Diseases Research Center, Chungbuk National University, Cheongju, Korea
| | - Rare Rollon
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea
| | - Seung-Gyu Jang
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea
| | - Min-Suk Song
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea.,Zoonotic Infectious Diseases Research Center, Chungbuk National University, Cheongju, Korea
| | - Su-Jin Park
- Division of Life Science, Research Institute of Life Science, Gyeongsang National University, Jinju, 52828, Korea
| | - Hye Won Jeong
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea
| | - Eung-Gook Kim
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea
| | - Ok-Jun Lee
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea
| | - Yong-Dae Kim
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea
| | - Younho Choi
- Cancer Biology Department and Global Center for Pathogens Research and Human Health, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Shin-Ae Lee
- Cancer Biology Department and Global Center for Pathogens Research and Human Health, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Youn Jung Choi
- Cancer Biology Department and Global Center for Pathogens Research and Human Health, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Su-Hyung Park
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Jae U Jung
- Cancer Biology Department and Global Center for Pathogens Research and Human Health, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
| | - Young Ki Choi
- College of Medicine and Medical Research Institute, Chungbuk National University, Cheongju, Republic of Korea. .,Zoonotic Infectious Diseases Research Center, Chungbuk National University, Cheongju, Korea. .,Center for Study of Emerging and Re-emerging Viruses, Korea Virus Research Institute, Institute for Basic Science (IBS), Daejeon, 34126, Republic of Korea.
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Ye Q, Wang D. Epidemiological changes of common respiratory viruses in children during the COVID-19 pandemic. J Med Virol 2022; 94:1990-1997. [PMID: 34981839 PMCID: PMC9015628 DOI: 10.1002/jmv.27570] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 12/24/2021] [Accepted: 01/02/2022] [Indexed: 12/27/2022]
Abstract
A variety of non‐pharmaceutical interventions (NPIs) have been implemented to control the transmission of COVID‐19 in China. The effect of NPIs on other common respiratory viruses in children of different age groups has not been examined thus far. Respiratory specimens of children were collected to detect common childhood respiratory viruses, including influenza A (FluA), influenza B (FluB), adenovirus, and respiratory syncytial virus (RSV), at the Children's Hospital of Zhejiang University School of Medicine from January 1, 2019 to December 31, 2020. The epidemiological characteristics of the respiratory viruses in 2020 were compared with those in 2019. From January 2019 to December 2020, 165 622 specimens were collected. The proportion of infants aged 0−28 days (683, 2.24% vs. 1295, 0.96%, p = 0.000) and 1−12 months (8560, 28.12% vs. 20 875, 15.43%, p = 0.000) in 2020 increased significantly compared with that in 2019. There were two obvious increases in April and September in the number of specimens in children aged 4−6 years and >7 years. FluA, FluB, and RSV's age distribution patterns were surprisingly consistent with each other in 2020, and the positive rates of children aged 1−12 months were the highest in all age groups (FluA: 4.45%, FluB: 3.30%, RSV: 7.35%). Our study further confirms that the NPIs significantly decreased the transmission of common childhood respiratory viruses. The change in circulation characteristics of common respiratory viruses of children in different age groups varied. Therefore, we recommend that different protection strategies should be introduced for children of different age groups. The epidemiological characteristics of common childhood respiratory viruses varied during the COVID‐19 pandemic. The non‐pharmaceutical interventions significantly decreased the transmission of common childhood respiratory viruses. Different protection strategies should be introduced for children of varying age groups. COVID‐19 article requiring a fast track process.
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Affiliation(s)
- Qing Ye
- Department of clinical laboratory, The Children's Hospital,Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou, China
| | - Dongjie Wang
- Department of clinical laboratory, The Children's Hospital,Zhejiang University School of Medicine, National Clinical Research Center for Child Health, National Children's Regional Medical Center, Hangzhou, China
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Costa-Martins AG, Mane K, Lindsey BB, Ogava RL, Castro Í, Jagne YJ, Sallah HJ, Armitage EP, Jarju S, Ahadzie B, Ellis-Watson R, Tregoning JS, Bingle CD, Bogaert D, Clarke E, Ordovas-Montanes J, Jeffries D, Kampmann B, Nakaya HI, de Silva TI. Prior upregulation of interferon pathways in the nasopharynx impacts viral shedding following live attenuated influenza vaccine challenge in children. Cell Rep Med 2021; 2:100465. [PMID: 35028607 PMCID: PMC8714852 DOI: 10.1016/j.xcrm.2021.100465] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Revised: 09/28/2021] [Accepted: 11/12/2021] [Indexed: 02/06/2023]
Abstract
In children lacking influenza-specific adaptive immunity, upper respiratory tract innate immune responses may influence viral replication and disease outcome. We use trivalent live attenuated influenza vaccine (LAIV) as a surrogate challenge model in children aged 24-59 months to identify pre-infection mucosal transcriptomic signatures associated with subsequent viral shedding. Upregulation of interferon signaling pathways prior to LAIV is significantly associated with lower strain-specific viral loads (VLs) at days 2 and 7. Several interferon-stimulated genes are differentially expressed in children with pre-LAIV asymptomatic respiratory viral infections and negatively correlated with LAIV VLs. Upregulation of genes enriched in macrophages, neutrophils, and eosinophils is associated with lower VLs and found more commonly in children with asymptomatic viral infections. Variability in pre-infection mucosal interferon gene expression in children may impact the course of subsequent influenza infections. This variability may be due to frequent respiratory viral infections, demonstrating the potential importance of mucosal virus-virus interactions in children.
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Affiliation(s)
- André G. Costa-Martins
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
- Scientific Platform Pasteur, University of São Paulo, São Paulo, Brazil
| | - Karim Mane
- Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, P.O. Box 273, Fajara, The Gambia
| | - Benjamin B. Lindsey
- The Florey Institute for Host-Pathogen Interactions and Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield S10 2RX, UK
| | - Rodrigo L.T. Ogava
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - Ícaro Castro
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
| | - Ya Jankey Jagne
- Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, P.O. Box 273, Fajara, The Gambia
| | - Hadijatou J. Sallah
- Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, P.O. Box 273, Fajara, The Gambia
| | - Edwin P. Armitage
- Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, P.O. Box 273, Fajara, The Gambia
| | - Sheikh Jarju
- Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, P.O. Box 273, Fajara, The Gambia
| | - Bankole Ahadzie
- Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, P.O. Box 273, Fajara, The Gambia
| | - Rebecca Ellis-Watson
- The University of Edinburgh/MRC Centre for Inflammation Research, The Queen’s Medical Research Institute, Edinburgh EH16 4TJ, UK
| | - John S. Tregoning
- Department of Infectious Disease, Imperial College London, London W2 1NY, UK
| | - Colin D. Bingle
- The Florey Institute for Host-Pathogen Interactions and Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield S10 2RX, UK
| | - Debby Bogaert
- The University of Edinburgh/MRC Centre for Inflammation Research, The Queen’s Medical Research Institute, Edinburgh EH16 4TJ, UK
| | - Ed Clarke
- Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, P.O. Box 273, Fajara, The Gambia
| | - Jose Ordovas-Montanes
- Division of Gastroenterology, Hepatology, and Nutrition, Boston Children’s Hospital, Boston, MA 02115, USA
- Program in Immunology, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Stem Cell Institute, Cambridge, MA 02138, USA
| | - David Jeffries
- Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, P.O. Box 273, Fajara, The Gambia
| | - Beate Kampmann
- Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, P.O. Box 273, Fajara, The Gambia
- The Vaccine Centre, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK
| | - Helder I. Nakaya
- Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil
- Scientific Platform Pasteur, University of São Paulo, São Paulo, Brazil
- Corresponding author
| | - Thushan I. de Silva
- Medical Research Council Unit The Gambia at the London School of Hygiene and Tropical Medicine, P.O. Box 273, Fajara, The Gambia
- The Florey Institute for Host-Pathogen Interactions and Department of Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield S10 2RX, UK
- Corresponding author
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Domenech de Cellès M, Casalegno JS, Lina B, Opatowski L. Estimating the impact of influenza on the epidemiological dynamics of SARS-CoV-2. PeerJ 2021; 9:e12566. [PMID: 34950537 PMCID: PMC8647717 DOI: 10.7717/peerj.12566] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 11/08/2021] [Indexed: 12/12/2022] Open
Abstract
As in past pandemics, co-circulating pathogens may play a role in the epidemiology of coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In particular, experimental evidence indicates that influenza infection can up-regulate the expression of ACE2-the receptor of SARS-CoV-2 in human cells-and facilitate SARS-CoV-2 infection. Here we hypothesized that influenza impacted the epidemiology of SARS-CoV-2 during the early 2020 epidemic of COVID-19 in Europe. To test this hypothesis, we developed a population-based model of SARS-CoV-2 transmission and of COVID-19 mortality, which simultaneously incorporated the impact of non-pharmaceutical control measures and of influenza on the epidemiological dynamics of SARS-CoV-2. Using statistical inference methods based on iterated filtering, we confronted this model with mortality incidence data in four European countries (Belgium, Italy, Norway, and Spain) to systematically test a range of assumptions about the impact of influenza. We found consistent evidence for a 1.8-3.4-fold (uncertainty range across countries: 1.1 to 5.0) average population-level increase in SARS-CoV-2 transmission associated with influenza during the period of co-circulation. These estimates remained robust to a variety of alternative assumptions regarding the epidemiological traits of SARS-CoV-2 and the modeled impact of control measures. Although further confirmatory evidence is required, our results suggest that influenza could facilitate the spread and hamper effective control of SARS-CoV-2. More generally, they highlight the possible role of co-circulating pathogens in the epidemiology of COVID-19.
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Affiliation(s)
| | - Jean-Sebastien Casalegno
- Laboratoire de Virologie des HCL, IAI, CNR des Virus à Transmission Respiratoire (dont la grippe) Hôpital de la Croix-Rousse F-69317 Lyon Cedex 04, France, Lyon, France
- Virpath, Centre International de Recherche en Infectiologie (CIRI), Université de Lyon Inserm U1111, CNRS UMR 5308, ENS de Lyon, UCBL F-69372, Lyon, France
| | - Bruno Lina
- Laboratoire de Virologie des HCL, IAI, CNR des Virus à Transmission Respiratoire (dont la grippe) Hôpital de la Croix-Rousse F-69317 Lyon Cedex 04, France, Lyon, France
- Virpath, Centre International de Recherche en Infectiologie (CIRI), Université de Lyon Inserm U1111, CNRS UMR 5308, ENS de Lyon, UCBL F-69372, Lyon, France
| | - Lulla Opatowski
- Université Paris-Saclay, UVSQ, Univ. Paris-Sud, Inserm, CESP, Anti-Infective Evasion and Pharma- Coepidemiology Team, Montigny-Le-Bretonneux, France
- Institut Pasteur, Epidemiology and Modelling of Evasion to Antibiotics, Paris, France
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Lumley SF, Richens N, Lees E, Cregan J, Kalimeris E, Oakley S, Morgan M, Segal S, Dawson M, Walker AS, Eyre DW, Crook DW, Beer S, Novak A, Stoesser NE, Matthews PC. Changes in paediatric respiratory infections at a UK teaching hospital 2016-2021; impact of the SARS-CoV-2 pandemic. J Infect 2021; 84:40-47. [PMID: 34757137 PMCID: PMC8591975 DOI: 10.1016/j.jinf.2021.10.022] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 10/25/2021] [Accepted: 10/26/2021] [Indexed: 01/21/2023]
Abstract
Objective To describe the impact of the SARS-CoV-2 pandemic on the incidence of paediatric viral respiratory tract infection in Oxfordshire, UK. Methods Data on paediatric Emergency Department (ED) attendances (0-15 years inclusive), respiratory virus testing, vital signs and mortality at Oxford University Hospitals were summarised using descriptive statistics. Results Between 1-March-2016 and 30-July-2021, 155,056 ED attendances occurred and 7,195 respiratory virus PCRs were performed. Detection of all pathogens was suppressed during the first national lockdown. Rhinovirus and adenovirus rates increased when schools reopened September-December 2020, then fell, before rising in March-May 2021. The usual winter RSV peak did not occur in 2020/21, with an inter-seasonal rise (32/1,000 attendances in 0-3 yr olds) in July 2021. Influenza remained suppressed throughout. A higher paediatric early warning score (PEWS) was seen for attendees with adenovirus during the pandemic compared to pre-pandemic (p = 0.04, Mann-Witney U test), no other differences in PEWS were seen. Conclusions SARS-CoV-2 caused major changes in the incidence of paediatric respiratory viral infection in Oxfordshire, with implications for clinical service demand, testing strategies, timing of palivizumab RSV prophylaxis, and highlighting the need to understand which public health interventions are most effective for preventing respiratory virus infections.
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Affiliation(s)
- Sheila F Lumley
- NHS Foundation Trust, Oxford University Hospitals, Oxford, UK; Nuffield Department of Medicine, University of Oxford, Medawar Building, South Parks Road, Oxford OX1 3SY, UK.
| | | | - Emily Lees
- Department of Paediatrics, University of Oxford, Oxford UK
| | - Jack Cregan
- Nuffield Department of Medicine, University of Oxford, Medawar Building, South Parks Road, Oxford OX1 3SY, UK
| | | | - Sarah Oakley
- NHS Foundation Trust, Oxford University Hospitals, Oxford, UK
| | - Marcus Morgan
- NHS Foundation Trust, Oxford University Hospitals, Oxford, UK
| | - Shelley Segal
- NHS Foundation Trust, Oxford University Hospitals, Oxford, UK
| | - Moya Dawson
- NHS Foundation Trust, Oxford University Hospitals, Oxford, UK
| | - A Sarah Walker
- Nuffield Department of Medicine, University of Oxford, Medawar Building, South Parks Road, Oxford OX1 3SY, UK; NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK
| | - David W Eyre
- NHS Foundation Trust, Oxford University Hospitals, Oxford, UK; NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK; Nuffield Department of Population Health, University of Oxford, Oxford, UK; Big Data Institute, University of Oxford, Oxford, UK
| | - Derrick W Crook
- NHS Foundation Trust, Oxford University Hospitals, Oxford, UK; Nuffield Department of Medicine, University of Oxford, Medawar Building, South Parks Road, Oxford OX1 3SY, UK; NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK
| | - Sally Beer
- NHS Foundation Trust, Oxford University Hospitals, Oxford, UK
| | - Alex Novak
- NHS Foundation Trust, Oxford University Hospitals, Oxford, UK
| | - Nicole E Stoesser
- NHS Foundation Trust, Oxford University Hospitals, Oxford, UK; Nuffield Department of Medicine, University of Oxford, Medawar Building, South Parks Road, Oxford OX1 3SY, UK; NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK
| | - Philippa C Matthews
- NHS Foundation Trust, Oxford University Hospitals, Oxford, UK; Nuffield Department of Medicine, University of Oxford, Medawar Building, South Parks Road, Oxford OX1 3SY, UK; NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK.
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49
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Achdout H, Vitner EB, Politi B, Melamed S, Yahalom-Ronen Y, Tamir H, Erez N, Avraham R, Weiss S, Cherry L, Bar-Haim E, Makdasi E, Gur D, Aftalion M, Chitlaru T, Vagima Y, Paran N, Israely T. Increased lethality in influenza and SARS-CoV-2 coinfection is prevented by influenza immunity but not SARS-CoV-2 immunity. Nat Commun 2021; 12:5819. [PMID: 34611155 PMCID: PMC8492774 DOI: 10.1038/s41467-021-26113-1] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Accepted: 09/16/2021] [Indexed: 11/10/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. The continued spread of SARS-CoV-2 increases the probability of influenza/SARS-CoV-2 coinfection, which may result in severe disease. In this study, we examine the disease outcome of influenza A virus (IAV) and SARS-CoV-2 coinfection in K18-hACE2 mice. Our data indicate enhance susceptibility of IAV-infected mice to developing severe disease upon coinfection with SARS-CoV-2 two days later. In contrast to nonfatal influenza and lower mortality rates due to SARS-CoV-2 alone, this coinfection results in severe morbidity and nearly complete mortality. Coinfection is associated with elevated influenza viral loads in respiratory organs. Remarkably, prior immunity to influenza, but not to SARS-CoV-2, prevents severe disease and mortality. This protection is antibody-dependent. These data experimentally support the necessity of seasonal influenza vaccination for reducing the risk of severe influenza/COVID-19 comorbidity during the COVID-19 pandemic.
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Affiliation(s)
- Hagit Achdout
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Einat B Vitner
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Boaz Politi
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Sharon Melamed
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Yfat Yahalom-Ronen
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Hadas Tamir
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Noam Erez
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Roy Avraham
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Shay Weiss
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Lilach Cherry
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Erez Bar-Haim
- Department of Biochemistry and Molecular Genetics, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Efi Makdasi
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - David Gur
- Department of Biochemistry and Molecular Genetics, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Moshe Aftalion
- Department of Biochemistry and Molecular Genetics, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Theodor Chitlaru
- Department of Biochemistry and Molecular Genetics, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Yaron Vagima
- Department of Biochemistry and Molecular Genetics, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Nir Paran
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel
| | - Tomer Israely
- Departments of Infectious Diseases, Israel Institute for Biological Research, Ness-Ziona, 7410001, Israel.
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50
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Rhedin SA, Ryd Rinder M, Hildenwall H, Herlenius E, Hertting O, Luthander J, Melén E, Nijman R, Olsson‐Åkefeldt S, Alfven T. Reduction in paediatric emergency visits during the COVID-19 pandemic in a region with open preschools and schools. Acta Paediatr 2021; 110:2802-2804. [PMID: 34107120 PMCID: PMC8222892 DOI: 10.1111/apa.15978] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 06/05/2021] [Accepted: 06/08/2021] [Indexed: 11/29/2022]
Affiliation(s)
- Samuel Arthur Rhedin
- Sachs’ Children and Youth Hospital at Södersjukhuset Stockholm Sweden
- Department of Medical Epidemiology and Biostatistics Karolinska Institutet Stockholm Sweden
| | - Malin Ryd Rinder
- Astrid Lindgren Children's Hospital, Karolinska University Hospital Stockholm Sweden
- Department of Women's and Children's Health Karolinska Institutet Stockholm Sweden
| | - Helena Hildenwall
- Astrid Lindgren Children's Hospital, Karolinska University Hospital Stockholm Sweden
- Department of Clinical Science, Intervention and Technology ‐ CLINTEC Karolinska Institutet Stockholm Sweden
- Department of Global Public Health Karolinska Institutet Stockholm Sweden
| | - Eric Herlenius
- Astrid Lindgren Children's Hospital, Karolinska University Hospital Stockholm Sweden
- Department of Women's and Children's Health Karolinska Institutet Stockholm Sweden
| | - Olof Hertting
- Astrid Lindgren Children's Hospital, Karolinska University Hospital Stockholm Sweden
- Department of Women's and Children's Health Karolinska Institutet Stockholm Sweden
| | - Joachim Luthander
- Astrid Lindgren Children's Hospital, Karolinska University Hospital Stockholm Sweden
- Department of Women's and Children's Health Karolinska Institutet Stockholm Sweden
| | - Erik Melén
- Sachs’ Children and Youth Hospital at Södersjukhuset Stockholm Sweden
- Department of Clinical Science and Education Södersjukhuset, Karolinska Institutet Stockholm Sweden
| | - Ruud Nijman
- Centre for Paediatrics and Child Health Faculty of Medicine Imperial College London London UK
- Section of Paediatric Infectious Diseases Department of Infectious Diseases Faculty of Medicine Imperial College London London UK
| | - Selma Olsson‐Åkefeldt
- Astrid Lindgren Children's Hospital, Karolinska University Hospital Stockholm Sweden
- Department of Women's and Children's Health Karolinska Institutet Stockholm Sweden
| | - Tobias Alfven
- Sachs’ Children and Youth Hospital at Södersjukhuset Stockholm Sweden
- Department of Global Public Health Karolinska Institutet Stockholm Sweden
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