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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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2
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Castro Blanco E, Dalmau Llorca MR, Aguilar Martín C, Carrasco-Querol N, Gonçalves AQ, Hernández Rojas Z, Coma E, Fernández-Sáez J. A Predictive Model of the Start of Annual Influenza Epidemics. Microorganisms 2024; 12:1257. [PMID: 39065025 PMCID: PMC11278734 DOI: 10.3390/microorganisms12071257] [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: 05/31/2024] [Revised: 06/14/2024] [Accepted: 06/17/2024] [Indexed: 07/28/2024] Open
Abstract
Influenza is a respiratory disease that causes annual epidemics during cold seasons. These epidemics increase pressure on healthcare systems, sometimes provoking their collapse. For this reason, a tool is needed to predict when an influenza epidemic will occur so that the healthcare system has time to prepare for it. This study therefore aims to develop a statistical model capable of predicting the onset of influenza epidemics in Catalonia, Spain. Influenza seasons from 2011 to 2017 were used for model training, and those from 2017 to 2018 were used for validation. Logistic regression, Support Vector Machine, and Random Forest models were used to predict the onset of the influenza epidemic. The logistic regression model was able to predict the start of influenza epidemics at least one week in advance, based on clinical diagnosis rates of various respiratory diseases and meteorological variables. This model achieved the best punctual estimates for two of three performance metrics. The most important variables in the model were the principal components of bronchiolitis rates and mean temperature. The onset of influenza epidemics can be predicted from clinical diagnosis rates of various respiratory diseases and meteorological variables. Future research should determine whether predictive models play a key role in preventing influenza.
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Affiliation(s)
- Elisabet Castro Blanco
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Campus Terres de l’Ebre, Universitat Rovira i Virgili, 43500 Tortosa, Spain
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
| | - Maria Rosa Dalmau Llorca
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Campus Terres de l’Ebre, Universitat Rovira i Virgili, 43500 Tortosa, Spain
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| | - Carina Aguilar Martín
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
- Unitat d’Avaluació, Direcció d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| | - Noèlia Carrasco-Querol
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
| | - Alessandra Queiroga Gonçalves
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
| | - Zojaina Hernández Rojas
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
| | - Ermengol Coma
- Primary Healthcare Information Systems, Health Institute of Catalonia, 08007 Catalonia, Spain;
| | - José Fernández-Sáez
- Primary Care Intervention Evaluation Research Group (GAVINA Research Group), IDIAPJGol Terres de l’Ebre, 43500 Tortosa, Spain; (E.C.B.); (N.C.-Q.); (A.Q.G.); (Z.H.R.); (J.F.-S.)
- Terres de l’Ebre Research Support Unit, Foundation University Institute for Primary Health Care Research Jordi Gol i Gurina (IDIAPJGol), 43500 Tortosa, Spain
- Servei d’Atenció Primària Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
- Unitat de Recerca, Gerència Territorial Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
- Unitat Docent de Medicina de Familia i Comunitària, Tortosa-Terres de l’Ebre, Institut Català de la Salut, 43500 Tortosa, Spain
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3
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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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4
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Petat H, Schuers M, Marguet C, Humbert X, Le Bas F, Rabiaza A, Corbet S, Leterrier B, Vabret A, Ar Gouilh M. Positive and negative viral associations in patients with acute respiratory tract infections in primary care: the ECOVIR study. Front Public Health 2023; 11:1269805. [PMID: 38074759 PMCID: PMC10706622 DOI: 10.3389/fpubh.2023.1269805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 10/30/2023] [Indexed: 12/18/2023] Open
Abstract
Introduction Acute respiratory infections (ARIs) are the most common viral infections encountered in primary care settings. The identification of causal viruses is still not available in routine practice. Although new strategies of prevention are being identified, knowledge of the relationships between respiratory viruses remains limited. Materials and methods ECOVIR was a multicentric prospective study in primary care, which took place during two pre-pandemic seasons (2018-2019 and 2019-2020). Patients presenting to their General practitioner (GP) with ARIs were included, without selecting for age or clinical conditions. Viruses were detected on nasal swab samples using a multiplex Polymerase Chain Reaction test focused on 17 viruses [Respiratory Syncytial Virus-A (RSV-A), RSV-B, Rhinovirus/Enterovirus (HRV), human Metapneumovirus (hMPV), Adenovirus (ADV), Coronaviruses (CoV) HKU1, NL63, 229E, OC43, Influenza virus (H1 and H3 subtypes), Influenza virus B, Para-Influenza viruses (PIVs) 1-4, and Bocavirus (BoV)]. Results Among the 668 analyzed samples, 66% were positive for at least one virus, of which 7.9% were viral codetections. The viral detection was negatively associated with the age of patients. BoV, ADV, and HRV occurred more significantly in younger patients than the other viruses (p < 0.05). Codetections were significantly associated with RSV, HRV, BoV, hMPV, and ADV and not associated with influenza viruses, CoV, and PIVs. HRV and influenza viruses were negatively associated with all the viruses. Conversely, a positive association was found between ADV and BoV and between PIVs and BoV. Conclusion Our study provides additional information on the relationships between respiratory viruses, which remains limited in primary care.
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Affiliation(s)
- Hortense Petat
- Department of Paediatrics and Adolescent Medicine Rouen, Univ Rouen Normandie, Dynamicure INSERM UMR 1311, CHU Rouen, Rouen, France
| | - Matthieu Schuers
- Department of General Practice, Univ Rouen Normandie, INSERM U1142, CHU Rouen, Rouen, France
| | - Christophe Marguet
- Department of Paediatrics and Adolescent Medicine Rouen, Univ Rouen Normandie, Dynamicure INSERM UMR 1311, CHU Rouen, Rouen, France
| | - Xavier Humbert
- Department of General Practice, Univ Caen Normandie santé, Caen, France
| | - François Le Bas
- Department of General Practice, Univ Caen Normandie santé, Caen, France
| | - Andry Rabiaza
- Department of General Practice, Univ Caen Normandie santé, Caen, France
| | - Sandrine Corbet
- Department of Virology, Univ Caen Normandie, INSERM Dynamicure UMR 1311, CHU Caen, Caen, France
| | - Bryce Leterrier
- Department of Virology, Univ Caen Normandie, INSERM Dynamicure UMR 1311, CHU Caen, Caen, France
| | - Astrid Vabret
- Department of Virology, Univ Caen Normandie, INSERM Dynamicure UMR 1311, CHU Caen, Caen, France
| | - Meriadeg Ar Gouilh
- Department of Virology, Univ Caen Normandie, INSERM Dynamicure UMR 1311, CHU Caen, Caen, France
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Roe K. Deadly interactions: Synergistic manipulations of concurrent pathogen infections potentially enabling future pandemics. Drug Discov Today 2023; 28:103762. [PMID: 37660981 DOI: 10.1016/j.drudis.2023.103762] [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: 06/08/2023] [Revised: 08/18/2023] [Accepted: 08/29/2023] [Indexed: 09/05/2023]
Abstract
Certain mono-infections of influenza viruses and novel coronaviruses, including severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) are significant threats to human health. Concurrent infections by influenza viruses and coronaviruses increases their danger. Influenza viruses have eight manipulations capable of assisting SARS-CoV-2 and other coronaviruses, and several of these manipulations, which are not specific to viruses, can also directly or indirectly boost dangerous secondary bacterial pneumonias. The influenza virus manipulations include: inhibiting transcription factors and cytokine expression; impairing defensive protein expression; increasing RNA viral replication; inhibiting defenses by manipulating cellular sensors and signaling pathways; inhibiting defenses by secreting exosomes; stimulating cholesterol production to increase synthesized virion infectivities; increasing cellular autophagy to assist viral replication; and stimulating glucocorticoid synthesis to suppress innate and adaptive immune defenses by inhibiting cytokine, chemokine, and adhesion molecule production. Teaser: Rapidly spreading multidrug-resistant respiratory bacteria, combined with influenza virus's far-reaching cellular defense manipulations benefiting evolving SARS-CoV-2 or other coronaviruses and/or respiratory bacteria, can enable more severe pandemics or co-pandemics.
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6
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Roe K. Increased Fungal Infection Mortality Induced by Concurrent Viral Cellular Manipulations. Lung 2023; 201:467-476. [PMID: 37670187 DOI: 10.1007/s00408-023-00642-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 08/16/2023] [Indexed: 09/07/2023]
Abstract
Certain respiratory fungal pathogen mono-infections can cause high mortality rates. Several viral pathogen mono-infections, including influenza viruses and coronaviruses including SARS-CoV-2, can also cause high mortality rates. Concurrent infections by fungal pathogens and highly manipulative viral pathogens can synergistically interact in the respiratory tract to substantially increase their mortality rates. There are at least five viral manipulations which can assist secondary fungal infections. These viral manipulations include the following: (1) inhibiting transcription factors and cytokine expressions, (2) impairing defensive protein expressions, (3) inhibiting defenses by manipulating cellular sensors and signaling pathways, (4) inhibiting defenses by secreting exosomes, and (5) stimulating glucocorticoid synthesis to suppress immune defenses by inhibiting cytokine, chemokine, and adhesion molecule production. The highest mortality respiratory viral pandemics up to now have had substantially boosted mortalities by inducing secondary bacterial pneumonias. However, numerous animal species besides humans are also carriers of endemic infections by viral and multidrug-resistant fungal pathogens. The vast multi-species scope of endemic infection opportunities make it plausible that the pro-fungal manipulations of a respiratory virus can someday evolve to enable a very high mortality rate viral pandemic inducing multidrug-resistant secondary fungal pathogen infections. Since such pandemics can quickly spread world-wide and outrun existing treatments, it would be worthwhile to develop new antifungal treatments well before such a high mortality event occurs.
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7
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O’Neill GK, Taylor J, Kok J, Dwyer DE, Dilcher M, Hua H, Levy A, Smith D, Minney-Smith CA, Wood T, Jelley L, Huang QS, Trenholme A, McAuliffe G, Barr I, Sullivan SG. Circulation of influenza and other respiratory viruses during the COVID-19 pandemic in Australia and New Zealand, 2020-2021. Western Pac Surveill Response J 2023; 14:1-9. [PMID: 37946717 PMCID: PMC10630701 DOI: 10.5365/wpsar.2023,14.3.948] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2023] Open
Abstract
Objective Circulation patterns of influenza and other respiratory viruses have been globally disrupted since the emergence of coronavirus disease (COVID-19) and the introduction of public health and social measures (PHSMs) aimed at reducing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. Methods We reviewed respiratory virus laboratory data, Google mobility data and PHSMs in five geographically diverse regions in Australia and New Zealand. We also described respiratory virus activity from January 2017 to August 2021. Results We observed a change in the prevalence of circulating respiratory viruses following the emergence of SARS-CoV-2 in early 2020. Influenza activity levels were very low in all regions, lower than those recorded in 2017-2019, with less than 1% of laboratory samples testing positive for influenza virus. In contrast, rates of human rhinovirus infection were increased. Respiratory syncytial virus (RSV) activity was delayed; however, once it returned, most regions experienced activity levels well above those seen in 2017-2019. The timing of the resurgence in the circulation of both rhinovirus and RSV differed within and between the two countries. Discussion The findings of this study suggest that as domestic and international borders are opened up and other COVID-19 PHSMs are lifted, clinicians and public health professionals should be prepared for resurgences in influenza and other respiratory viruses. Recent patterns in RSV activity suggest that these resurgences in non-COVID-19 viruses have the potential to occur out of season and with increased impact.
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Affiliation(s)
- Genevieve K O’Neill
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Janette Taylor
- Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology-Institute of Clinical Pathology and Medical Research, Westmead Hospital, Westmead, New South Wales, Australia
| | - Jen Kok
- Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology-Institute of Clinical Pathology and Medical Research, Westmead Hospital, Westmead, New South Wales, Australia
| | - Dominic E Dwyer
- Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology-Institute of Clinical Pathology and Medical Research, Westmead Hospital, Westmead, New South Wales, Australia
| | - Meik Dilcher
- Canterbury Health Laboratories, Christchurch, New Zealand
| | - Harry Hua
- Canterbury Health Laboratories, Christchurch, New Zealand
| | - Avram Levy
- PathWest Laboratory Medicine WA, Nedlands, Western Australia, Australia
- Infection and Immunity, School of Biomedical Sciences, University of Western Australia, Perth, Western Australia, Australia
| | - David Smith
- PathWest Laboratory Medicine WA, Nedlands, Western Australia, Australia
- Faculty of Health and Medical Sciences, University of Western Australia, Nedlands, Western Australia, Australia
| | | | - Timothy Wood
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Lauren Jelley
- Institute of Environmental Science and Research, Wellington, New Zealand
| | - Q Sue Huang
- Faculty of Health and Medical Sciences, University of Western Australia, Nedlands, Western Australia, Australia
- Institute of Environmental Science and Research, Wellington, New Zealand
| | | | - Gary McAuliffe
- Virology and Immunology Department, LabPLUS, Auckland City Hospital, Auckland District Health Board, Auckland, New Zealand
| | - Ian Barr
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Department of Microbiology and Immunology, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
| | - Sheena G Sullivan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Melbourne, Victoria, Australia
- Department of Infectious Diseases and Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, Victoria, Australia
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8
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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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9
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Zheng Z, Warren JL, Shapiro ED, Pitzer VE, Weinberger DM. Estimated incidence of respiratory hospitalizations attributable to RSV infections across age and socioeconomic groups. Pneumonia (Nathan) 2022; 14:6. [PMID: 36280891 PMCID: PMC9592130 DOI: 10.1186/s41479-022-00098-x] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 09/20/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Surveillance for respiratory syncytial virus (RSV) likely captures just a fraction of the burden of disease. Understanding the burden of hospitalizations and disparities between populations can help to inform upcoming RSV vaccine programs and to improve surveillance. METHODS We obtained monthly age-, ZIP code- and cause-specific hospitalizations in New York, New Jersey, and Washington from the US State Inpatient Databases (2005-2014). We estimated the incidence of respiratory hospitalizations attributable to RSV by age and by socioeconomic status using regression models. We compared the estimated incidence and the recorded incidence (based on ICD9-CM) of RSV hospitalizations to estimate the under-recorded ratio in different subpopulations. RESULTS The estimated annual incidence of respiratory hospitalizations due to RSV was highest among infants < 1 year of age with low socioeconomic status (2800, 95% CrI [2600, 2900] per 100,000 person-years). We also estimated a considerable incidence in older adults (≥ 65 years of age), ranging from 130 to 960 per 100,000 person-years across different socioeconomic strata. The incidence of hospitalization recorded as being due to RSV represented a significant undercount, particularly in adults. Less than 5% of the estimated RSV hospitalizations were captured for those ≥ 65 years of age. CONCLUSIONS RSV causes a considerable burden of hospitalization in young children and in older adults in the US, with variation by socioeconomic group. Recorded diagnoses substantially underestimate the incidence of hospitalization due to RSV in older adults.
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Affiliation(s)
- Zhe Zheng
- Department of Epidemiology of Microbial Diseases and the Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, CT, USA.
| | - Joshua L Warren
- Department of Biostatistics and the Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Eugene D Shapiro
- Department of Pediatrics, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Virginia E Pitzer
- Department of Epidemiology of Microbial Diseases and the Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Daniel M Weinberger
- Department of Epidemiology of Microbial Diseases and the Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, CT, USA
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10
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Chen Z, Bancej C, Lee L, Champredon D. Antigenic drift and epidemiological severity of seasonal influenza in Canada. Sci Rep 2022; 12:15625. [PMID: 36115880 PMCID: PMC9482630 DOI: 10.1038/s41598-022-19996-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 09/07/2022] [Indexed: 12/05/2022] Open
Abstract
Seasonal influenza epidemics circulate globally every year with varying levels of severity. One of the major drivers of this seasonal variation is thought to be the antigenic drift of influenza viruses, resulting from the accumulation of mutations in viral surface proteins. In this study, we aimed to investigate the association between the genetic drift of seasonal influenza viruses (A/H1N1, A/H3N2 and B) and the epidemiological severity of seasonal epidemics within a Canadian context. We obtained hemagglutinin protein sequences collected in Canada between the 2006/2007 and 2019/2020 flu seasons from GISAID and calculated Hamming distances in a sequence-based approach to estimating inter-seasonal antigenic differences. We also gathered epidemiological data on cases, hospitalizations and deaths from national surveillance systems and other official sources, as well as vaccine effectiveness estimates to address potential effect modification. These aggregate measures of disease severity were integrated into a single seasonal severity index. We performed linear regressions of our severity index with respect to the inter-seasonal antigenic distances, controlling for vaccine effectiveness. We did not find any evidence of a statistical relationship between antigenic distance and seasonal influenza severity in Canada. Future studies may need to account for additional factors, such as co-circulation of other respiratory pathogens, population imprinting, cohort effects and environmental parameters, which may drive seasonal influenza severity.
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Affiliation(s)
- Zishu Chen
- National Microbiology Laboratory, Public Health Risk Sciences Division, Public Health Agency of Canada, Guelph, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Christina Bancej
- Surveillance and Epidemiology Division, Centre for Immunization and Respiratory Infectious Disease, Public Health Agency of Canada, Ottawa, ON, Canada
| | - Liza Lee
- Surveillance and Epidemiology Division, Centre for Immunization and Respiratory Infectious Disease, Public Health Agency of Canada, Ottawa, ON, Canada
| | - David Champredon
- National Microbiology Laboratory, Public Health Risk Sciences Division, Public Health Agency of Canada, Guelph, ON, Canada.
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11
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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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12
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Longitudinal surveillance of influenza in Japan, 2006-2016. Sci Rep 2022; 12:12026. [PMID: 35835833 PMCID: PMC9281223 DOI: 10.1038/s41598-022-15867-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 06/30/2022] [Indexed: 12/04/2022] Open
Abstract
We analysed 2006–2016 national influenza surveillance data in Japan with regards to age-, sex-, and predominant virus-related epidemic patterns and the prevalence of serum influenza virus antibodies. We found a significant increase in influenza prevalence in both children (≤ 19 years old) and adults (≥ 20 years old) over time. The influenza prevalence was higher in children (0.33 [95% CI 0.26–0.40]) than in adults (0.09 [95% CI 0.07–0.11]). Additionally, the mean prevalence of antibodies for A(H1N1)pdm09 and A(H3N2) was significantly higher in children than in adults, whereas the mean prevalence of antibodies for B lineages was relatively low in both children and adults. There was a biennial cycle of the epidemic peak in children, which was associated with a relatively higher prevalence of B lineages. The female-to-male ratios of the influenza prevalence were significantly different in children (≤ 19 years old; 1.10 [95% CI:1.08–1.13]), adults (20–59 years old; 0.79 [95% CI 0.75–0.82]), and older adults (≥ 60 years old; 1.01 [95% CI 0.97–1.04]). The significant increase in influenza prevalence throughout the study period suggests a change of immunity to influenza infection. Long-term surveillance is important for developing a strategy to monitor, prevent and control for influenza epidemics.
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13
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Waterlow NR, Toizumi M, van Leeuwen E, Thi Nguyen HA, Myint-Yoshida L, Eggo RM, Flasche S. Evidence for influenza and RSV interaction from 10 years of enhanced surveillance in Nha Trang, Vietnam, a modelling study. PLoS Comput Biol 2022; 18:e1010234. [PMID: 35749561 PMCID: PMC9262224 DOI: 10.1371/journal.pcbi.1010234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Revised: 07/07/2022] [Accepted: 05/20/2022] [Indexed: 11/19/2022] Open
Abstract
Influenza and Respiratory Syncytial Virus (RSV) interact within their host posing the concern for impacts on heterologous viruses following vaccination. We aimed to estimate the population level impact of their interaction. We developed a dynamic age-stratified two-pathogen mathematical model that includes pathogen interaction through competition for infection and enhanced severity of dual infections. We used parallel tempering to fit its parameters to 11 years of enhanced hospital-based surveillance for acute respiratory illnesses (ARI) in children under 5 years old in Nha Trang, Vietnam. The data supported either a 41% (95%CrI: 36–54) reduction in susceptibility following infection and for 10.0 days (95%CrI 7.1–12.8) thereafter, or no change in susceptibility following infection. We estimate that co-infection increased the probability for an infection in <2y old children to be reported 7.2 fold (95%CrI 5.0–11.4); or 16.6 fold (95%CrI 14.5–18.4) in the moderate or low interaction scenarios. Absence of either pathogen was not to the detriment of the other. We find stronger evidence for severity enhancing than for acquisition limiting interaction. In this setting vaccination against either pathogen is unlikely to have a major detrimental effect on the burden of disease caused by the other. Influenza and Respiratory Syncytial Virus (RSV) cause large burdens of disease. Instead of acting independently, there may be short term cross-protection between them. The evidence of this to date comes from ecological studies which are unable to test the mechanism, or biological studies that are unable to determine the population level impacts of such cross-protection. We create a mathematical model that simulates the circulation of these two viruses, and allows for cross-protection between them. We then fit this model to hospital reported cases of confirmed infection from Nha Trang, Vietnam in order to estimate whether any cross-protection exists in this setting. We show that there are two possibilities—either no interaction or moderate interaction that can result in the observed circulation patterns. However, we further show that co-infection results in an increased reporting rate, presumably due to increased severity.
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Affiliation(s)
- Naomi R. Waterlow
- Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
- * E-mail:
| | - Michiko Toizumi
- Department of Pediatric Infectious Diseases, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan
| | - Edwin van Leeuwen
- Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Statistics, Modelling and Economics Department, UKHSA, London, United Kingdom
| | | | - Lay Myint-Yoshida
- Department of Pediatric Infectious Diseases, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan
| | - Rosalind M. Eggo
- Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Stefan Flasche
- Centre for Mathematical Modelling of Infectious Disease, London School of Hygiene and Tropical Medicine, London, United Kingdom
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14
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Sawires R, Kuldorff M, Fahey M, Clothier H, Buttery J. Snotwatch: an ecological analysis of the relationship between febrile seizures and respiratory virus activity. BMC Pediatr 2022; 22:359. [PMID: 35733118 PMCID: PMC9215000 DOI: 10.1186/s12887-022-03222-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 03/15/2022] [Indexed: 11/30/2022] Open
Abstract
Background Febrile seizures are the commonest type of seizure in occurring in the first few years of life, mostly affecting children aged six months to five years old. While largely benign, the incidence of each febrile seizure increases the risk of recurrence, afebrile seizures and epilepsy. Viruses are the most frequent cause of febrile illnesses in which a febrile seizure occurs. Febrile seizure presentation patterns appear to follow a seasonal trend. Aims To identify patterns of febrile seizure incidence across different seasons with specific viral activity, and to establish a framework for analysing virus circulation data with common illnesses within a shared region and population. Setting Our study was a study of febrile seizure presentations in Victoria, Australia and respiratory virus detection. Participants We obtained independent datasets of emergency department febrile seizure presentations at Monash Health and all respiratory multiplex PCR tests performed at Monash Health from January 2010–December 2019 to observe common trends in virus circulation and febrile seizure incidence. Study design Trends were studied temporally through mixed effects Poisson regression analysis of the monthly incidence of febrile seizures and the rate of positive PCR tests. Peak viral seasons (95th centile incidence) were compared to median viral circulation (50th centile incidence) to calculate peak season risk ratios. Results We found a 1.75–2.06 annual risk ratio of febrile seizure incidence in June–September. Temporal analysis of our data showed this peak in febrile seizures was attributable to circulating viruses in this season, and virus modelling showed correlation with increased rates of positive Influenza A (1.48 peak season risk ratio), Influenza B (1.31 peak season risk ratio), Human metapneumovirus (1.19 peak season risk ratio) and Respiratory Syncytial Virus (1.53 peak season risk ratio) on PCR testing. Conclusion Our ecological study statistically demonstrates the recognised winter peak in febrile seizure incidence and ascribes the seasonal relationship to several viral infections which affect the community, including a novel association with Human metapneumovirus. Supplementary Information The online version contains supplementary material available at 10.1186/s12887-022-03222-4.
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Affiliation(s)
- Rana Sawires
- Department of Paediatrics, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia. .,Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.
| | - Martin Kuldorff
- Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Harvard Medical School and Brigham and Women's Hospital, Boston, MA, USA
| | - Michael Fahey
- Department of Neurology, Monash Children's Hospital, Clayton, Victoria, Australia.,Neurogenetics Department, Monash Paediatrics, Monash University, Clayton, Victoria, Australia
| | - Hazel Clothier
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.,School of Population & Global health, University of Melbourne, Parkville, Victoria, Australia
| | - Jim Buttery
- Department of Paediatrics, Faculty of Medicine, Nursing and Health Sciences, Monash University, Clayton, Victoria, Australia.,Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.,Child Health Informatics, Department of Paediatrics, University of Melbourne, Parkville, Victoria, Australia
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15
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Off-season RSV epidemics in Australia after easing of COVID-19 restrictions. Nat Commun 2022; 13:2884. [PMID: 35610217 PMCID: PMC9130497 DOI: 10.1038/s41467-022-30485-3] [Citation(s) in RCA: 147] [Impact Index Per Article: 73.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 04/27/2022] [Indexed: 11/10/2022] Open
Abstract
Human respiratory syncytial virus (RSV) is an important cause of acute respiratory infection with the most severe disease in the young and elderly. Non-pharmaceutical interventions and travel restrictions for controlling COVID-19 have impacted the circulation of most respiratory viruses including RSV globally, particularly in Australia, where during 2020 the normal winter epidemics were notably absent. However, in late 2020, unprecedented widespread RSV outbreaks occurred, beginning in spring, and extending into summer across two widely separated regions of the Australian continent, New South Wales (NSW) and Australian Capital Territory (ACT) in the east, and Western Australia. Through genomic sequencing we reveal a major reduction in RSV genetic diversity following COVID-19 emergence with two genetically distinct RSV-A clades circulating cryptically, likely localised for several months prior to an epidemic surge in cases upon relaxation of COVID-19 control measures. The NSW/ACT clade subsequently spread to the neighbouring state of Victoria and to cause extensive outbreaks and hospitalisations in early 2021. These findings highlight the need for continued surveillance and sequencing of RSV and other respiratory viruses during and after the COVID-19 pandemic, as mitigation measures may disrupt seasonal patterns, causing larger or more severe outbreaks. Non-pharmaceutical interventions for COVID-19 also reduced incidence of respiratory pathogens such as respiratory syncytial virus (RSV). Here, the authors report the resurgence of RSV in Australia following lifting of some of the restrictions and describe reduction in genetic diversity in circulating clades.
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16
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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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17
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Wang G, Zhao RQ, Xiang-Tang, Ren L, Zhang YF, Ding H, Li Y, Wang YN, Li S, Zhang LY, Liu EM, Xu HM, Zhang XA, Liu W. Age specific spectrum of etiological pathogens for viral diarrhea among children in twelve consecutive winter-spring seasons (2009-2021) in China. J Med Virol 2022; 94:3840-3846. [PMID: 35441419 PMCID: PMC9324210 DOI: 10.1002/jmv.27790] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 04/12/2022] [Indexed: 12/04/2022]
Abstract
Viral diarrhea is one of the leading causes of morbidity and mortality in children. This study was conducted to disclose the etiological cause and epidemiological features of viral diarrhea among children in China. From 2009 to 2021, active surveillance was performed on pediatric patients with acute diarrhea and tested for five enteric viruses. Positive detection was determined in 65.56% (3325/5072) patients and an age‐specific infection pattern was observed. A significantly higher positive rate was observed in 12–23‐month‐old children for rotavirus (47.46%) and adenovirus (7.06%), while a significantly higher positive rate was observed for norovirus (37.62%) in 6–11‐month‐old patients, and for astrovirus (11.60%) and sapovirus (10.79%) in 24–47‐month‐old patients. A higher positive rate of rotavirus in girls and norovirus in boys was observed only among 6–11 months of patients. We also observed more norovirus among patients from rural areas in the 0–5‐ and 36–47‐month groups and more rotavirus among those from rural areas in the 12–23‐month group. Diarrhea severity was greater for rotavirus in the 6–23‐month group and norovirus in the 6–11‐month group. Coinfections were observed in 29.26% (973/3325) of positive patients, and were most frequently observed between rotavirus and others (89.31%). Our findings could help the prediction, prevention, and potential therapeutic approaches to viral diarrhea in children.
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Affiliation(s)
- Gang Wang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Rui-Qiu Zhao
- Children's Hospital of Chongqing Medical University, Chongqing, P. R China
| | - Xiang-Tang
- Children's Hospital of Chongqing Medical University, Chongqing, P. R China
| | - Luo Ren
- Children's Hospital of Chongqing Medical University, Chongqing, P. R China
| | - Yun-Fa Zhang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Heng Ding
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Yue Li
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Yu-Na Wang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Shuang Li
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Ling Yu Zhang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - En-Mei Liu
- Children's Hospital of Chongqing Medical University, Chongqing, P. R China
| | - Hong-Mei Xu
- Children's Hospital of Chongqing Medical University, Chongqing, P. R China
| | - Xiao-Ai Zhang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Wei Liu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China.,School of Public Health, Peking University, Beijing, P. R. China
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18
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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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19
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20
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Nichols GL, Gillingham EL, Macintyre HL, Vardoulakis S, Hajat S, Sarran CE, Amankwaah D, Phalkey R. Coronavirus seasonality, respiratory infections and weather. BMC Infect Dis 2021; 21:1101. [PMID: 34702177 PMCID: PMC8547307 DOI: 10.1186/s12879-021-06785-2] [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: 10/23/2020] [Accepted: 10/12/2021] [Indexed: 12/23/2022] Open
Abstract
Background The survival of coronaviruses are influenced by weather conditions and seasonal coronaviruses are more common in winter months. We examine the seasonality of respiratory infections in England and Wales and the associations between weather parameters and seasonal coronavirus cases. Methods Respiratory virus disease data for England and Wales between 1989 and 2019 was extracted from the Second-Generation Surveillance System (SGSS) database used for routine surveillance. Seasonal coronaviruses from 2012 to 2019 were compared to daily average weather parameters for the period before the patient’s specimen date with a range of lag periods. Results The seasonal distribution of 985,524 viral infections in England and Wales (1989–2019) showed coronavirus infections had a similar seasonal distribution to influenza A and bocavirus, with a winter peak between weeks 2 to 8. Ninety percent of infections occurred where the daily mean ambient temperatures were below 10 °C; where daily average global radiation exceeded 500 kJ/m2/h; where sunshine was less than 5 h per day; or where relative humidity was above 80%. Coronavirus infections were significantly more common where daily average global radiation was under 300 kJ/m2/h (OR 4.3; CI 3.9–4.6; p < 0.001); where average relative humidity was over 84% (OR 1.9; CI 3.9–4.6; p < 0.001); where average air temperature was below 10 °C (OR 6.7; CI 6.1–7.3; p < 0.001) or where sunshine was below 4 h (OR 2.4; CI 2.2–2.6; p < 0.001) when compared to the distribution of weather values for the same time period. Seasonal coronavirus infections in children under 3 years old were more frequent at the start of an annual epidemic than at the end, suggesting that the size of the susceptible child population may be important in the annual cycle. Conclusions The dynamics of seasonal coronaviruses reflect immunological, weather, social and travel drivers of infection. Evidence from studies on different coronaviruses suggest that low temperature and low radiation/sunlight favour survival. This implies a seasonal increase in SARS-CoV-2 may occur in the UK and countries with a similar climate as a result of an increase in the R0 associated with reduced temperatures and solar radiation. Increased measures to reduce transmission will need to be introduced in winter months for COVID-19. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-021-06785-2.
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Affiliation(s)
- G L Nichols
- Climate Change and Health Group, Centre for Radiation Chemicals and Environmental Hazards, UK Health Security Agency (Formerly Public Health England), Chilton, Oxon, OX11 0RQ, UK. .,European Centre for Environment and Human Health, University of Exeter Medical School, C/O Knowledge Spa RCHT, Truro, Cornwall, TR1 3HD, UK. .,School of Environmental Sciences, UEA, Norwich, NR4 7TJ, UK.
| | - E L Gillingham
- Climate Change and Health Group, Centre for Radiation Chemicals and Environmental Hazards, UK Health Security Agency (Formerly Public Health England), Chilton, Oxon, OX11 0RQ, UK
| | - H L Macintyre
- Climate Change and Health Group, Centre for Radiation Chemicals and Environmental Hazards, UK Health Security Agency (Formerly Public Health England), Chilton, Oxon, OX11 0RQ, UK.,School of Geography Earth and Environmental Sciences, University of Birmingham, Edgbaston, B15 2TT, UK
| | - S Vardoulakis
- European Centre for Environment and Human Health, University of Exeter Medical School, C/O Knowledge Spa RCHT, Truro, Cornwall, TR1 3HD, UK.,National Centre for Epidemiology and Population Health, Research School of Population Health, Australian National University, Canberra, ACT, 2601, Australia
| | - S Hajat
- Centre on Climate Change and Planetary Health, London School of Hygiene and Tropical Medicine, London, UK
| | - C E Sarran
- Met Office, Fitzroy Road, Exeter, EX1 3PB, UK.,Institute of Health Research, University of Exeter, Saint Luke's Campus, Heavitree Road, Exeter, EX1 2LU, UK
| | - D Amankwaah
- Climate Change and Health Group, Centre for Radiation Chemicals and Environmental Hazards, UK Health Security Agency (Formerly Public Health England), Chilton, Oxon, OX11 0RQ, UK
| | - R Phalkey
- Climate Change and Health Group, Centre for Radiation Chemicals and Environmental Hazards, UK Health Security Agency (Formerly Public Health England), Chilton, Oxon, OX11 0RQ, UK.,Heidelberg Institute of Global Health, University of Heidelberg, Heidelberg, Germany.,Division of Epidemiology and Public Health, University of Nottingham, Nottingham, UK
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21
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Spantideas N, Bougea AM, Drosou EG, Khanderia N, Rai S. COVID-19 and Seasonal Influenza: No Room for Two. Cureus 2021; 13:e18007. [PMID: 34667682 PMCID: PMC8516323 DOI: 10.7759/cureus.18007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/15/2021] [Indexed: 11/05/2022] Open
Abstract
Objective With the outbreak of COVID-19 in December 2019 fears were expressed for a possible twindemic in the coming flu seasons. Fortunately, this was not the case for the 2019-2020 and 2020-2021 flu seasons as flu showed very low historical rates during these periods. The objective of our study was to look at the existing flu data for the 2019-2021 period and analyze possible reasons for the near absence of seasonal flu. Methods We performed retrospective surveillance regarding seasonal influenza rates for the years 2019-2021, the years that the COVID-19 was present. Epidemiological data concerning seasonal influenza for the years 2019-2021 were collected and analyzed Results Extremely low numbers of flu cases were reported in FluNet, FluView, and TESSy influenza surveillance systems during the years 2019, 2020, and 2021 compared to previous years prior to COVID-19. Conclusions A twindemic outbreak during the 2019-2021 flu seasons did not occur despite expressed concerns. The worldwide implementation of mitigation measures for individuals and communities to control severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, the increased flu vaccination rate, the virus interference and the lower rate of testing for flu are the main reasons for the marked decrease in reported flu cases during 2019-2021 flu seasons.
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Affiliation(s)
| | - Anastasia M Bougea
- Neurology, Aeginition Hospital, National and Kapodistrian University of Athens, Athens, GRC
| | - Eirini G Drosou
- Speech Therapy, Athens Speech Language and Swallowing Institute, Athens, GRC
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22
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Subissi L, Bossuyt N, Reynders M, Gérard M, Dauby N, Lacor P, Daelemans S, Lissoir B, Holemans X, Magerman K, Jouck D, Bourgeois M, Delaere B, Quoilin S, Van Gucht S, Thomas I, Barbezange C. Spotlight influenza: Extending influenza surveillance to detect non-influenza respiratory viruses of public health relevance: analysis of surveillance data, Belgium, 2015 to 2019. ACTA ACUST UNITED AC 2021; 26. [PMID: 34558405 PMCID: PMC8462033 DOI: 10.2807/1560-7917.es.2021.26.38.2001104] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
BackgroundSeasonal influenza-like illness (ILI) affects millions of people yearly. Severe acute respiratory infections (SARI), mainly influenza, are a leading cause of hospitalisation and mortality. Increasing evidence indicates that non-influenza respiratory viruses (NIRV) also contribute to the burden of SARI. In Belgium, SARI surveillance by a network of sentinel hospitals has been ongoing since 2011.AimWe report the results of using in-house multiplex qPCR for the detection of a flexible panel of viruses in respiratory ILI and SARI samples and the estimated incidence rates of SARI associated with each virus.MethodsWe defined ILI as an illness with onset of fever and cough or dyspnoea. SARI was defined as an illness requiring hospitalisation with onset of fever and cough or dyspnoea within the previous 10 days. Samples were collected in four winter seasons and tested by multiplex qPCR for influenza virus and NIRV. Using catchment population estimates, we calculated incidence rates of SARI associated with each virus.ResultsOne third of the SARI cases were positive for NIRV, reaching 49.4% among children younger than 15 years. In children younger than 5 years, incidence rates of NIRV-associated SARI were twice that of influenza (103.5 vs 57.6/100,000 person-months); co-infections with several NIRV, respiratory syncytial viruses, human metapneumoviruses and picornaviruses contributed most (33.1, 13.6, 15.8 and 18.2/100,000 person-months, respectively).ConclusionEarly testing for NIRV could be beneficial to clinical management of SARI patients, especially in children younger than 5 years, for whom the burden of NIRV-associated disease exceeds that of influenza.
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Affiliation(s)
- Lorenzo Subissi
- European Public Health Microbiology Training Programme (EUPHEM), European Centre for Disease Prevention and Control, Stockholm, Sweden.,National Influenza Centre, Sciensano, Brussels, Belgium
| | - Nathalie Bossuyt
- Epidemiology of Infectious Diseases, Sciensano, Brussels, Belgium
| | - Marijke Reynders
- Department of Laboratory Medicine, Medical Microbiology, Algemeen Ziekenhuis Sint-Jan, Brugge-Oostende AV, Belgium
| | - Michèle Gérard
- Centre Hospitalier Universitaire St-Pierre, Brussels, Belgium
| | - Nicolas Dauby
- Centre for Environmental Health and Occupational Health, School of Public Health, Université Libre de Bruxelles (ULB), Brussels, Belgium.,Centre Hospitalier Universitaire St-Pierre, Brussels, Belgium
| | - Patrick Lacor
- Internal Medicine-Infectious Diseases, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Siel Daelemans
- Pediatric Pulmonary and Infectious Diseases, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | | | - Xavier Holemans
- Infectiology, Grand Hôpital de Charleroi, Charleroi, Belgium
| | - Koen Magerman
- Infection Control, Jessa Ziekenhuis, Hasselt, Belgium.,Clinical Laboratory, Jessa Ziekenhuis, Hasselt, Belgium
| | - Door Jouck
- Infection Control, Jessa Ziekenhuis, Hasselt, Belgium
| | - Marc Bourgeois
- Centre Hospitalier Universitaire UCL Namur, Ysoir, Belgium
| | | | - Sophie Quoilin
- Epidemiology of Infectious Diseases, Sciensano, Brussels, Belgium
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23
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Du X, Wu G, Zhu Y, Zhang S. Exploring the epidemiological changes of common respiratory viruses since the COVID-19 pandemic: a hospital study in Hangzhou, China. Arch Virol 2021; 166:3085-3092. [PMID: 34480636 PMCID: PMC8417671 DOI: 10.1007/s00705-021-05214-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 07/09/2021] [Indexed: 11/28/2022]
Abstract
Adenovirus, respiratory syncytial virus, and influenza virus are common causes of respiratory infections. The COVID-19 pandemic had a significant impact on their prevalence. The aim of this study was to analyze the epidemic changes of common respiratory viruses in the Affiliated Hospital of Hangzhou Normal University in Hangzhou, China, from October of 2017 to February of 2021. We collected statistics from 121,529 patients in the outpatient and inpatient departments of the hospital who had throat or nose swabs collected for testing for four virus antigens by the colloidal gold method. Of these, 13,200 (10.86%) were positive for influenza A virus, 8,402 (6.91%) were positive for influenza B virus, 6,056 (4.98%) were positive for adenovirus, and 4,739 (3.90%) were positive for respiratory syncytial virus. The positivity rates of the influenza A virus (0-14 years old, P = 0.376; over 14 years old, P = 0.197) and respiratory syncytial virus (0-14 years old, P = 0.763; over 14 years old, P = 0.465) did not differ significantly by gender. After January of 2020, influenza virus infection decreased significantly. The positivity rate of respiratory syncytial virus remained high, and its epidemic season was similar to before. Strict respiratory protection and regulation of crowd activities have a great impact on the epidemic characteristics of viruses. After major changes in the public health environment, virus epidemics and their mutations should be monitored closely, extensively, and continuously.
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Affiliation(s)
- Xinke Du
- Department of Pediatrics, The Affiliated Hospital of Hangzhou Normal University, No. 126 Wenzhou Road, Gongchenqiao Street, Gongshu District, Hangzhou, China
| | - Guangsheng Wu
- Department of Pediatrics, The Affiliated Hospital of Hangzhou Normal University, No. 126 Wenzhou Road, Gongchenqiao Street, Gongshu District, Hangzhou, China.
| | - Yafei Zhu
- Department of Pediatrics, The Affiliated Hospital of Hangzhou Normal University, No. 126 Wenzhou Road, Gongchenqiao Street, Gongshu District, Hangzhou, China
| | - Siqi Zhang
- Clinical Medicine College of Hangzhou Normal University, Hangzhou, China
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24
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George JA, AlShamsi SH, Alhammadi MH, Alsuwaidi AR. Exacerbation of Influenza A Virus Disease Severity by Respiratory Syncytial Virus Co-Infection in a Mouse Model. Viruses 2021; 13:v13081630. [PMID: 34452495 PMCID: PMC8402720 DOI: 10.3390/v13081630] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 08/16/2021] [Accepted: 08/16/2021] [Indexed: 01/15/2023] Open
Abstract
Influenza A virus (IAV) and respiratory syncytial virus (RSV) are leading causes of childhood infections. RSV and influenza are competitive in vitro. In this study, the in vivo effects of RSV and IAV co-infection were investigated. Mice were intranasally inoculated with RSV, with IAV, or with both viruses (RSV+IAV and IAV+RSV) administered sequentially, 24 h apart. On days 3 and 7 post-infection, lung tissues were processed for viral loads and immune cell populations. Lung functions were also evaluated. Mortality was observed only in the IAV+RSV group (50% of mice did not survive beyond 7 days). On day 3, the viral loads in single-infected and co-infected mice were not significantly different. However, on day 7, the IAV titer was much higher in the IAV+RSV group, and the RSV viral load was reduced. CD4 T cells were reduced in all groups on day 7 except in single-infected mice. CD8 T cells were higher in all experimental groups except the RSV-alone group. Increased airway resistance and reduced thoracic compliance were demonstrated in both co-infected groups. This model indicates that, among all the infection types we studied, infection with IAV followed by RSV is associated with the highest IAV viral loads and the most morbidity and mortality.
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Affiliation(s)
- Junu A. George
- Department of Pediatrics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain 17666, United Arab Emirates;
| | - Shaikha H. AlShamsi
- Department of Medical Education, Sheikh Khalifa Medical City, Abu Dhabi Health Services Company (SEHA), Abu Dhabi 51900, United Arab Emirates;
| | - Maryam H. Alhammadi
- Department of Medical Affairs, Sheikh Shakhbout Medical City, Abu Dhabi Health Services Company (SEHA), Abu Dhabi 11001, United Arab Emirates;
| | - Ahmed R. Alsuwaidi
- Department of Pediatrics, College of Medicine and Health Sciences, United Arab Emirates University, Al Ain 17666, United Arab Emirates;
- Correspondence:
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25
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Li ZJ, Zhang HY, Ren LL, Lu QB, Ren X, Zhang CH, Wang YF, Lin SH, Zhang XA, Li J, Zhao SW, Yi ZG, Chen X, Yang ZS, Meng L, Wang XH, Liu YL, Wang X, Cui AL, Lai SJ, Jiang T, Yuan Y, Shi LS, Liu MY, Zhu YL, Zhang AR, Zhang ZJ, Yang Y, Ward MP, Feng LZ, Jing HQ, Huang LY, Xu WB, Chen Y, Wu JG, Yuan ZH, Li MF, Wang Y, Wang LP, Fang LQ, Liu W, Hay SI, Gao GF, Yang WZ. Etiological and epidemiological features of acute respiratory infections in China. Nat Commun 2021; 12:5026. [PMID: 34408158 PMCID: PMC8373954 DOI: 10.1038/s41467-021-25120-6] [Citation(s) in RCA: 110] [Impact Index Per Article: 36.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 07/26/2021] [Indexed: 12/18/2022] Open
Abstract
Nationwide prospective surveillance of all-age patients with acute respiratory infections was conducted in China between 2009‒2019. Here we report the etiological and epidemiological features of the 231,107 eligible patients enrolled in this analysis. Children <5 years old and school-age children have the highest viral positivity rate (46.9%) and bacterial positivity rate (30.9%). Influenza virus, respiratory syncytial virus and human rhinovirus are the three leading viral pathogens with proportions of 28.5%, 16.8% and 16.7%, and Streptococcus pneumoniae, Mycoplasma pneumoniae and Klebsiella pneumoniae are the three leading bacterial pathogens (29.9%, 18.6% and 15.8%). Negative interactions between viruses and positive interactions between viral and bacterial pathogens are common. A Join-Point analysis reveals the age-specific positivity rate and how this varied for individual pathogens. These data indicate that differential priorities for diagnosis, prevention and control should be highlighted in terms of acute respiratory tract infection patients' demography, geographic locations and season of illness in China.
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Affiliation(s)
- Zhong-Jie Li
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hai-Yang Zhang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Li-Li Ren
- Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qing-Bin Lu
- Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, China
| | - Xiang Ren
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Cui-Hong Zhang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yi-Fei Wang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Sheng-Hong Lin
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiao-Ai Zhang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Jun Li
- Sun Yat-sen University, Guangzhou, China
| | - Shi-Wen Zhao
- Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Zhi-Gang Yi
- Shanghai Public Health Clinical Center, Shanghai, China
| | - Xiao Chen
- Zhejiang University, Hangzhou, China
| | - Zuo-Sen Yang
- Liaoning Provincial Center for Disease Control and Prevention, Shenyang, China
| | - Lei Meng
- Gansu Provincial Center for Disease Control and Prevention, Lanzhou, China
| | - Xin-Hua Wang
- Gansu Provincial Center for Disease Control and Prevention, Lanzhou, China
| | | | - Xin Wang
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ai-Li Cui
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Sheng-Jie Lai
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.,School of Geography and Environmental Science, University of Southampton, Southampton, UK.,School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China
| | - Tao Jiang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Yang Yuan
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Lu-Sha Shi
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Meng-Yang Liu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Yu-Liang Zhu
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - An-Ran Zhang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Zhi-Jie Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai, China
| | - Yang Yang
- Department of Biostatistics, College of Public Health and Health Professions, and Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - Michael P Ward
- Sydney School of Veterinary Science, The University of Sydney, Camden, NSW, Australia
| | - Lu-Zhao Feng
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Huai-Qi Jing
- National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Liu-Yu Huang
- The Institute for Disease Prevention and Control of PLA, Beijing, China
| | - Wen-Bo Xu
- National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yu Chen
- Zhejiang University, Hangzhou, China
| | | | | | | | - Yu Wang
- Chinese Centre for Disease Control and Prevention, Beijing, China
| | - Li-Ping Wang
- Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
| | - Li-Qun Fang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
| | - Wei Liu
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China.
| | - Simon I Hay
- Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.,Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA
| | - George F Gao
- Chinese Centre for Disease Control and Prevention, Beijing, China
| | - Wei-Zhong Yang
- Chinese Centre for Disease Control and Prevention, Beijing, China
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26
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Liang J, Wang Z, Liu Y, Zeng L, Li Z, Liang J, Liang H, Jiang M, Yang Z. Epidemiology and co-infection patterns in patients with respiratory tract infections in southern China between 2018 and 2020. J Infect 2021; 83:e6-e8. [PMID: 34302865 DOI: 10.1016/j.jinf.2021.07.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 07/15/2021] [Indexed: 11/18/2022]
Affiliation(s)
- Jingyi Liang
- National center for respiratory medicine, state Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510120, P.R. China; Guangzhou KingMed Diagnostics Group Co., Ltd., Guangzhou 510120, China
| | - Zhufeng Wang
- National center for respiratory medicine, state Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510120, P.R. China
| | - Yong Liu
- National center for respiratory medicine, state Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510120, P.R. China
| | - Linxiu Zeng
- Guangzhou KingMed Diagnostics Group Co., Ltd., Guangzhou 510120, China
| | - Zhengtu Li
- National center for respiratory medicine, state Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510120, P.R. China
| | - Jiamin Liang
- Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Hanwen Liang
- National center for respiratory medicine, state Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510120, P.R. China
| | - Mei Jiang
- National center for respiratory medicine, state Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510120, P.R. China.
| | - Zifeng Yang
- National center for respiratory medicine, state Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, 510120, P.R. China.
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27
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Howard LM, Liu Y, Zhu Y, Liu D, Willams JV, Gil AI, Griffin MR, Edwards KM, Lanata CF, Grijalva CG. Assessing the impact of acute respiratory illnesses on the risk of subsequent respiratory illness. J Infect Dis 2021; 225:42-49. [PMID: 34120189 DOI: 10.1093/infdis/jiab313] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 06/09/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Whether acute respiratory illnesses (ARIs), often associated with virus detection, are associated with lower risk for subsequent ARI remains unclear. We assessed the association between symptomatic ARI and subsequent ARI in young children. METHODS In a prospective cohort of Peruvian children <3 years, we examined the impact of index ARI on subsequent ARI risk. Index ARI were matched with ≤3 asymptomatic observations and followed over 28 days. We compared risk of subsequent ARI between groups using conditional logistic regression adjusting for several covariates, accounting for repeat observations from individual children. RESULTS Among 983 index ARI, 339 (34%) had an ARI event during follow-up, compared with 876/2826 (31%) matched asymptomatic observations. We found no significant association of index ARI and subsequent ARI risk during follow-up overall (aOR 1.10, 95% CI 0.98, 1.23) or when limited to index ARI with respiratory viruses detected (aOR 1.03, 95% CI 0.86, 1.24). Similarly, when the outcome was limited to ARI in which viruses were detected, no significant association was seen (aOR 1.05, 95% CI 0.87, 1.27). DISCUSSION ARIs were not associated with short-term protection against subsequent ARI in these children. Additional longitudinal studies are needed to understand drivers of recurrent ARI in young children.
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Affiliation(s)
- Leigh M Howard
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuhan Liu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yuwei Zhu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dandan Liu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - John V Willams
- Department of Pediatrics, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Ana I Gil
- Instituto de Investigación Nutricional, Lima, Peru
| | - Marie R Griffin
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kathryn M Edwards
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Carlos G Grijalva
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, TN, USA
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28
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Hendaus MA, Jomha FA. Can virus-virus interactions impact the dynamics of the covid-19 pandemic? J Biomol Struct Dyn 2021; 40:9571-9575. [PMID: 33998968 DOI: 10.1080/07391102.2021.1926327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Viral respiratory infections can occur in pandemics and can spread rapidly within communities resulting in health concerns globally. Several respiratory viruses co-circulate at one specific time. However, interface between different viruses has not been clearly established. This interaction is crucial to delineate, especially during pandemics, including the one relate to covid-19. This commentary will provide a brief description of how respiratory viruses interact and the outcome of this interaction on a pandemic.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Mohamed A Hendaus
- Department of Pediatrics, Sidra Medicine, Doha, Qatar.,Weill Cornell Medicine, Ar-Rayyan, Qatar
| | - Fatima A Jomha
- School of Pharmacy, Lebanese International University, Beirut, Lebanon
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29
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Aung AH, Lye DC, Cui L, Ooi CK, Chow ALP. The "timeless" use of influenza-like illness criteria for influenza detection in the tropics. Int J Infect Dis 2021; 106:160-168. [PMID: 33741485 DOI: 10.1016/j.ijid.2021.03.045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 03/09/2021] [Accepted: 03/11/2021] [Indexed: 10/21/2022] Open
Abstract
OBJECTIVE We assessed the performance of influenza-like illness (ILI) case definitions by the Centers for Disease Control and Prevention (CDC), European Centers for Disease Control and Prevention and World Health Organization (WHO) in the tropics where seasonal patterns of respiratory viruses in acute upper respiratory tract infections (AURTIs) are ill-defined. METHODS Clinical data and samples for respiratory multiplex polymerase chain reaction test were collected from 717 consecutive patients attending an emergency department in Singapore for uncomplicated AURTI in 2016-2018. RESULTS Influenza (20.6%), rhinoviruses (14.4%), and coronaviruses (3.6%) were the most common viral pathogens identified. Biannual peaks with year-round activity were identified for influenza. Although higher rhinovirus activity was observed in inter-influenza seasonal periods, rhinoviruses and coronaviruses circulated year-round without distinct seasonal patterns. During high influenza activity months, the CDC and WHO ILI case definitions had moderate-to-high positive likelihood ratio (LR+) of 3.8-6.8 and 4.5-10.7, respectively, for ruling in influenza. They had moderately-high LR + of 3.3-3.8 and 3.9-4.6 for diagnosing influenza during other months. The ILI case definitions had high specificity (77.2%-85.4%) for rhinoviruses and coronaviruses. CONCLUSION The CDC and WHO ILI case definitions can be applied to clinically diagnose influenza in the tropics, regardless of the time of the year.
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Affiliation(s)
- Aung H Aung
- Department of Clinical Epidemiology, Office of Clinical Epidemiology, Analytics, and Knowledge, Tan Tock Seng Hospital, Singapore
| | - David C Lye
- Department of Infectious Disease, Tan Tock Seng Hospital, Singapore
| | - Lin Cui
- National Public Health Laboratory, Ministry of Health, Singapore
| | - Chee K Ooi
- Department of Emergency Medicine, Tan Tock Seng Hospital, Singapore
| | - Angela L P Chow
- Department of Clinical Epidemiology, Office of Clinical Epidemiology, Analytics, and Knowledge, Tan Tock Seng Hospital, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
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30
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Sherman AC, Babiker A, Sieben AJ, Pyden A, Steinberg J, Kraft CS, Koelle K, Kanjilal S. The Effect of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Mitigation Strategies on Seasonal Respiratory Viruses: A Tale of 2 Large Metropolitan Centers in the United States. Clin Infect Dis 2021; 72:e154-e157. [PMID: 33161424 PMCID: PMC7717225 DOI: 10.1093/cid/ciaa1704] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 11/04/2020] [Indexed: 12/22/2022] Open
Abstract
To assess the impact of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic on seasonal respiratory viruses, absolute case counts and viral reproductive rates from 2019-2020 were compared against previous seasons. Our findings suggest that the public health measures implemented to reduce SARS-CoV-2 transmission significantly reduced the transmission of other respiratory viruses.
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Affiliation(s)
- Amy C Sherman
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.,Division of Infectious Diseases, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Ahmed Babiker
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.,Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, Georgia, USA
| | | | - Alexander Pyden
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - James Steinberg
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Colleen S Kraft
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA.,Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Katia Koelle
- Department of Biology, Emory University, Atlanta, Georgia, USA
| | - Sanjat Kanjilal
- Division of Infectious Diseases, Brigham and Women's Hospital, Boston, Massachusetts, USA.,Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA
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31
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Andrews C, L Maxwell S, Kerns E, McCulloh R, Alverson B. The Association of Seasonality With Resource Use in a Large National Cohort of Infants With Bronchiolitis. Hosp Pediatr 2021; 11:126-134. [PMID: 33436417 PMCID: PMC7831374 DOI: 10.1542/hpeds.2020-0120] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
OBJECTIVES Examine the degree of seasonal variation in nonrecommended resource use for bronchiolitis management subsequent to publication of the American Academy of Pediatrics (AAP) 2014 guidelines. METHODS We performed a multicenter retrospective cohort study using the Pediatric Health Information System database, examining patients aged 1 to 24 months, diagnosed with bronchiolitis between November 2015 and November 2018. Exclusions included presence of a complex chronic condition, admission to the PICU, hospital stay >10 days, or readmission. Primary outcomes were use rates of viral testing, complete blood count, blood culture, chest radiography, antibiotics, albuterol, and systemic steroids. Each hospital's monthly bronchiolitis census was aggregated into hospital bronchiolitis census quartiles. Mixed-effect logistic regression was performed, comparing the primary outcomes between bronchiolitis census quartiles, adjusting for patient age, race, insurance, hospitalization status, bacterial coinfection, time since publication of latest AAP bronchiolitis guidelines, and clustering by site. RESULTS In total, 196 902 bronchiolitis patient encounters across 50 US hospitals were analyzed. All hospitals followed a similar census pattern, with peaks during winter months and nadirs during summer months. Chest radiography, albuterol, and systemic steroid use were found to significantly increase in lower bronchiolitis census quartiles, whereas rates of viral testing significantly decreased. No significant variation was found for complete blood count testing, blood culture testing, or antibiotic use. Overall adherence with AAP guidelines increased over time. CONCLUSIONS Resource use for patients with bronchiolitis varied significantly across hospital bronchiolitis census quartiles despite adjusting for potential known confounders. There remains a need for greater standardization of bronchiolitis management.
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Affiliation(s)
- Christine Andrews
- Hasbro Children's Hospital and Alpert Medical School, Brown University, Providence, Rhode Island;
| | - Sarah L Maxwell
- Department of Pediatrics, University of California, San Francisco and UCSF Benioff Children's Hospital, San Francisco, California; and
| | - Ellen Kerns
- Children's Hospital and Medical Center Omaha and University of Nebraska Medical Center, Omaha, Nebraska
| | - Russell McCulloh
- Children's Hospital and Medical Center Omaha and University of Nebraska Medical Center, Omaha, Nebraska
| | - Brian Alverson
- Hasbro Children's Hospital and Alpert Medical School, Brown University, Providence, Rhode Island
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Wu A, Mihaylova VT, Landry ML, Foxman EF. Interference between rhinovirus and influenza A virus: a clinical data analysis and experimental infection study. THE LANCET. MICROBE 2020; 1:e254-e262. [PMID: 33103132 PMCID: PMC7580833 DOI: 10.1016/s2666-5247(20)30114-2] [Citation(s) in RCA: 137] [Impact Index Per Article: 34.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND During the 2009 pandemic of an emerging influenza A virus (IAV; H1N1pdm09), data from several European countries indicated that the spread of the virus might have been interrupted by the annual autumn rhinovirus epidemic. We aimed to investigate viral interference between rhinovirus and IAV with use of clinical data and an experimental model. METHODS We did a clinical data analysis and experimental infection study to investigate the co-occurrence of rhinovirus and IAV in respiratory specimens from adults (≥21 years) tested with a multiplex PCR panel at Yale-New Haven Hospital (CT, USA) over three consecutive winter seasons (Nov 1 to March 1, 2016-17, 2017-18, and 2018-19). We compared observed versus expected co-detections using data extracted from the Epic Systems electronic medical record system. To assess how rhinovirus infection affects subsequent IAV infection, we inoculated differentiated primary human airway epithelial cultures with rhinovirus (HRV-01A; multiplicity of infection [MOI] 0·1) or did mock infection. On day 3 post-infection, we inoculated the same cultures with IAV (H1N1 green fluorescent protein [GFP] reporter virus or H1N1pdm09; MOI 0·1). We used reverse transcription quantitative PCR or microscopy to quantify host cell mRNAs for interferon-stimulated genes (ISGs) on day 3 after rhinovirus or mock infection and IAV RNA on days 4, 5, or 6 after rhinovirus or mock infection. We also did sequential infection studies in the presence of BX795 (6 μM), to inhibit the interferon response. We compared ISG expression and IAV RNA and expression of GFP by IAV reporter virus. FINDINGS Between July 1, 2016, and June 30, 2019, examination of 8284 respiratory samples positive for either rhinovirus (n=3821) or IAV (n=4463) by any test method was used to establish Nov 1 to March 1 as the period of peak virus co-circulation. After filtering for samples within this time frame meeting the inclusion criteria (n=13 707), there were 989 (7·2%) rhinovirus and 922 (6·7%) IAV detections, with a significantly lower than expected odds of co-detection (odds ratio 0·16, 95% CI 0·09-0·28). Rhinovirus infection of cell cultures induced ISG expression and protected against IAV infection 3 days later, resulting in an approximate 50 000-fold decrease in IAV H1N1pdm09 viral RNA on day 5 post-rhinovirus inoculation. Blocking the interferon response restored IAV replication following rhinovirus infection. INTERPRETATION These findings show that one respiratory virus can block infection with another through stimulation of antiviral defences in the airway mucosa, supporting the idea that interference from rhinovirus disrupted the 2009 IAV pandemic in Europe. These results indicate that viral interference can potentially affect the course of an epidemic, and this possibility should be considered when designing interventions for seasonal influenza epidemics and the ongoing COVID-19 pandemic. FUNDING National Institutes of Health, National Institute of General Medical Sciences, and the Yale Department of Laboratory Medicine.
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Affiliation(s)
- Anchi Wu
- Department of Laboratory Medicine (A Wu BSE, V T Mihaylova PhD, Prof M L Landry MD, Prof E F Foxman MD), Department of Internal Medicine (Prof M L Landry), and Department of Immunobiology (A Wu, Prof E F Foxman), Yale University School of Medicine, New Haven, CT, USA
| | - Valia T Mihaylova
- Department of Laboratory Medicine (A Wu BSE, V T Mihaylova PhD, Prof M L Landry MD, Prof E F Foxman MD), Department of Internal Medicine (Prof M L Landry), and Department of Immunobiology (A Wu, Prof E F Foxman), Yale University School of Medicine, New Haven, CT, USA
| | - Marie L Landry
- Department of Laboratory Medicine (A Wu BSE, V T Mihaylova PhD, Prof M L Landry MD, Prof E F Foxman MD), Department of Internal Medicine (Prof M L Landry), and Department of Immunobiology (A Wu, Prof E F Foxman), Yale University School of Medicine, New Haven, CT, USA
| | - Ellen F Foxman
- Department of Laboratory Medicine (A Wu BSE, V T Mihaylova PhD, Prof M L Landry MD, Prof E F Foxman MD), Department of Internal Medicine (Prof M L Landry), and Department of Immunobiology (A Wu, Prof E F Foxman), Yale University School of Medicine, New Haven, CT, USA
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Dynamics and predisposition of respiratory viral co-infections in children and adults. Clin Microbiol Infect 2020; 27:631.e1-631.e6. [PMID: 32540470 DOI: 10.1016/j.cmi.2020.05.042] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 05/26/2020] [Accepted: 05/30/2020] [Indexed: 01/06/2023]
Abstract
OBJECTIVES The epidemiology of respiratory co-infection pairings is poorly understood. Here we assess the dynamics of respiratory viral co-infections in children and adults and determine predisposition for or against specific viral pairings. METHODS Over five respiratory seasons from 30 November 2013 through 6 June 2018, the mono-infection and co-infection prevalence of 13 viral pathogens was tabulated at The Cleveland Clinic. Employing a model to proportionally distribute viral pairs using individual virus co-infection rate with prevalence patterns of concurrent co-circulating viruses, we compared predicted occurrence with observed occurrence of 132 viral pairing permutations using binomial analysis. RESULTS Of 30 535 respiratory samples, 9843 (32.2%) were positive for at least one virus and 1018 (10.8%) of these were co-infected. Co-infected samples predominantly originated from children. Co-infection rate in paediatric population was 35.0% (2068/5906), compared with only 5.8% (270/4591) in adults. Adenovirus C (ADVC) had the highest co-infection rate (426/623, 68.3%) while influenza virus B had the lowest (55/546, 10.0%). ADVC-rhinovirus (HRV), respiratory syncytial virus A (RSVA)-HRV and RSVB-HRV pairings occurred at significantly higher frequencies than predicted by the proportional distribution model (p < 0.05). Additionally, several viral pairings had fewer co-infections than predicted by our model: notably metapneumovirus (hMPV)-parainfluenza virus 3, hMPV-RSVA and RSVA-RSVB. CONCLUSIONS This is one of the largest studies on respiratory viral co-infections in children and adults. Co-infections are substantially more common in children, especially under 5 years of age, and the most frequent pairings occurred at a higher frequency than would be expected by random. Specific pairings occur at altered rates compared with those predicted by proportional distribution, suggesting either direct or indirect interactions result between specific viral pathogens.
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Detection of Eight Respiratory Bacterial Pathogens Based on Multiplex Real-Time PCR with Fluorescence Melting Curve Analysis. CANADIAN JOURNAL OF INFECTIOUS DISEASES & MEDICAL MICROBIOLOGY 2020; 2020:2697230. [PMID: 32184908 PMCID: PMC7061119 DOI: 10.1155/2020/2697230] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Revised: 11/22/2019] [Accepted: 12/13/2019] [Indexed: 01/23/2023]
Abstract
Background and Objective. Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Streptococcus pneumoniae, Haemophilus influenzae, Staphylococcus aureus, Pseudomonas aeruginosa, and Mycobacterium tuberculosis are primary respiratory bacterial pathogens contributing to morbidity and mortality in developing countries. This study evaluated the diagnostic performance of multiplex real-time PCR with fluorescence melting curve analysis (MCA) assay, which was used to detect eight respiratory bacterial pathogens simultaneously. Methods A total of 157 sputum specimens were examined by multiplex real-time with fluorescence MCA, and the results were compared with the conventional culture method. Results Multiplex real-time PCR with fluorescence MCA specifically detected and differentiated eight respiratory bacterial pathogens by different melting curve peaks for each amplification product within 2 hours and exhibited high repeatability. The limit of detection ranged from 64 to 102 CFU/mL in the multiplex PCR system. Multiplex real-time PCR with fluorescence MCA showed a sensitivity greater than 80% and a 100% specificity for each pathogen. The kappa correlation of eight bacteria ranged from 0.89 to 1.00, and the coefficient of variation ranged from 0.05% to 0.80%. Conclusions Multiplex real-time PCR with fluorescence MCA assay is a sensitive, specific, high-throughput, and cost-effective method to detect multiple bacterial pathogens simultaneously.
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Ang LW, Mak TM, Cui L, Leo YS, Lee VJM, Lin RTP. Characterisation of respiratory syncytial virus activity in children and adults presenting with acute respiratory illness at primary care clinics in Singapore, 2014-2018. Influenza Other Respir Viruses 2020; 14:412-419. [PMID: 32090482 PMCID: PMC7298310 DOI: 10.1111/irv.12730] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 02/03/2020] [Accepted: 02/08/2020] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Respiratory syncytial virus (RSV) is an important respiratory pathogen that affects people of all ages. OBJECTIVES We examined the patterns of RSV circulation in 2014-2018, and investigated their age-specific differences in tropical Singapore. METHODS Nasopharyngeal and/or throat swabs were taken from outpatient attendees for the national influenza virological surveillance among those who presented with acute respiratory illness in the community. Specimens tested negative for influenza were then tested for RSV and other respiratory pathogens. RESULTS Among 8436 influenza-negative specimens tested during the five-year period, 5.8% (95% confidence interval 5.3%-6.3%) were positive for RSV. The peak of RSV activity occurred around middle of the year. The age-specific proportion of RSV detections showed a reverse J-shaped pattern; RSV positivity was the highest in young children ≤2 years of age (10.9%), followed by those aged 3-5 years (6.4%) and persons aged ≥65 years (5.3%), while the nadir was observed in the age group of 15-24 years (1.2%). RSV type A was predominantly circulating in children ≤5 years of age from 2014 to 2015 and 2017, whereas in 2016, they were more affected by type B. CONCLUSION Respiratory syncytial virus was more frequently detected among the two age groups that have been recommended for influenza vaccination; persons ≥65 years of age and children 6 months to <5 years of age. Characterisation of RSV activity in the community helps to better inform public health policies for effective prevention and control interventions.
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Affiliation(s)
- Li Wei Ang
- National Centre for Infectious Diseases, Singapore City, Singapore.,Public Health Group, Ministry of Health, Singapore City, Singapore
| | - Tze Minn Mak
- National Centre for Infectious Diseases, Singapore City, Singapore
| | - Lin Cui
- National Centre for Infectious Diseases, Singapore City, Singapore
| | - Yee Sin Leo
- National Centre for Infectious Diseases, Singapore City, Singapore
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