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Mahesh DN, Sreelatha B, Vinoth S, Nancy S. Clinical profile of children with influenza like illness during pre-monsoon at coastal Karaikal, Puducherry, India. Bioinformation 2024; 20:252-257. [PMID: 38712005 PMCID: PMC11069598 DOI: 10.6026/973206300200252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 03/31/2024] [Accepted: 03/31/2024] [Indexed: 05/08/2024] Open
Abstract
Influenza infections in developing countries are under reported and WHO estimates that nearly 99% of influenza deaths worldwide occur in children under-five years of age in Asian and African countries. Consequently, this study aims to analyze the use of clinical profile and easily available laboratory parameters to aid identification of the possible viral etiology in the setting of pre-monsoon ILI. A cross-sectional study was carried out for three months among children with ILI attending fever clinic of a tertiary care hospital in Karaikal, South India. In the study population the prevalence of ILI was highest in the age group four to five years followed by school aged children. Adolescents were affected the least. Influenza B was most common virus causing ILI in this region, followed by covid-19 infection. Laboratory parameters depicted a significantly high ESR in COVID-19 infected ILI children. They also exhibited leucopenia and normal platelet counts. Clinical symptoms and laboratory parameters which are easily available and cheaper can be used in resource poor settings of healthcare to identify possible influenza and COVID-19 infected children amongst cases presenting with ILI.
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Affiliation(s)
- Dande Naga Mahesh
- Department of Paediatrics, Vinayaka Mission's Medical College and Hospital, Vinayaka Mission's Research Foundation - Deemed to be University (VMRF-DU), Karaikal, Puducherry, India
| | - B Sreelatha
- Department of Paediatrics, Vinayaka Mission's Medical College and Hospital, Vinayaka Mission's Research Foundation - Deemed to be University (VMRF-DU), Karaikal, Puducherry, India
| | - S Vinoth
- Department of Paediatrics, Vinayaka Mission's Medical College and Hospital, Vinayaka Mission's Research Foundation - Deemed to be University (VMRF-DU), Karaikal, Puducherry, India
| | - S Nancy
- Department of Community Medicine, Vinayaka Mission's Medical College and Hospital, Vinayaka Mission's Research Foundation - Deemed to be University (VMRF-DU), Karaikal, Puducherry, India
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Han SM, Robert A, Masuda S, Yasaka T, Kanda S, Komori K, Saito N, Suzuki M, Endo A, Baguelin M, Ariyoshi K. Transmission dynamics of seasonal influenza in a remote island population. Sci Rep 2023; 13:5393. [PMID: 37012350 PMCID: PMC10068240 DOI: 10.1038/s41598-023-32537-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 03/29/2023] [Indexed: 04/05/2023] Open
Abstract
Seasonal influenza outbreaks remain an important public health concern, causing large numbers of hospitalizations and deaths among high-risk groups. Understanding the dynamics of individual transmission is crucial to design effective control measures and ultimately reduce the burden caused by influenza outbreaks. In this study, we analyzed surveillance data from Kamigoto Island, Japan, a semi-isolated island population, to identify the drivers of influenza transmission during outbreaks. We used rapid influenza diagnostic test (RDT)-confirmed surveillance data from Kamigoto island, Japan and estimated age-specific influenza relative illness ratios (RIRs) over eight epidemic seasons (2010/11 to 2017/18). We reconstructed the probabilistic transmission trees (i.e., a network of who-infected-whom) using Bayesian inference with Markov-chain Monte Carlo method and then performed a negative binomial regression on the inferred transmission trees to identify the factors associated with onwards transmission risk. Pre-school and school-aged children were most at risk of getting infected with influenza, with RIRs values consistently above one. The maximal RIR values were 5.99 (95% CI 5.23, 6.78) in the 7-12 aged-group and 5.68 (95%CI 4.59, 6.99) in the 4-6 aged-group in 2011/12. The transmission tree reconstruction suggested that the number of imported cases were consistently higher in the most populated and busy districts (Tainoura-go and Arikawa-go) ranged from 10-20 to 30-36 imported cases per season. The number of secondary cases generated by each case were also higher in these districts, which had the highest individual reproduction number (Reff: 1.2-1.7) across the seasons. Across all inferred transmission trees, the regression analysis showed that cases reported in districts with lower local vaccination coverage (incidence rate ratio IRR = 1.45 (95% CI 1.02, 2.05)) or higher number of inhabitants (IRR = 2.00 (95% CI 1.89, 2.12)) caused more secondary transmissions. Being younger than 18 years old (IRR = 1.38 (95%CI 1.21, 1.57) among 4-6 years old and 1.45 (95% CI 1.33, 1.59) 7-12 years old) and infection with influenza type A (type B IRR = 0.83 (95% CI 0.77, 0.90)) were also associated with higher numbers of onwards transmissions. However, conditional on being infected, we did not find any association between individual vaccination status and onwards transmissibility. Our study showed the importance of focusing public health efforts on achieving high vaccine coverage throughout the island, especially in more populated districts. The strong association between local vaccine coverage (including neighboring regions), and the risk of transmission indicate the importance of achieving homogeneously high vaccine coverage. The individual vaccine status may not prevent onwards transmission, though it may reduce the severity of infection.
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Affiliation(s)
- Su Myat Han
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan.
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK.
| | - Alexis Robert
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK
| | - Shingo Masuda
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
- Department of Internal Medicine, Kamigoto Hospital, Kamigoto, Japan
| | - Takahiro Yasaka
- Department of Internal Medicine, Kamigoto Hospital, Kamigoto, Japan
| | - Satoshi Kanda
- Department of Internal Medicine, Kamigoto Hospital, Kamigoto, Japan
| | - Kazuhiri Komori
- Department of Internal Medicine, Kamigoto Hospital, Kamigoto, Japan
| | - Nobuo Saito
- Department of Microbiology, Faculty of Medicine, Oita University, Yufu, Japan
- Department of Clinical Medicine, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan
| | - Motoi Suzuki
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
- Infectious Disease Surveillance Center, National Institute of Infectious Diseases, Tokyo, Japan
| | - Akira Endo
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London, UK
| | - Marc Baguelin
- Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
- MRC Centre for Global Infectious Disease Analysis and the Abdul Latif Jameel Institute for Disease, London, UK
| | - Koya Ariyoshi
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
- Department of Clinical Medicine, Institute of Tropical Medicine, Nagasaki University, Nagasaki, Japan
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Johnson EK, Sylte D, Chaves SS, Li Y, Mahe C, Nair H, Paget J, van Pomeren T, Shi T, Viboud C, James SL. Hospital utilization rates for influenza and RSV: a novel approach and critical assessment. Popul Health Metr 2021; 19:31. [PMID: 34126993 PMCID: PMC8204427 DOI: 10.1186/s12963-021-00252-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 03/31/2021] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Influenza and respiratory syncytial virus (RSV) contribute significantly to the burden of acute lower respiratory infection (ALRI) inpatient care, but heterogeneous coding practices and availability of inpatient data make it difficult to estimate global hospital utilization for either disease based on coded diagnoses alone. METHODS This study estimates rates of influenza and RSV hospitalization by calculating the proportion of ALRI due to influenza and RSV and applying this proportion to inpatient admissions with ALRI coded as primary diagnosis. Proportions of ALRI attributed to influenza and RSV were extracted from a meta-analysis of 360 total sources describing inpatient hospital admissions which were input to a Bayesian mixed effects model over age with random effects over location. Results of this model were applied to inpatient admission datasets for 44 countries to produce rates of hospital utilization for influenza and RSV respectively, and rates were compared to raw coded admissions for each disease. RESULTS For most age groups, these methods estimated a higher national admission rate than the rate of directly coded influenza or RSV admissions in the same inpatient sources. In many inpatient sources, International Classification of Disease (ICD) coding detail was insufficient to estimate RSV burden directly. The influenza inpatient burden estimates in older adults appear to be substantially underestimated using this method on primary diagnoses alone. Application of the mixed effects model reduced heterogeneity between countries in influenza and RSV which was biased by coding practices and between-country variation. CONCLUSIONS This new method presents the opportunity of estimating hospital utilization rates for influenza and RSV using a wide range of clinical databases. Estimates generally seem promising for influenza and RSV associated hospitalization, but influenza estimates from primary diagnosis seem highly underestimated among older adults. Considerable heterogeneity remains between countries in ALRI coding (i.e., primary vs non-primary cause), and in the age profile of proportion positive for influenza and RSV across studies. While this analysis is interesting because of its wide data utilization and applicability in locations without laboratory-confirmed admission data, understanding the sources of variability and data quality will be essential in future applications of these methods.
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Affiliation(s)
- Emily K Johnson
- Institute of Health Metrics and Evaluation, University of Washington, Seattle, USA.
| | - Dillon Sylte
- Institute of Health Metrics and Evaluation, University of Washington, Seattle, USA
| | - Sandra S Chaves
- Foundation for Influenza Epidemiology, Fondation de France, Paris, France
- Vaccine Epidemiology and Modeling Department, Sanofi Pasteur, Lyon, France
| | - You Li
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Cedric Mahe
- Foundation for Influenza Epidemiology, Fondation de France, Paris, France
- Vaccine Epidemiology and Modeling Department, Sanofi Pasteur, Lyon, France
| | - Harish Nair
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - John Paget
- Netherlands Institute for Health Services Research (Nivel), Utrecht, Netherlands
| | - Tayma van Pomeren
- Netherlands Institute for Health Services Research (Nivel), Utrecht, Netherlands
| | - Ting Shi
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Cecile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, USA
| | - Spencer L James
- Institute of Health Metrics and Evaluation, University of Washington, Seattle, USA
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Coletti P, Poletto C, Turbelin C, Blanchon T, Colizza V. Shifting patterns of seasonal influenza epidemics. Sci Rep 2018; 8:12786. [PMID: 30143689 PMCID: PMC6109160 DOI: 10.1038/s41598-018-30949-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Accepted: 07/24/2018] [Indexed: 12/25/2022] Open
Abstract
Seasonal waves of influenza display a complex spatiotemporal pattern resulting from the interplay of biological, sociodemographic, and environmental factors. At country level many studies characterized the robust properties of annual epidemics, depicting a typical season. Here we analyzed season-by-season variability, introducing a clustering approach to assess the deviations from typical spreading patterns. The classification is performed on the similarity of temporal configurations of onset and peak times of regional epidemics, based on influenza-like-illness time-series in France from 1984 to 2014. We observed a larger variability in the onset compared to the peak. Two relevant classes of clusters emerge: groups of seasons sharing similar recurrent spreading patterns (clustered seasons) and single seasons displaying unique patterns (monoids). Recurrent patterns exhibit a more pronounced spatial signature than unique patterns. We assessed how seasons shift between these classes from onset to peak depending on epidemiological, environmental, and socio-demographic variables. We found that the spatial dynamics of influenza and its association with commuting, previously observed as a general property of French influenza epidemics, apply only to seasons exhibiting recurrent patterns. The proposed methodology is successful in providing new insights on influenza spread and can be applied to incidence time-series of different countries and different diseases.
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Affiliation(s)
- Pietro Coletti
- ISI Foundation, Turin, Italy
- Universiteit Hasselt, I-Biostat, 3500, Hasselt, Belgium
| | - Chiara Poletto
- INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, F75012, Paris, France
| | - Clément Turbelin
- INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, F75012, Paris, France
| | - Thierry Blanchon
- INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, F75012, Paris, France
| | - Vittoria Colizza
- INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, F75012, Paris, France.
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Multiple Viral Infection Detected from Influenza-Like Illness Cases in Indonesia. BIOMED RESEARCH INTERNATIONAL 2017; 2017:9541619. [PMID: 28232948 PMCID: PMC5292373 DOI: 10.1155/2017/9541619] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2016] [Revised: 11/22/2016] [Accepted: 12/13/2016] [Indexed: 01/30/2023]
Abstract
Influenza is one of the common etiologies of the upper respiratory tract infection (URTI). However, influenza virus only contributes about 20 percent of influenza-like illness patients. The aim of the study is to investigate the other viral etiologies from ILI cases in Indonesia. Of the 334 samples, 266 samples (78%) were positive at least for one virus, including 107 (42%) cases of multiple infections. Influenza virus is the most detected virus. The most frequent combination of viruses identified was adenovirus and human rhinovirus. This recent study demonstrated high detection rate of several respiratory viruses from ILI cases in Indonesia. Further studies to determine the relationship between viruses and clinical features are needed to improve respiratory disease control program.
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Masse S, Minodier L, Heuze G, Blanchon T, Capai L, Falchi A. Influenza-like illness outbreaks in nursing homes in Corsica, France, 2014-2015: epidemiological and molecular characterization. SPRINGERPLUS 2016; 5:1338. [PMID: 27563533 PMCID: PMC4981007 DOI: 10.1186/s40064-016-2957-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2016] [Accepted: 07/29/2016] [Indexed: 11/25/2022]
Abstract
Background To study the molecular epidemiology of the influenza outbreaks in nursing homes (NHs) to determine whether multiple influenza strains were involved. Methods From September to December 2014, NHs in Corsica were invited to participate in an ongoing daily epidemiological and microbiological surveillance for influenza-like illness (ILI) among residents and health care workers (HCWs). Results The study involved 12 NHs. Respiratory illness meeting the ILI case definition was observed among 44 residents from whom 22 specimens were collected. Of the 22 residents with a nasopharyngeal sample, 13 (59 %) were positive for at least one of the 11 pathogens analysed. Among these 13 patients, 11 (92 %) presented a confirmed influenza (A/H3N2) and two had another respiratory virus: one human metapneumovirus and one human coronavirus. Of patients with a confirmed influenza A(H3N2), 10 (91 %) were vaccinated against influenza during the 2014–2015 season. Two influenza outbreaks were reported in two NHs, caused by influenza A(H3N2) strains belonging to cluster 3C.3 and 3C.2a. Although antivirals were available, prophylaxis was not used. Conclusions Phylogenetic analysis seems to suggest no multiple introduction into the two NHs reporting the two influenza A(H3N2) outbreaks. A number of factors could have contributed to transmitting influenza in NHs including, the absence of administration of antiviral treatment for prophylaxis of all residents/staff regardless of immunization status because of the poor vaccine match during each outbreak, the intensive contacts with incompletely protected residents and HCWs, and the low adherence of NHs to notification of ILI outbreaks to the health authorities. Electronic supplementary material The online version of this article (doi:10.1186/s40064-016-2957-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- S Masse
- EA 7310, Laboratory of Virology, University of Corsica-Inserm, Corte, France
| | - L Minodier
- EA 7310, Laboratory of Virology, University of Corsica-Inserm, Corte, France
| | - G Heuze
- CIRE-SUD Paca Corse, InVS, Saint-Maurice Cedex, Paris, France
| | - T Blanchon
- UPMC Univ Paris 06, UMR_S 1136, Sorbonne Universités, Paris, France ; INSERM, UMR_S 1136, Paris, France
| | - L Capai
- EA 7310, Laboratory of Virology, University of Corsica-Inserm, Corte, France ; UPMC Univ Paris 06, UMR_S 1136, Sorbonne Universités, Paris, France ; INSERM, UMR_S 1136, Paris, France
| | - A Falchi
- EA 7310, Laboratory of Virology, University of Corsica-Inserm, Corte, France
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NICKBAKHSH S, THORBURN F, VON WISSMANN B, McMENAMIN J, GUNSON RN, MURCIA PR. Extensive multiplex PCR diagnostics reveal new insights into the epidemiology of viral respiratory infections. Epidemiol Infect 2016; 144:2064-76. [PMID: 26931455 PMCID: PMC7113017 DOI: 10.1017/s0950268816000339] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2015] [Revised: 11/20/2015] [Accepted: 02/03/2016] [Indexed: 12/14/2022] Open
Abstract
Viral respiratory infections continue to pose a major global healthcare burden. At the community level, the co-circulation of respiratory viruses is common and yet studies generally focus on single aetiologies. We conducted the first comprehensive epidemiological analysis to encompass all major respiratory viruses in a single population. Using extensive multiplex PCR diagnostic data generated by the largest NHS board in Scotland, we analysed 44230 patient episodes of respiratory illness that were simultaneously tested for 11 virus groups between 2005 and 2013, spanning the 2009 influenza A pandemic. We measured viral infection prevalence, described co-infections, and identified factors independently associated with viral infection using multivariable logistic regression. Our study provides baseline measures and reveals new insights that will direct future research into the epidemiological consequences of virus co-circulation. In particular, our study shows that (i) human coronavirus infections are more common during influenza seasons and in co-infections than previously recognized, (ii) factors associated with co-infection differ from those associated with viral infection overall, (iii) virus prevalence has increased over time especially in infants aged <1 year, and (iv) viral infection risk is greater in the post-2009 pandemic era, likely reflecting a widespread change in the viral population that warrants further investigation.
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Affiliation(s)
- S. NICKBAKHSH
- MRC-University of Glasgow Centre for Virus Research, Institute of Infection, Inflammation and Immunity, Glasgow, UK
| | - F. THORBURN
- MRC-University of Glasgow Centre for Virus Research, Institute of Infection, Inflammation and Immunity, Glasgow, UK
| | - B. VON WISSMANN
- Health Protection Scotland, NHS National Services Scotland, Glasgow, UK
| | - J. McMENAMIN
- Health Protection Scotland, NHS National Services Scotland, Glasgow, UK
| | - R. N. GUNSON
- West of Scotland Specialist Virology Centre, NHS Greater Glasgow and Clyde, GlasgowUK
| | - P. R. MURCIA
- MRC-University of Glasgow Centre for Virus Research, Institute of Infection, Inflammation and Immunity, Glasgow, UK
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