cohort profile the flu watch study CORD-Papers-2022-06-02 (Version 1)

Title: Cohort Profile: The Flu Watch Study
Published: 2016-03-03
Journal: Int J Epidemiol
DOI: 10.1093/ije/dyv370
DOI_URL: http://doi.org/10.1093/ije/dyv370
Author Name: Fragaszy Ellen B
Author link: https://covid19-data.nist.gov/pid/rest/local/author/fragaszy_ellen_b
Author Name: Warren Gash Charlotte
Author link: https://covid19-data.nist.gov/pid/rest/local/author/warren_gash_charlotte
Author Name: Wang Lili
Author link: https://covid19-data.nist.gov/pid/rest/local/author/wang_lili
Author Name: Copas Andrew
Author link: https://covid19-data.nist.gov/pid/rest/local/author/copas_andrew
Author Name: Dukes Oliver
Author link: https://covid19-data.nist.gov/pid/rest/local/author/dukes_oliver
Author Name: Edmunds W John
Author link: https://covid19-data.nist.gov/pid/rest/local/author/edmunds_w_john
Author Name: Goonetilleke Nilu
Author link: https://covid19-data.nist.gov/pid/rest/local/author/goonetilleke_nilu
Author Name: Harvey Gabrielle
Author link: https://covid19-data.nist.gov/pid/rest/local/author/harvey_gabrielle
Author Name: Johnson Anne M
Author link: https://covid19-data.nist.gov/pid/rest/local/author/johnson_anne_m
Author Name: Kovar Jana
Author link: https://covid19-data.nist.gov/pid/rest/local/author/kovar_jana
Author Name: Lim Megan SC
Author link: https://covid19-data.nist.gov/pid/rest/local/author/lim_megan_sc
Author Name: McMichael Andrew
Author link: https://covid19-data.nist.gov/pid/rest/local/author/mcmichael_andrew
Author Name: Millett Elizabeth RC
Author link: https://covid19-data.nist.gov/pid/rest/local/author/millett_elizabeth_rc
Author Name: Nazareth Irwin
Author link: https://covid19-data.nist.gov/pid/rest/local/author/nazareth_irwin
Author Name: Nguyen Van Tam Jonathan S
Author link: https://covid19-data.nist.gov/pid/rest/local/author/nguyen_van_tam_jonathan_s
Author Name: Tabassum Faiza
Author link: https://covid19-data.nist.gov/pid/rest/local/author/tabassum_faiza
Author Name: Watson John M
Author link: https://covid19-data.nist.gov/pid/rest/local/author/watson_john_m
Author Name: Wurie Fatima
Author link: https://covid19-data.nist.gov/pid/rest/local/author/wurie_fatima
Author Name: Zambon Maria
Author link: https://covid19-data.nist.gov/pid/rest/local/author/zambon_maria
Author Name: Hayward Andrew C
Author link: https://covid19-data.nist.gov/pid/rest/local/author/hayward_andrew_c
sha: 64ee665b9ca47283ff31e1789655e70838efc849
license: cc-by
license_url: https://creativecommons.org/licenses/by/4.0/
source_x: Medline; PMC
source_x_url: https://www.medline.com/https://www.ncbi.nlm.nih.gov/pubmed/
pubmed_id: 26940466
pubmed_id_url: https://www.ncbi.nlm.nih.gov/pubmed/26940466
pmcid: PMC5837336
pmcid_url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5837336
url: https://doi.org/10.1093/ije/dyv370 https://www.ncbi.nlm.nih.gov/pubmed/26940466/
has_full_text: TRUE
Keywords Extracted from Text Content: Baseline/pre-season phase A Serology Human T cell Blood T cells Flu Watch UK rhinovirus human C;(ii children human influenza viruses participants muscle human metapneumovirus serum samples bloods T cell samples RSV pigs coronavirus Virology blood samples SMS adenovirus swine women people AH1N1 nasal swabs H3N2 strains blood volunteer nasal swab influenza-specific T cells B wipe-clean H1N1 pandemic strain hMPV IFN-celispots CD8/4 Post-season T cell Peripheral blood mononuclear cells IFN-celispot Flu Watch participants intracellular PBMC
Extracted Text Content in Record: First 5000 Characters:Influenza is a common, highly contagious respiratory virus which infects all age groups, causing a range of outcomes from asymptomatic infection and mild respiratory disease to severe respiratory disease and death. 1 If infected, the adaptive immune system produces a humoral (antibody) and cell-mediated (T cell) immune response to fight the infection. 2 Influenza viruses continually evolve through antigenic drift, resulting in slightly different 'seasonal' influenza strains circulating each year. Population-level antibody immunity to these seasonal viruses builds up over time, so in any given season only a proportion of the population is susceptible to the circulating strains. Occasionally, influenza A viruses evolve rapidly through antigenic shift by swapping genes with influenza viruses usually circulating in animals. This process creates an immunologically distinct virus to which the population may have little to no antibody immunity. The virus can result in a pandemic if a large portion of the population is susceptible and the virus is easily spread. 1 International influenza surveillance is typically based upon cases seeking medical care. [3] [4] [5] However, this focus greatly underestimates the true community burden of seasonal influenza: the majority of cases are mild and self-limiting, with asymptomatic infections accounting for 25% to 75% of all infections. 6, 7 Effective influenza control requires knowledge of disease burden and factors affecting influenza transmission. Existing parameters for mathematical models of influenza interventions are largely derived from household cohort studies conducted in the USA between 1948 and 1981. [8] [9] [10] Since then there have been profound social changes affecting population contact and mixing patterns that are likely to impact on influenza transmission. These changes include more women working, more children attending day care, more commuting and international travel and increased vaccine coverage. Evolutionary changes to circulating viruses may affect transmission dynamics, patterns of clinical illness and the adaptive immune responses elicited. 1, 11 Rapid advances in laboratory methods have also occurred, providing unique opportunities to investigate immune correlates, both humoral and T cell based, with influenza infection rates and disease severity. 11, 12 The initial Flu Watch cohort, funded by the UK Medical Research Council (MRC), began in 2006 as a collaboration between epidemiologists at the Centre for Infectious Disease Epidemiology at University College London (UCL), virologists and mathematical modellers from the Health Protection Agency (HPA, now Public Health England), immunologists at the MRC Human Immunology Unit at Oxford University and the MRC General Practice Research Framework (GPRF). It aimed to estimate community burden of influenza and influenza-like illness, generate up-to-date knowledge of demographic, social and behavioural factors affecting influenza transmission, measure antibody and T cell immune responses to influenza and to use knowledge generated to inform modelling parameters. In addition, a pandemic preparedness cohort was envisioned, in which participants already familiar with the study consented to be re-contacted in the event of a pandemic, to allow rapid redeployment of the study. When the 2009 influenza AH1N1 pandemic arose, further funding was secured jointly from the MRC and Wellcome Trust, allowing continued follow-up and an expansion in cohort size. New collaborators for this phase included the MRC Centre for Outbreak Analysis and Modelling, the Wellcome Sanger Institute, the Primary Care Research Network and additional epidemiology and public health experts from the HPA. Additional study aims were to inform the national and international response to the current and future pandemics. Specific objectives were to examine clinical profiles of illness, estimate population infection denominators and case fatality risk, describe epidemiological characteristics of the infection in real-time, monitor changes in population behaviour, and investigate access to services, attitudes to and uptake of antivirals and vaccine, and immunity to infection in order to inform vaccination policy and development. During the pandemic, Flu Watch also provided control data and samples for studies of severe influenza (MOSAIC) and studies of influenza infection risk in people working with pigs (COSI). 13, 14 Who is in the cohort? Households were recruited from registers of 146 volunteer general practices (GP) across England, who formed part of the MRC GPRF or (from the 2009 pandemic onwards) the Primary Care Research Network. Participants were selected from GP lists by computer-based random number generation. GPs sent invitation letters inviting the randomly selected person and their household to participate. Although it was recognized that this would bias invitations towards larger households, such as those with children, this was accepted
Keywords Extracted from PMC Text: women O.D. people previously.18–20 and2008/09 volunteer muscle nasal swab T cell samples H3N2 strains blood samples ≥ pigs (COSI).13,14 human T cells Nutshell Flu Flu Watch see influenza-specific T cells children human influenza viruses H1N1 pandemic strain bloods serum samples periods.16 human metapneumovirus Virology coronavirus H1N1 Serology swine Flu Watch nasal swabs rhinovirus AH1N1 participants C;(ii pigs Blood Human B England.21 SMS wipe-clean blood adenovirus RSV T cells).Data T cell M.S.C.L. Flu NHS UK MC_U122785833 hMPV
Extracted PMC Text Content in Record: First 5000 Characters:Influenza is a common, highly contagious respiratory virus which infects all age groups, causing a range of outcomes from asymptomatic infection and mild respiratory disease to severe respiratory disease and death.1 If infected, the adaptive immune system produces a humoral (antibody) and cell-mediated (T cell) immune response to fight the infection.2 Influenza viruses continually evolve through antigenic drift, resulting in slightly different 'seasonal' influenza strains circulating each year. Population-level antibody immunity to these seasonal viruses builds up over time, so in any given season only a proportion of the population is susceptible to the circulating strains. Occasionally, influenza A viruses evolve rapidly through antigenic shift by swapping genes with influenza viruses usually circulating in animals. This process creates an immunologically distinct virus to which the population may have little to no antibody immunity. The virus can result in a pandemic if a large portion of the population is susceptible and the virus is easily spread.1 International influenza surveillance is typically based upon cases seeking medical care.3–5 However, this focus greatly underestimates the true community burden of seasonal influenza: the majority of cases are mild and self-limiting, with asymptomatic infections accounting for 25% to 75% of all infections.6,7 Effective influenza control requires knowledge of disease burden and factors affecting influenza transmission. Existing parameters for mathematical models of influenza interventions are largely derived from household cohort studies conducted in the USA between 1948 and 1981.8–10 Since then there have been profound social changes affecting population contact and mixing patterns that are likely to impact on influenza transmission. These changes include more women working, more children attending day care, more commuting and international travel and increased vaccine coverage. Evolutionary changes to circulating viruses may affect transmission dynamics, patterns of clinical illness and the adaptive immune responses elicited.1,11 Rapid advances in laboratory methods have also occurred, providing unique opportunities to investigate immune correlates, both humoral and T cell based, with influenza infection rates and disease severity.11,12 The initial Flu Watch cohort, funded by the UK Medical Research Council (MRC), began in 2006 as a collaboration between epidemiologists at the Centre for Infectious Disease Epidemiology at University College London (UCL), virologists and mathematical modellers from the Health Protection Agency (HPA, now Public Health England), immunologists at the MRC Human Immunology Unit at Oxford University and the MRC General Practice Research Framework (GPRF). It aimed to estimate community burden of influenza and influenza-like illness, generate up-to-date knowledge of demographic, social and behavioural factors affecting influenza transmission, measure antibody and T cell immune responses to influenza and to use knowledge generated to inform modelling parameters. In addition, a pandemic preparedness cohort was envisioned, in which participants already familiar with the study consented to be re-contacted in the event of a pandemic, to allow rapid redeployment of the study. When the 2009 influenza AH1N1 pandemic arose, further funding was secured jointly from the MRC and Wellcome Trust, allowing continued follow-up and an expansion in cohort size. New collaborators for this phase included the MRC Centre for Outbreak Analysis and Modelling, the Wellcome Sanger Institute, the Primary Care Research Network and additional epidemiology and public health experts from the HPA. Additional study aims were to inform the national and international response to the current and future pandemics. Specific objectives were to examine clinical profiles of illness, estimate population infection denominators and case fatality risk, describe epidemiological characteristics of the infection in real-time, monitor changes in population behaviour, and investigate access to services, attitudes to and uptake of antivirals and vaccine, and immunity to infection in order to inform vaccination policy and development. During the pandemic, Flu Watch also provided control data and samples for studies of severe influenza (MOSAIC) and studies of influenza infection risk in people working with pigs (COSI).13,14 Households were recruited from registers of 146 volunteer general practices (GP) across England, who formed part of the MRC GPRF or (from the 2009 pandemic onwards) the Primary Care Research Network. Participants were selected from GP lists by computer-based random number generation. GPs sent invitation letters inviting the randomly selected person and their household to participate. Although it was recognized that this would bias invitations towards larger households, such as those with children, this was accepted as the role of children in influenza transmission
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