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      Influenza vaccine effectiveness against influenza A in children based on the results of various rapid influenza tests in the 2018/19 season

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          Abstract

          During influenza epidemics, Japanese clinicians routinely conduct rapid influenza diagnostic tests (RIDTs) in patients with influenza-like illness, and patients with positive test results are treated with anti-influenza drugs within 48 h after the onset of illness. We assessed the vaccine effectiveness (VE) of inactivated influenza vaccine (IIV) in children (6 months–15 years old, N = 4243), using a test-negative case-control design based on the results of RIDTs in the 2018/19 season. The VE against influenza A(H1N1)pdm and A(H3N2) was analyzed separately using an RIDT kit specifically for detecting A(H1N1)pdm09. The adjusted VE against combined influenza A (H1N1pdm and H3N2) and against A(H1N1)pdm09 was 39% (95% confidence interval [CI], 30%–46%) and 74% (95% CI, 39%–89%), respectively. By contrast, the VE against non-A(H1N1)pdm09 influenza A (presumed to be H3N2) was very low at 7%. The adjusted VE for preventing hospitalization was 56% (95% CI, 16%–77%) against influenza A. The VE against A(H1N1)pdm09 was consistently high in our studies. By contrast, the VE against A(H3N2) was low not only in adults but also in children in the 2018/19 season.

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          Methodologic issues regarding the use of three observational study designs to assess influenza vaccine effectiveness.

          Influenza causes substantial morbidity and annual vaccination is the most important prevention strategy. Accurately measuring vaccine effectiveness (VE) is difficult. The clinical syndrome most closely associated with influenza virus infection, influenza-like illness (ILI), is not specific. In addition, laboratory confirmation is infrequently done, and available rapid diagnostic tests are imperfect. The objective of this study was to estimate the joint impact of rapid diagnostic test sensitivity and specificity on VE for three types of study designs: a cohort study, a traditional case-control study, and a case-control study that used as controls individuals with ILI who tested negative for influenza virus infection. We developed a mathematical model with five input parameters: true VE, attack rates (ARs) of influenza-ILI and non-influenza-ILI and the sensitivity and specificity of the diagnostic test. With imperfect specificity, estimates from all three designs tended to underestimate true VE, but were similar except if fairly extreme inputs were used. Only if test specificity was 95% or more or if influenza attack rates doubled that of background illness did the case-control method slightly overestimate VE. The case-control method usually produced the highest and most accurate estimates, followed by the test-negative design. The bias toward underestimating true VE introduced by low test specificity increased as the AR of influenza- relative to non-influenza-ILI decreases and, to a lesser degree, with lower test sensitivity. Demonstration of a high influenza VE using tests with imperfect sensitivity and specificity should provide reassurance that the program has been effective in reducing influenza illnesses, assuming adequate control of confounding factors.
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            Spread of Antigenically Drifted Influenza A(H3N2) Viruses and Vaccine Effectiveness in the United States During the 2018–2019 Season

            Increased illness due to antigenically drifted A(H3N2) clade 3C.3a influenza viruses prompted concerns about vaccine effectiveness (VE) and vaccine strain selection. We used US virologic surveillance and US Influenza Vaccine Effectiveness (Flu VE) Network data to evaluate consequences of this clade. Distribution of influenza viruses was described using virologic surveillance data. The Flu VE Network enrolled ambulatory care patients aged ≥6 months with acute respiratory illness at 5 sites. Respiratory specimens were tested for influenza by means of reverse-transcriptase polymerase chain reaction and were sequenced. Using a test-negative design, we estimated VE, comparing the odds of influenza among vaccinated versus unvaccinated participants. During the 2018–2019 influenza season, A(H3N2) clade 3C.3a viruses caused an increasing proportion of influenza cases. Among 2763 Flu VE Network case patients, 1325 (48%) were infected with A(H1N1)pdm09 and 1350 (49%) with A(H3N2); clade 3C.3a accounted for 977 (93%) of 1054 sequenced A(H3N2) viruses. VE was 44% (95% confidence interval, 37%–51%) against A(H1N1)pdm09 and 9% (−4% to 20%) against A(H3N2); VE was 5% (−10% to 19%) against A(H3N2) clade 3C.3a viruses. The predominance of A(H3N2) clade 3C.3a viruses during the latter part of the 2018–2019 season was associated with decreased VE, supporting the A(H3N2) vaccine component update for 2019–2020 northern hemisphere influenza vaccines.
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              Diagnostic Accuracy of Novel and Traditional Rapid Tests for Influenza Infection Compared With Reverse Transcriptase Polymerase Chain Reaction: A Systematic Review and Meta-analysis.

              Rapid and accurate influenza diagnostics can improve patient care.
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                Author and article information

                Contributors
                Role: Data curationRole: InvestigationRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: Project administrationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: MethodologyRole: SupervisionRole: Validation
                Role: Data curationRole: Project administration
                Role: Data curationRole: Software
                Role: Data curationRole: InvestigationRole: Methodology
                Role: Data curationRole: Investigation
                Role: Data curationRole: Investigation
                Role: Data curationRole: Investigation
                Role: Data curationRole: Investigation
                Role: Data curationRole: Investigation
                Role: Data curationRole: Investigation
                Role: Data curationRole: Methodology
                Role: Data curationRole: Investigation
                Role: Data curationRole: Investigation
                Role: Data curationRole: Investigation
                Role: Data curationRole: InvestigationRole: Methodology
                Role: Data curationRole: InvestigationRole: Software
                Role: Data curationRole: InvestigationRole: Validation
                Role: Data curationRole: Formal analysis
                Role: Data curationRole: Investigation
                Role: InvestigationRole: Validation
                Role: Data curationRole: Investigation
                Role: InvestigationRole: Methodology
                Role: ConceptualizationRole: Formal analysis
                Role: ConceptualizationRole: Supervision
                Role: ConceptualizationRole: Data curationRole: SupervisionRole: Validation
                Role: ConceptualizationRole: Project administrationRole: SupervisionRole: Validation
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                26 March 2021
                2021
                : 16
                : 3
                : e0249005
                Affiliations
                [1 ] Department of Pediatrics, Keio University School of Medicine, Tokyo, Japan
                [2 ] Department of Pediatrics, Keiyu Hospital, Kanagawa, Japan
                [3 ] Institute of Clinical Research & Department of Infection and Allergy, National Hospital Organization Tochigi Hospital, Tochigi, Japan
                [4 ] Department of Pediatrics, Japanese Red Cross Shizuoka Hospital, Shizuoka, Japan
                [5 ] Department of Pediatrics, Nippon Koukan Hospital, Kanagawa, Japan
                [6 ] Department of Pediatrics, Kawasaki Municipal Hospital, Kanagawa, Japan
                [7 ] Department Pediatrics, Yokohama Municipal Citizen’s Hospital, Kanagawa, Japan
                [8 ] Department of Pediatrics, Subaru Health Insurance Society Ota Memorial Hospital, Gunma, Japan
                [9 ] Department of Pediatrics, Japanese Red Cross Ashikaga Hospital, Tochigi, Japan
                [10 ] Department of Pediatrics, Saitama City Hospital, Saitama, Japan
                [11 ] Department of Pediatrics, Tokyo Dental College Ichikawa General Hospital, Chiba, Japan
                [12 ] Department of Pediatrics, Tokyo Metropolitan Ohtsuka Hospital, Tokyo, Japan
                [13 ] Department of Pediatrics, Saiseikai Utsunomiya Hospital, Tochigi, Japan
                [14 ] Department of Pediatrics, National Hospital Organization Tokyo Medical Center, Tokyo, Japan
                [15 ] Department of Pediatrics, National Hospital Organization Saitama Hospital, Saitama, Japan
                [16 ] Department of Pediatrics, Shizuoka City Shimizu Hospital, Shizuoka, Japan
                [17 ] Department of Pediatrics, Sano Kosei General Hospital, Tochigi, Japan
                [18 ] Department of Pediatrics, Hino Municipal Hospital, Tokyo, Japan
                [19 ] Department of Pediatrics, Yokohama Rosai Hospital, Kanagawa, Japan
                [20 ] Department of Pediatrics, Hiratsuka City Hospital, Kanagawa, Japan
                [21 ] Yokohama City Institute of Public Health, Yokohama, Japan
                [22 ] Department of Pediatrics, Eiju General Hospital, Tokyo, Japan
                The Chinese University of Hong Kong, HONG KONG
                Author notes

                Competing Interests: We have read the journal’s policy and the authors of this manuscript have the following competing interests: within 36 months, Dr. Norio Sugaya has received speakers’ honoraria from Chugai, Shionogi, Daiichi Sankyo, Astellas, Merck, and Denka Seiken. Dr. Masayoshi Shinjoh has received speakers’ honoraria from Shionogi, Meiji Seika, Merck, Sumitomo Dainippon, Japan Vaccine, Maruho, Astellas, Daiichi Sankyo, and grant support from Janssen. Dr. Keiko Mitamura has received speakers’ honoraria from Shionogi, Meiji Seika, and manuscript fee from Astellas. Dr. Takao Takahashi has received speakers’ honoraria from Daiichi Sankyo, GlaxoSmithKline, Japan Vaccine, Pfizer, Merck, and grant support from Daiichi Sankyo, Japan Vaccine, Pfizer, Merck, Takeda, and Astellas. Other authors have no competing interests regarding this study. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                Author information
                https://orcid.org/0000-0003-4198-7414
                Article
                PONE-D-20-17391
                10.1371/journal.pone.0249005
                7997015
                33770132
                54f78be2-b9d6-45a3-b195-7389ee8a9ec2
                © 2021 Shinjoh et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 8 June 2020
                : 9 March 2021
                Page count
                Figures: 1, Tables: 6, Pages: 12
                Funding
                The authors received no specific funding for this work.
                Categories
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                Custom metadata
                Data cannot be shared publicly because the data set includes patients’ personal information. Data other than confidential data are available from the Keio University Ethics Committee ( https://www.ctr.med.keio.ac.jp/forms/form_a.html or FAX: 81-3-5379-1978) or Dr. Masayoshi Shinjoh ( m-shinjo@ 123456z2.keio.jp ) for researchers who meet the criteria to access the data.

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