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Oguz MM, Senel S. Effectiveness of cocoon strategy vaccination on prevention of influenza-like illness in young infants. Hum Vaccin Immunother 2024; 20:2350090. [PMID: 38738691 DOI: 10.1080/21645515.2024.2350090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 04/26/2024] [Indexed: 05/14/2024] Open
Abstract
During the initial half-year of their existence, infants cannot receive the influenza vaccine, yet they face the greatest susceptibility to severe influenza complications. In this study, we seek to determine whether influenza vaccination of maternal and household contacts is associated with a reduced risk of influenza-like illness (ILI) and severe acute respiratory infection (SARI) in infants. This work was prospectively conducted during the influenza season. A total of 206 infants were included in this study. The percentage of infants with only the mother vaccinated is 12.6% (n:26), and the percent of infants with all household contacts vaccinated is 16% (n:33). Among the infants with only the mother vaccinated, the effectiveness of influenza vaccine is estimated as 35.3% for ILI and 41.3% for SARI. Among infants with all household contacts vaccinated, the effectiveness is estimated as 48.9% for ILI and 76.9% for SARI. Based on the results of multivariate logistic regression analysis, all-household vaccination is a protective factor against SARI (OR: 0.07 95% CI [0.01-0.56]), household size (OR: 1.75, 95% CI [1.24-2.48]) and presence of secondhand smoke (OR: 2.2, 95% CI [1.12-4.45]) significant risk factors for SARI in infants. The mother alone being vaccinated is not a statistically significant protective factor against ILI (OR: 0.46, 95% CI [0.19-1.18]) or SARI (OR: 0.3, 95% CI [0.11-1.21]). Along with the obtained results and analysis, this study provides clear evidence that influenza vaccination of all household contacts of infants aged 0-6 months is significantly associated with protecting infants from both ILI and SARI.
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Affiliation(s)
- Melahat Melek Oguz
- Department of Pediatrics, Dr. Sami Ulus Maternity and Children's Health and Diseases Training and Research Hospital, University of Health Sciences, Ankara, Turkey
| | - Saliha Senel
- Department of Pediatrics, Yildirim Beyazit University, Ankara, Turkey
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Gu X, Watson C, Agrawal U, Whitaker H, Elson WH, Anand S, Borrow R, Buckingham A, Button E, Curtis L, Dunn D, Elliot AJ, Ferreira F, Goudie R, Hoang U, Hoschler K, Jamie G, Kar D, Kele B, Leston M, Linley E, Macartney J, Marsden GL, Okusi C, Parvizi O, Quinot C, Sebastianpillai P, Sexton V, Smith G, Suli T, Thomas NPB, Thompson C, Todkill D, Wimalaratna R, Inada-Kim M, Andrews N, Tzortziou-Brown V, Byford R, Zambon M, Lopez-Bernal J, de Lusignan S. Postpandemic Sentinel Surveillance of Respiratory Diseases in the Context of the World Health Organization Mosaic Framework: Protocol for a Development and Evaluation Study Involving the English Primary Care Network 2023-2024. JMIR Public Health Surveill 2024; 10:e52047. [PMID: 38569175 PMCID: PMC11024753 DOI: 10.2196/52047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 01/02/2024] [Accepted: 01/17/2024] [Indexed: 04/05/2024] Open
Abstract
BACKGROUND Prepandemic sentinel surveillance focused on improved management of winter pressures, with influenza-like illness (ILI) being the key clinical indicator. The World Health Organization (WHO) global standards for influenza surveillance include monitoring acute respiratory infection (ARI) and ILI. The WHO's mosaic framework recommends that the surveillance strategies of countries include the virological monitoring of respiratory viruses with pandemic potential such as influenza. The Oxford-Royal College of General Practitioner Research and Surveillance Centre (RSC) in collaboration with the UK Health Security Agency (UKHSA) has provided sentinel surveillance since 1967, including virology since 1993. OBJECTIVE We aim to describe the RSC's plans for sentinel surveillance in the 2023-2024 season and evaluate these plans against the WHO mosaic framework. METHODS Our approach, which includes patient and public involvement, contributes to surveillance objectives across all 3 domains of the mosaic framework. We will generate an ARI phenotype to enable reporting of this indicator in addition to ILI. These data will support UKHSA's sentinel surveillance, including vaccine effectiveness and burden of disease studies. The panel of virology tests analyzed in UKHSA's reference laboratory will remain unchanged, with additional plans for point-of-care testing, pneumococcus testing, and asymptomatic screening. Our sampling framework for serological surveillance will provide greater representativeness and more samples from younger people. We will create a biomedical resource that enables linkage between clinical data held in the RSC and virology data, including sequencing data, held by the UKHSA. We describe the governance framework for the RSC. RESULTS We are co-designing our communication about data sharing and sampling, contextualized by the mosaic framework, with national and general practice patient and public involvement groups. We present our ARI digital phenotype and the key data RSC network members are requested to include in computerized medical records. We will share data with the UKHSA to report vaccine effectiveness for COVID-19 and influenza, assess the disease burden of respiratory syncytial virus, and perform syndromic surveillance. Virological surveillance will include COVID-19, influenza, respiratory syncytial virus, and other common respiratory viruses. We plan to pilot point-of-care testing for group A streptococcus, urine tests for pneumococcus, and asymptomatic testing. We will integrate test requests and results with the laboratory-computerized medical record system. A biomedical resource will enable research linking clinical data to virology data. The legal basis for the RSC's pseudonymized data extract is The Health Service (Control of Patient Information) Regulations 2002, and all nonsurveillance uses require research ethics approval. CONCLUSIONS The RSC extended its surveillance activities to meet more but not all of the mosaic framework's objectives. We have introduced an ARI indicator. We seek to expand our surveillance scope and could do more around transmissibility and the benefits and risks of nonvaccine therapies.
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Affiliation(s)
- Xinchun Gu
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Conall Watson
- Immunisation and Vaccine-Preventable Diseases Division, UK Health Security Agency, London, United Kingdom
| | - Utkarsh Agrawal
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Heather Whitaker
- Statistics, Modelling and Economics Department, UK Health Security Agency, London, United Kingdom
| | - William H Elson
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Sneha Anand
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Ray Borrow
- Vaccine Evaluation Unit, UK Health Security Agency, Manchester, United Kingdom
| | | | - Elizabeth Button
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Lottie Curtis
- Royal College of General Practitioners, London, United Kingdom
| | - Dominic Dunn
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Alex J Elliot
- Real-time Syndromic Surveillance Team, UK Health Security Agency, Birmingham, United Kingdom
| | - Filipa Ferreira
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Rosalind Goudie
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Uy Hoang
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Katja Hoschler
- Respiratory Virus Unit, UK Health Security Agency, London, United Kingdom
| | - Gavin Jamie
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Debasish Kar
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Beatrix Kele
- Respiratory Virus Unit, UK Health Security Agency, London, United Kingdom
| | - Meredith Leston
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Ezra Linley
- Vaccine Evaluation Unit, UK Health Security Agency, Manchester, United Kingdom
| | - Jack Macartney
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Gemma L Marsden
- Royal College of General Practitioners, London, United Kingdom
| | - Cecilia Okusi
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Omid Parvizi
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
- Respiratory Virus Unit, UK Health Security Agency, London, United Kingdom
| | - Catherine Quinot
- Immunisation and Vaccine-Preventable Diseases Division, UK Health Security Agency, London, United Kingdom
| | | | - Vanashree Sexton
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Gillian Smith
- Real-time Syndromic Surveillance Team, UK Health Security Agency, Birmingham, United Kingdom
| | - Timea Suli
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | | | - Catherine Thompson
- Respiratory Virus Unit, UK Health Security Agency, London, United Kingdom
| | - Daniel Todkill
- Real-time Syndromic Surveillance Team, UK Health Security Agency, Birmingham, United Kingdom
| | - Rashmi Wimalaratna
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | | | - Nick Andrews
- Immunisation and Vaccine-Preventable Diseases Division, UK Health Security Agency, London, United Kingdom
| | | | - Rachel Byford
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
| | - Maria Zambon
- Virus Reference Department, UK Health Security Agency, London, United Kingdom
| | - Jamie Lopez-Bernal
- Immunisation and Vaccine-Preventable Diseases Division, UK Health Security Agency, London, United Kingdom
| | - Simon de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
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Dietz E, Pritchard E, Pouwels K, Ehsaan M, Blake J, Gaughan C, Haduli E, Boothe H, Vihta KD, Peto T, Stoesser N, Matthews P, Taylor N, Diamond I, Studley R, Rourke E, Birrell P, De Angelis D, Fowler T, Watson C, Eyre D, House T, Walker AS. SARS-CoV-2, influenza A/B and respiratory syncytial virus positivity and association with influenza-like illness and self-reported symptoms, over the 2022/23 winter season in the UK: a longitudinal surveillance cohort. BMC Med 2024; 22:143. [PMID: 38532381 DOI: 10.1186/s12916-024-03351-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 03/07/2024] [Indexed: 03/28/2024] Open
Abstract
BACKGROUND Syndromic surveillance often relies on patients presenting to healthcare. Community cohorts, although more challenging to recruit, could provide additional population-wide insights, particularly with SARS-CoV-2 co-circulating with other respiratory viruses. METHODS We estimated the positivity and incidence of SARS-CoV-2, influenza A/B, and RSV, and trends in self-reported symptoms including influenza-like illness (ILI), over the 2022/23 winter season in a broadly representative UK community cohort (COVID-19 Infection Survey), using negative-binomial generalised additive models. We estimated associations between test positivity and each of the symptoms and influenza vaccination, using adjusted logistic and multinomial models. RESULTS Swabs taken at 32,937/1,352,979 (2.4%) assessments tested positive for SARS-CoV-2, 181/14,939 (1.2%) for RSV and 130/14,939 (0.9%) for influenza A/B, varying by age over time. Positivity and incidence peaks were earliest for RSV, then influenza A/B, then SARS-CoV-2, and were highest for RSV in the youngest and for SARS-CoV-2 in the oldest age groups. Many test positives did not report key symptoms: middle-aged participants were generally more symptomatic than older or younger participants, but still, only ~ 25% reported ILI-WHO and ~ 60% ILI-ECDC. Most symptomatic participants did not test positive for any of the three viruses. Influenza A/B-positivity was lower in participants reporting influenza vaccination in the current and previous seasons (odds ratio = 0.55 (95% CI 0.32, 0.95)) versus neither season. CONCLUSIONS Symptom profiles varied little by aetiology, making distinguishing SARS-CoV-2, influenza and RSV using symptoms challenging. Most symptoms were not explained by these viruses, indicating the importance of other pathogens in syndromic surveillance. Influenza vaccination was associated with lower rates of community influenza test positivity.
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Affiliation(s)
- Elisabeth Dietz
- Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK.
| | - Emma Pritchard
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK
| | - Koen Pouwels
- The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK
- Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - Joshua Blake
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | | | - Eric Haduli
- Berkshire and Surrey Pathology Services, Camberley, UK
| | - Hugh Boothe
- Berkshire and Surrey Pathology Services, Camberley, UK
| | | | - Tim Peto
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK
- Department of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Nicole Stoesser
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK
- Department of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK
| | - Philippa Matthews
- The Francis Crick Institute, 1 Midland Road, London, UK
- Division of Infection and Immunity, University College London, London, UK
| | | | | | | | | | - Paul Birrell
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
- UK Health Security Agency, London, UK
| | | | - Tom Fowler
- UK Health Security Agency, London, UK
- William Harvey Research Institute, Queen Mary University of London, London, UK
| | | | - David Eyre
- The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK
- Big Data Institute, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - Ann Sarah Walker
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK
- The National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
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Barbieri E, Porcu G, Donà D, Cavagnis S, Cantarutti L, Scamarcia A, McGovern I, Haag M, Giaquinto C, Cantarutti A. Epidemiology and Burden of Influenza in Children 0-14 Years Over Ten Consecutive Seasons in Italy. Pediatr Infect Dis J 2023; 42:e440-e446. [PMID: 37725811 PMCID: PMC10629601 DOI: 10.1097/inf.0000000000004090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/21/2023]
Abstract
BACKGROUND In Europe, influenza vaccination coverage in the pediatric population is low. This study describes the influenza incidence and associated healthcare utilization in the pediatric population in Italy. METHODS Deidentified data from electronic medical records for children 0-14 years old seen by >150 family pediatricians in the Pedianet network in Italy were evaluated for 10 influenza seasons spanning 2010-2020. Incidence of influenza (cases per 1000 person-months), related sequelae and associated healthcare resource use were determined using diagnostic, prescription and medical examination data. RESULTS Over 10 seasons, an average of 8892 influenza cases (range, 4700-12,419; total 88,921) were diagnosed in a cohort of 1,432,384 children 0-14 years of age. Influenza vaccination coverage was 3.6% among children with an influenza diagnosis and 6.8% among children without. Influenza-related healthcare resource utilization included 1.58 family pediatrician visits per influenza episode and 220 ED and 111 hospital admissions, with the highest resource usage among children 1-4 years and lowest among children <6 months old. The most common influenza complications were acute otitis media (2.9% of influenza cases) and pneumonia (0.5%). Antibiotics were prescribed in 38.7% of influenza cases; no antiviral agents were prescribed. One intensive care unit admission and 2 cases requiring ventilatory support were documented. No influenza-related deaths were reported. CONCLUSION Pediatric influenza vaccination was low despite the burden and healthcare use related to seasonal influenza in the pediatric population during a 10-year period in Italy.
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Affiliation(s)
- Elisa Barbieri
- From the Division of Pediatric Infectious Diseases, Department for Women’s and Children’s Health, University of Padua, Padua, Italy
| | - Gloria Porcu
- Unit of Biostatistics, Epidemiology and Public Health
- National Centre for Healthcare Research and Pharmacoepidemiology, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy
| | - Daniele Donà
- From the Division of Pediatric Infectious Diseases, Department for Women’s and Children’s Health, University of Padua, Padua, Italy
| | - Sara Cavagnis
- Società Servizi Telematici (SoSeTe), Pedianet Project, Padova, Italy
| | - Luigi Cantarutti
- Società Servizi Telematici (SoSeTe), Pedianet Project, Padova, Italy
| | - Antonio Scamarcia
- Società Servizi Telematici (SoSeTe), Pedianet Project, Padova, Italy
| | | | - Mendel Haag
- Seqirus Netherlands BV, Amsterdam, The Netherlands
| | - Carlo Giaquinto
- From the Division of Pediatric Infectious Diseases, Department for Women’s and Children’s Health, University of Padua, Padua, Italy
- Società Servizi Telematici (SoSeTe), Pedianet Project, Padova, Italy
| | - Anna Cantarutti
- Unit of Biostatistics, Epidemiology and Public Health
- National Centre for Healthcare Research and Pharmacoepidemiology, Department of Statistics and Quantitative Methods, University of Milano-Bicocca, Milan, Italy
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Potdar V, Vijay N, Mukhopadhyay L, Aggarwal N, Bhardwaj SD, Choudhary ML, Gupta N, Kaur H, Narayan J, Kumar P, Singh H, Abdulkader RS, Murhekar M, Mishra M, Thangavel S, Nagamani K, Dhodapkar R, Fomda BA, Varshney U, Majumdar A, Dutta S, Vijayachari P, Turuk J, Majumdar T, Sahoo GC, Pandey K, Bhargava A, Negi SS, Khatri PK, Kalawat U, Biswas D, Khandelwal N, Borkakoty B, Manjushree S, Singh MP, Iravane J, Kaveri K, Shantala GB, Brijwal M, Choudhary A, Dar L, Malhotra B, Jain A. Pan-India influenza-like illness (ILI) and Severe acute respiratory infection (SARI) surveillance: epidemiological, clinical and genomic analysis. Front Public Health 2023; 11:1218292. [PMID: 37927860 PMCID: PMC10624221 DOI: 10.3389/fpubh.2023.1218292] [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: 05/06/2023] [Accepted: 09/18/2023] [Indexed: 11/07/2023] Open
Abstract
Background Over time, COVID-19 testing has significantly declined across the world. However, it is critical to monitor the virus through surveillance. In late 2020, WHO released interim guidance advising the use of the existing Global Influenza Surveillance and Response System (GISRS) for the integrated surveillance of influenza and SARS-CoV-2. Methods In July 2021, we initiated a pan-India integrated surveillance for influenza and SARS-CoV-2 through the geographically representative network of Virus Research and Diagnostic Laboratories (VRDLs) across 26 hospital and laboratory sites and 70 community sites. A total of 34,260 cases of influenza-like illness (ILI) and Severe acute respiratory infection (SARI) were enrolled from 4 July 2021 to 31 October 2022. Findings Influenza A(H3) and B/Victoria dominated during 2021 monsoon season while A(H1N1)pdm09 dominated during 2022 monsoon season. The SARS-CoV-2 "variants of concern" (VoC) Delta and Omicron predominated in 2021 and 2022, respectively. Increased proportion of SARI was seen in extremes of age: 90% cases in < 1 year; 68% in 1 to 5 years and 61% in ≥ 8 years age group. Approximately 40.7% of enrolled cases only partially fulfilled WHO ILI and SARI case definitions. Influenza- and SARS-CoV-2-infected comorbid patients had higher risks of hospitalization, ICU admission, and oxygen requirement. Interpretation The results depicted the varying strains and transmission dynamics of influenza and SARS-CoV-2 viruses over time, thus emphasizing the need to continue and expand surveillance across countries for improved decision making. The study also describes important information related to clinical outcomes of ILI and SARI patients and highlights the need to review existing WHO ILI and SARI case definitions.
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Affiliation(s)
| | - Neetu Vijay
- Division of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, India
| | - Labanya Mukhopadhyay
- Division of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, India
| | - Neeraj Aggarwal
- Division of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, India
| | | | | | - Nivedita Gupta
- Division of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, India
| | - Harmanmeet Kaur
- Division of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, India
| | - Jitendra Narayan
- Division of Epidemiology and Communicable Diseases, Indian Council of Medical Research, New Delhi, India
| | - Prabhat Kumar
- Biomedical Informatics (BMI) Division, Indian Council of Medical Research, New Delhi, India
| | - Harpreet Singh
- Biomedical Informatics (BMI) Division, Indian Council of Medical Research, New Delhi, India
| | | | | | - Meena Mishra
- VRDL, All India Institute of Medical Sciences, Nagpur, India
| | | | - K. Nagamani
- VRDL, Gandhi Medical College, Secunderabad, India
| | - Rahul Dhodapkar
- VRDL, Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India
| | | | | | - Agniva Majumdar
- ICMR-National Institute of Cholera and Enteric Diseases, Kolkata, India
| | - Shanta Dutta
- ICMR-National Institute of Cholera and Enteric Diseases, Kolkata, India
| | - P. Vijayachari
- ICMR-Regional Medical Research Centre, Port Blair, India
| | | | | | | | - Krishna Pandey
- ICMR-Rajendra Memorial Research Institute of Medical Sciences, Patna, India
| | | | | | | | - Usha Kalawat
- VRDL, Sri Venkateswara Institute of Medical Sciences, Tirupati, India
| | - Debasis Biswas
- VRDL, All India Institute of Medical Sciences, Bhopal, India
| | | | | | | | - Mini P. Singh
- VRDL, Post Graduate Institute of Medical Education and Research, Chandigarh, India
| | | | - K. Kaveri
- VRDL, King Institute of Preventive Medicine and Research, Chennai, India
| | - G. B. Shantala
- VRDL, Bangalore Medical College and Research Institute, Bangalore, India
| | - Megha Brijwal
- VRDL, All India Institute of Medical Sciences, New Delhi, India
| | | | - Lalit Dar
- VRDL, All India Institute of Medical Sciences, New Delhi, India
| | | | - Amita Jain
- VRDL, King George’s Medical University, Lucknow, India
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Influenza Adverse Events in Patients with Rheumatoid Arthritis, Ulcerative Colitis, or Psoriatic Arthritis in the Tofacitinib Clinical Development Programs. Rheumatol Ther 2023; 10:357-373. [PMID: 36526796 PMCID: PMC9758022 DOI: 10.1007/s40744-022-00507-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 11/03/2022] [Indexed: 12/23/2022] Open
Abstract
INTRODUCTION This post hoc analysis evaluated influenza adverse events (AEs) across rheumatoid arthritis (RA), ulcerative colitis (UC), and psoriatic arthritis (PsA) tofacitinib clinical programs. METHODS Available data from phase 1, randomized phase 2/3/3b/4 clinical trials (completed by 2018), and long-term extension (LTE) studies (up to May 2019) in patients with RA, UC, and PsA were included [randomized or Overall (phase 1-3b/4 and LTE studies) tofacitinib cohorts]. Incidence rates (IRs; events per 100 patient-years) of combined influenza AEs (seasons 2004/2005 to 2018/2019) were analyzed, including by tofacitinib dose [5 or 10 mg twice daily (BID)] and age (< 65 versus ≥ 65 years). Logistic regression models evaluated risk factors for influenza AEs in the RA Overall tofacitinib cohort. RESULTS In randomized cohorts, combined influenza AE IRs were generally similar across tofacitinib, adalimumab, methotrexate, and placebo groups, across indications. Among Overall tofacitinib cohorts, combined influenza AE IRs with tofacitinib 5/10 mg BID, respectively, were higher in the UC (3.66/5.09) versus RA (2.38/2.19) and PsA (1.74/1.29) cohorts. IRs were generally similar across tofacitinib dose and age groups. Most influenza AEs were nonserious and did not require changes to tofacitinib treatment. Significant risk factors for influenza AEs in patients with RA were geographic region, baseline oral corticosteroid and methotrexate use, and tofacitinib dose. CONCLUSIONS In the RA, UC, and PsA clinical programs, combined influenza AE IRs were highest in UC, while in each indication they were generally similar across tofacitinib, placebo, and comparator groups. Influenza AEs were predominantly nonserious and not associated with changes to tofacitinib treatment. TRIAL REGISTRATION NUMBERS NCT01262118, NCT01484561, NCT00147498, NCT00413660, NCT00550446, NCT00603512, NCT00687193, NCT01164579, NCT00976599, NCT01059864, NCT01359150, NCT02147587, NCT00960440, NCT00847613, NCT00814307, NCT00856544, NCT00853385, NCT01039688, NCT02281552, NCT02187055, NCT02831855, NCT00413699, NCT00661661, NCT00787202, NCT01465763, NCT01458951, NCT01458574, NCT01470612, NCT01877668, NCT01882439, NCT01976364.
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Muacevic A, Adler JR, Jurebi RM, Almutiri MK, Alghamdi B, Alghamdi AS, Alhajry HH, Al-Helali SM, Alzaidi AH, Alzahrani YS, Al-Mutairy MH, Jurebi A, Alshareef A, Almarzooq A, Alsaedi MQ. Compliance of Primary Healthcare Workers in Saudi Arabia With the National Surveillance System of Tropical and Non-tropical Dermatological Diseases. Cureus 2023; 15:e34306. [PMID: 36865961 PMCID: PMC9973668 DOI: 10.7759/cureus.34306] [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] [Accepted: 01/19/2023] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Control and prevention of infectious diseases has been a primary health mandate. The reporting system is a vital step in preventing and controlling of these diseases. Most important, healthcare workers who have a responsibility to report must be aware of this responsibility. The present study aimed to improve the compliance of primary healthcare workers against reportable tropical and non-tropical dermatological diseases. OBJECTIVE OF THE STUDY The objective was to assess the knowledge, skills, and practice of primary healthcare workers in Saudi Arabia regarding the surveillance system of reportable tropical and non-tropical dermatological diseases using an assessment tool featuring closed-ended questions. As a secondary objective, this study assessed the satisfaction of primary healthcare workers with the surveillance system. SUBJECTS AND METHODS Through a cross-sectional design, the study used an electronic self-administered questionnaire targeting the primary healthcare workers who met the inclusion criteria through a non-probability sampling technique. RESULTS By the end of the study period, data had been collected from 377 primary healthcare workers. Slightly more than half of them worked for the ministry of health facilities. In the last year, the vast majority (88%) of participants did not report any infectious diseases. Poor or low knowledge was reported by almost half of the participants concerning which dermatological diseases should be notified immediately on clinical suspicion or routinely on a weekly basis. Clinically and in response to the skills assessment, 57% of the participants had lower skills scores in detecting and identifying the skin ulcer of leishmania. Half of the participants were less satisfied with the feedback after their notification and considered the notification forms complicated and time-consuming, especially with the usual high workload in primary healthcare centers. Furthermore, the observed significant differences (p < 0.001) in knowledge and skill scores were demonstrated with female healthcare workers, older participants, employees from the Ministry of National Guard Health Affairs, and workers with more than ten years of experience. CONCLUSION The present study has shown the limitations of public health surveillance due to underreporting and lack of timeliness. The dissatisfaction of study participants with feedback after the notification step is another finding that demonstrates the need for collaboration among public health authorities and healthcare workers. Fortunately, health departments can implement measures to improve practitioners' awareness through continuous medical education and providing frequent feedback to overcome these hurdles.
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Li J, Wu C, Tseng Y, Han S, Pekosz A, Rothman R, Chen K. Applying symptom dynamics to accurately predict influenza virus infection: An international multicenter influenza-like illness surveillance study. Influenza Other Respir Viruses 2022; 17:e13081. [PMID: 36480419 PMCID: PMC9835452 DOI: 10.1111/irv.13081] [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: 11/04/2022] [Revised: 11/21/2022] [Accepted: 11/22/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Public health organizations have recommended various definitions of influenza-like illnesses under the assumption that the symptoms do not change during influenza virus infection. To explore the relationship between symptoms and influenza over time, we analyzed a dataset from an international multicenter prospective emergency department (ED)-based influenza-like illness cohort study. METHODS We recruited patients in the US and Taiwan between 2015 and 2020 with: (1) flu-like symptoms (fever and cough, headache, or sore throat), (2) absence of any of the respiratory infection symptoms, or (3) positive laboratory test results for influenza from the current ED visit. We evaluated the association between the symptoms and influenza virus infection on different days of illness. The association was evaluated among different subgroups, including different study countries, influenza subtypes, and only patients with influenza. RESULTS Among the 2471 recruited patients, 45.7% tested positive for influenza virus. Cough was the most predictive symptom throughout the week (odds ratios [OR]: 7.08-11.15). In general, all symptoms were more predictive during the first 2 days (OR: 1.55-10.28). Upper respiratory symptoms, such as sore throat and productive cough, and general symptoms, such as body ache and fatigue, were more predictive in the first half of the week (OR: 1.51-3.25). Lower respiratory symptoms, such as shortness of breath and wheezing, were more predictive in the second half of the week (OR: 1.52-2.52). Similar trends were observed for most symptoms in the different subgroups. CONCLUSIONS The time course is an important factor to be considered when evaluating the symptoms of influenza virus infection.
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Affiliation(s)
- Jin‐Hua Li
- Clinical Informatics and Medical Statistics Research CenterChang Gung UniversityTaoyuanTaiwan,Department of Medical EducationChang Gung Memorial HospitalChiayiTaiwan
| | - Chin‐Chieh Wu
- Clinical Informatics and Medical Statistics Research CenterChang Gung UniversityTaoyuanTaiwan
| | - Yi‐Ju Tseng
- Department of Computer ScienceNational Yang Ming Chiao Tung UniversityHsinchuTaiwan
| | - Shih‐Tsung Han
- Department of Emergency MedicineChang Gung Memorial HospitalLinkouTaiwan
| | - Andrew Pekosz
- W. Harry Feinstone Department of Molecular Microbiology and ImmunologyThe Johns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Richard Rothman
- Department of Emergency MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Kuan‐Fu Chen
- Clinical Informatics and Medical Statistics Research CenterChang Gung UniversityTaoyuanTaiwan,Department of Emergency MedicineChang Gung Memorial HospitalKeelungTaiwan
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Tunnicliffe L, Warren‐Gash C. Investigating the effects of population density of residence and rural/urban classification on rate of influenza-like illness symptoms in England and Wales. Influenza Other Respir Viruses 2022; 16:1183-1190. [PMID: 35922884 PMCID: PMC9530544 DOI: 10.1111/irv.13032] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 07/15/2022] [Accepted: 07/21/2022] [Indexed: 11/05/2022] Open
Abstract
BACKGROUND Better understanding of risk factors for influenza could help improve seasonal and pandemic planning. There is a dearth of literature on area-level risk factors such as population density and rural/urban living. METHODS We used data from Flusurvey, an online community-based cohort that records influenza events. The study outcome was symptoms of influenza-like illness (ILI). Multivariable Poisson regression analysis was used to explore associations of both population density and rural/urban status with rate of ILI symptoms and whether these effects differed by vaccination status. RESULTS Of the 6177 study participants, the median age was 45 (IQR 32-57), 65.73% were female, and 66% reported at least one episode of ILI symptoms between 2011 and 2016. We found no evidence to suggest that the rate of ILI symptoms was higher in the medium [RR 1.02 (95% CI 0.95-1.09)] or high [RR 1.02 (95% CI 0.96-1.09)] population density group versus the low population density group. This was the same for the effect of urban living [RR 0.96 (95% CI 0.90-1.03)] versus rural living on symptom rate. There was weak evidence to suggest that the ILI symptom rate was lower in urban areas compared with rural areas among unvaccinated individuals only [RR 0.90 (95% CI 0.83-0.99)], whereas no difference was seen among vaccinated individuals [1.04 (95% CI 0.94-1.16)]. CONCLUSIONS Although neither population density nor rural/urban status was associated with ILI symptom rate in this community cohort, future research that incorporates activity and contact patterns will help to elucidate this relationship further.
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Affiliation(s)
- Louis Tunnicliffe
- Department of Non‐communicable Disease Epidemiology, Faculty of Epidemiology and Population HealthLondon School of Hygiene and Tropical MedicineLondonUK
| | - Charlotte Warren‐Gash
- Department of Non‐communicable Disease Epidemiology, Faculty of Epidemiology and Population HealthLondon School of Hygiene and Tropical MedicineLondonUK
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Murillo-Zamora E, Hernández-Suárez CM. [Performance of the case definition of suspected influenza before and during the COVID-19 pandemic]. Rev Clin Esp 2021; 221:582-586. [PMID: 33024341 PMCID: PMC7528731 DOI: 10.1016/j.rce.2020.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 09/13/2020] [Indexed: 12/03/2022]
Abstract
OBJECTIVE This study aimed to evaluate the performance, before and during the COVID-19 pandemic, of the case definition of suspected influenza used in community surveillance in Mexico. METHODS A cross-sectional analysis of a cohort study was perfomed and cases that met the suspected case criteria (n = 20,511) and that had laboratory-conclusive evidence (quantitative real-time polymerase chain reaction) to confirm or discard influenza virus infection, were analysed. RESULTS A high sensitivity and modest specificity were documented, which later decreased during the COVID-19 outbreak, as well as its diagnostic accuracy. However, no significant differences were observed in the area under the receiver operating characteristics curve among the analysed periods. CONCLUSION The evaluated case definition remains to be a cost-effective alternative for identifying patients who may benefit from influenza-specific antiviral drugs, even during the global COVID-19 outbreak.
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Affiliation(s)
- E Murillo-Zamora
- Departamento de Epidemiología, Unidad de Medicina Familiar No. 19, Instituto Mexicano del Seguro Social, Colima, México
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Murillo-Zamora E, Hernández-Suárez CM. Performance of the case definition of suspected influenza before and during the COVID-19 pandemic. Rev Clin Esp 2021; 221:582-586. [PMID: 34839891 PMCID: PMC7997690 DOI: 10.1016/j.rceng.2020.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 09/13/2020] [Indexed: 11/03/2022]
Abstract
OBJECTIVE This study aimed to evaluate the performance, before and during the COVID-19 pandemic, of the case definition of suspected influenza used in community surveillance in Mexico. METHODS A cross-sectional analysis of a cohort study was performed and cases that met the suspected case criteria (n = 20,511) and that had laboratory-conclusive evidence (quantitative real-time polymerase chain reaction) to confirm or discard influenza virus infection were analysed. RESULTS A high sensitivity and modest specificity were documented, which later decreased during the COVID-19 outbreak, as well as its diagnostic accuracy. However, no significant differences were observed in the area under the receiver operating characteristics curve among the analysed periods. CONCLUSIONS The evaluated case definition remains to be a cost-effective alternative for identifying patients who may benefit from influenza-specific antiviral drugs, even during the global COVID-19 outbreak.
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Affiliation(s)
- E Murillo-Zamora
- Departamento de Epidemiología, Unidad de Medicina Familiar No. 19, Instituto Mexicano del Seguro Social, Colima, Mexico
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Callahan A, Steinberg E, Fries JA, Gombar S, Patel B, Corbin CK, Shah NH. Estimating the efficacy of symptom-based screening for COVID-19. NPJ Digit Med 2020; 3:95. [PMID: 32695885 PMCID: PMC7359358 DOI: 10.1038/s41746-020-0300-0] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 06/16/2020] [Indexed: 11/28/2022] Open
Abstract
There is substantial interest in using presenting symptoms to prioritize testing for COVID-19 and establish symptom-based surveillance. However, little is currently known about the specificity of COVID-19 symptoms. To assess the feasibility of symptom-based screening for COVID-19, we used data from tests for common respiratory viruses and SARS-CoV-2 in our health system to measure the ability to correctly classify virus test results based on presenting symptoms. Based on these results, symptom-based screening may not be an effective strategy to identify individuals who should be tested for SARS-CoV-2 infection or to obtain a leading indicator of new COVID-19 cases.
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Affiliation(s)
- Alison Callahan
- Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA USA
| | - Ethan Steinberg
- Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA USA
| | - Jason A. Fries
- Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA USA
| | - Saurabh Gombar
- Department of Pathology, School of Medicine, Stanford University, Stanford, CA USA
| | - Birju Patel
- Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA USA
| | - Conor K. Corbin
- Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA USA
| | - Nigam H. Shah
- Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, CA USA
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