Early estimation of pandemic influenza antiviral and vaccine effectiveness (EAVE) : use of a unique community and laboratory national data-linked cohort study
Simpson, Colin R and Lone, Nazir and McMenamin, Jim and Gunson, Rory and Robertson, Chris and Ritchie, Lewis D and Sheikh, Aziz (2015) Early estimation of pandemic influenza antiviral and vaccine effectiveness (EAVE) : use of a unique community and laboratory national data-linked cohort study. Health Technology Assessment, 19 (79). pp. 1-32. ISSN 1366-5278 (https://doi.org/10.3310/hta19790)
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Abstract
After the introduction of any new pandemic influenza, population-level surveillance and rapid assessment of the effectiveness of a new vaccination will be required to ensure that it is targeted to those at increased risk of serious illness or death from influenza. We aimed to build a pandemic influenza reporting platform that will determine, once a new pandemic is under way: the uptake and effectiveness of any new pandemic vaccine or any protective effect conferred by antiviral drugs once available; the clinical attack rate of pandemic influenza; and the existence of protection provided by previous exposure to, and vaccination from, A/H1N1 pandemic or seasonal influenza/identification of susceptible groups. An observational cohort and test-negative study design will be used (post pandemic). A national linkage of patient-level general practice data from 41 Practice Team Information general practices, hospitalisation and death certification, virological swab and serology-linked data. We will study a nationally representative sample of the Scottish population comprising 300,000 patients. Confirmation of influenza using reverse transcription polymerase chain reaction and, in a subset of the population, serology. Future available pandemic influenza vaccination and antivirals will be evaluated. To build a reporting platform tailored towards the evaluation of pandemic influenza vaccination. This system will rapidly measure vaccine effectiveness (VE), adjusting for confounders, estimated by determining laboratory-confirmed influenza; influenza-related morbidity and mortality, including general practice influenza-like illnesses (ILIs); and hospitalisation and death from influenza and pneumonia. Once a validated haemagglutination inhibition assay has been developed (and prior to the introduction of any vaccination), cross-reactivity with previous exposure to A/H1N1 or A/H1N1 vaccination, other pandemic influenza or other seasonal influenza vaccination or exposure will be measured. A new sentinel system, capable of rapidly determining the estimated incidence of pandemic influenza, and pandemic influenza vaccine and antiviral uptake and effectiveness in preventing influenza and influenza-related clinical outcomes, has been created. We have all of the required regulatory approvals to allow rapid activation of the sentinel systems in the event of a pandemic. Of the 41 practices expressing an interest in participating, 40 have completed all of the necessary paperwork to take part in the reporting platform. The data extraction tool has been installed in these practices. Data extraction and deterministic linkage systems have been tested. Four biochemistry laboratories have been recruited, and systems for serology collection and linkage of samples to general practice data have been put in place. Future work: The reporting platform has been set up and is ready to be activated in the event of any pandemic of influenza. Building on this infrastructure, there is now the opportunity to extend the network of general practices to allow important subgroup analyses of VE (e.g. for patients with comorbidities, at risk of serious ILI) and to link to other data sources, in particular to test for maternal outcomes in pregnant patients.
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Item type: Article ID code: 56437 Dates: DateEvent1 October 2015Published20 July 2015AcceptedSubjects: Medicine > Public aspects of medicine > Public health. Hygiene. Preventive Medicine
Science > Mathematics > Probabilities. Mathematical statisticsDepartment: Faculty of Science > Mathematics and Statistics Depositing user: Pure Administrator Date deposited: 19 May 2016 11:16 Last modified: 17 Dec 2024 01:14 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/56437