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Using population-wide administrative and laboratory data to estimate type- and subtype-specific influenza vaccine effectiveness: a surveillance protocol

INTRODUCTION: The appropriateness of using routinely collected laboratory data combined with administrative data for estimating influenza vaccine effectiveness (VE) is still being explored. This paper outlines a protocol to estimate influenza VE using linked laboratory and administrative data which...

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Detalles Bibliográficos
Autores principales: Scott, Allison Nicole, Buchan, Sarah A, Kwong, Jeffrey C, Drews, Steven J, Simmonds, Kimberley A, Svenson, Lawrence W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6773297/
https://www.ncbi.nlm.nih.gov/pubmed/31575570
http://dx.doi.org/10.1136/bmjopen-2019-029708
Descripción
Sumario:INTRODUCTION: The appropriateness of using routinely collected laboratory data combined with administrative data for estimating influenza vaccine effectiveness (VE) is still being explored. This paper outlines a protocol to estimate influenza VE using linked laboratory and administrative data which could act as a companion to estimates derived from other methods. METHODS AND ANALYSIS: We will use the test-negative design to estimate VE for each influenza type/subtype and season. Province-wide individual-level records of positive and negative influenza tests at the Provincial Laboratory for Public Health in Alberta will be linked, by unique personal health numbers, to administrative databases and vaccination records held at the Ministry of Health in Alberta to determine covariates and influenza vaccination status, respectively. Covariates of interests include age, sex, immunocompromising chronic conditions and healthcare setting. Cases will be defined based on an individual’s first positive influenza test during the season, and potential controls will be defined based on an individual’s first negative influenza test during the season. One control for each case will be randomly selected based on the week the specimen was collected. We will estimate VE using multivariable logistic regression. ETHICS AND DISSEMINATION: Ethics approval was obtained from the University of Alberta’s Health Research Ethics Board—Health Panel under study ID Pro00075997. Results will be disseminated by public health officials in Alberta.