Estimating the burden of adult hospitalized RSV infection using local and state data - methodology. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Balasubramani, G. K.; Nowalk, Mary Patricia; Eng, Heather; Zimmerman, Richard K.
• Is Part Of: Human vaccines & immunotherapeutics. Volume 18:Issue 1(2022)
• Publication Date: 2022-12-31
• Subjects: RSV burden -- acute respiratory illness -- statistical analysis plan -- retrospective cohort study -- adults; Vaccines -- Periodicals; 615.372
• DOI: 10.1080/21645515.2021.1958610
• Languages: English
• ISSNs: 2164-5515

Abstract

ABSTRACT: Respiratory syncytial virus (RSV) is becoming increasingly recognized as a serious threat to vulnerable population subgroups. This study describes the statistical analysis plan for a retrospective cohort study of adults hospitalized for acute respiratory infection (ARI) to estimate the population burden of RSV especially for groups such as the elderly, pregnant women and solid organ transplant patients. Disease burden estimates are essential for setting vaccine policy, e.g., should RSV vaccine become available, burden estimates may inform recommendations to prioritize certain high-risk groups. The study population is residents of Allegheny County, Pennsylvania ≥18 years of age who were hospitalized in Pennsylvania during the period September 1, 2015–August 31, 2018. Data sources will include U.S. Census, Pennsylvania Health Care Cost Containment Council (PHC4) and the electronic medical record for the health system to which the hospitals belong. The algorithm involves: 1) ARI-associated hospitalizations in PHC4 data; 2) adjustment for ARI hospitalizations among county residents but admitted to hospitals outside the county; and 3) RSV detections from respiratory viral panels. Key sensitivity analyses will adjust for undertesting for viruses in the fall and spring quarters. The results will be population-based estimates, stratified by age and risk groups. Adjusting hospitalization data using a multiplier method is a simple means to estimate the impact of RSV in a given area. This algorithm can be applied to other health systems and localities to estimate RSV and other respiratory pathogen burden in adults, to estimate burden following introduction of RSV vaccine and to make cost-effectiveness estimates.