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Background: Accurate population estimates of disease incidence and burden are needed to set appropriate public health policy. The capture-recapture (C-R) method combines data from multiple sources to better estimate prevalence than is possible using single sources. This study used the C-R method to estimate influenza cases using research and administrative databases to calculate county-wide influenza hospitalization burden. Methods: Data were derived from a database of clinical virology test results and research data from an influenza vaccine effectiveness study from seasons 2015-2016 to 2018-2019. Missed influenza cases were estimated using C-R method. These estimates were used to calculate disease burden using the multiplier method to correct for underreporting due to curtailing data collection before the end of influenza circulation. Results: Over all seasons, 422 influenza cases were reported in the administrative database and 382 influenza cases in the research database. Seventy-five cases (18%) reported in the administrative database were not captured in the research database, and 35 (9%) cases in the research database were not captured in the administrative database. Completeness of the influenza hospitalization was estimated to be 76%. Influenza hospitalizations were higher among unvaccinated (32%) than vaccinated (22%) in the current season and among unvaccinated (28%) than vaccinated (23%) in the previous year. The incidence rates for influenza hospitalizations varied by age and season and averaged 421 cases/100,000 population annually. Conclusion: The capture-recapture method offers a more accurate method for estimating influenza hospitalization than relying on a single data source. Using the multiplier method with adjustments improves the detection of influenza disease burden through a matched database. The incidence rates are consistent with national estimates.

Background Respiratory tract infections are a major cause of outpatient visits, yet only a portion is tested to determine the etiologic organism. Multiplex reverse transcriptase polymerase chain reaction (MRT-PCR) assays for detection of multiple viruses are being used increasingly in clinical settings. Methods During January–April 2012, outpatients with acute respiratory illness (≤7 days) were tested for influenza using singleplex RT-PCR (SRT-PCR). A subset was assayed for 18 viruses using MRT-PCR to compare detection of influenza and examine the distribution of viruses and characteristics of patients using multinomial logistic regression. Results Among 662 participants (6 months–82 years), detection of influenza was similar between the MRT-PCR and SRT-PCR (κ = 0·83). No virus was identified in 267 (40.3%) samples. Commonly detected viruses were human rhinovirus (HRV, 15·4%), coronavirus (CoV, 10·4%), respiratory syncytial virus (RSV, 8·4%), human metapneumovirus (hMPV, 8·3%), and influenza (6%). Co-detections were infrequent (6·9%) and most commonly occurred among those