期刊
INFLUENZA AND OTHER RESPIRATORY VIRUSES
卷 12, 期 1, 页码 113-121出版社
WILEY
DOI: 10.1111/irv.12497
关键词
completeness of case ascertainment; disease burden; influenza-attributed hospitalization rates; respiratory syncytial virus; respiratory viral identification; severe acute respiratory infections
资金
- World Health Organization (WHO)
BackgroundA regression-based study design has commonly been used to estimate the influenza burden; however, these estimates are not timely and many countries lack sufficient virological data. Alternative approaches that would permit a timelier assessment of the burden, including a sentinel surveillance approach recommended by the World Health Organization (WHO), have been proposed. We aimed to estimate the hospitalization burden attributable to influenza, respiratory syncytial virus (RSV), and other respiratory viruses (ORV) and to assess both the completeness of viral identification among respiratory inpatients in Canada and the implications of adopting other approaches. MethodsRespiratory inpatient records were extracted from the Canadian Discharge Abstract Database from 2003 to 2014. A regression model was used to estimate excess respiratory hospitalizations attributable to influenza, RSV, and ORV by age group and diagnostic category and compare these estimates with the number with a respiratory viral identification. ResultsAn estimated 33 (95% CI: 29, 38), 27 (95% CI: 22, 33), and 27 (95% CI: 18, 36) hospitalizations per 100000 population per year were attributed to influenza, RSV, and ORV, respectively. An influenza virus was identified in an estimated 78% (95% CI: 75, 81) and 17% (95% CI: 15, 21) of respiratory hospitalizations attributed to influenza for children and adults, respectively, and 75% of influenza-attributed hospitalizations had an ARI diagnosis. ConclusionsHospitalization rates with respiratory viral identification still underestimate the burden. Approaches based on acute respiratory case definitions will likely underestimate the burden as well, although each proposed method should be compared with regression-based estimates of influenza-attributed burden as a way of assessing their validity.
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