Burden of influenza, respiratory syncytial virus, and other respiratory viruses and the completeness of respiratory viral identification among respiratory inpatients, Canada, 2003‐2014

Abstract

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 100 000 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.

Burden of medically attended influenza in Norway 2008‐2017

“…We found on average 48 hospitalizations per 100 000 population during an influenza season, which is within the range found in other countries, but among the higher country‐specific rates . The increase in hospitalizations in the elderly could be a result of improved diagnostics in this group.…”

“…We found on average 48 hospitalizations per 100 000 population during an influenza season, which is within the range found in other countries, but among the higher country-specific rates. 4,12,[27][28][29] The increase in hospitalizations in the elderly could be a result of improved diagnostics in this group. From 2008 to 2017, the number of tests performed for influenza increased from approximately ten thousand a year to around 140 000.…”

Characteristics of hospitalizations with an influenza diagnosis, France, 2012‐2013 to 2016‐2017 influenza seasons

“…Hospital discharge databases are a valuable source of information to estimate the burden of hospitalized seasonal influenza cases. [3][4][5][6][7][8][9] In France, a recent evaluation of the completeness of the ICU surveillance system for influenza cases, using capture-recapture methods, estimated the exhaustivity of the French national hospital discharge database (PMSI) to 73%. 10 Using the PMSI database in order to estimate the burden of severe influenza illness in hospital is consequently of relevance.…”

“…Restricting influenza hospitalizations to hospitalizations with a diagnosis of influenza, we estimated that influenza epidemics caused 6 In Spain, based on data from active surveillance of confirmed severe influenza cases, the hospitalization rate was 7.8/100 000 between 2010 and 2016. 5 Despite the use of various methodologies which does not allow strict comparisons, those data confirm that influenza has a strong impact on the use of hospital resources.…”

Advances in measuring influenza burden of disease

“…Eighteen population‐specific articles have been included in this Special Edition—including five from Asia, four from Africa, four from Europe, three from North America, and one each from South America and the Middle East . (Figure and Table ) This reflects a broad geographical breadth of new research, and these data will add to our understanding of the burden of disease worldwide, especially in LMICs.…”