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Background: Children with comorbidities are at greater risk of severe influenza outcomes compared with healthy children. In Australia, influenza vaccination was funded for those with comorbidities from 2010 and all children aged

Background Parainfluenza viruses are significant contributors to childhood respiratory illness worldwide, although detailed epidemiological studies are lacking. Few recent Australian studies have investigated serotype‐specific PIV epidemiology, and there is a paucity of southern hemisphere PIV reports. We report age‐stratified PIV hospitalisation rates and a mathematical model of PIV seasonality and dynamics in Western Australia (WA). Methods We used linked perinatal, hospital admission and laboratory diagnostic data of 469 589 children born in WA between 1996 and 2012. Age‐specific rates of viral testing and PIV detection in hospitalised children were determined using person time‐at‐risk analysis. PIV seasonality was modelled using a compartmental SEIRS model and complex demodulation methods. Results From 2000 to 2012, 9% (n = 43 627) of hospitalised children underwent PIV testing, of which 5% (n = 2218) were positive for PIV‐1, 2 or 3. The highest incidence was in children aged 1‐5 months (PIV‐1:62.6 per 100 000 child‐years, PIV‐2:26.3/100 000, PIV‐3:256/100 000), and hospitalisation rates were three times higher for Aboriginal children compared with non‐Aboriginal children overall (IRR: 2.93). PIV‐1 peaked in the autumn of even‐numbered years, and PIV‐3 annually in the spring, whereas PIV‐2 had inconsistent peak timing. Fitting models to the higher incidence serotypes estimated reproduction numbers of 1.24 (PIV‐1) and 1.72 (PIV‐3). Conclusion PIV‐1 and 3 are significant contributors towards infant respiratory hospitalisations. Interventions should prioritise children in the first 6 months of life, with respect to the observed autumn PIV‐1 and spring PIV‐3 activity peaks. Continued surveillance of all serotypes and investigation into PIV‐1 and 3 interventions should be prioritised.

Background Influenza is a major cause of respiratory illness in young children. Assessing the impact of infection on children and the community is required to guide immunisation policies. Objectives To describe the impact of laboratory-proven influenza in young children and to compare its impact with that of other respiratory viruses on the child, their family and the health care system. Methods Preschool children presenting for care or admission to a tertiary paediatric hospital during the 2008-2014 influenza seasons were tested for respiratory virus by polymerase chain reaction and culture. Parental surveys were used to determine the impact of infection on illness duration, medication use, absenteeism and health service utilisation. Multivariate regression analyses were used to assess the impact of influenza and to evaluate the association between influenza status and outcomes. Results Among 1191 children assessed, 238 had influenza. Among children with influenza, 87.8% were administered antipyretics and 40.9% antibiotics. 28.6% had secondary complications. 65.4% of children missed school/day care, and 53.4% of parents missed work. When influenza and other viruses were compared, significant differences were noted including duration of illness (influenza: 9.54 days, other viruses: 8.50 days; P = 0.005) and duration of absenteeism for both the child (23.1 vs 17.3 hours; P = 0.015) and their parents (28.5 vs 22.7 hours; P = 0.012). Conclusions Influenza infection in young children has a significant impact on medication use, absenteeism and the use of health care service. Significant differences are identified when compared with other ILI. These data demonstrate that influenza prevention strategies including immunisation are likely to have wide and significant impacts.

Background Influenza C is usually considered a minor cause of respiratory illness in humans with many infections being asymptomatic or clinically mild. Large outbreaks can occur periodically resulting in significant morbidity. Objectives This study aimed at analyzing the available influenza C clinical samples from two widely separated states of Australia, collected over a 7-year period and to compare them with influenza C viruses detected in other parts of the world in recent years. Patients/Methods Between 2008 and 2014, 86 respiratory samples that were influenza C positive were collected from subjects with influenza-like illness living in the states of Victoria and Western Australia. A battery of other respiratory viruses were also tested for in these influenza C-positive samples. Virus isolation was attempted on all of these clinical samples, and gene sequencing was performed on all influenza C-positive cultures. Results and conclusions Detections of influenza C in respiratory samples were sporadic in most years studied, but higher rates of infection occurred in 2012 and 2014. Many of the patients with influenza C had coinfections with other respiratory pathogens. Phylogenetic analysis of the full-length hemagglutinin–esterase–fusion (HE) gene found that most of the viruses grouped in the C/Sao Paulo/378/82 clade with the remainder grouping in the C/Kanagawa/1/76 clade.

Background Reliance on hospital discharge diagnosis codes alone will likely underestimate the burden of respiratory viruses. Objectives To describe the epidemiology of respiratory viruses more accurately, we used record linkage to examine data relating to all children hospitalized in Western Australia between 2000 and 2012. Patients/Methods We extracted hospital, infectious disease notification and laboratory data of a cohort of children born in Western Australia between 1996 and 2012. Laboratory records of respiratory specimens collected within 48 hours of admission were linked to hospitalisation records. We calculated the frequency and rates of virus detection. To identify groups where under-ascertainment for respiratory viruses was greatest, we used logistic regression to determine factors associated with failure to test. Results and conclusions 9% of 484,992 admissions linked to a laboratory record for respiratory virus testing. While 62% (n=26,893) of laboratory-confirmed admissions received respiratory infection diagnosis codes, 38% (n=16,734) had other diagnoses, notably viral infection of unspecified sites. Of those tested, incidence rates were highest for respiratory syncytial virus (247 per 100,000 child-years) followed by parainfluenza (63 per 100,000 child-years). Admissions among older children and those without a respiratory diagnosis were associated with failure to test for respiratory viruses. Linked data can significantly enhance diagnostic codes when estimating the true burden of disease. In contrast to current emphasis on influenza, respiratory syncytial virus and parainfluenza were the most common viral pathogens among hospitalized children. By characterising those failing to be tested, we can begin to quantify the under-ascertainment of respiratory viruses. This article is protected by copyright. All rights reserved.

Please cite this paper as: Blyth et al. (2013) The impact of bacterial and viral co-infection in severe influenza. Influenza and Other Respiratory Viruses 7(2) 168–176. Background Many questions remain concerning the burden, risk factors and impact of bacterial and viral co-infection in patients with pandemic influenza admitted to the intensive care unit (ICU). Objectives To examine the burden, risk factors and impact of bacterial and viral co-infection in Australian patients with severe influenza. Patients/Methods A cohort study conducted in 14 ICUs was performed. Patients with proven influenza A during the 2009 influenza season were eligible for inclusion. Demographics, risk factors, clinical data, microbiological data, complications and outcomes were collected. Polymerase chain reaction for additional bacterial and viral respiratory pathogens was performed on stored respiratory samples. Results Co-infection was identified in 23·3–26·9% of patients with severe influenza A infection: viral co-infection, 3·2–3·4% and bacterial co-infection, 20·5–24·7%. Staphylococcus aureus was the most frequent bacterial co-infection followed by Streptococcus pneumoniae and Haemophilus influenzae. Patients with co-infection were younger [mean difference in age = 8·46 years (95% CI: 0·18–16·74 years)], less likely to have significant co-morbidities (32·0% versus 66·2%, P = 0·004) and less frequently obese [mean difference in body mass index = 6·86 (95% CI: 1·77–11·96)] compared to those without co-infection. Conclusions Bacterial or viral co-infection complicated one in four patients admitted to ICU with severe influenza A infection. Despite the co-infected patients being younger and with fewer co-morbidities, no significant difference in outcomes was observed. It is likely that co-infection contributed to a need for ICU admission in those without other risk factors for severe influenza disease. Empiric antibiotics with staphylococcal activity should be strongly considered in all patients with severe influenza A infection.

Please cite this paper as: Blyth et al. (2013) The impact of bacterial and viral co‐infection in severe influenza. Influenza and Other Respiratory Viruses 7(2) 168–176. Background Many questions remain concerning the burden, risk factors and impact of bacterial and viral co‐infection in patients with pandemic influenza admitted to the intensive care unit (ICU). Objectives To examine the burden, risk factors and impact of bacterial and viral co‐infection in Australian patients with severe influenza. Patients/Methods A cohort study conducted in 14 ICUs was performed. Patients with proven influenza A during the 2009 influenza season were eligible for inclusion. Demographics, risk factors, clinical data, microbiological data, complications and outcomes were collected. Polymerase chain reaction for additional bacterial and viral respiratory pathogens was performed on stored respiratory samples. Results Co‐infection was identified in 23·3–26·9% of patients with severe influenza A infection: viral co‐infection, 3·2–3·4% and bacterial co‐infection, 20·5–24·7%. Staphylococcus aureus was the most frequent bacterial co‐infection followed by Streptococcus pneumoniae and Haemophilus influenzae. Patients with co‐infection were younger [mean difference in age = 8·46 years (95% CI: 0·18–16·74 years)], less likely to have significant co‐morbidities (32·0% versus 66·2%, P = 0·004) and less frequently obese [mean difference in body mass index = 6·86 (95% CI: 1·77–11·96)] compared to those without co‐infection. Conclusions Bacterial or viral co‐infection complicated one in four patients admitted to ICU with severe influenza A infection. Despite the co‐infected patients being younger and with fewer co‐morbidities, no significant difference in outcomes was observed. It is likely that co‐infection contributed to a need for ICU admission in those without other risk factors for severe influenza disease. Empiric antibiotics with staphylococcal activity should be strongly considered in all patients with severe influenza A infection.