Differential age-specific distribution of influenza virus types and subtypes in tropical Singapore, 2011 to 2017

Age-dependent influenza infection patterns and subtype circulation in Denmark, in seasons 2015/16 to 2021/22

BackgroundInfluenza was almost absent for 2 years following the implementation of strict public health measures to prevent the spread of SARS-CoV-2. The consequence of this on infections in different age groups is not yet known.AimTo describe the age groups infected with the influenza virus in 2021/22, the first post-pandemic influenza season in Denmark, compared with the previous six seasons, and subtypes circulating therein.MethodsInfection and hospitalisation incidences per season and age group were estimated from data in Danish registries. Influenza virus subtypes and lineages were available from samples sent to the National Influenza Centre at Statens Serum Institut.ResultsTest incidence followed a similar pattern in all seasons, being highest in 0-1-year-olds and individuals over 75 years, and lowest in 7-14-year-olds and young people 15 years to late twenties. When the influenza A virus subtypes A(H3N2) and A(H1N1)pdm09 co-circulated in seasons 2015/16 and 2017/18 to 2019/20, the proportion of A(H1N1)pdm09 was higher in 0-1-year-olds and lower in the over 85-year-olds  compared with the overall proportion of A(H1N1)pdm09 in these seasons. The proportion of A(H3N2) was higher in the over 85 years age group compared with the overall proportion of A(H3N2). The 2016/17 and 2021/22 seasons were dominated by A(H3N2) but differed in age-specific trends, with the over 85 years age group initiating the 2016/17 season, while the 2021/22 season was initiated by the 15-25-year-olds, followed by 7-14-year-olds.ConclusionThe 2021/22 influenza season had a different age distribution compared with pre-COVID-19 pandemic seasons.

Developing and validating clinical features-based machine learning algorithms to predict influenza infection in influenza-like illness patients

BACKGROUND

Seasonal influenza poses a significant risk, and patients can benefit from early diagnosis and treatment. However, underdiagnosis and undertreatment remain widespread. We developed and compared clinical feature-based machine learning (ML) algorithms that can accurately predict influenza infection in emergency departments (EDs) among patients with influenza-like illness (ILI).

MATERIAL AND METHODS

We conducted a prospective cohort study in five EDs in the US and Taiwan from 2015 to 2020. Adult patients visiting the EDs with symptoms of ILI were recruited and tested by real-time RT-PCR for influenza. We evaluated seven ML algorithms and compared their results with previously developed clinical prediction models.

RESULTS

Out of the 2189 enrolled patients, 1104 tested positive for influenza. The eXtreme Gradient Boosting achieved superior performance with an area under the receiver operating characteristic curve of 0.82 (95% confidence interval [CI] = 0.79-0.85), with a sensitivity of 0.92 (95% CI = 0.88-0.95), specificity of 0.89 (95% CI = 0.86-0.92), and accuracy of 0.72 (95% CI = 0.69-0.76) in the testing set over cut-offs of 0.4, 0.6 and 0.5, respectively. These results were superior to those of previously proposed clinical prediction models. The model interpretation revealed that body temperature, cough, rhinorrhea, and exposure history were positively associated with and the days of illness and influenza vaccine were negatively associated with influenza infection. We also found the week of the influenza season, pulse rate, and oxygen saturation to be associated with influenza infection.

CONCLUSIONS

The clinical feature-based ML model outperformed conventional models for predicting influenza infection.

Epidemiological and genetic characteristics of influenza virus and the effects of air pollution on laboratory-confirmed influenza cases in Hulunbuir, China, from 2010 to 2019

Objective

A continuous survey on influenza was conducted in Hulunbuir, China from January 2010 to May 2019 to reveal epidemiological, microbiological and air pollutants associated with laboratory-confirmed influenza cases.

Methods

Influenza-like illness and severe acute respiratory infection subjects were enrolled from a sentinel hospital in Hulunbuir during the study period for epidemiological and virological investigation. The association between air pollutants and influenza-positivity rate was assessed by a generalised additive model.

Results

Of 4667 specimens, 550 (11.8%) were tested positive for influenza. The influenza-positivity was highest in the age groups of 5–14 years, 50–69 years and ⩾70 years. We found that the effect of particulate matter ⩽2.5 μm (PM_2.5) concentrations on the influenza-positivity rate was statistically significant, particularly on day lag-4 and lag-5. Genetic characterisations showed that (H1N1) pdm09 strains belonged to subclade 6B.1 and that influenza B isolates belonged to subclade 1A-3Del, with significant substitutions in the haemagglutinin and neuraminidase proteins compared with those in the WHO-recommended vaccine strains.

Conclusions

Elderly individuals and school-age children were at high risk for influenza infection. PM_2.5 concentrations showed significant effects on influenza-positivity rate in Hulunbuir, which could be considered in local influenza prevention strategies.

Characterisation of respiratory syncytial virus activity in children and adults presenting with acute respiratory illness at primary care clinics in Singapore, 2014-2018

BACKGROUND

Respiratory syncytial virus (RSV) is an important respiratory pathogen that affects people of all ages.

OBJECTIVES

We examined the patterns of RSV circulation in 2014-2018, and investigated their age-specific differences in tropical Singapore.

METHODS

Nasopharyngeal and/or throat swabs were taken from outpatient attendees for the national influenza virological surveillance among those who presented with acute respiratory illness in the community. Specimens tested negative for influenza were then tested for RSV and other respiratory pathogens.

RESULTS

Among 8436 influenza-negative specimens tested during the five-year period, 5.8% (95% confidence interval 5.3%-6.3%) were positive for RSV. The peak of RSV activity occurred around middle of the year. The age-specific proportion of RSV detections showed a reverse J-shaped pattern; RSV positivity was the highest in young children ≤2 years of age (10.9%), followed by those aged 3-5 years (6.4%) and persons aged ≥65 years (5.3%), while the nadir was observed in the age group of 15-24 years (1.2%). RSV type A was predominantly circulating in children ≤5 years of age from 2014 to 2015 and 2017, whereas in 2016, they were more affected by type B.

CONCLUSION

Respiratory syncytial virus was more frequently detected among the two age groups that have been recommended for influenza vaccination; persons ≥65 years of age and children 6 months to <5 years of age. Characterisation of RSV activity in the community helps to better inform public health policies for effective prevention and control interventions.

Virological Surveillance of Influenza in the eight epidemic seasons after the 2009 pandemic in Emilia-Romagna (Northern Italy)

BACKGROUND AND AIM OF THE WORK

Influenza virological surveillance is essential for monitoring the evolution of influenza viruses (IVs) as well as for annual updating of the vaccine composition. The aim of this study is to analyse IVs circulation in Emilia-Romagna during the eight epidemic seasons after the 2009 pandemic and to evaluate their match with seasonal vaccine strains.

METHODS

A total of 7882 respiratory specimens from patients with influenza-like illness (ILI), were collected by regional sentinel practitioners and hospital physicians. Viral investigations were conducted by rRT-PCR assay. Genetic characterization was performed for a spatial-temporal representative number of influenza laboratory-confirmed specimens.

RESULTS

Influenza-positive samples per season ranged between 28.9% (2013-2014) and 66.8% (2012-2013). Co-circulation of IVs type A and type B was observed in all seasons, although with a different intensity. In all seasons, the highest number of positive samples was recorded in younger patients aged 5-14 years with relative frequencies ranging from 40% in the 2013-2014 season and 78% in the 2012-2013 season. Since the 2009 pandemic, A/H1N1pdm09 IVs circulating were closely related to the vaccine strain A/California/7/2009. Antigenic mismatch between vaccine strain and A/H3N2 IVs was observed in the 2011-2012 and 2014-2015 seasons. During 2015-2016, 2016-2017 and 2017-2018 seasons a complete or nearly complete mismatch between the predominant influenza B lineage of IVs type B circulating and vaccine B lineage occurred.

CONCLUSIONS

This analysis confirms the importance of the virological surveillance and highlights the need of a continuous monitoring of IVs circulation, to improve the most appropriate vaccination strategies. (www.actabiomedica.it).