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

Ang, Li Wei; Cui, Lin; Mak, Tze Minn; Ng, Yixiang; Leo, Yee Sin; Lee, Vernon Jian Ming; Lin, Raymond Tzer‐Pin

doi:10.1002/jmv.25473

Cited by 7 publications

(8 citation statements)

References 33 publications

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“…Therefore, local vaccination and other prevention strategies for influenza infection should attach importance to the elderly population and school-age children, including consideration of the different predominant subtypes in the different age groups. Additionally, the positive rate in the 0-4 years old group (9.1%) was lower than that in the other age groups, which is consistent with previous reports in Singapore [40]. The transmission pattern may account for this result, as influenza infection in this age Epidemiology and Infection group relies on household transmission, and thus, children have a reduced chance to be exposed to influenza viruses.…”

Section: Discussionsupporting

confidence: 88%

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

Wang

Zhu

et al. 2020

Epidemiol. Infect.

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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 (PM2.5) 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. PM2.5 concentrations showed significant effects on influenza-positivity rate in Hulunbuir, which could be considered in local influenza prevention strategies.

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Section: Discussionsupporting

confidence: 88%

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

Wang

Zhu

et al. 2020

Epidemiol. Infect.

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“…These five years were characterised by relatively high influenza positivity percentages (46.3% to 53.6%), with four of them (excluding 2010) having higher proportions of influenza B among influenza‐positive specimens (32.7% to 47.9%) compared to other years. Yamagata was the predominant influenza B lineage in 2014 and 2017, while 2012 and 2016 were observed to have co‐circulating lineages with slightly higher proportions of the Victoria lineage . There is, however, insufficient evidence to conclude that the influenza B virus was driving influenza‐associated hospitalisations in Singapore.…”

Section: Discussionmentioning

confidence: 99%

“…16.3% of all P&I hospitalisations in Singapore from 2010 to 2017 were estimated to be attributed to influenza, corresponding to an and 2016 were observed to have co-circulating lineages with slightly higher proportions of the Victoria lineage. 25 There is, however, insufficient evidence to conclude that the influenza B virus was driving influenza-associated hospitalisations in Singapore. One hypothesis is that influenza B could have played an additive effect in the above-mentioned four years, contributing to the burden generated by influenza A thus leading to greater overall morbidity burden.…”

Section: Discussionmentioning

confidence: 99%

“…We used the all‐age weekly influenza positivity from 2010 to 2017, derived by calculating the proportion of specimens that had been laboratory‐confirmed positive for influenza, as a proxy variable for influenza activity. We also highlighted the dominant influenza type/subtype for each year based on results from another study . To adjust for potential confounding, we also obtained the weekly respiratory syncytial virus (RSV) positivity data from the paediatric departments of two government acute hospitals, as well as meteorological data (weekly mean temperature and weekly mean relative humidity) from the National Environment Agency (NEA).…”

Section: Methodsmentioning

confidence: 99%

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Estimates of influenza‐associated hospitalisations in tropical Singapore, 2010‐2017: Higher burden estimated in more recent years

Chua

et al. 2019

Influenza Resp Viruses

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Background We previously estimated Singapore's influenza‐associated hospitalisation rate for pneumonia and influenza (P&I) in 2010‐2012 to be 29.6 per 100 000 person‐years, which corresponds to 11.2% of all P&I hospitalisations. Objectives This study aims to update Singapore's estimates of the influenza‐associated pneumonia and influenza (P&I) hospitalisation burden using the latest data from 2010 to 2017. Methods We estimated the number of P&I hospitalisations associated with influenza using generalised additive models. We specified the weekly number of admissions for P&I and the weekly influenza positivity in the models, along with potential confounders such as weekly respiratory syncytial virus (RSV) positivity and meteorological data. Results In 2010‐2017, 16.3% of all P&I hospitalisations in Singapore were estimated to be attributed to influenza, corresponding to an excess influenza‐associated P&I hospitalisation rate of 50.1 per 100 000 person‐years. Higher excess rates were estimated for children aged 0‐4 years (186.8 per 100 000 person‐years) and elderly aged ≥ 65 years (338.0 per 100 000 person‐years). Higher influenza‐associated hospitalisation rates were estimated for 2016 and 2017 (67.9 and 75.1 per 100 000 persons, respectively) years when the influenza A(H3N2) subtype was dominant. Conclusion Influenza burden in Singapore has increased since 2010. Influenza vaccination programmes should continue to be prioritised for the young and the elderly.

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“…This will allow us to recognize the atrisk subpopulations when facing an epidemic caused by a specific combination of several influenza subtypes/lineages. Differential age-specific distribution of influenza virus types and subtypes have been indicated [5][6][7], but that of influenza virus lineages has not been clearly demonstrated. In this study, we aim to depict the seasonal patterns and age-specific crossreferencing infection risk at influenza virus subtype/lineage level.…”

Section: Introductionmentioning

confidence: 99%

Influenza virus subtype/lineage-specific seasonal patterns and age-related infection risk, in Eastern China

Huo

Fu²,

Dai³

et al. 2022

J Infect Dev Ctries

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Introduction: Differences in seasonal pattern and age-related infection risk have been reported between Influenza type A and B, but have not been elaborated at subtype/lineage level. Methodology: All laboratory-confirmed influenza cases reported in the influenza surveillance system of Jiangsu Province, China from January 2011 to August 2019 were analyzed. Influenza seasonality was characterized using the Seasonal Decomposition method. Binary and multinomial logistic regressions were employed to calculate the odds ratios of influenza subtypes/lineages in relation to age. Results: A total of 28,772 confirmed influenza cases were included. Among them, a majority (64.1%) were influenza A infections. One annual peak was observed for A (H1N1) pdm and B-Yamagata in winter months, and for B-Victoria in spring months, while biannual peaks were observed for A (H3N2) in winter and summer months. Using all ages as the reference, children younger than 5 years and adults of 25-59 years were more likely to infect with A (H1N1) pdm. Older children aged 5-14 years had significantly higher odds of infection with influenza B of both lineages, while individuals aged 15-24 years had higher odds for A (H3N2) and B-Victoria. The elderly (60 years or older) were prone to be infected with A (H3N2) and B-Yamagata. For a specific age group, their likelihood of getting infected with an influenza subtype or lineage was related to the co-circulating influenza subtype or lineage. Conclusions: Influenza viruses have divergent seasonal peak times and age-related infection risk at subtype/lineage level.

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

Abstract: Surveillance and reporting of epidemiological features of seasonal influenza mostly are aggregates across all-ages. We investigated age-specific differences in distribu-

Cited by 7 publications

References 33 publications

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

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

Estimates of influenza‐associated hospitalisations in tropical Singapore, 2010‐2017: Higher burden estimated in more recent years

Influenza virus subtype/lineage-specific seasonal patterns and age-related infection risk, in Eastern China

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