Influenza Seasonality

Tang, Julian W.; Loh, Tze Ping

doi:10.1007/s40506-016-0088-2

Cited by 8 publications

(12 citation statements)

References 115 publications

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“…It is clear that our approach, using mostly routine diagnostic test data, has some disadvantages, as it is not based on systematic sentinel surveillance, unlike the routine influenza surveillance in many countries. However, our findings, based mostly on routinely collected diagnostic data for influenza and RSV, are similar to those reported by other global studies using mainly national surveillance data, [31][32][33][34] i.e. that there are annual seasonal peaks of influenza and RSV in the colder months in the Northern and Southern hemispheres, with more year-round activity in the subtropical/tropical regions.…”

Section: Discussionsupporting

confidence: 90%

“…over the same time period) incidence patterns of common respiratory viruses across different countries -and nearly all of these used mostly publicly available surveillance data extracted from national surveillance websites, or published studies. [31][32][33][34][35] However, it is clear from the literature that international collaborations are increasing, in an effort to pool and compare such contemporaneous epidemiological data, to improve our understanding of how these respiratory viruses are behaving -not just within our local or national populations, but simultaneously across the world. Although national surveillance data are invaluable to reveal how these viruses are behaving and moving through populations, and also capture the incidence of viral infections in the community to some extent, the bulk of that population's healthcare burden may be more accurately represented by the routine diagnostic testing data obtained from patients who were sufficiently ill to be admitted to hospital.…”

Section: Introductionmentioning

confidence: 99%

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Comparative global epidemiology of influenza, respiratory syncytial and parainfluenza viruses, 2010–2015

Lam

Tang

Lai

et al. 2019

Journal of Infection

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s u m m a r yObjectives: To improve our understanding of the global epidemiology of common respiratory viruses by analysing their contemporaneous incidence at multiple sites. Methods: 2010-2015 incidence data for influenza A (IAV), influenza B (IBV), respiratory syncytial (RSV) and parainfluenza (PIV) virus infections were collected from 18 sites (14 countries), consisting of local ( n = 6), regional ( n = 9) and national ( n = 3) laboratories using molecular diagnostic methods. Each site submitted monthly virus incidence data, together with details of their patient populations tested and diagnostic assays used.Results: For the Northern Hemisphere temperate countries, the IAV, IBV and RSV incidence peaks were 2-6 months out of phase with those in the Southern Hemisphere, with IAV having a sharp out-of-phase difference at 6 months, whereas IBV and RSV showed more variable out-of-phase differences of 2-6 months. The tropical sites Singapore and Kuala Lumpur showed fluctuating incidence of these viruses throughout the year, whereas subtropical sites such as Hong Kong, Brisbane and Sydney showed distinctive biannual peaks for IAV but not for RSV and PIV. Conclusions: There was a notable pattern of synchrony of IAV, IBV and RSV incidence peaks globally, and within countries with multiple sampling sites (Canada, UK, Australia), despite significant distances between these sites.

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Comparative global epidemiology of influenza, respiratory syncytial and parainfluenza viruses, 2010–2015

Lam

Tang

Lai

et al. 2019

Journal of Infection

View full text Add to dashboard Cite

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“…Influenza A and B are the two major circulating viruses that cause epidemics worldwide, and both types exhibit an intriguing dynamic of infection pattern where different climate zones appear to have their own pattern of seasonal variation in incidence. 1 Understanding and predicting the seasonality of influenza is crucial for optimizing public health decisions on vaccination strategy and healthcare resource preparedness. Moreover, cross-disciplinary collaboration on climate and public health is one of the priority areas of the United Nations World Health Organization and World Meteorological Organization (WMO) under the Global Framework for Climate Services initiative.…”

Section: Introductionmentioning

confidence: 99%

Association between meteorological variations and activities of influenza A and B across different climate zones: a multi-region modelling analysis across the globe

Chong

Lee

Bialasiewicz

et al. 2020

Journal of Infection

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“…Studies have revealed that seasonal influenza is virus type specific and climate dependent (Ye et al 2019 ; Alonso et al 2007 ; Tamerius et al 2013 ; Lofgren et al 2007 ). Influenza A (Flu-A) and influenza B (Flu-B) are presently the two major viruses circulating globally, which exhibit distinctive but intriguing dynamics of infection patterns (Tang and Loh 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Influenza A and B outbreaks differed in their associations with climate conditions in Shenzhen, China

Tang

Zhang

et al. 2021

Int J Biometeorol

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Under the variant climate conditions in the transitional regions between tropics and subtropics, the impacts of climate factors on influenza subtypes have rarely been evaluated. With the available influenza A (Flu-A) and influenza B (Flu-B) outbreak data in Shenzhen, China, which is an excellent example of a transitional marine climate, the associations of multiple climate variables with these outbreaks were explored in this study. Daily laboratory-confirmed influenza virus and climate data were collected from 2009 to 2015. Potential impacts of daily mean/maximum/minimum temperatures ( T / T max / T min ), relative humidity (RH), wind velocity ( V ), and diurnal temperature range (DTR) were analyzed using the distributed lag nonlinear model (DLNM) and generalized additive model (GAM). Under its local climate partitions, Flu-A mainly prevailed in summer months (May to June), and a second peak appeared in early winter (December to January). Flu-B outbreaks usually occurred in transitional seasons, especially in autumn. Although low temperature caused an instant increase in both Flu-A and Flu-B risks, its effect could persist for up to 10 days for Flu-B and peak at 17 C (relative risk (RR) = 14.16, 95% CI: 7.46–26.88). For both subtypes, moderate–high temperature (28 C) had a significant but delayed effect on influenza, especially for Flu-A (RR = 26.20, 95% CI: 13.22–51.20). The Flu-A virus was sensitive to RH higher than 76%, while higher Flu-B risks were observed at both low (< 65%) and high (> 83%) humidity. Flu-A was active for a short term after exposure to large DTR (e.g., DTR = 10 C, RR = 12.45, 95% CI: 6.50–23.87), whereas Flu-B mainly circulated under stable temperatures. Although the overall wind speed in Shenzhen was low, moderate wind (2–3 m/s) was found to favor the outbreaks of both subtypes. This study revealed the thresholds of various climatic variables promoting influenza outbreaks, as well as the distinctions between the flu subtypes. These data can be helpful in predicting seasonal influenza outbreaks and minimizing the impacts, based on integrated forecast systems coupled with short-term climate models. Supplementary Information The online version contains supplementary material available at 10.1007/s00484-021-02204-y.

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Influenza Seasonality

Cited by 8 publications

References 115 publications

Comparative global epidemiology of influenza, respiratory syncytial and parainfluenza viruses, 2010–2015

Comparative global epidemiology of influenza, respiratory syncytial and parainfluenza viruses, 2010–2015

Association between meteorological variations and activities of influenza A and B across different climate zones: a multi-region modelling analysis across the globe

Influenza A and B outbreaks differed in their associations with climate conditions in Shenzhen, China

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