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. 2019 Oct;79(4):373-382.
doi: 10.1016/j.jinf.2019.07.008. Epub 2019 Jul 16.

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

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

Tommy T Lam et al. J Infect. 2019 Oct.

Abstract

Objectives: 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.

Keywords: Epidemiology; Global; Incidence; Influenza virus; Parainfluenza virus; Respiratory syncytial virus; Seasonality.

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Figures

Fig. 1
Fig. 1
The incidence of the four respiratory viruses in the eighteen surveillance sites. Panels (A)–(D) show the monthly incidence of (A) influenza A virus, (B) influenza B virus, (C) respiratory syncytial virus, and (D) parainfluenza viruses from January 2010 to December 2015. The left-hand column displays the order of the geographical origin of the data for each of the four heat maps in the central column. The final right-hand column indicates the individual viruses for which the monthly incidence is displayed at each of these geographical sites. The maximum value of the colour scale is set to the highest incidence value (against which the other data for that site is normalised) at each surveillance site after excluding any outliers. The grey boxes indicate that no data was available from that site during that period. Some sites were only able to provide data for only some of these viruses for a limited period (usually within the period of a specifically funded study).
Fig. 2
Fig. 2
A comparison of the overall incidence of the four respiratory RNA viruses in the tested samples. IAV – influenza A virus, IBV – influenza B virus, RSV – respiratory syncytial virus, PIV parainfluenza virus. Site abbreviations: NZ – New Zealand, UK – United Kingdom, KL – Kuala Lumpur. The white/grey squares indicate whether the samples are mostly children (white) or adult (grey) patients, or both.
Fig. 3
Fig. 3
Month of peak incidence for the four RNA respiratory viruses. IAV – influenza A virus, IBV – influenza B virus, RSV – respiratory syncytial virus, PIV3 - parainfluenza type 3 virus. Peak incidence months showing significant annual and biannual seasonality (determined by wavelet analysis) were estimated via a circular statistics method. Study sites are ordered by their latitudes. *no PIV3-specific data. ⁎⁎only IAV and IBV data available.
Fig. 4
Fig. 4
Patterns of viral incidence between geographically closely related cities within the same counties. Note that the incidence peaks for influenza A (IAV), influenza B (IBV), respiratory syncytial virus (RSV) and (where available) parainfluenza virus 3 (PIV3) are more or less coincident for Leicester-Cambridge, Brisbane-Sydney, and Vancouver-Edmonton-Halifax, despite the variable and large distances between these cities within the same country. The coincidence is less obvious when all subtypes of PIV are grouped and compared. In contrast, note that there is much less synchrony between the incidence peaks of these viruses in the Singaporean and Malaysian populations. * Sydney and Edmonton do not have PIV3 specific data.

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