Journal
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
Volume 374, Issue 1775, Pages -Publisher
ROYAL SOC
DOI: 10.1098/rstb.2018.0259
Keywords
avian influenza virus; wild birds; H5NX; epidemiology; serology; genetics
Categories
Funding
- Natural Environment Research Council [NE/R002126/1]
- John Fell Fund (Oxford, UK)
- European Research Council [614725-PATHPHYLODYN]
- Defra [SV3032]
- BBSRC [BB/K004468/1] Funding Source: UKRI
- MRC [MR/R015600/1] Funding Source: UKRI
- NERC [NE/R002126/1] Funding Source: UKRI
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Understanding the epidemiological dynamics of highly pathogenic avian influenza virus (HPAIV) in wild birds is crucial for guiding effective surveillance and control measures. The spread of H5 HPAIV has been well characterized over large geographical and temporal scales. However, information about the detailed dynamics and demographics of individual outbreaks in wild birds is rare and important epidemiological parameters remain unknown. We present data from a wild population of long-lived birds (mute swans; Cygnus olor) that has experienced three outbreaks of related H5 HPAIVs in the past decade, specifically, H5N1 (2007), H5N8 (2016) and H5N6 (2017). Detailed demographic data were available and intense sampling was conducted before and after the outbreaks; hence the population is unusually suitable for exploring the natural epidemiology, evolution and ecology of HPAIV in wild birds. We show that key epidemiological features remain remarkably consistent across multiple outbreaks, including the timing of virus incursion and outbreak duration, and the presence of a strong age-structure in morbidity that likely arises from an equivalent age-structure in immunological responses. The predictability of these features across a series of outbreaks in a complex natural population is striking and contributes to our understanding of HPAIV in wild birds. This article is part of the theme issue 'Modelling infectious disease out-breaks in humans, animals and plants: approaches and important themes'. This issue is linked with the subsequent theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'.
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