Research Article: Transmission of Equine Influenza Virus during an Outbreak Is Characterized by Frequent Mixed Infections and Loose Transmission Bottlenecks

Date Published: December 20, 2012

Publisher: Public Library of Science

Author(s): Joseph Hughes, Richard C. Allen, Marc Baguelin, Katie Hampson, Gregory J. Baillie, Debra Elton, J. Richard Newton, Paul Kellam, James L. N. Wood, Edward C. Holmes, Pablo R. Murcia, Marco Vignuzzi.

http://doi.org/10.1371/journal.ppat.1003081

Abstract

The ability of influenza A viruses (IAVs) to cross species barriers and evade host immunity is a major public health concern. Studies on the phylodynamics of IAVs across different scales – from the individual to the population – are essential for devising effective measures to predict, prevent or contain influenza emergence. Understanding how IAVs spread and evolve during outbreaks is critical for the management of epidemics. Reconstructing the transmission network during a single outbreak by sampling viral genetic data in time and space can generate insights about these processes. Here, we obtained intra-host viral sequence data from horses infected with equine influenza virus (EIV) to reconstruct the spread of EIV during a large outbreak. To this end, we analyzed within-host viral populations from sequences covering 90% of the infected yards. By combining gene sequence analyses with epidemiological data, we inferred a plausible transmission network, in turn enabling the comparison of transmission patterns during the course of the outbreak and revealing important epidemiological features that were not apparent using either approach alone. The EIV populations displayed high levels of genetic diversity, and in many cases we observed distinct viral populations containing a dominant variant and a number of related minor variants that were transmitted between infectious horses. In addition, we found evidence of frequent mixed infections and loose transmission bottlenecks in these naturally occurring populations. These frequent mixed infections likely influence the size of epidemics.

Partial Text

Studying the evolution of influenza A viruses (IAVs) across different scales – from the individual to the global population – is critical for understanding the risk of cross-species transmissions and the potential for emergence of novel pandemic viruses. Time-informed phylogenetic approaches have been instrumental in understanding the evolutionary origin of recent pandemic strains [1], and experimental studies of naturally transmitted IAVs have revealed the patterns of genetic variation at the level of single hosts as well as the inter-host transmission of viral variants [2], [3]. To date, however, few studies have achieved sufficiently dense sampling during a naturally occurring outbreak to integrate epidemiological processes with evolution at the scale of individual hosts [4].

 

Source:

http://doi.org/10.1371/journal.ppat.1003081

 

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