Dataset Information

Unifying viral genetics and human transportation data to predict the global transmission dynamics of human influenza H3N2.

ABSTRACT: Information on global human movement patterns is central to spatial epidemiological models used to predict the behavior of influenza and other infectious diseases. Yet it remains difficult to test which modes of dispersal drive pathogen spread at various geographic scales using standard epidemiological data alone. Evolutionary analyses of pathogen genome sequences increasingly provide insights into the spatial dynamics of influenza viruses, but to date they have largely neglected the wealth of information on human mobility, mainly because no statistical framework exists within which viral gene sequences and empirical data on host movement can be combined. Here, we address this problem by applying a phylogeographic approach to elucidate the global spread of human influenza subtype H3N2 and assess its ability to predict the spatial spread of human influenza A viruses worldwide. Using a framework that estimates the migration history of human influenza while simultaneously testing and quantifying a range of potential predictive variables of spatial spread, we show that the global dynamics of influenza H3N2 are driven by air passenger flows, whereas at more local scales spread is also determined by processes that correlate with geographic distance. Our analyses further confirm a central role for mainland China and Southeast Asia in maintaining a source population for global influenza diversity. By comparing model output with the known pandemic expansion of H1N1 during 2009, we demonstrate that predictions of influenza spatial spread are most accurate when data on human mobility and viral evolution are integrated. In conclusion, the global dynamics of influenza viruses are best explained by combining human mobility data with the spatial information inherent in sampled viral genomes. The integrated approach introduced here offers great potential for epidemiological surveillance through phylogeographic reconstructions and for improving predictive models of disease control.

SUBMITTER: Lemey P

PROVIDER: S-EPMC3930559 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Unifying viral genetics and human transportation data to predict the global transmission dynamics of human influenza H3N2.

Lemey Philippe P Rambaut Andrew A Bedford Trevor T Faria Nuno N Bielejec Filip F Baele Guy G Russell Colin A CA Smith Derek J DJ Pybus Oliver G OG Brockmann Dirk D Suchard Marc A MA

PLoS pathogens 20140220 2

Information on global human movement patterns is central to spatial epidemiological models used to predict the behavior of influenza and other infectious diseases. Yet it remains difficult to test which modes of dispersal drive pathogen spread at various geographic scales using standard epidemiological data alone. Evolutionary analyses of pathogen genome sequences increasingly provide insights into the spatial dynamics of influenza viruses, but to date they have largely neglected the wealth of i ...[more]

PMID: 24586153

Similar Datasets

Project description:Two subtypes of influenza A virus (IAV), avian-origin canine influenza virus (CIV) H3N2 (CIV-H3N2) and equine-origin CIV H3N8 (CIV-H3N8), are enzootic in the canine population. Dogs have been demonstrated to seroconvert in response to diverse IAVs, and naturally occurring reassortants of CIV-H3N2 and the 2009 H1N1 pandemic virus (pdmH1N1) have been isolated. We conducted a thorough phenotypic evaluation of CIV-H3N2 in order to assess its threat to human health. Using ferret-generated antiserum, we determined that CIV-H3N2 is antigenically distinct from contemporary human H3N2 IAVs, suggesting that there may be minimal herd immunity in humans. We assessed the public health risk of CIV-H3N2 × pandemic H1N1 (pdmH1N1) reassortants by characterizing their in vitro genetic compatibility and in vivo pathogenicity and transmissibility. Using a luciferase minigenome assay, we quantified the polymerase activity of all possible 16 ribonucleoprotein (RNP) complexes (PB2, PB1, PA, NP) between CIV-H3N2 and pdmH1N1, identifying some combinations that were more active than either parental virus complex. Using reverse genetics and fixing the CIV-H3N2 hemagglutinin (HA), we found that 51 of the 127 possible reassortant viruses were viable and able to be rescued. Nineteen of these reassortant viruses had high-growth phenotypes in vitro, and 13 of these replicated in mouse lungs. A single reassortant with the NP and HA gene segments from CIV-H3N2 was selected for characterization in ferrets. The reassortant was efficiently transmitted by contact but not by the airborne route and was pathogenic in ferrets. Our results suggest that CIV-H3N2 reassortants may pose a moderate risk to public health and that the canine host should be monitored for emerging IAVs.IMPORTANCE IAV pandemics are caused by the introduction of novel viruses that are capable of efficient and sustained transmission into a human population with limited herd immunity. Dogs are a a potential mixing vessel for avian and mammalian IAVs and represent a human health concern due to their susceptibility to infection, large global population, and close physical contact with humans. Our results suggest that humans are likely to have limited preexisting immunity to CIV-H3N2 and that CIV-H3N2 × pdmH1N1 reassortants have moderate genetic compatibility and are transmissible by direct contact in ferrets. Our study contributes to the increasing evidence that surveillance of the canine population for IAVs is an important component of pandemic preparedness.

Dataset Information

Unifying viral genetics and human transportation data to predict the global transmission dynamics of human influenza H3N2.

Publications

Unifying viral genetics and human transportation data to predict the global transmission dynamics of human influenza H3N2.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets