Mair, C., Nickbakhsh, S. , Reeve, R. , McMenamin, J., Reynolds, A., Gunson, R. N., Murcia, P. R. and Matthews, L. (2019) Estimation of temporal covariances in pathogen dynamics using Bayesian multivariate autoregressive models. PLoS Computational Biology, 15(12), e1007492. (doi: 10.1371/journal.pcbi.1007492) (PMID:31834896) (PMCID:PMC6934324)
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Abstract
It is well recognised that animal and plant pathogens form complex ecological communities of interacting organisms within their hosts, and there is growing interest in the health implications of such pathogen interactions. Although community ecology approaches have been used to identify pathogen interactions at the within-host scale, methodologies enabling robust identification of interactions from population-scale data such as that available from health authorities are lacking. To address this gap, we developed a statistical framework that jointly identifies interactions between multiple viruses from contemporaneous non-stationary infection time series. Our conceptual approach is derived from a Bayesian multivariate disease mapping framework. Importantly, our approach captures within- and between-year dependencies in infection risk while controlling for confounding factors such as seasonality, demographics and infection frequencies, allowing genuine pathogen interactions to be distinguished from simple correlations. We validated our framework using a broad range of synthetic data. We then applied it to diagnostic data available for five respiratory viruses co-circulating in a major urban population between 2005 and 2013: adenovirus, human coronavirus, human metapneumovirus, influenza B virus and respiratory syncytial virus. We found positive and negative covariances indicative of epidemiological interactions among specific virus pairs. This statistical framework enables a community ecology perspective to be applied to infectious disease epidemiology with important utility for public health planning and preparedness.
Item Type: | Articles |
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Additional Information: | This work was funded by the Medical Research Council of the United Kingdom MC_UU_12014/9, www.mrc.ukri.org/ (S.N, C.M, P.M, R.R and L.M). We are grateful for the support from the National Science Foundation DEB1216040/BB/K01126X/1, www.nsf.gov (L.M), MR/S004815/1 (L.M) MR/R00241X/1 (L.M. and R.R), www.mrc.ukri.org, BB/L018926/1 (L.M), BB/M003949/1 (L.M) BB/L004070/1 (L.M and R.R), BB/R012679/1 (R.R), www.bbsrc.ukri.org, the Foods Standards Agency FS101055, www.food.gov.uk (L.M) and the Scottish Government Rural and Environment Science and Analytical Services Division, as part of the Centre of Expertise on Animal Disease Outbreaks (EPIC), www.epicscotland.org (L.M). |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | McMenamin, Dr James and Nickbakhsh, Dr Sema and Reeve, Professor Richard and Gunson, Dr Rory and Mair, Dr Colette and Matthews, Professor Louise and Reynolds, Dr Arlene and Murcia, Professor Pablo |
Creator Roles: | Mair, C.Formal analysis, Funding acquisition, Methodology, Validation, Visualization, Writing – original draft, Writing – review and editing Nickbakhsh, S.Conceptualization, Data curation, Funding acquisition, Investigation, Validation, Writing – review and editing Reeve, R.Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Validation, Writing – review and editing McMenamin, J.Data curation, Writing – review and editing Reynolds, A.Data curation, Writing – review and editing Gunson, R. N.Data curation, Writing – review and editing Murcia, P. R.Conceptualization, Formal analysis, Funding acquisition, Investigation, Supervision, Validation, Writing – review and editing Matthews, L.Formal analysis, Funding acquisition, Methodology, Supervision, Validation, Writing – review and editing |
Authors: | Mair, C., Nickbakhsh, S., Reeve, R., McMenamin, J., Reynolds, A., Gunson, R. N., Murcia, P. R., and Matthews, L. |
College/School: | College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Public Health College of Medical Veterinary and Life Sciences > School of Infection & Immunity College of Science and Engineering > School of Mathematics and Statistics > Statistics College of Medical Veterinary and Life Sciences > School of Infection & Immunity > Centre for Virus Research College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine |
Journal Name: | PLoS Computational Biology |
Publisher: | Public Library of Science |
ISSN: | 1553-734X |
ISSN (Online): | 1553-7358 |
Copyright Holders: | Copyright © 2019 Mair et al. |
First Published: | First published in PLoS Computational Biology 15:e1007492 |
Publisher Policy: | Reproduced under a creative commons licence |
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