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      Virus–virus interactions impact the population dynamics of influenza and the common cold

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          Significance

          When multiple pathogens cocirculate this can lead to competitive or cooperative forms of pathogen–pathogen interactions. It is believed that such interactions occur among cold and flu viruses, perhaps through broad-acting immunity, resulting in interlinked epidemiological patterns of infection. However, to date, quantitative evidence has been limited. We analyzed a large collection of diagnostic reports collected over multiple years for 11 respiratory viruses. Our analyses provide strong statistical support for the existence of interactions among respiratory viruses. Using computer simulations, we found that very short-lived interferences may explain why common cold infections are less frequent during flu seasons. Improved understanding of how the epidemiology of viral infections is interlinked can help improve disease forecasting and evaluation of disease control interventions.

          Abstract

          The human respiratory tract hosts a diverse community of cocirculating viruses that are responsible for acute respiratory infections. This shared niche provides the opportunity for virus–virus interactions which have the potential to affect individual infection risks and in turn influence dynamics of infection at population scales. However, quantitative evidence for interactions has lacked suitable data and appropriate analytical tools. Here, we expose and quantify interactions among respiratory viruses using bespoke analyses of infection time series at the population scale and coinfections at the individual host scale. We analyzed diagnostic data from 44,230 cases of respiratory illness that were tested for 11 taxonomically broad groups of respiratory viruses over 9 y. Key to our analyses was accounting for alternative drivers of correlated infection frequency, such as age and seasonal dependencies in infection risk, allowing us to obtain strong support for the existence of negative interactions between influenza and noninfluenza viruses and positive interactions among noninfluenza viruses. In mathematical simulations that mimic 2-pathogen dynamics, we show that transient immune-mediated interference can cause a relatively ubiquitous common cold-like virus to diminish during peak activity of a seasonal virus, supporting the potential role of innate immunity in driving the asynchronous circulation of influenza A and rhinovirus. These findings have important implications for understanding the linked epidemiological dynamics of viral respiratory infections, an important step towards improved accuracy of disease forecasting models and evaluation of disease control interventions.

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          Most cited references54

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          Estimating the impact of school closure on influenza transmission from Sentinel data.

          The threat posed by the highly pathogenic H5N1 influenza virus requires public health authorities to prepare for a human pandemic. Although pre-pandemic vaccines and antiviral drugs might significantly reduce illness rates, their stockpiling is too expensive to be practical for many countries. Consequently, alternative control strategies, based on non-pharmaceutical interventions, are a potentially attractive policy option. School closure is the measure most often considered. The high social and economic costs of closing schools for months make it an expensive and therefore controversial policy, and the current absence of quantitative data on the role of schools during influenza epidemics means there is little consensus on the probable effectiveness of school closure in reducing the impact of a pandemic. Here, from the joint analysis of surveillance data and holiday timing in France, we quantify the role of schools in influenza epidemics and predict the effect of school closure during a pandemic. We show that holidays lead to a 20-29% reduction in the rate at which influenza is transmitted to children, but that they have no detectable effect on the contact patterns of adults. Holidays prevent 16-18% of seasonal influenza cases (18-21% in children). By extrapolation, we find that prolonged school closure during a pandemic might reduce the cumulative number of cases by 13-17% (18-23% in children) and peak attack rates by up to 39-45% (47-52% in children). The impact of school closure would be reduced if it proved difficult to maintain low contact rates among children for a prolonged period.
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            Ecological and immunological determinants of influenza evolution.

            In pandemic and epidemic forms, influenza causes substantial, sometimes catastrophic, morbidity and mortality. Intense selection from the host immune system drives antigenic change in influenza A and B, resulting in continuous replacement of circulating strains with new variants able to re-infect hosts immune to earlier types. This 'antigenic drift' often requires a new vaccine to be formulated before each annual epidemic. However, given the high transmissibility and mutation rate of influenza, the constancy of genetic diversity within lineages over time is paradoxical. Another enigma is the replacement of existing strains during a global pandemic caused by 'antigenic shift'--the introduction of a new avian influenza A subtype into the human population. Here we explore ecological and immunological factors underlying these patterns using a mathematical model capturing both realistic epidemiological dynamics and viral evolution at the sequence level. By matching model output to phylogenetic patterns seen in sequence data collected through global surveillance, we find that short-lived strain-transcending immunity is essential to restrict viral diversity in the host population and thus to explain key aspects of drift and shift dynamics.
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              Species interactions in a parasite community drive infection risk in a wildlife population.

              Most hosts, including humans, are simultaneously or sequentially infected with several parasites. A key question is whether patterns of coinfection arise because infection by one parasite species affects susceptibility to others or because of inherent differences between hosts. We used time-series data from individual hosts in natural populations to analyze patterns of infection risk for a microparasite community, detecting large positive and negative effects of other infections. Patterns remain once variations in host susceptibility and exposure are accounted for. Indeed, effects are typically of greater magnitude, and explain more variation in infection risk, than the effects associated with host and environmental factors more commonly considered in disease studies. We highlight the danger of mistaken inference when considering parasite species in isolation rather than parasite communities.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                pnas
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                26 December 2019
                16 December 2019
                16 December 2019
                : 116
                : 52
                : 27142-27150
                Affiliations
                [1] aMRC-University of Glasgow Centre for Virus Research, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow , G61 1QH Glasgow, United Kingdom;
                [2] bSchool of Mathematics and Statistics, College of Science and Engineering, University of Glasgow , G12 8QQ Glasgow, United Kingdom;
                [3] cBoyd Orr Centre for Population and Ecosystem Health, Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow , G12 8QQ Glasgow, United Kingdom;
                [4] dThe Queen Elizabeth University Hospital, NHS Greater Glasgow and Clyde , G51 4TF Glasgow, United Kingdom;
                [5] ePublic Health, NHS Greater Glasgow and Clyde , G12 0XH Glasgow, United Kingdom;
                [6] fHealth Protection Scotland, NHS National Services Scotland , G2 6QE Glasgow, United Kingdom;
                [7] gWest of Scotland Specialist Virology Centre, NHS Greater Glasgow and Clyde , G31 2ER Glasgow, United Kingdom
                Author notes
                1To whom correspondence may be addressed. Email: louise.matthews@ 123456glasgow.ac.uk or Pablo.Murcia@ 123456glasgow.ac.uk .

                Edited by Burton H. Singer, University of Florida, Gainesville, FL, and approved November 12, 2019 (received for review June 27, 2019)

                Author contributions: S.N., L.M., R.R., P.C.D.J., R.N.G., and P.R.M. designed research; S.N., C.M., and P.C.D.J. performed research; F.T., A.R., J.M., and R.N.G. contributed new reagents/analytic tools; S.N., C.M., and P.C.D.J. analyzed data; and S.N., C.M., L.M., R.R., P.C.D.J., F.T., B.v.W., A.R., J.M., R.N.G., and P.R.M. wrote the paper.

                Author information
                http://orcid.org/0000-0003-4420-8367
                http://orcid.org/0000-0003-2589-8091
                http://orcid.org/0000-0002-4352-394X
                Article
                201911083
                10.1073/pnas.1911083116
                6936719
                31843887
                ab66b88f-6500-4e72-b69f-ab7216a2427f
                Copyright © 2019 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

                History
                Page count
                Pages: 9
                Funding
                Funded by: RCUK | Medical Research Council (MRC) 501100000265
                Award ID: MC_UU_12014/9
                Award Recipient : Sema Nickbakhsh Award Recipient : Colette Mair Award Recipient : Louise Matthews Award Recipient : Richard Reeve Award Recipient : Pablo R Murcia
                Funded by: RCUK | Medical Research Council (MRC) 501100000265
                Award ID: MC_UU_12014/9
                Award Recipient : Sema Nickbakhsh Award Recipient : Colette Mair Award Recipient : Louise Matthews Award Recipient : Richard Reeve Award Recipient : Pablo R Murcia
                Funded by: RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) 501100000268
                Award ID: BB/K01126X/1
                Award Recipient : Louise Matthews Award Recipient : Richard Reeve
                Funded by: RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) 501100000268
                Award ID: BB/L004070/1
                Award Recipient : Louise Matthews Award Recipient : Richard Reeve
                Funded by: RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) 501100000268
                Award ID: BB/L018926/1
                Award Recipient : Louise Matthews Award Recipient : Richard Reeve
                Funded by: RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) 501100000268
                Award ID: BB/N013336/1
                Award Recipient : Louise Matthews Award Recipient : Richard Reeve
                Funded by: RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) 501100000268
                Award ID: BB/R012679/1
                Award Recipient : Louise Matthews Award Recipient : Richard Reeve
                Funded by: RCUK | Biotechnology and Biological Sciences Research Council (BBSRC) 501100000268
                Award ID: BB/L004828/1
                Award Recipient : Louise Matthews Award Recipient : Richard Reeve
                Funded by: NSF | BIO | Division of Environmental Biology (DEB) 100000155
                Award ID: DEB1216040
                Award Recipient : Louise Matthews Award Recipient : Richard Reeve
                Funded by: Foods Standards Agency
                Award ID: FS101055
                Award Recipient : Louise Matthews Award Recipient : Richard Reeve
                Categories
                PNAS Plus
                Biological Sciences
                Population Biology
                PNAS Plus

                epidemiology,virology,ecology
                epidemiology, virology, ecology

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