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      Relating Phylogenetic Trees to Transmission Trees of Infectious Disease Outbreaks

      , ,
      Genetics
      Genetics Society of America

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          Abstract

          Transmission events are the fundamental building blocks of the dynamics of any infectious disease. Much about the epidemiology of a disease can be learned when these individual transmission events are known or can be estimated. Such estimations are difficult and generally feasible only when detailed epidemiological data are available. The genealogy estimated from genetic sequences of sampled pathogens is another rich source of information on transmission history. Optimal inference of transmission events calls for the combination of genetic data and epidemiological data into one joint analysis. A key difficulty is that the transmission tree, which describes the transmission events between infected hosts, differs from the phylogenetic tree, which describes the ancestral relationships between pathogens sampled from these hosts. The trees differ both in timing of the internal nodes and in topology. These differences become more pronounced when a higher fraction of infected hosts is sampled. We show how the phylogenetic tree of sampled pathogens is related to the transmission tree of an outbreak of an infectious disease, by the within-host dynamics of pathogens. We provide a statistical framework to infer key epidemiological and mutational parameters by simultaneously estimating the phylogenetic tree and the transmission tree. We test the approach using simulations and illustrate its use on an outbreak of foot-and-mouth disease. The approach unifies existing methods in the emerging field of phylodynamics with transmission tree reconstruction methods that are used in infectious disease epidemiology.

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          Inferring phylogeny despite incomplete lineage sorting.

          It is now well known that incomplete lineage sorting can cause serious difficulties for phylogenetic inference, but little attention has been paid to methods that attempt to overcome these difficulties by explicitly considering the processes that produce them. Here we explore approaches to phylogenetic inference designed to consider retention and sorting of ancestral polymorphism. We examine how the reconstructability of a species (or population) phylogeny is affected by (a) the number of loci used to estimate the phylogeny and (b) the number of individuals sampled per species. Even in difficult cases with considerable incomplete lineage sorting (times between divergences less than 1 N(e) generations), we found the reconstructed species trees matched the "true" species trees in at least three out of five partitions, as long as a reasonable number of individuals per species were sampled. We also studied the tradeoff between sampling more loci versus more individuals. Although increasing the number of loci gives more accurate trees for a given sampling effort with deeper species trees (e.g., total depth of 10 N(e) generations), sampling more individuals often gives better results than sampling more loci with shallower species trees (e.g., depth = 1 N(e)). Taken together, these results demonstrate that gene sequences retain enough signal to achieve an accurate estimate of phylogeny despite widespread incomplete lineage sorting. Continued improvement in our methods to reconstruct phylogeny near the species level will require a shift to a compound model that considers not only nucleotide or character state substitutions, but also the population genetics processes of lineage sorting. [Coalescence; divergence; population; speciation.].
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            Whole-genome sequencing for analysis of an outbreak of meticillin-resistant Staphylococcus aureus: a descriptive study

            Summary Background The emergence of meticillin-resistant Staphylococcus aureus (MRSA) that can persist in the community and replace existing hospital-adapted lineages of MRSA means that it is necessary to understand transmission dynamics in terms of hospitals and the community as one entity. We assessed the use of whole-genome sequencing to enhance detection of MRSA transmission between these settings. Methods We studied a putative MRSA outbreak on a special care baby unit (SCBU) at a National Health Service Foundation Trust in Cambridge, UK. We used whole-genome sequencing to validate and expand findings from an infection-control team who assessed the outbreak through conventional analysis of epidemiological data and antibiogram profiles. We sequenced isolates from all colonised patients in the SCBU, and sequenced MRSA isolates from patients in the hospital or community with the same antibiotic susceptibility profile as the outbreak strain. Findings The hospital infection-control team identified 12 infants colonised with MRSA in a 6 month period in 2011, who were suspected of being linked, but a persistent outbreak could not be confirmed with conventional methods. With whole-genome sequencing, we identified 26 related cases of MRSA carriage, and showed transmission occurred within the SCBU, between mothers on a postnatal ward, and in the community. The outbreak MRSA type was a new sequence type (ST) 2371, which is closely related to ST22, but contains genes encoding Panton-Valentine leucocidin. Whole-genome sequencing data were used to propose and confirm that MRSA carriage by a staff member had allowed the outbreak to persist during periods without known infection on the SCBU and after a deep clean. Interpretation Whole-genome sequencing holds great promise for rapid, accurate, and comprehensive identification of bacterial transmission pathways in hospital and community settings, with concomitant reductions in infections, morbidity, and costs. Funding UK Clinical Research Collaboration Translational Infection Research Initiative, Wellcome Trust, Health Protection Agency, and the National Institute for Health Research Cambridge Biomedical Research Centre.
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              Different epidemic curves for severe acute respiratory syndrome reveal similar impacts of control measures.

              Severe acute respiratory syndrome (SARS) has been the first severe contagious disease to emerge in the 21st century. The available epidemic curves for SARS show marked differences between the affected regions with respect to the total number of cases and epidemic duration, even for those regions in which outbreaks started almost simultaneously and similar control measures were implemented at the same time. The authors developed a likelihood-based estimation procedure that infers the temporal pattern of effective reproduction numbers from an observed epidemic curve. Precise estimates for the effective reproduction numbers were obtained by applying this estimation procedure to available data for SARS outbreaks that occurred in Hong Kong, Vietnam, Singapore, and Canada in 2003. The effective reproduction numbers revealed that epidemics in the various affected regions were characterized by markedly similar disease transmission potentials and similar levels of effectiveness of control measures. In controlling SARS outbreaks, timely alerts have been essential: Delaying the institution of control measures by 1 week would have nearly tripled the epidemic size and would have increased the expected epidemic duration by 4 weeks.
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                Author and article information

                Journal
                Genetics
                Genetics
                Genetics Society of America
                0016-6731
                1943-2631
                November 04 2013
                November 2013
                November 2013
                September 13 2013
                : 195
                : 3
                : 1055-1062
                Article
                10.1534/genetics.113.154856
                3813836
                24037268
                cd7fa8d6-f0a7-4376-8f2c-8be477722cb9
                © 2013
                History

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