Publications
307 results found
Shirreff G, Alizon S, Cori A, et al., 2013, How effectively can HIV phylogenies be used to measure heritability?, Evol Med Public Health, Vol: 2013, Pages: 209-224, ISSN: 2050-6201
BACKGROUND AND OBJECTIVES: The severity of HIV-1 infection, measured by set-point viral load (SPVL), is highly variable between individuals. Its heritability between infections quantifies the control the pathogen genotype has over disease severity. Heritability estimates vary widely between studies, but differences in methods make comparison difficult. Phylogenetic comparative analysis offers measures of phylogenetic signal, but it is unclear how to interpret them in terms of the fraction of variance in SPVL controlled by the virus genotype. METHODOLOGY: We present computational methods which link statistics summarizing phylogenetic signal to heritability, h(2) in order to test for and quantify it. We re-analyse data from Switzerland and Uganda, and apply it to new data from the Netherlands. We systematically compare established and new (e.g. phylogenetic pairs, PP) phylogenetic signal statistics. RESULTS: Heritability estimates varied by method and dataset. Several methods were consistently able to detect simulated heritability above , but none below. Pagel's λ was the most robust and sensitive. The PP method found no heritability in the Netherlands data, whereas Pagel's λ found significant heritability only in a narrow subdivision (P = 0.038). Heritability was estimated at h(2) = 0.52 (95% confidence interval 0.00-0.63). CONCLUSIONS AND IMPLICATIONS: This standardized measure, h(2), allows comparability of heritability between cohorts. We confirm high heritability in Swiss data, but neither in Ugandan data nor in the Netherlands, where it is barely significant or undetectable. Existing phylogenetic methods are ill-suited for detecting heritability below , which may nonetheless be biologically important.
Ratmann O, Donker G, Meijer A, et al., 2012, Phylodynamic Inference and Model Assessment with Approximate Bayesian Computation: Influenza as a Case Study, PLoS Computational Biology, Vol: 8, ISSN: 1553-7358
A key priority in infectious disease research is to understand the ecological and evolutionary drivers of viral diseases from data on disease incidence as well as viral genetic and antigenic variation. We propose using a simulation-based, Bayesian method known as Approximate Bayesian Computation (ABC) to fit and assess phylodynamic models that simulate pathogen evolution and ecology against summaries of these data. We illustrate the versatility of the method by analyzing two spatial models describing the phylodynamics of interpandemic human influenza virus subtype A(H3N2). The first model captures antigenic drift phenomenologically with continuously waning immunity, and the second epochal evolution model describes the replacement of major, relatively long-lived antigenic clusters. Combining features of long-term surveillance data from the Netherlands with features of influenza A (H3N2) hemagglutinin gene sequences sampled in northern Europe, key phylodynamic parameters can be estimated with ABC. Goodness-of-fit analyses reveal that the irregularity in interannual incidence and H3N2's ladder-like hemagglutinin phylogeny are quantitatively only reproduced under the epochal evolution model within a spatial context. However, the concomitant incidence dynamics result in a very large reproductive number and are not consistent with empirical estimates of H3N2's population level attack rate. These results demonstrate that the interactions between the evolutionary and ecological processes impose multiple quantitative constraints on the phylodynamic trajectories of influenza A(H3N2), so that sequence and surveillance data can be used synergistically. ABC, one of several data synthesis approaches, can easily interface a broad class of phylodynamic models with various types of data but requires careful calibration of the summaries and tolerance parameters.
van Sighem A, Vidondo B, Glass TR, et al., 2012, Resurgence of HIV Infection among Men Who Have Sex with Men in Switzerland: Mathematical Modelling Study, PLOS ONE, Vol: 7, ISSN: 1932-6203
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- Citations: 57
van Sighem A, Jansen I, Bezemer D, et al., 2012, Increasing sexual risk behaviour among Dutch men who have sex with men: mathematical models versus prospective cohort data, AIDS, Vol: 26, Pages: 1840-1843, ISSN: 0269-9370
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- Citations: 16
Lythgoe KA, Fraser C, 2012, New insights into the evolutionary rate of HIV-1 at the within-host and epidemiological levels, PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, Vol: 279, Pages: 3367-3375, ISSN: 0962-8452
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- Citations: 56
de Silva E, Ferguson NM, Fraser C, 2012, Inferring pandemic growth rates from sequence data, JOURNAL OF THE ROYAL SOCIETY INTERFACE, Vol: 9, Pages: 1797-1808, ISSN: 1742-5689
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- Citations: 32
HIV Modelling Consortium Treatment as Prevention Editorial Writing Group, 2012, HIV treatment as prevention: models, data, and questions--towards evidence-based decision-making., PLOS Medicine, Vol: 9, ISSN: 1549-1277
Antiretroviral therapy (ART) for those infected with HIV can prevent onward transmission of infection, but biological efficacy alone is not enough to guide policy decisions about the role of ART in reducing HIV incidence. Epidemiology, economics, demography, statistics, biology, and mathematical modelling will be central in framing key decisions in the optimal use of ART. PLoS Medicine, with the HIV Modelling Consortium, has commissioned a set of articles that examine different aspects of HIV treatment as prevention with a forward-looking research agenda. Interlocking themes across these articles are discussed in this introduction. We hope that this article, and others in the collection, will provide a foundation upon which greater collaborations between disciplines will be formed, and will afford deeper insights into the key factors involved, to help strengthen the support for evidence-based decision-making in HIV prevention.
Delva W, Eaton JW, Meng F, et al., 2012, HIV Treatment as Prevention: Optimising the Impact of Expanded HIV Treatment Programmes, PLOS Medicine, Vol: 9, ISSN: 1549-1277
Until now, decisions about how to allocate ART have largely been based on maximising the therapeutic benefit of ART for patients. Since the results of the HPTN 052 study showed efficacy of antiretroviral therapy (ART) in preventing HIV transmission, there has been increased interest in the benefits of ART not only as treatment, but also in prevention. Resources for expanding ART in the short term may be limited, so the question is how to generate the most prevention benefit from realistic potential increases in the availability of ART. Although not a formal systematic review, here we review different ways in which access to ART could be expanded by prioritising access to particular groups based on clinical or behavioural factors. For each group we consider (i) the clinical and epidemiological benefits, (ii) the potential feasibility, acceptability, and equity, and (iii) the affordability and cost-effectiveness of prioritising ART access for that group. In re-evaluating the allocation of ART in light of the new data about ART preventing transmission, the goal should be to create policies that maximise epidemiological and clinical benefit while still being feasible, affordable, acceptable, and equitable.
Eaton JW, Johnson LF, Salomon JA, et al., 2012, HIV Treatment as Prevention: Systematic Comparison of Mathematical Models of the Potential Impact of Antiretroviral Therapy on HIV Incidence in South Africa, PLOS MEDICINE, Vol: 9, ISSN: 1549-1277
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- Citations: 255
Cohen MS, Dye C, Fraser C, et al., 2012, HIV Treatment as Prevention: Debate and Commentary-Will Early Infection Compromise Treatment-as-Prevention Strategies?, PLOS MEDICINE, Vol: 9, ISSN: 1549-1676
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- Citations: 85
Truscott J, Fraser C, Cauchemez S, et al., 2012, Essential epidemiological mechanisms underpinning the transmission dynamics of seasonal influenza, Journal of the Royal Society Interface, Vol: 9, Pages: 304-312, ISSN: 1742-5662
Seasonal influenza has considerable impact around the world, both economically and in mortality among risk groups, but there is considerable uncertainty as to the essential mechanisms and their parametrization. In this paper, we identify a number of characteristic features of influenza incidence time series in temperate regions, including ranges of annual attack rates and outbreak durations. By constraining the output of simple models to match these characteristic features, we investigate the role played by population heterogeneity, multiple strains, cross-immunity and the rate of strain evolution in the generation of incidence time series. Results indicate that an age-structured model with non-random mixing and co-circulating strains are both required to match observed time-series data. Our work gives estimates of the seasonal peak basic reproduction number, R0, in the range 1.6–3. Estimates of R0 are strongly correlated with the timescale for waning of immunity to current circulating seasonal influenza strain, which we estimate is between 3 and 8 years. Seasonal variation in transmissibility is largely confined to 15–30% of its mean value. While population heterogeneity and cross-immunity are required mechanisms, the degree of heterogeneity and cross-immunity is not tightly constrained. We discuss our findings in the context of other work fitting to seasonal influenza data.
Pellis L, Ferguson NM, Fraser C, 2011, Epidemic growth rate and household reproduction number in communities of households, schools and workplaces, JOURNAL OF MATHEMATICAL BIOLOGY, Vol: 63, Pages: 691-734, ISSN: 0303-6812
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- Citations: 16
Shirreff G, Pellis L, Laeyendecker O, et al., 2011, Transmission Selects for HIV-1 Strains of Intermediate Virulence: A Modelling Approach, PLOS COMPUTATIONAL BIOLOGY, Vol: 7, ISSN: 1553-734X
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- Citations: 28
Fraser C, Cummings DAT, Klinkenberg D, et al., 2011, Influenza Transmission in Households During the 1918 Pandemic, AMERICAN JOURNAL OF EPIDEMIOLOGY, Vol: 174, Pages: 505-514, ISSN: 0002-9262
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- Citations: 55
Opatowski L, Fraser C, Griffin J, et al., 2011, Transmission Characteristics of the 2009 H1N1 Influenza Pandemic: Comparison of 8 Southern Hemisphere Countries, PLOS PATHOGENS, Vol: 7, ISSN: 1553-7366
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- Citations: 55
Muller V, Fraser C, Herbeck JT, 2011, A Strong Case for Viral Genetic Factors in HIV Virulence, VIRUSES-BASEL, Vol: 3, Pages: 204-216, ISSN: 1999-4915
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- Citations: 23
Croucher NJ, Harris SR, Fraser C, et al., 2011, Rapid Pneumococcal Evolution in Response to Clinical Interventions, SCIENCE, Vol: 331, Pages: 430-434, ISSN: 0036-8075
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- Citations: 663
Fraser C, Hollingsworth TD, 2010, Interpretation of correlations in setpoint viral load in transmitting couples, AIDS, Vol: 24, Pages: 2596-2597, ISSN: 0269-9370
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- Citations: 8
Baggaley RF, Fraser C, 2010, Modelling sexual transmission of HIV: testing the assumptions, validating the predictions, CURRENT OPINION IN HIV AND AIDS, Vol: 5, Pages: 269-276, ISSN: 1746-630X
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- Citations: 23
Colijn C, Cohen T, Fraser C, et al., 2010, What is the mechanism for persistent coexistence of drug-susceptible and drug-resistant strains of <i>Streptococcus pneumoniae</i>?, JOURNAL OF THE ROYAL SOCIETY INTERFACE, Vol: 7, Pages: 905-919, ISSN: 1742-5689
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- Citations: 61
Bezemer D, de Wolf F, Boerlijst MC, et al., 2010, 27 years of the HIV epidemic amongst men having sex with men in the Netherlands: An in depth mathematical model-based analysis, Epidemics, Vol: 2, Pages: 66-79
BackgroundThere has been increasing concern about a resurgent epidemic of HIV-1 amongst men having sex with men in the Netherlands, which has parallels with similar epidemics now occurring in many other countries.MethodsA transmission model applicable to HIV-1 epidemics, including the use of antiretroviral therapy, is presented in a set of ordinary differential equations. The model is fitted by maximum likelihood to national HIV-1 and AIDS diagnosis data from 1980 to 2006, estimating parameters on average changes in unsafe sex and time to diagnosis. Robustness is studied with a detailed univariate sensitivity analysis, and a range of hypothetical scenarios are explored for the past and next decade.ResultsWith a reproduction number around the epidemic threshold one, the HIV-1 epidemic amongst men having sex with men in the Netherlands is still not under control. Scenario analysis showed that in the absence of antiretroviral therapy limiting infectiousness in treated patients, the epidemic could have been more than double its current size. Ninety percent of new HIV transmissions are estimated to take place before diagnosis of the index case. Decreasing time from infection to diagnosis, which was 2.5 years on average in 2006, can prevent many future infections.ConclusionsSexual risk behaviour amongst men having sex with men who are not aware of their infection is the most likely factor driving this epidemic.
Hanage WP, Finkelstein JA, Huang SS, et al., 2010, Evidence that pneumococcal serotype replacement in Massachusetts following conjugate vaccination is now complete, EPIDEMICS, Vol: 2, Pages: 80-84, ISSN: 1755-4365
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- Citations: 105
Hollingsworth TD, Laeyendecker O, Shirreff G, et al., 2010, HIV-1 Transmitting Couples Have Similar Viral Load Set-Points in Rakai, Uganda, PLOS PATHOGENS, Vol: 6, ISSN: 1553-7366
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- Citations: 76
van Kerkhove MD, Asikainen T, Becker NG, et al., 2010, Studies needed to address public health challenges of the 2009 H1N1 influenza pandemic: insights from modeling., PLoS Med, Vol: 7, Pages: e1000275-e1000275
Cauchemez S, Donnelly CA, Reed C, et al., 2009, Household Transmission of 2009 Pandemic Influenza A (H1N1) Virus in the United States, NEW ENGLAND JOURNAL OF MEDICINE, Vol: 361, Pages: 2619-2627, ISSN: 0028-4793
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- Citations: 365
Pellis L, Ferguson NM, Fraser C, 2009, Threshold parameters for a model of epidemic spread among households and workplaces, Journal of The Royal Society Interface, Vol: 6, Pages: 979-987
The basic reproduction number is one of the most important concepts in modern infectious disease epidemiology. However, for more realistic and more complex models than those assuming homogeneous mixing in the population, other threshold quantities can be defined that are sometimes more useful and easily derived in terms of model parameters. In this paper, we present a model for the spread of a permanently immunizing infection in a population socially structured into households and workplaces/schools, and we propose and discuss a new household-to-household reproduction number for it. We show how overcomes some of the limitations of a previously proposed threshold parameter, and we highlight its relationship with the effort required to control an epidemic when interventions are targeted at randomly selected households.
Truscott J, Fraser C, Hinsley W, et al., 2009, Quantifying the transmissibility of human influenza and its seasonal variation in temperate regions., PLoS Curr, Vol: 1
Seasonal influenza has considerable impact around the world, both economically and in mortality among risk groups. The long term patterns of disease are hard to capture with simple models, while the interplay of epidemiological processes with antigenic evolution makes detailed modelling difficult and computationally intensive. We identify a number of characteristic features of flu incidence time series in temperate regions, including ranges of annual attack rates and outbreak durations. We construct pseudo-likelihoods to capture these characteristic features and examine the ability of a collection of simple models to reproduce them under seasonal variation in transmission. Results indicate that an age-structured model with non-random mixing and co-circulating strains are both required to match time series data. The extent of matching behaviour also serves to define informative ranges for parameters governing essential dynamics. Our work gives estimates of the seasonal peak basic reproduction, R0, in the range 1.7-2.1, with the degree of seasonal variation having limited impact of these estimates. We find that it is only really possible to estimate a lower bound on the degree of seasonal variation in influenza transmissibility, namely that transmissibility in the low transmission season may be only 5-10% less than the peak value. These results give some insight into the extent to which transmissibility of the H1N1pdm pandemic virus may increase in Northern Hemisphere temperate countries in winter 2009. We find that the timescale for waning of immunity to current circulating seasonal influenza strain is between 4 and 8 years, consistent with studies of the antigenic variation of influenza, and that inter-subtype cross-immunity is restricted to low levels.
Gras L, Jurriaans S, Bakker M, et al., 2009, Viral Load Levels Measured at Set-Point Have Risen Over the Last Decade of the HIV Epidemic in the Netherlands, PLOS ONE, Vol: 4, ISSN: 1932-6203
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- Citations: 36
Goldstein E, Paur K, Fraser C, et al., 2009, Reproductive numbers, epidemic spread and control in a community of households, MATHEMATICAL BIOSCIENCES, Vol: 221, Pages: 11-25, ISSN: 0025-5564
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- Citations: 36
Fraser C, Donnelly CA, Cauchemez S, et al., 2009, Influenza: Making Privileged Data Public Response, SCIENCE, Vol: 325, Pages: 1072-1073, ISSN: 0036-8075
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- Citations: 2
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