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Search Results: 1 - 10 of 6567 matches for " Alex Welte "
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Transient antiretroviral therapy selecting for common HIV-1 mutations substantially accelerates the appearance of rare mutations
Tinevimbo Shiri, Alex Welte
Theoretical Biology and Medical Modelling , 2008, DOI: 10.1186/1742-4682-5-25
Abstract: We develop a new strain-differentiated hybrid deterministic-stochastic population dynamic type model of healthy and infected cells. We explore how the transient increase in a population of cells transcribed with a common mutation (modelled deterministically), which occurs in response to a short course of monotherapy, has an impact on the risk of appearance of rarer, higher-order, therapy-defeating mutations (modelled stochastically).Scenarios with a transient of a magnitude and duration such as is known to occur under NVP monotherapy exhibit significantly accelerated viral evolution compared to no-treatment scenarios. We identify a possibly important new biological timescale; namely, the duration of persistence, after a seminal mutation, of a sub-population of cells bearing the new mutant gene, and we show how increased persistence leads to an increased probability that a rare mutant will be present at the moment at which a new treatment regimen is initiated.Even transient increases in subpopulations of common mutants are associated with accelerated appearance of further rarer mutations. Experimental data on the persistence of small subpopulations of rare mutants, in unfavourable environments, should be sought, as this affects the risk of subverting later regimens.The rapidity of human immunodeficiency virus (HIV) replication, combined with its high reverse transcriptase error rate [1], leads to rapid viral evolution, in particular the emergence of drug resistance. Treatment that is unable to sufficiently inhibit viral replication allows the appearance and/or selection of drug-resistant strains. Further accumulation of resistant variants may limit therapeutic efficacy and jeorpadize subsequent treatment options.A single dose nevirapine (NVP) regimen for prevention of mother to child transmission (PMTCT) is a well known example of a suboptimal regimen that inevitably, if temporarily, exerts selective pressure in favour of resistant strains. This is still a major conc
A Comparison of Biomarker Based Incidence Estimators
Thomas A. McWalter, Alex Welte
PLOS ONE , 2009, DOI: 10.1371/journal.pone.0007368
Abstract: Background Cross-sectional surveys utilizing biomarkers that test for recent infection provide a convenient and cost effective way to estimate HIV incidence. In particular, the BED assay has been developed for this purpose. Controversy surrounding the way in which false positive results from the biomarker should be handled has lead to a number of different estimators that account for imperfect specificity. We compare the estimators proposed by McDougal et al., Hargrove et al. and McWalter & Welte. Methodology/Principal Findings The three estimators are analyzed and compared. An identity showing a relationship between the calibration parameters in the McDougal methodology is shown. When the three estimators are tested under a steady state epidemic, which includes individuals who fail to progress on the biomarker, only the McWalter/Welte method recovers an unbiased result. Conclusions/Significance Our analysis shows that the McDougal estimator can be reduced to a formula that only requires calibration of a mean window period and a long-term specificity. This allows simpler calibration techniques to be used and shows that all three estimators can be expressed using the same set of parameters. The McWalter/Welte method is applicable under the least restrictive assumptions and is the least prone to bias of the methods reviewed.
Relating Recent Infection Prevalence to Incidence with a Sub-population of Non-progressors
Thomas A. McWalter,Alex Welte
Quantitative Biology , 2008,
Abstract: We present a new analysis of relationships between disease incidence and the prevalence of an experimentally defined state of `recent infection'. This leads to a clean separation between biological parameters (properties of disease progression as reflected in a test for recent infection), which need to be calibrated, and epidemiological state variables, which are estimated in a cross-sectional survey. The framework takes into account the possibility that details of the assay and host/pathogen chemistry leave a (knowable) fraction of the population in the recent category for all times. This systematically addresses an issue which is the source of some controversy about the appropriate use of the BED assay for defining recent HIV infection. Analysis of relative contributions of error arising variously from statistical considerations and simplifications of general expressions indicate that statistical error dominates heavily over all sources of bias for realistic epidemiological and biological scenarios. Numerical calculations validate the approximations made in analytical relations.
A General HIV Incidence Inference Scheme Based on Likelihood of Individual Level Data and a Population Renewal Equation
Guy Severin Mahiane, Rachid Ouifki, Hilmarie Brand, Wim Delva, Alex Welte
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0044377
Abstract: We derive a new method to estimate the age specific incidence of an infection with a differential mortality, using individual level infection status data from successive surveys. The method consists of a) an SI-type model to express the incidence rate in terms of the prevalence and its derivatives as well as the difference in mortality rate, and b) a maximum likelihood approach to estimate the prevalence and its derivatives. Estimates can in principle be obtained for any chosen age and time, and no particular assumptions are made about the epidemiological or demographic context. This is in contrast with earlier methods for estimating incidence from prevalence data, which work with aggregated data, and the aggregated effect of demographic and epidemiological rates over the time interval between prevalence surveys. Numerical simulation of HIV epidemics, under the presumption of known excess mortality due to infection, shows improved control of bias and variance, compared to previous methods. Our analysis motivates for a) effort to be applied to obtain accurate estimates of excess mortality rates as a function of age and time among HIV infected individuals and b) use of individual level rather than aggregated data in order to estimate HIV incidence rates at times between two prevalence surveys.
Towards Eliminating Bias in Cluster Analysis of TB Genotyped Data
Cari van Schalkwyk, Madeleine Cule, Alex Welte, Paul van Helden, Gian van der Spuy, Pieter Uys
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0034109
Abstract: The relative contributions of transmission and reactivation of latent infection to TB cases observed clinically has been reported in many situations, but always with some uncertainty. Genotyped data from TB organisms obtained from patients have been used as the basis for heuristic distinctions between circulating (clustered strains) and reactivated infections (unclustered strains). Na?ve methods previously applied to the analysis of such data are known to provide biased estimates of the proportion of unclustered cases. The hypergeometric distribution, which generates probabilities of observing clusters of a given size as realized clusters of all possible sizes, is analyzed in this paper to yield a formal estimator for genotype cluster sizes. Subtle aspects of numerical stability, bias, and variance are explored. This formal estimator is seen to be stable with respect to the epidemiologically interesting properties of the cluster size distribution (the number of clusters and the number of singletons) though it does not yield satisfactory estimates of the number of clusters of larger sizes. The problem that even complete coverage of genotyping, in a practical sampling frame, will only provide a partial view of the actual transmission network remains to be explored.
A physician led approach to telehealth-enabled care coordination: innovation in reimbursement and delivery system models to support physician engagement
Ileana Welte
International Journal of Integrated Care , 2012,
Abstract:
How can we reduce the mortality of invasive pneumococcal disease?
T. Welte
European Respiratory Review , 2012,
Abstract:
Central extension of graded Lie algebras
Angelika Welte
Mathematics , 2010,
Abstract: In this thesis we describe the universal central extension of two important classes of so-called root-graded Lie algebras defined over a commutative associative unital ring $k.$ Root-graded Lie algebras are Lie algebras which are graded by the root lattice of a locally finite root system and contain enough $\mathfrak{sl}_2$-triples to separate the homogeneous spaces of the grading. Examples include the infinite rank analogs of the simple finite-dimensional complex Lie algebras. \\ In the thesis we show that in general the universal central extension of a root-graded Lie algebra $L$ is not root-graded anymore, but that we can measure quite easily how far it is away from being so, using the notion of degenerate sums, introduced by van der Kallen. We then concentrate on root-graded Lie algebras which are graded by the root systems of type $A$ with rank at least 2 and of type $C$. For them one can use the theory of Jordan algebras.
HIV Treatment as Prevention: Principles of Good HIV Epidemiology Modelling for Public Health Decision-Making in All Modes of Prevention and Evaluation
Wim Delva,David P. Wilson,Laith Abu-Raddad,Marelize Gorgens,David Wilson,Timothy B. Hallett,Alex Welte
PLOS Medicine , 2012, DOI: 10.1371/journal.pmed.1001239
Abstract: Public health responses to HIV epidemics have long relied on epidemiological modelling analyses to help prospectively project and retrospectively estimate the impact, cost-effectiveness, affordability, and investment returns of interventions, and to help plan the design of evaluations. But translating model output into policy decisions and implementation on the ground is challenged by the differences in background and expectations of modellers and decision-makers. As part of the PLoS Medicine Collection “Investigating the Impact of Treatment on New HIV Infections”—which focuses on the contribution of modelling to current issues in HIV prevention—we present here principles of “best practice” for the construction, reporting, and interpretation of HIV epidemiological models for public health decision-making on all aspects of HIV. Aimed at both those who conduct modelling research and those who use modelling results, we hope that the principles described here will become a shared resource that facilitates constructive discussions about the policy implications that emerge from HIV epidemiology modelling results, and that promotes joint understanding between modellers and decision-makers about when modelling is useful as a tool in quantifying HIV epidemiological outcomes and improving prevention programming.
Seroconverting Blood Donors as a Resource for Characterising and Optimising Recent Infection Testing Algorithms for Incidence Estimation
Reshma Kassanjee,Alex Welte,Thomas A. McWalter,Sheila M. Keating,Marion Vermeulen,Susan L. Stramer,Michael P. Busch
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0020027
Abstract: Biomarker-based cross-sectional incidence estimation requires a Recent Infection Testing Algorithm (RITA) with an adequately large mean recency duration, to achieve reasonable survey counts, and a low false-recent rate, to minimise exposure to further bias and imprecision. Estimating these characteristics requires specimens from individuals with well-known seroconversion dates or confirmed long-standing infection. Specimens with well-known seroconversion dates are typically rare and precious, presenting a bottleneck in the development of RITAs.
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