Biomedical subjects

Andrew R Francis

Publications and source records attributed to Andrew R Francis.

4 recordsLinked to original sources

PubMed2006

Detecting emerging strains of tuberculosis by using spoligotypes.

The W-Beijing strain of tuberculosis has been identified in many molecular epidemiological studies as being particularly prevalent. This identification has been made possible through the development of a number of genotyping technologies including spoligotyping. Highly prevalent genotypes associated with outbreaks, such as the W-Beijing strain, are implicitly regarded as fast spreading. Here we present a quantitative method to identify "emerging" strains, those that are spreading faster than the background rate inferred from spoligotype data. The approach uses information about the mutation process specific to spoligotypes, combined with a model of both transmission and mutation. The core principle is that if two comparable strains have the same number of isolates, then the strain with fewer inferred mutation events must have spread faster if the mutation process is common. Applying this method to four different data sets, we find not only the W-Beijing strain, but also a number of other strains, to be emerging in this sense. Importantly, the strains that are identified as emerging are not simply those with the largest number of cases. The use of this method should facilitate the targeting of individual genotypes in intervention programs.

Animals↗

PubMed2006

An evaluation of indices for quantifying tuberculosis transmission using genotypes of pathogen isolates.

BACKGROUND: Infectious diseases are often studied by characterising the population structure of the pathogen using genetic markers. An unresolved problem is the effective quantification of the extent of transmission using genetic variation data from such pathogen isolates. METHODS: It is important that transmission indices reflect the growth of the infectious population as well as account for the mutation rate of the marker and the effects of sampling. That is, while responding to this growth rate, indices should be unresponsive to the sample size and the mutation rate. We use simulation methods taking into account both the mutation and sampling processes to evaluate indices designed to quantify transmission of tuberculosis. RESULTS: Previously proposed indices generally perform inadequately according to the above criteria, with the partial exception of the recently proposed Transmission-Mutation Index. CONCLUSION: Any transmission index needs to take into account mutation of the marker and the effects of sampling. Simple indices are unlikely to capture the full complexity of the underlying processes.

Computer Simulation↗

PubMed2006

Using approximate Bayesian computation to estimate tuberculosis transmission parameters from genotype data.

Tuberculosis can be studied at the population level by genotyping strains of Mycobacterium tuberculosis isolated from patients. We use an approximate Bayesian computational method in combination with a stochastic model of tuberculosis transmission and mutation of a molecular marker to estimate the net transmission rate, the doubling time, and the reproductive value of the pathogen. This method is applied to a published data set from San Francisco of tuberculosis genotypes based on the marker IS6110. The mutation rate of this marker has previously been studied, and we use those estimates to form a prior distribution of mutation rates in the inference procedure. The posterior point estimates of the key parameters of interest for these data are as follows: net transmission rate, 0.69/year [95% credibility interval (C.I.) 0.38, 1.08]; doubling time, 1.08 years (95% C.I. 0.64, 1.82); and reproductive value 3.4 (95% C.I. 1.4, 79.7). These figures suggest a rapidly spreading epidemic, consistent with observations of the resurgence of tuberculosis in the United States in the 1980s and 1990s.

Algorithms↗

PubMed2005

Methods of quantifying and visualising outbreaks of tuberculosis using genotypic information.

Genotypic data from pathogenic isolates are often used to measure the extent of infectious disease transmission. These methods include phylogenetic reconstruction and the evaluation of clustering indices. The first aim of this paper is to critique current methods used to analyse genotypic data from molecular epidemiological studies of tuberculosis. In particular, by not accounting for the mutation rate of markers, errors arise in making inferences about outbreaks based on genotypic information. The second aim is to suggest a new way to represent genotypic data visually, involving graphs and trees. We also discuss some interpretations and modifications of existing indices. Although our focus is tuberculosis, the methods we discuss are generally applicable to any directly transmissible clonal pathogen.

Cluster Analysis↗