Extinction times in the subcritical stochastic SIS logistic epidemic

Many real epidemics of an infectious disease are not straightforwardly super- or sub-critical, and the understanding of epidemic models that exhibit such complexity has been identified as a priority for theoretical work. We provide insights into the near-critical regime by considering the stochastic SIS logistic epidemic, a well-known birth-and-death chain used to model the spread of an epidemic within a population of a given size $N$. We study the behaviour of the process as the population size $N$ tends to infinity. Our results cover the entire subcritical regime, including the "barely subcritical" regime, where the recovery rate exceeds the infection rate by an amount that tends to 0 as $N \to \infty$ but more slowly than $N^{-1/2}$. We derive precise asymptotics for the distribution of the extinction time and the total number of cases throughout the subcritical regime, give a detailed description of the course of the epidemic, and compare to numerical results for a range of parameter values. We hypothesise that features of the course of the epidemic will be seen in a wide class of other epidemic models, and we use real data to provide some tentative and preliminary support for this theory.Comment: Revised; 34 pages; 6 figure

An Optimized Chloroplast DNA Extraction Protocol for Grasses (Poaceae) Proves Suitable for Whole Plastid Genome Sequencing and SNP Detection

peer-reviewedBackground Obtaining chloroplast genome sequences is important to increase the knowledge about the fundamental biology of plastids, to understand evolutionary and ecological processes in the evolution of plants, to develop biotechnological applications (e.g. plastid engineering) and to improve the efficiency of breeding schemes. Extraction of pure chloroplast DNA is required for efficient sequencing of chloroplast genomes. Unfortunately, most protocols for extracting chloroplast DNA were developed for eudicots and do not produce sufficiently pure yields for a shotgun sequencing approach of whole plastid genomes from the monocot grasses. Methodology/Principal Findings We have developed a simple and inexpensive method to obtain chloroplast DNA from grass species by modifying and extending protocols optimized for the use in eudicots. Many protocols for extracting chloroplast DNA require an ultracentrifugation step to efficiently separate chloroplast DNA from nuclear DNA. The developed method uses two more centrifugation steps than previously reported protocols and does not require an ultracentrifuge. Conclusions/Significance The described method delivered chloroplast DNA of very high quality from two grass species belonging to highly different taxonomic subfamilies within the grass family (Lolium perenne, Pooideae; Miscanthus×giganteus, Panicoideae). The DNA from Lolium perenne was used for whole chloroplast genome sequencing and detection of SNPs. The sequence is publicly available on EMBL/GenBank

How big is an outbreak likely to be? Methods for epidemic final-size calculation

Epidemic models have become a routinely used tool to inform policy on infectious disease. A particular interest at the moment is the use of computationally intensive inference to parametrize these models. In this context, numerical efficiency is critically important. We consider methods for evaluating the probability mass function of the total number of infections over the course of a stochastic epidemic, with a focus on homogeneous finite populations, but also considering heterogeneous and large populations. Relevant methods are reviewed critically, with existing and novel extensions also presented. We provide code in Matlab and a systematic comparison of numerical efficiency.Thomas House, Joshua V. Ross and David Sir

Phylogenomics Reshuffles the Eukaryotic Supergroups

Background. Resolving the phylogenetic relationships between eukaryotes is an ongoing challenge of evolutionary biology. In recent years, the accumulation of molecular data led to a new evolutionary understanding, in which all eukaryotic diversity has been classified into five or six supergroups. Yet, the composition of these large assemblages and their relationships remain controversial. Methodology/Principle Findings. Here, we report the sequencing of expressed sequence tags (ESTs) for two species belonging to the supergroup Rhizaria and present the analysis of a unique dataset combining 29908 amino acid positions and an extensive taxa sampling made of 49 mainly unicellular species representative of all supergroups. Our results show a very robust relationship between Rhizaria and two main clades of the supergroup chromalveolates: stramenopiles and alveolates. We confirm the existence of consistent affinities between assemblages that were thought to belong to different supergroups of eukaryotes, thus not sharing a close evolutionary history. Conclusions. This well supported phylogeny has important consequences for our understanding of the evolutionary history of eukaryotes. In particular, it questions a single red algal origin of the chlorophyll-c containing plastids among the chromalveolates. We propose the abbreviated name ‘SAR’ (Stramenopiles+Alveolates+Rhizaria) to accommodate this new super assemblage of eukaryotes, which comprises the largest diversity of unicellular eukaryotes

How to Minimize the Attack Rate during Multiple Influenza Outbreaks in a Heterogeneous Population

<div><h3>Background</h3><p>If repeated interventions against multiple outbreaks are not feasible, there is an optimal level of control during the first outbreak. Any control measures above that optimal level will lead to an outcome that may be as sub-optimal as that achieved by an intervention that is too weak. We studied this scenario in more detail.</p> <h3>Method</h3><p>An age-stratified ordinary-differential-equation model was constructed to study infectious disease outbreaks and control in a population made up of two groups, adults and children. The model was parameterized using influenza as an example. This model was used to simulate two consecutive outbreaks of the same infectious disease, with an intervention applied only during the first outbreak, and to study how cumulative attack rates were influenced by population composition, strength of inter-group transmission, and different ways of triggering and implementing the interventions. We assumed that recovered individuals are fully immune and the intervention does not confer immunity.</p> <h3>Results/Conclusion</h3><p>The optimal intervention depended on coupling between the two population sub-groups, the length, strength and timing of the intervention, and the population composition. Population heterogeneity affected intervention strategies only for very low cross-transmission between groups. At more realistic values, coupling between the groups led to synchronization of outbreaks and therefore intervention strategies that were optimal in reducing the attack rates for each subgroup and the population overall coincided. For a sustained intervention of low efficacy, early intervention was found to be best, while at high efficacies, a delayed start was better. For short interventions, a delayed start was always advantageous, independent of the intervention efficacy. For most scenarios, starting the intervention after a certain cumulative proportion of children were infected seemed more robust in achieving close to optimal outcomes compared to a strategy that used a specified duration after an outbreak’s beginning as the trigger.</p> </div

Modelers' Perception of Mathematical Modeling in Epidemiology: A Web-Based Survey

International audienceBackground: Mathematical modeling in epidemiology (MME) is being used increasingly. However, there are many uncertainties in terms of definitions, uses and quality features of MME. Methodology/Principal Findings: To delineate the current status of these models, a 10-item questionnaire on MME was devised. Proposed via an anonymous internet-based survey, the questionnaire was completed by 189 scientists who had published in the domain of MME. A small minority (18%) of respondents claimed to have in mind a concise definition of MME. Some techniques were identified by the researchers as characterizing MME (e.g. Markov models), while others–at the same level of sophistication in terms of mathematics–were not (e.g. Cox regression). The researchers' opinions were also contrasted about the potential applications of MME, perceived as higly relevant for providing insight into complex mechanisms and less relevant for identifying causal factors. The quality criteria were those of good science and were not related to the size and the nature of the public health problems addressed. Conclusions/Significance: This study shows that perceptions on the nature, uses and quality criteria of MME are contrasted, even among the very community of published authors in this domain. Nevertheless, MME is an emerging discipline in epidemiology and this study underlines that it is associated with specific areas of application and methods. The development of this discipline is likely to deserve a framework providing recommendations and guidance at various steps of the studies, from design to report

Emergence and maintenance of actionable genetic drivers at medulloblastoma relapse

BACKGROUND: 90% of tumors) and established genetic drivers (e.g. SHH/WNT/P53 mutations; 60% of rMB events) were maintained from diagnosis. Critically, acquired and maintained rMB events converged on targetable pathways which were significantly enriched at relapse (e.g. DNA damage-signaling) and specific events (e.g. 3p loss) predicted survival post-relapse. CONCLUSIONS: rMB is defined by the emergence of novel events and pathways, in concert with selective maintenance of established genetic drivers. Together, these define the actionable genetic landscape of rMB and provide a basis for improved clinical management and development of stratified therapeutics, across disease-course

Molecular Phylogeny and Evolution of Parabasalia with Improved Taxon Sampling and New Protein Markers of Actin and Elongation Factor-1α

BACKGROUND: Inferring the evolutionary history of phylogenetically isolated, deep-branching groups of taxa-in particular determining the root-is often extraordinarily difficult because their close relatives are unavailable as suitable outgroups. One of these taxonomic groups is the phylum Parabasalia, which comprises morphologically diverse species of flagellated protists of ecological, medical, and evolutionary significance. Indeed, previous molecular phylogenetic analyses of members of this phylum have yielded conflicting and possibly erroneous inferences. Furthermore, many species of Parabasalia are symbionts in the gut of termites and cockroaches or parasites and therefore formidably difficult to cultivate, rendering available data insufficient. Increasing the numbers of examined taxa and informative characters (e.g., genes) is likely to produce more reliable inferences. PRINCIPAL FINDINGS: Actin and elongation factor-1α genes were identified newly from 22 species of termite-gut symbionts through careful manipulations and seven cultured species, which covered major lineages of Parabasalia. Their protein sequences were concatenated and analyzed with sequences of previously and newly identified glyceraldehyde-3-phosphate dehydrogenase and the small-subunit rRNA gene. This concatenated dataset provided more robust phylogenetic relationships among major groups of Parabasalia and a more plausible new root position than those previously reported. CONCLUSIONS/SIGNIFICANCE: We conclude that increasing the number of sampled taxa as well as the addition of new sequences greatly improves the accuracy and robustness of the phylogenetic inference. A morphologically simple cell is likely the ancient form in Parabasalia as opposed to a cell with elaborate flagellar and cytoskeletal structures, which was defined as most basal in previous inferences. Nevertheless, the evolution of Parabasalia is complex owing to several independent multiplication and simplification events in these structures. Therefore, systematics based solely on morphology does not reflect the evolutionary history of parabasalids

The Anticoagulation of Calf Thrombosis (ACT) project: study protocol for a randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>Half of all lower limb deep vein thrombi (DVT) in symptomatic ambulatory patients are located in the distal (calf) veins. While proximal disease warrants therapeutic anticoagulation to reduce the associated risks, distal DVT often goes untreated. However, a proportion of untreated distal disease will undoubtedly propagate or embolize. Concern also exists that untreated disease could lead to long-term post thrombotic changes. Currently, it is not possible to predict which distal thrombi will develop such complications. Whether these potential risks outweigh those associated with unrestricted anticoagulation remains unclear. The Anticoagulation of Calf Thrombosis (ACT) trial aims to compare therapeutic anticoagulation against conservative management for patients with acute symptomatic distal deep vein thrombosis.</p> <p>Methods</p> <p>ACT is a pragmatic, open-label, randomized controlled trial. Adult patients diagnosed with acute distal DVT will be allocated to either therapeutic anticoagulation or conservative management. All patients will undergo 3 months of clinical and assessor blinded sonographic follow-up, followed by 2-year final review. The project will commence initially as an external pilot study, recruiting over a 16-month period at a single center to assess feasibility measures and clinical event rates. Primary outcome measures will assess feasibility endpoints. Secondary clinical outcomes will be collected to gather accurate data for the design of a definitive clinical trial and will include: (1) a composite endpoint combining thrombus propagation to the popliteal vein or above, development of symptomatic pulmonary embolism or sudden death attributable to venous thromboembolic disease; (2) the incidence of major and minor bleeding episodes; (3) the incidence of post-thrombotic leg syndrome at 2 years using a validated screening tool; and (4) the incidence of venous thromboembolism (VTE) recurrence at 2 years.</p> <p>Discussion</p> <p>The ACT trial will explore the feasibility of comparing therapeutic anticoagulation to conservative management in acute distal DVT, within a modern cohort. We also aim to provide contemporary data on clot propagation, bleeding rates and long-term outcomes within both groups. These results will inform the conduct of a definitive study if feasibility is established.</p> <p>Trial registration</p> <p>Current Controlled Trials <a href="http://www.controlled-trials.com/ISRCTN75175695">ISRCTN75175695</a></p

A Detailed History of Intron-rich Eukaryotic Ancestors Inferred from a Global Survey of 100 Complete Genomes

Protein-coding genes in eukaryotes are interrupted by introns, but intron densities widely differ between eukaryotic lineages. Vertebrates, some invertebrates and green plants have intron-rich genes, with 6–7 introns per kilobase of coding sequence, whereas most of the other eukaryotes have intron-poor genes. We reconstructed the history of intron gain and loss using a probabilistic Markov model (Markov Chain Monte Carlo, MCMC) on 245 orthologous genes from 99 genomes representing the three of the five supergroups of eukaryotes for which multiple genome sequences are available. Intron-rich ancestors are confidently reconstructed for each major group, with 53 to 74% of the human intron density inferred with 95% confidence for the Last Eukaryotic Common Ancestor (LECA). The results of the MCMC reconstruction are compared with the reconstructions obtained using Maximum Likelihood (ML) and Dollo parsimony methods. An excellent agreement between the MCMC and ML inferences is demonstrated whereas Dollo parsimony introduces a noticeable bias in the estimations, typically yielding lower ancestral intron densities than MCMC and ML. Evolution of eukaryotic genes was dominated by intron loss, with substantial gain only at the bases of several major branches including plants and animals. The highest intron density, 120 to 130% of the human value, is inferred for the last common ancestor of animals. The reconstruction shows that the entire line of descent from LECA to mammals was intron-rich, a state conducive to the evolution of alternative splicing