Bio::NEXUS: a Perl API for the NEXUS format for comparative biological data

<p>Abstract</p> <p>Background</p> <p>Evolutionary analysis provides a formal framework for comparative analysis of genomic and other data. In evolutionary analysis, observed data are treated as the terminal states of characters that have evolved (via transitions between states) along the branches of a tree. The NEXUS standard of Maddison, et al. (1997; <it>Syst. Biol</it>. 46: 590–621) provides a portable, expressive and flexible text format for representing character-state data and trees. However, due to its complexity, NEXUS is not well supported by software and is not easily accessible to bioinformatics users and developers.</p> <p>Results</p> <p>Bio::NEXUS is an application programming interface (API) implemented in Perl, available from CPAN and SourceForge. The 22 Bio::NEXUS modules define 351 methods in 4229 lines of code, with 2706 lines of POD (Plain Old Documentation). Bio::NEXUS provides an object-oriented interface to reading, writing and manipulating the contents of NEXUS files. It closely follows the extensive explanation of the NEXUS format provided by Maddison et al., supplemented with a few extensions such as support for the NHX (New Hampshire Extended) tree format.</p> <p>Conclusion</p> <p>In spite of some limitations owing to the complexity of NEXUS files and the lack of a formal grammar, NEXUS will continue to be useful for years to come. Bio::NEXUS provides a user-friendly API for NEXUS supplemented with an extensive set of methods for manipulations such as re-rooting trees and selecting subsets of data. Bio::NEXUS can be used as glue code for connecting existing software that uses NEXUS, or as a framework for new applications.</p

Epidemic Wave Dynamics Attributable to Urban Community Structure: A Theoretical Characterization of Disease Transmission in a Large Network.

BACKGROUND: Multiple waves of transmission during infectious disease epidemics represent a major public health challenge, but the ecological and behavioral drivers of epidemic resurgence are poorly understood. In theory, community structure—aggregation into highly intraconnected and loosely interconnected social groups—within human populations may lead to punctuated outbreaks as diseases progress from one community to the next. However, this explanation has been largely overlooked in favor of temporal shifts in environmental conditions and human behavior and because of the difficulties associated with estimating large-scale contact patterns. OBJECTIVE: The aim was to characterize naturally arising patterns of human contact that are capable of producing simulated epidemics with multiple wave structures. METHODS: We used an extensive dataset of proximal physical contacts between users of a public Wi-Fi Internet system to evaluate the epidemiological implications of an empirical urban contact network. We characterized the modularity (community structure) of the network and then estimated epidemic dynamics under a percolation-based model of infectious disease spread on the network. We classified simulated epidemics as multiwave using a novel metric and we identified network structures that were critical to the network's ability to produce multiwave epidemics. RESULTS: We identified robust community structure in a large, empirical urban contact network from which multiwave epidemics may emerge naturally. This pattern was fueled by a special kind of insularity in which locally popular individuals were not the ones forging contacts with more distant social groups. CONCLUSIONS: Our results suggest that ordinary contact patterns can produce multiwave epidemics at the scale of a single urban area without the temporal shifts that are usually assumed to be responsible. Understanding the role of community structure in epidemic dynamics allows officials to anticipate epidemic resurgence without having to forecast future changes in hosts, pathogens, or the environment

Evaluating the probability of silent circulation of polio in small populations using the silent circulation statistic.

As polio-endemic countries move towards elimination, infrequent first infections and incomplete surveillance make it difficult to determine when the virus has been eliminated from the population. Eichner and Dietz [American Journal of Epidemiology, 143, 8 (1996)] proposed a model to estimate the probability of silent polio circulation depending upon when the last paralytic case was detected. Using the same kind of stochastic model they did, we additionally model waning polio immunity in the context of isolated, small, and unvaccinated populations. We compare using the Eichner and Dietz assumption of an initial case at the start of the simulation to a more accurate determination that observes the first case. The former estimates a higher probability of silent circulation in small populations, but this effect diminishes with increasing model population. We also show that stopping the simulation after a specific time estimates a lower probability of silent circulation than when all replicates are run to extinction, though this has limited impact on small populations. Our extensions to the Eichner and Dietz work improve the basis for decisions concerning the probability of silent circulation. Further model realism will be needed for accurate silent circulation risk assessment

Serostatus testing and dengue vaccine cost-benefit thresholds.

The World Health Organization (WHO) currently recommends pre-screening for past infection prior to administration of the only licensed dengue vaccine, CYD-TDV. Using a threshold modelling analysis, we identify settings where this guidance prohibits positive net-benefits, and are thus unfavourable. Generally, however, our model shows test-then-vaccinate strategies can improve CYD-TDV economic viability: effective testing reduces unnecessary vaccination costs while increasing health benefits. With sufficiently low testing cost, those trends outweigh additional screening costs, expanding the range of settings with positive net-benefits. This work highlights two aspects for further analysis of test-then-vaccinate strategies. We found that starting routine testing at younger ages could increase benefits; if real tests are shown to sufficiently address safety concerns, the manufacturer, regulators and WHO should revisit guidance restricting use to 9-years-and-older recipients. We also found that repeat testing could improve return-on-investment (ROI), despite increasing intervention costs. Thus, more detailed analyses should address questions on repeat testing and testing periodicity, in addition to real test sensitivity and specificity. Our results follow from a mathematical model relating ROI to epidemiology, intervention strategy, and costs for testing, vaccination and dengue infections. We applied this model to a range of strategies, costs and epidemiological settings pertinent to CYD-TDV. However, general trends may not apply locally, so we provide our model and analyses as an R package available via CRAN, denvax. To apply to their setting, decision-makers need only local estimates of age-specific seroprevalence and costs for secondary infections

Potential test-negative design study bias in outbreak settings: application to Ebola vaccination in Democratic Republic of Congo.

BACKGROUND: Infectious disease outbreaks present unique challenges to study designs for vaccine evaluation. Test-negative design (TND) studies have previously been used to estimate vaccine effectiveness and have been proposed for Ebola virus disease (EVD) vaccines. However, there are key differences in how cases and controls are recruited during outbreaks and pandemics of novel pathogens, whcih have implications for the reliability of effectiveness estimates using this design. METHODS: We use a modelling approach to quantify TND bias for a prophylactic vaccine under varying study and epidemiological scenarios. Our model accounts for heterogeneity in vaccine distribution and for two potential routes to testing and recruitment into the study: self-reporting and contact-tracing. We derive conventional and hybrid TND estimators for this model and suggest ways to translate public health response data into the parameters of the model. RESULTS: Using a conventional TND study, our model finds biases in vaccine effectiveness estimates. Bias arises due to differential recruitment from self-reporting and contact-tracing, and due to clustering of vaccination. We estimate the degree of bias when recruitment route is not available, and propose a study design to eliminate the bias if recruitment route is recorded. CONCLUSIONS: Hybrid TND studies can resolve the design bias with conventional TND studies applied to outbreak and pandemic response testing data, if those efforts collect individuals' routes to testing. Without route to testing, other epidemiological data will be required to estimate the magnitude of potential bias in a conventional TND study. Since these studies may need to be conducted retrospectively, public health responses should obtain these data, and generic protocols for outbreak and pandemic response studies should emphasize the need to record routes to testing

Spatio-temporal coherence of dengue, chikungunya and Zika outbreaks in Merida, Mexico

Longitudinal Dengue (DENV) data generated patterns indicative of the resulting introduction and transmission patterns of chikungunya (CHIKV) and Zika virus (ZIKV), leading to important insights for the surveillance and targeted control of emerging Aedes-borne viruses. About 42% of the 40,028 DENV cases reported during 2008–2015 clustered in 27% of Merida (Mexico), and these clustering areas were where the first CHIKV and ZIKV cases were reported in 2015 and 2016. Findings from this article open a window to the consideration of spatially-targeted approaches for delivery of vector control interventions and surveillance.National Science FoundationOffice of Infectious Disease, Bureau for Global Health, U.S. Agency for International DevelopmentUS Centers for Disease Control and Preventio

The Supertree Tool Kit

<p>Abstract</p> <p>Background</p> <p>Large phylogenies are crucial for many areas of biological research. One method of creating such large phylogenies is the supertree method, but creating supertrees containing thousands of taxa, and hence providing a comprehensive phylogeny, requires hundred or even thousands of source input trees. Managing and processing these data in a systematic and error-free manner is challenging and will become even more so as supertrees contain ever increasing numbers of taxa. Protocols for processing input source phylogenies have been proposed to ensure data quality, but no robust software implementations of these protocols as yet exist.</p> <p>Findings</p> <p>The aim of the Supertree Tool Kit (STK) is to aid in the collection, storage and processing of input source trees for use in supertree analysis. It is therefore invaluable when creating supertrees containing thousands of taxa and hundreds of source trees. The STK is a Perl module with executable scripts to carry out various steps in the processing protocols. In order to aid processing we have added meta-data, via XML, to each tree which contains information such as the bibliographic source information for the tree and how the data were derived, for instance the character data used to carry out the original analysis. These data are essential parts of previously proposed protocols.</p> <p>Conclusions</p> <p>The STK is a bioinformatics tool designed to make it easier to process source phylogenies for inclusion in supertree analysis from hundreds or thousands of input source trees, whilst reducing potential errors and enabling easy sharing of such datasets. It has been successfully used to create the largest known supertree to date containing over 5000 taxa from over 700 source phylogenies.</p

Forecasting the effectiveness of indoor residual spraying for reducing dengue burden.

BACKGROUND: Historically, mosquito control programs successfully helped contain malaria and yellow fever, but recent efforts have been unable to halt the spread of dengue, chikungunya, or Zika, all transmitted by Aedes mosquitoes. Using a dengue transmission model and results from indoor residual spraying (IRS) field experiments, we investigated how IRS-like campaign scenarios could effectively control dengue in an endemic setting. METHODS AND FINDINGS: In our model, we found that high levels of household coverage (75% treated once per year), applied proactively before the typical dengue season could reduce symptomatic infections by 89.7% (median of 1000 simulations; interquartile range [IQR]:[83.0%, 94.8%]) in year one and 78.2% (IQR: [71.2%, 88.0%]) cumulatively over the first five years of an annual program. Lower coverage had correspondingly lower effectiveness, as did reactive campaigns. Though less effective than preventative campaigns, reactive and even post-epidemic interventions retain some effectiveness; these campaigns disrupt inter-seasonal transmission, highlighting an off-season control opportunity. Regardless, none of the campaign scenarios maintain their initial effectiveness beyond two seasons, instead stabilizing at much lower levels of benefit: in year 20, median effectiveness was only 27.3% (IQR: [-21.3%, 56.6%]). Furthermore, simply ceasing an initially successful program exposes a population with lowered herd immunity to the same historical threat, and we observed outbreaks more than four-fold larger than pre-intervention outbreaks. These results do not take into account evolving insecticide resistance, thus long-term effectiveness may be lower if new, efficacious insecticides are not developed. CONCLUSIONS: Using a detailed agent-based dengue transmission model for Yucatán State, Mexico, we predict that high coverage indoor residual spraying (IRS) interventions can largely eliminate transmission for a few years, when applied a few months before the typical seasonal epidemic peak. However, vector control succeeds by preventing infections, which precludes natural immunization. Thus, as a population benefits from mosquito control, it gradually loses naturally acquired herd immunity, and the control effectiveness declines; this occurs across all of our modeled scenarios, and is consistent with other empirical work. Long term control that maintains early effectiveness would require some combination of increasing investment, complementary interventions such as vaccination, and control programs across a broad region to diminish risk of importation

NeXML: Rich, Extensible, and Verifiable Representation of Comparative Data and Metadata

In scientific research, integration and synthesis require a common understanding of where data come from, how much they can be trusted, and what they may be used for. To make such an understanding computer-accessible requires standards for exchanging richly annotated data. The challenges of conveying reusable data are particularly acute in regard to evolutionary comparative analysis, which comprises an ever-expanding list of data types, methods, research aims, and subdisciplines. To facilitate interoperability in evolutionary comparative analysis, we present NeXML, an XML standard (inspired by the current standard, NEXUS) that supports exchange of richly annotated comparative data. NeXML defines syntax for operational taxonomic units, character-state matrices, and phylogenetic trees and networks. Documents can be validated unambiguously. Importantly, any data element can be annotated, to an arbitrary degree of richness, using a system that is both flexible and rigorous. We describe how the use of NeXML by the TreeBASE and Phenoscape projects satisfies user needs that cannot be satisfied with other available file formats. By relying on XML Schema Definition, the design of NeXML facilitates the development and deployment of software for processing, transforming, and querying documents. The adoption of NeXML for practical use is facilitated by the availability of (1) an online manual with code samples and a reference to all defined elements and attributes, (2) programming toolkits in most of the languages used commonly in evolutionary informatics, and (3) input–output support in several widely used software applications. An active, open, community-based development process enables future revision and expansion of NeXML