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Recent years have seen an explosion in new kinds of data on infectious diseases, including data on social contacts, whole genome sequences of pathogens, biomarkers for susceptibility to infection, serological panel data, and surveillance data. The Handbook of Infectious Disease Data Analysis provides an overview of many key statistical methods that have been developed in response to such new data streams and the associated ability to address key scientific and epidemiological questions. A unique feature of the Handbook is the wide range of topics covered. Key features Contributors include many leading researchers in the field Divided into four main sections: Basic concepts, Analysis of Outbreak Data, Analysis of Seroprevalence Data, Analysis of Surveillance Data Numerous case studies and examples throughout Provides both introductory material and key reference material 　 　 　 　 　 I Introduction 1. Introduction Leonhard Held, Niel Hens, Philip O’Neill, Jacco Wallinga II Basic Concepts 2. Population dynamics of pathogens Ottar Bjornstad 3. Infectious disease data from surveillance, outbreak investigation and epidemiological studies Susan Hahné, Richard Pebody 4. Key concepts in infectious disease epidemiology Nick Jewell 5. Key parameters in infectious disease epidemiology Laura White 6. Contact patterns for contagious diseases Jacco Wallinga, Jan van de Kassteele, Niel Hens 7. Basic stochastic transmission models and their inference Tom Britton 8. Analysis of vaccine studies and causal inference Betz Halloran III Analysis of Outbreak Data 9. Markov chain Monte Carlo methods for outbreak data Philip O’Neill, Theodore Kypraios 10. Approximate Bayesian Computation methods for epidemic models Peter Neal 11. Iterated filtering methods for Markov process epidemic models Theresa Stocks 12. Pairwise survival analysis of infectious disease transmission data Eben Kenah 13. Methods for outbreaks using genomic data Don Klinkenberg, Caroline Colijn, Xavier Didelot IV Analysis of Seroprevalence Data 14. Persistence of passive immunity, natural immunity (and vaccination) Amy Winter, Jess Metcalf 15. Inferring the time of infection from serological data Maciej Boni, Kåre Mølbak, Karen Angeliki Krogfelt 16. The use of seroprevalence data to estimate cumulative incidence of infection Ben Cowling, Jessica Wong 17. The analysis of serological data with transmission models Marc Baguelin 18. The analysis of multivariate serological data Steven Abrams 19. Mixture modelling Emanuele Del Fava, Ziv Shkedy V Analysis of Surveillance Data 20. Modeling infectious diseases distributions: applications of point process methods Peter J Diggle 21. Prospective detection of outbreaks Benjamin Allevius, Michael Höhle 22. Underreporting and reporting delays Angela Noufaily 23. Spatio-temporal analysis of surveillance data Jon Wakefield, Tracy Q Dong, Vladimir N Minin 24. Analysing multiple epidemic data sources Daniela De Angelis, Anne Presanis 25. Forecasting based on surveillance data Leonhard Held, Sebastian Meyer 26. Spatial mapping of infectious disease risk Ewan Cameron \"One of the editors of the book, Jacco Wallinga, is heading the group at the Dutch Institute of Public Health and the Environment that does all of the statistical analyses to feed their director with information. The latter has had a strong influence on the policy our government chose . . . The book is well produced . . . \" ~Paul Eilers, ISCB News Leonhard Held is Professor of Biostatistics at the University of Zurich. Niel Hens is Professor of Biostatistics at Hasselt University and the University of Antwerp. Philip O’Neill is Professor of Applied Probability at the University of Nottingham. Jacco Wallinga is Professor of Mathematical Modelling of Infectious Diseases at the Leiden University Medical Center.

1. Introduced species disrupt native communities and biodiversity worldwide. Parasitic infections (and at times, their absence) are thought to be a key component in the success and impact of biological invasions by plants and animals. They can facilitate or limit invasions, and positively or negatively impact native species. 2. Parasites have not only direct effects on their hosts, but also indirect effects on the species with which their hosts interact. Indirect effects include density-mediated effects (resulting from parasite-induced reduction in host reproduction and survival) as well as trait-mediated indirect effects (resulting from parasite-induced changes in host phenotype, behaviour or life history). These effects are not mutually exclusive but often interact. 3. The importance of these indirect interactions for invasion success, and the extent to which these effects ramify throughout communities and influence ecosystems undergoing biological invasion provide the focus of our review. Examples from the animal and plant literature illustrate the importance of parasites in mediating both competitive and consumer—resource interactions between native and invasive species. 4. Parasites are involved in indirect interactions at all trophic levels. Furthermore, the indirect effects of parasitic infection are important at a range of biological scales from within a host to the whole ecosystem in determining invasion success and impact. 5. To understand the importance of parasitic infection in invasion success and in the outcomes for invaded communities requires an interdisciplinary approach by ecologists and parasitologists, across animal and plant systems. Future research should develop a framework integrating community ecology, evolution and immunology to better understand and manage the spread of invasive species and their diseases.

Correctly understanding and using medical statistics is a key skill for all medical students and health professionals. In an informal and friendly style, Medical Statistics from Scratch provides a practical foundation for everyone whose first interest is probably not medical statistics. Keeping the level of mathematics to a minimum, it clearly illustrates statistical concepts and practice with numerous real-world examples and cases drawn from current medical literature. Medical Statistics from Scratch is an ideal learning partner for all medical students and health professionals needing an accessible introduction, or a friendly refresher, to the fundamentals of medical statistics.

Wearable physical activity monitors are growing in popularity and provide the opportunity for large numbers of the public to self-monitor physical activity behaviours. The latest generation of these devices feature multiple sensors, ostensibly similar or even superior to advanced research instruments. However, little is known about the accuracy of their energy expenditure estimates. Here, we assessed their performance against criterion measurements in both controlled laboratory conditions (simulated activities of daily living and structured exercise) and over a 24 hour period in free-living conditions. Thirty men (n = 15) and women (n = 15) wore three multi-sensor consumer monitors (Microsoft Band, Apple Watch and Fitbit Charge HR), an accelerometry-only device as a comparison (Jawbone UP24) and validated research-grade multi-sensor devices (BodyMedia Core and individually calibrated Actiheart™). During discrete laboratory activities when compared against indirect calorimetry, the Apple Watch performed similarly to criterion measures. The Fitbit Charge HR was less consistent at measurement of discrete activities, but produced similar free-living estimates to the Apple Watch. Both these devices underestimated free-living energy expenditure (-394 kcal/d and -405 kcal/d, respectively; P<0.01). The multi-sensor Microsoft Band and accelerometry-only Jawbone UP24 devices underestimated most laboratory activities and substantially underestimated free-living expenditure (-1128 kcal/d and -998 kcal/d, respectively; P<0.01). None of the consumer devices were deemed equivalent to the reference method for daily energy expenditure. For all devices, there was a tendency for negative bias with greater daily energy expenditure. No consumer monitors performed as well as the research-grade devices although in some (but not all) cases, estimates were close to criterion measurements. Thus, whilst industry-led innovation has improved the accuracy of consumer monitors, these devices are not yet equivalent to the best research-grade devices or indeed equivalent to each other. We propose independent quality standards and/or accuracy ratings for consumer devices are required.

1. Classic theory holds that the main interaction within the herbivore guild is competition, based on research focused on co-occurring, similarly sized species that reduce the quantity of shared plant resources. However, plant quality may also be crucial in mediating herbivore interspecific interactions. This is especially true when competition occurs between distantly related herbivore species, given that small terrestrial herbivores (e.g., insect herbivores) appear to be more sensitive to alterations of plant quality than plant quantity. 2. In this study, we first tested in the field whether large vertebrate herbivores (cattle Bos taurus) exerted a negative effect on smaller insect herbivores (grasshopper Euchorthippus unicolor) through their overlapping foraging preferences for a dominant grass Leymus chinensis. We measured changes in grass quantity, grass quality, and microclimatic conditions in response to vertebrate grazing and conducted additional manipulative studies in the field and the laboratory to identify potential mechanisms underlying the interaction. 3. Our results showed that grazing by large herbivores caused a significant decline in grasshopper population density and individual performance (survival, size, and weight of both female and male E. unicolor), despite a 38% increase in grass nitrogen (N) content in grazed plots. Experiments manipulating N levels of L. chinensis in the field and the laboratory confirmed that enriching plant N had a negative effect on grasshopper individual performance and population size. Therefore, enhanced quality (N content) of plant resources appears to be an important driver in mediating the negative effect of vertebrate grazing on grasshoppers.a 4. Synthesis. We document that phylogenetic relatedness and trait similarity can be poor predictors of interaction strength in some cases, since distantly related herbivores of disparate size can interact indirectly via changes in plant quality. Counter-intuitively, the observed negative effect of cattle on grasshoppers was mediated, at least in part, by an increase in plant quality in cattle grazed areas. The implication is that light to moderate grazing, a common management strategy, may contribute to suppression of grasshoppers in the Eurasian steppe grassland system by altering plant nutrient supplies.

Mediation analysis is widely used to test and inform theory and debate about the mechanism(s) by which causal effects operate, quantitatively operationalized as an indirect effect in a mediation model. Most effects operate through multiple mechanisms simultaneously, and a mediation model is likely to be more realistic when it is specified to capture multiple mechanisms at the same time with the inclusion of more than one mediator in the model. This also allows an investigator to compare indirect effects to each other. After an overview of the mechanics of mediation analysis, we advocate formally comparing indirect effects in models that include more than one mediator, focusing on the important distinction between questions and claims about value (i.e., are two indirect effects the same number?) versus magnitude (i.e., are two indirect effects equidistant from zero or the same in strength?). After discussing the shortcomings of the conventional method for comparing two indirect effects in a multiple mediator model—which only answers a question about magnitude in some circumstances—we introduce several methods that, unlike the conventional approach, always answer questions about difference in magnitude. We illustrate the use of these methods and provide code that implements them in popular software. We end by summarizing simulation findings and recommending which method(s) to prefer when comparing like- and opposite-signed indirect effects.

Indirect species interactions are ubiquitous in nature, often outnumbering direct species interactions. Yet despite evidence that indirect interactions have strong ecological effects, relatively little is known about whether they can shape adaptive evolution by altering the strength and/or direction of natural selection. We tested whether indirect interactions affect the strength and direction of pollinator-mediated selection on floral traits of the bumble-bee pollinated wildflower Lobelia siphilitica. We estimated the indirect effects of two pollinator predators with contrasting hunting modes: dragonflies (Aeshnidae and Corduliidae) and ambush bugs (Phymata americana, Reduviidae). Because dragonflies are active pursuit predators, we hypothesized that they would strengthen pollinator-mediated selection by weakening plant–pollinator interactions (i.e., a density-mediated indirect effect). In contrast, because ambush bugs are sit-and-wait predators, we hypothesized that they would weaken or reverse the direction of pollinator-mediated selection by altering pollinator foraging behavior (i.e., a trait-mediated indirect effect). Specifically, if ambush bugs hunt from plants with traits that attract pollinators (i.e., prey), then pollinators will spend less time visiting those plants, weakening or reversing the direction of selection on attractive floral traits. We did not find evidence that high dragonfly abundance strengthened selection on floral traits via a density-mediated indirect effect: neither pollen limitation (a proxy for the strength of plant–pollinator interactions) nor directional selection on floral traits of L. siphilitica differed significantly between high- and low-dragonfly abundance treatments. In contrast, we did find evidence that ambush bug presence affected selection on floral traits via a trait-mediated indirect effect: ambush bugs hunted from L. siphilitica plants with larger daily floral displays, reversing the direction of pollinator-mediated selection on daily display size. These results suggest that indirect species interactions have the potential to shape adaptive evolution by altering natural selection.

Having the ability to work with complex models can be highly beneficial. However, complex models often have intractable likelihoods, so methods that involve evaluation of the likelihood function are infeasible. In these situations, the benefits of working with likelihood-free methods become apparent. Likelihood-free methods, such as parametric Bayesian indirect likelihood that uses the likelihood of an alternative parametric auxiliary model, have been explored throughout the literature as a viable alternative when the model of interest is complex. One of these methods is called the synthetic likelihood (SL), which uses a multivariate normal approximation of the distribution of a set of summary statistics. This article explores the accuracy and computational efficiency of the Bayesian version of the synthetic likelihood (BSL) approach in comparison to a competitor known as approximate Bayesian computation (ABC) and its sensitivity to its tuning parameters and assumptions. We relate BSL to pseudo-marginal methods and propose to use an alternative SL that uses an unbiased estimator of the SL, when the summary statistics have a multivariate normal distribution. Several applications of varying complexity are considered to illustrate the findings of this article.

ObjectivesThis study compared the reliability of two metabolic cart systems, Vyntus CPX and Vmax Encore 29N, to measure whole-body energy metabolism by indirect calorimetry (IC) in individuals with type 2 diabetes (T2D).DesignRandomised, prospective, crossover study.SettingSingle-centre study conducted in the clinical research centre of the German Diabetes Study (GDS).ParticipantsFive participants (3 men, 2 women, mean age 49±6 years, body mass index (BMI) 32.62±4.2 kg/m²) with T2D completed the study protocol. Eligibility requires existing participation in GDS and availability for four consecutive study days.InterventionsParticipants underwent four IC measurements per day on four consecutive days, totalling 16 measurements per device. On each study day, two measurements with both devices, Vyntus CPX and Vmax Encore 29N, were performed in randomised order. Postcalorimetric gas calibration with normalisation was applied after each measurement.Primary outcome measuresReliability of respiratory quotient (RQ) and resting energy expenditure (REE), as assessed from the coefficient of variation (CV) and 95% CIs.ResultsDevice comparison showed minor differences in CV (95% CI) for carbon dioxide production (VCO₂) (3.5% vs 5.3%; 95% CI −8.2% to 8.0%), oxygen consumption (VO₂) (3.4% vs 5.7%; 95% CI −9.3% to 8.2%), RQ (3.6% vs 2.3%; 95% CI −3.5% to 3.7%) and REE (3.1% vs 5.6%; 95% CI −8.4% to 7.8%). Postcalorimetric calibration did not consistently affect RQ or REE. ConclusionsVyntus CPX provides reliable IC measurements comparable to Vmax Encore 29N and may serve as a suitable replacement in clinical settings.Trial registration numberClinicalTrials.gov identifier: NCT01055093.