Disease Surveillance on Complex Social Networks

As infectious disease surveillance systems expand to include digital, crowd-sourced, and social network data, public health agencies are gaining unprecedented access to high-resolution data and have an opportunity to selectively monitor informative individuals. Contact networks, which are the webs of interaction through which diseases spread, determine whether and when individuals become infected, and thus who might serve as early and accurate surveillance sensors. Here, we evaluate three strategies for selecting sensors—sampling the most connected, random, and friends of random individuals—in three complex social networks—a simple scale-free network, an empirical Venezuelan college student network, and an empirical Montreal wireless hotspot usage network. Across five different surveillance goals—early and accurate detection of epidemic emergence and peak, and general situational awareness—we find that the optimal choice of sensors depends on the public health goal, the underlying network and the reproduction number of the disease (R₀). For diseases with a low R₀, the most connected individuals provide the earliest and most accurate information about both the onset and peak of an outbreak. However, identifying network hubs is often impractical, and they can be misleading if monitored for general situational awareness, if the underlying network has significant community structure, or if R₀ is high or unknown. Taking a theoretical approach, we also derive the optimal surveillance system for early outbreak detection but find that real-world identification of such sensors would be nearly impossible. By contrast, the friends-of-random strategy offers a more practical and robust alternative. It can be readily implemented without prior knowledge of the network, and by identifying sensors with higher than average, but not the highest, epidemiological risk, it provides reasonably early and accurate information.     

Effectively Communicating the Uncertainties Surrounding Ebola Virus Transmission

The current Ebola virus outbreak has highlighted the uncertainties surrounding many aspects of Ebola virus virology, including routes of transmission. The scientific community played a leading role during the outbreak—potentially, the largest of its kind—as many of the questions surrounding ebolaviruses have only been interrogated in the laboratory. Scientists provided an invaluable resource for clinicians, public health officials, policy makers, and the lay public in understanding the progress of Ebola virus disease and the continuing outbreak. Not all of the scientific communication, however, was accurate or effective. There were multiple instances of published articles during the height of the outbreak containing potentially misleading scientific language that spurred media overreaction and potentially jeopardized preparedness and policy decisions at critical points. Here, we use articles declaring the potential for airborne transmission of Ebola virus as a case study in the inaccurate reporting of basic science, and we provide recommendations for improving the communication about unknown aspects of disease during public health crises.     

Disagreeing on Whether Agreement Is Persuasive: Perceptions of Expert Group Decisions

While expert groups often make recommendations on a range of non-controversial as well as controversial issues, little is known about how the level of expert consensus—the level of expert agreement—influences perceptions of the recommendations. This research illustrates that for non-controversial issues expert groups that exhibit high levels of agreement are more persuasive than expert groups that exhibit low levels of agreement. This effect is mediated by the perceived entitativity—the perceived cohesiveness or unification of the group—of the expert group. But for controversial issues, this effect is moderated by the perceivers’ implicit assumptions about the group composition. When perceivers are provided no information about a group supporting the Affordable Care Act—a highly controversial piece of U.S. legislation that is divided by political party throughout the country—higher levels of agreement are less persuasive than lower levels of agreement because participants assume there were more democrats and fewer republicans in the group. But when explicitly told that the group was half republicans and half democrats, higher levels of agreement are more persuasive.     

Reconciling competing mechanisms posited to underlie auditory verbal hallucinations

Perception is not the passive registration of incoming sensory data. Rather, it involves some analysis by synthesis, based on past experiences and context. One adaptive consequence of this arrangement is imagination—the ability to richly simulate sensory experiences, interrogate and manipulate those simulations, in service of action and decision making. In this paper, we will discuss one possible cost of this adaptation, namely hallucinations—perceptions without sensory stimulation, which characterize serious mental illnesses like schizophrenia, but which also occur in neurological illnesses, and—crucially for the present piece—are common also in the non-treatment-seeking population. We will draw upon a framework for imagination that distinguishes voluntary from non-voluntary experiences and explore the extent to which the varieties and features of hallucinations map onto this distinction, with a focus on auditory-verbal hallucinations (AVHs)—colloquially, hearing voices. We will propose that sense of agency for the act of imagining is key to meaningfully dissecting different forms and features of AVHs, and we will outline the neural, cognitive and phenomenological sequelae of this sense. We will conclude that a compelling unifying framework for action, perception and belief—predictive processing—can incorporate observations regarding sense of agency, imagination and hallucination.This article is part of the theme issue ‘Offline perception: voluntary and spontaneous perceptual experiences without matching external stimulation’.     

Efficient Synthesis and Anti-Tubercular Activity of a Series of Spirocycles: An Exercise in Open Science

Tuberculosis afflicts an estimated 2 billion people worldwide and causes 1.3 million deaths annually. Chemotherapeutic solutions rely on drugs developed many years ago, with only one new therapeutic having been approved in the last 40 years. Given the rise of drug-resistant strains, there is an urgent need for the development of a more robust drug development pipeline. GlaxoSmithKline recently placed the structures and activities of 177 novel anti-tubercular leads in the public domain, as well as the results of ongoing optimisation of some of the series. Since many of the compounds arose from screening campaigns, their provenance was unclear and synthetic routes were in many cases not reported. Here we present the efficient synthesis of several novel analogues of one family of the GSK compounds—termed “Spiros”—using an oxa-Pictet–Spengler reaction. The new compounds are attractive from a medicinal chemistry standpoint and some were potent against the virulent strain, suggesting this class is worthy of further study. The research was carried out using open source methodology, providing the community with full access to all raw experimental data in real time.     

The evolutionary ecology of early weaning in Kilimanjaro,Tanzania

Public health recommendations promote prolonged breastfeeding of all children; however, parental investment (PI) theory predicts that breastfeeding will be allocated among a mothers'' offspring to maximize her reproductive success. We evaluated PI in terms of risk for weaning before age two among 283 children in Kilimanjaro, Tanzania. Results demonstrate: (i) a Trivers–Willard effect—high socioeconomic status (SES) females and low SES males were more likely to be weaned early; (ii) later-born children were less likely to be weaned early; (iii) higher birthweight children were less likely to be weaned early, and (iv) no effect of cattle (a source of supplementary milk) ownership. These associations were largely independent and remained significant in models controlling for potential confounders; however, the inverse association between early weaning and birth order lost significance in the model containing birthweight. These patterns were observed despite public health recommendations encouraging breastfeeding for at least two years.     

Cell groups reveal structure of stimulus space

An important task of the brain is to represent the outside world. It is unclear how the brain may do this, however, as it can only rely on neural responses and has no independent access to external stimuli in order to “decode” what those responses mean. We investigate what can be learned about a space of stimuli using only the action potentials (spikes) of cells with stereotyped—but unknown—receptive fields. Using hippocampal place cells as a model system, we show that one can (1) extract global features of the environment and (2) construct an accurate representation of space, up to an overall scale factor, that can be used to track the animal's position. Unlike previous approaches to reconstructing position from place cell activity, this information is derived without knowing place fields or any other functions relating neural responses to position. We find that simply knowing which groups of cells fire together reveals a surprising amount of structure in the underlying stimulus space; this may enable the brain to construct its own internal representations.     

Some Limitations of Public Sequence Data for Phylogenetic Inference (in Plants)

The GenBank database contains essentially all of the nucleotide sequence data generated for published molecular systematic studies, but for the majority of taxa these data remain sparse. GenBank has value for phylogenetic methods that leverage data–mining and rapidly improving computational methods, but the limits imposed by the sparse structure of the data are not well understood. Here we present a tree representing 13,093 land plant genera—an estimated 80% of extant plant diversity—to illustrate the potential of public sequence data for broad phylogenetic inference in plants, and we explore the limits to inference imposed by the structure of these data using theoretical foundations from phylogenetic data decisiveness. We find that despite very high levels of missing data (over 96%), the present data retain the potential to inform over 86.3% of all possible phylogenetic relationships. Most of these relationships, however, are informed by small amounts of data—approximately half are informed by fewer than four loci, and more than 99% are informed by fewer than fifteen. We also apply an information theoretic measure of branch support to assess the strength of phylogenetic signal in the data, revealing many poorly supported branches concentrated near the tips of the tree, where data are sparse and the limiting effects of this sparseness are stronger. We argue that limits to phylogenetic inference and signal imposed by low data coverage may pose significant challenges for comprehensive phylogenetic inference at the species level. Computational requirements provide additional limits for large reconstructions, but these may be overcome by methodological advances, whereas insufficient data coverage can only be remedied by additional sampling effort. We conclude that public databases have exceptional value for modern systematics and evolutionary biology, and that a continued emphasis on expanding taxonomic and genomic coverage will play a critical role in developing these resources to their full potential.     

Does the Wage Gap between Private and Public Sectors Encourage Political Corruption?

We present a dynamic network model of corrupt and noncorrupt employees representing two states in the public and private sector. Corrupt employees are more connected to one another and are less willing to change their attitudes regarding corruption than noncorrupt employees. This behavior enables them to prevail and become the majority in the workforce through a first-order phase transition even though they initially represented a minority. In the model, democracy—understood as the principle of majority rule—does not create corruption, but it serves as a mechanism that preserves corruption in the long run. The motivation for our network model is a paradox that exists on the labor market. Although economic theory indicates that higher risk investments should lead to larger rewards, in many developed and developing countries workers in lower-risk public sector jobs are paid more than workers in higher-risk private sector jobs. To determine the long-run sustainability of this economic paradox, we study data from 28 EU countries and find that the public sector wage premium increases with the level of corruption.     

Effect of Various Essential Oils Isolated from Douglas Fir Needles upon Sheep and Deer Rumen Microbial Activity

The effects of essential oils isolated from Douglas fir needles on sheep and deer rumen microbial activity were tested by use of an anaerobic manometric technique. Rumen microorganisms were obtained from a sheep which had been fed mainly on alfalfa hay and dried range grass. One deer used in this study had access to Douglas fir trees the year around, whereas the other deer had no access to Douglas fir. All of the monoterpene hydrocarbons isolated from Douglas fir needles—α-pinene, β-pinene, limonene, myrcene, camphene, Δ³-carene, and terpinolene—promoted only slightly or had no effect on deer rumen microbial activity, whereas all of them promoted activity in sheep rumen microbes, except Δ³-carene and terpinolene, which inhibited activity. Of the oxygenated monoterpenes, all monoterpene alcohols—α-terpineol, terpinen-4-ol, linalool, citronellol, and fenchyl alcohol—strongly inhibited the rumen microbial activity of both sheep and deer. Monoterpene esters (bornyl acetate) produced mild inhibition for both sheep and deer microbes, and citronellyl acetate inhibited rumen microbial activity in sheep, whereas it promoted activity in both deer. Monoterpene aldehyde (citronellal) inhibited the activity of rumen microbes from both sheep and deer having no access to Douglas fir from the Hopland Field Station, whereas they produced no effect upon the deer having access to Douglas fir from the Masonite forest. Rumen microbial activity for sheep and deer was promoted slightly with aliphatic ester (ethyl-n-caproate). There was a marked difference between sheep and deer rumen microbes as affected by addition of the various essential oils. The monoterpene hydrocarbons promoted activity more on sheep rumen microbes than on deer, and the monoterpene alcohols inhibited sheep rumen microbial activity more than that of deer. Furthermore, the deer rumen microbes from Hopland Field Station were affected more than the deer from Masonite forest.     

Tinbergen on mirror neurons

Fifty years ago, Niko Tinbergen defined the scope of behavioural biology with his four problems: causation, ontogeny, survival value and evolution. About 20 years ago, there was another highly significant development in behavioural biology—the discovery of mirror neurons (MNs). Here, I use Tinbergen''s original four problems (rather than the list that appears in textbooks) to highlight the differences between two prominent accounts of MNs, the genetic and associative accounts; to suggest that the latter provides the defeasible ‘best explanation’ for current data on the causation and ontogeny of MNs; and to argue that functional analysis, of the kind that Tinbergen identified somewhat misleadingly with studies of ‘survival value’, should be a high priority for future research. In this kind of functional analysis, system-level theories would assign MNs a small, but potentially important, role in the achievement of action understanding—or another social cognitive function—by a production line of interacting component processes. These theories would be tested by experimental intervention in human and non-human animal samples with carefully documented and controlled developmental histories.     

Integration of biological data by kernels on graph nodes allows prediction of new genes involved in mitotic chromosome condensation

The advent of genome-wide RNA interference (RNAi)–based screens puts us in the position to identify genes for all functions human cells carry out. However, for many functions, assay complexity and cost make genome-scale knockdown experiments impossible. Methods to predict genes required for cell functions are therefore needed to focus RNAi screens from the whole genome on the most likely candidates. Although different bioinformatics tools for gene function prediction exist, they lack experimental validation and are therefore rarely used by experimentalists. To address this, we developed an effective computational gene selection strategy that represents public data about genes as graphs and then analyzes these graphs using kernels on graph nodes to predict functional relationships. To demonstrate its performance, we predicted human genes required for a poorly understood cellular function—mitotic chromosome condensation—and experimentally validated the top 100 candidates with a focused RNAi screen by automated microscopy. Quantitative analysis of the images demonstrated that the candidates were indeed strongly enriched in condensation genes, including the discovery of several new factors. By combining bioinformatics prediction with experimental validation, our study shows that kernels on graph nodes are powerful tools to integrate public biological data and predict genes involved in cellular functions of interest.     

Generalist bird exhibits site‐dependent resource selection

Quantifying resource selection (an organism''s disproportionate use of available resources) is essential to infer habitat requirements of a species, develop management recommendations, predict species responses to changing conditions, and improve our understanding of the processes that underlie ecological patterns. Because study sites, even within the same region, can differ in both the amount and the arrangement of cover types, our objective was to determine whether proximal sites can yield markedly different resource selection results for a generalist bird, northern bobwhite (Colinus virginianus). We used 5 years of telemetry locations and newly developed land cover data at two, geographically distinct but relatively close sites in the south‐central semi‐arid prairies of North America. We fit a series of generalized linear mixed models and used an information‐theoretic model comparison approach to identify and compare resource selection patterns at each site. We determined that the importance of different cover types to northern bobwhite is site‐dependent on relatively similar and nearby sites. Specifically, whether bobwhite selected for shrub cover and whether they strongly avoided trees, depended on the study site in focus. Additionally, the spatial scale of selection was nearly an order of magnitude different between the cover types. Our study demonstrates that—even for one of the most intensively studied species in the world—we may oversimplify resource selection by using a single study site approach. Managing the trade‐offs between practical, generalized conclusions and precise but complex conclusions is one of the central challenges in applied ecology. However, we caution against setting recommendations for broad extents based on information gathered at small extents, even for a generalist species at adjacent sites. Before extrapolating information to areas beyond the data collected, managers should account for local differences in the availability, arrangement, and scaling of resources.     

The Effect of Framing and Normative Messages in Building Support for Climate Policies

Deep cuts in greenhouse gas emissions are required to mitigate climate change. However, there is low willingness amongst the public to prioritise climate policies for reducing emissions. Here we show that the extent to which Australians are prepared to reduce their country''s CO₂ emissions is greater when the costs to future national income are framed as a “foregone-gain”—incomes rise in the future but not by as much as in the absence of emission cuts—rather than as a “loss”—incomes decrease relative to the baseline expected future levels (Studies 1 & 2). The provision of a normative message identifying Australia as one of the world''s largest CO₂ emitters did not increase the amount by which individuals were prepared to reduce emissions (Study 1), whereas a normative message revealing the emission policy preferences of other Australians did (Study 2). The results suggest that framing the costs of reducing emissions as a smaller increase in future income and communicating normative information about others'' emission policy preferences are effective methods for leveraging public support for emission cuts.     

Explaining Disparities in Use of Skilled Birth Attendants in Developing Countries: A Conceptual Framework

Despite World Health Organization recommendations that all women deliver with a skilled birth attendant (SBA), research continues to demonstrate large disparities in use of SBAs by socioeconomic status (SES). Yet few quantitative studies empirically examine the factors underlying these disparities, due in part to the fact that current models do not provide clear pathways—with measurable mediators—for how distal factors like SES may affect maternal health-seeking behaviors like delivering with SBAs. We propose the Disparities in Skilled Birth Attendance (DiSBA) framework for examining the determinants of use of SBAs. We posit that three proximal factors directly affect use of SBAs: perceived need, perceived accessibility of maternal health services, and perceived quality of care. Distal factors like SES affect use of SBAs indirectly through these proximal factors, and the effects can be measured. We test the assumptions of the DiSBA framework using data from the Ghana Maternal Health Survey. The analytic techniques we use include logistic regression with mediation analysis to examine the intervening effects. We find that our proxies for perceived access, perceived need, and perceived quality of care account for approximately 23% of the difference between women with no education and those with primary school education, and about 55% of the difference between women in the lowest wealth quintile and those in the middle wealth quintiles. This study suggests that proximal factors are worthy of increased attention in terms of measurement, data collection, analysis, programmatic efforts, and policy interventions, as these factors are potentially more amenable to change than the distal factors. The effects of proximal factors are also likely context specific, thus sufficient understanding in different contexts is essential to developing appropriate interventions.