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The main goal of this paper is to study the effects of (1) trust in government medical experts and (2) proximity to a recent disease outbreak on vaccine propensity. More specifically, we explore how these variables affect attitudes with regards to measles. Using original survey data, collected in January/February 2017, we obtain three main empirical findings. First, contrary to our expectations, an individual’s proximity to a recent measles outbreak has no independent effect on vaccination attitudes. Second, corroborating previous studies in the field, we find that trust in institutions such as the CDC has a positive effect on our dependent variable. Third, there is a significant interactive relationship between proximity and trust in governmental medical experts. While distance from a previous measles outbreak has no effect on vaccination attitudes for respondents with medium or high levels of trust, the variable exerts a negative effect for subjects with little confidence in government medical experts. In other words: low-trust individuals who live farther away from a recent measles outbreak harbor less favorable views about vaccination for this particular disease than low-trust respondents who live close to an affected area. This implies that citizens who are skeptical of the CDC and similar institutions base their vaccination decision-making to some degree on whether or not a given disease occurs in close vicinity to their community. [ABSTRACT FROM AUTHOR]

Scholarly studies and common accounts of national politics enjoy pointing out the resilience of ideological divides among populations. Building on the image of political cleavages and geographic polarization, the regionalization of politics has become a truism across Northern democracies. Left unquestioned, this geography plays a central role in shaping electoral and referendum campaigns. In Europe and North America, observers identify recurring patterns dividing local populations during national votes. While much research describes those patterns in relation to ethnicity, religious affiliation, historic legacy and party affiliation, current approaches in political research lack the capacity to measure their evolution over time or other vote subsets. This article introduces “Dyadic Agreement Modeling” (DyAM), a transdisciplinary method to assess the evolution of geographic cleavages in vote outcomes by implementing a metric of agreement/disagreement through Network Analysis. Unlike existing approaches, DyAM offers a stable measure for political agreement and disagreement—accounting for chance, statistically robust and remaining structurally independent from the number of entries and missing data. The method opens up to a range of statistical, structural and visual tools specific to Network Analysis and its usage across disciplines. In order to illustrate DyAM, I use more than 680,000 municipal outcomes from Swiss federal popular votes and assess the evolution of political cleavages across local populations since 1981. Results suggest that political congruence between Swiss local populations increased in the last forty years, while regional political factions and linguistic alignments have lost their salience to new divides. I discuss how choices about input parameters and data subsets nuance findings, and consider confounding factors that may influence conclusions over the dynamic equilibrium of national politics and the strengthening effect of globalization on democratic institutions. [ABSTRACT FROM AUTHOR]

The availability alongside growing awareness of medicine has led to increased self-treatment of minor ailments. Self-medication is where one ‘self’ diagnoses and prescribes over the counter medicines for treatment. The self-care movement has important policy implications, perceived to relieve the National Health Service (NHS) burden, increasing patient subsistence and freeing resources for more serious ailments. However, there has been little research exploring how self-medication behaviours vary between population groups due to a lack of available data. The aim of our study is to evaluate how high street retailer loyalty card data can help inform our understanding of how individuals self-medicate in England. Transaction level loyalty card data was acquired from a national high street retailer for England for 2012–2014. We calculated the proportion of loyalty card customers (n ~ 10 million) within Lower Super Output Areas who purchased the following medicines: ‘coughs and colds’, ‘Hayfever’, ‘pain relief’ and ‘sun preps’. Machine learning was used to explore how 50 sociodemographic and health accessibility features were associated towards explaining purchasing of each product group. Random Forests are used as a baseline and Gradient Boosting as our final model. Our results showed that pain relief was the most common medicine purchased. There was little difference in purchasing behaviours by sex other than for sun preps. The gradient boosting models demonstrated that socioeconomic status of areas, as well as air pollution, were important predictors of each medicine. Our study adds to the self-medication literature through demonstrating the usefulness of loyalty card records for producing insights about how self-medication varies at the national level. Big data offer novel insights that add to and address issues that traditional studies are unable to consider. New forms of data through data linkage may offer opportunities to improve current public health decision making surrounding at risk population groups within self-medication behaviours. [ABSTRACT FROM AUTHOR]

Research suggests that partisans are increasingly avoiding members of the other party—in their choice of neighborhood, social network, even their spouse. Leveraging a national database of voter registration records, we analyze 18 million households in the U.S. We find that three in ten married couples have mismatched party affiliations. We observe the relationship between inter-party marriage and gender, age, and geography. We discuss how the findings bear on key questions of political behavior in the US. Then, we test whether mixed-partisan couples participate less actively in politics. We find that voter turnout is correlated with the party of one’s spouse. A partisan who is married to a co-partisan is more likely to vote. This phenomenon is especially pronounced for partisans in closed primaries, elections in which non-partisan registered spouses are ineligible to participate. [ABSTRACT FROM AUTHOR]

The rapid growth of mobile payment and geo-aware systems as well as the resulting emergence of Big Data present opportunities to explore individual consuming patterns across space and time. Here we analyze a one-year transaction dataset of a leading commercial bank to understand to what extent customer mobility behavior and financial indicators can predict the use of a target product, namely the Individual Consumer Loan product. After data preprocessing, we generate 13 datasets covering different time intervals and feature groups, and test combinations of 3 feature selection methods and 10 classification algorithms to determine, for each dataset, the best feature selection method and the most influential features, and the best classification algorithm. We observe the importance of spatio-temporal mobility features and financial features, in addition to demography, in predicting the use of this exemplary product with high accuracy (AUC = 0.942). Finally, we analyze the classification results and report on most interesting customer characteristics and product usage implications. Our findings can be used to potentially increase the success rates of product recommendation systems. [ABSTRACT FROM AUTHOR]

Yonaguni Island is a remote and isolated westernmost island in Japan, which is the fastest aging country in the world. This study evaluated the current status of medical supply-and-demand on the island and compared these results with previous surveys carried out in rural parts of Japan. This was a retrospective cohort study conducted at the Yonaguni Municipal Clinic, the only medical facility in Yonaguni Island. The participants were patients who visited the clinic over one year, between July 2015 and June 2016. We calculated the rate per 1,000 persons per month of clinic visits, referrals to off-island medical facilities (e.g., hospitals and specialist clinics), referrals to off-island emergency departments, off-island hospitalizations after referral, home visits, and overnight observations at the clinic. In total, 6,197 patients (males, 46.3%) visited the clinic. The rate of clinic visits per 1,000 persons per month was 516.4 (Standard deviation [SD] 28.1, 95% confidence interval [CI]: 500.5–532.3). The rate per 1,000 persons per month was 14.0 (SD 3.9, 95% CI: 11.8–16.2) for off-island referrals, 3.8 (SD 2.1, 95% CI: 2.6–5.0) for referrals to emergency departments, 4.8 (SD 2.6, 95% CI: 3.3–6.2) for hospitalizations, and 3.2 (SD 1.7, 95% CI: 2.2–4.1) for home visits. The rate of clinic visits was higher in Yonaguni Island than in other rural areas, although the rate of off-island referrals was lower. There were no significant differences between the number of referrals to emergency departments, hospitalizations, and home visits in Yonaguni Island, in comparison to other studies. Our study showed that patients presenting with emergencies had similar rates of healthcare-seeking behavior to those reported in previous studies in Japan; however, the referral rate was lower. We assessed the ecology of medical care in this district by evaluating patient behavior on an isolated island where access to medical care is geographically limited. [ABSTRACT FROM AUTHOR]

The analyses of geographic variations in the prevalence of major chronic conditions, such as overweight and obesity, are an important public health tool to identify “hot spots” and inform allocation of funding for policy and health promotion campaigns, yet rarely performed. Here we aimed at exploring, for the first time in Luxembourg, potential geographic patterns in overweight/obesity prevalence in the country, adjusted for several demographic, socioeconomic, behavioural and health status characteristics. Data came from 720 men and 764 women, 25–64 years old, who participated in the European Health Examination Survey in Luxembourg (2013–2015). To investigate the geographical variation, geo-additive semi-parametric mixed model and Bayesian modelisations based on Markov Chain Monte Carlo techniques for inference were performed. Large disparities in the prevalence of overweight and obesity were found between municipalities, with the highest rates of obesity found in 3 municipalities located in the South-West of the country. Bayesian approach also underlined a nonlinear effect of age on overweight and obesity in both genders (significant in men) and highlighted the following risk factors: 1. country of birth for overweight in men born in a non-European country (Posterior Odds Ratio (POR): 3.24 [1.61–8.69]) and women born in Portugal (POR: 2.44 [1.25–4.43]), 2. low educational level (secondary or below) for overweight (POR: 1.66 (1.06–2.72)] and obesity (POR:2.09 [1.05–3.65]) in men, 3. single marital status for obesity in women (POR: 2.20 [1.24–3.91]), 4.fair (men: POR: 3.19 [1.58–6.79], women: POR: 2.24 [1.33–3.73]) to very bad health perception (men: POR: 15.01 [2.16–98.09]) for obesity, 5. sleeping more than 6 hours for obesity in unemployed men (POR: 3.66 [2.02–8.03]). Protective factors highlighted were: 1. single marital status against overweight (POR: [0.60 (0.38–0.96)]) and obesity (POR: 0.39 [0.16–0.84]) in men, 2. the fact to be widowed against overweight in women (POR: [0.30 (0.07–0.86)], as well as a non European country of birth (POR: 0.49 [0.19–0.98]), tertiary level of education (POR: 0.34 [0.18–0.64]), moderate alcohol consumption (POR: 0.54 [0.36–0.90]) and aerobic physical activity practice (POR: 0.44 [0.27–0.77]) against obesity in women. A double burden of environmental exposure due to historic mining and industrial activities and past economic vulnaribility in the South-West of the country may have participated to the higher prevalence of obesity found in this region. Other demographic, socioeconomic, behavioural and health status covariates could have been involved as well. [ABSTRACT FROM AUTHOR]

We introduce a Schelling model in which people are modelled as agents following simple behavioural rules which dictate their tolerance to others, their corresponding preference for particular locations, and in turn their movement through a geographic or social space. Our innovation over previous work is to allow agents to adapt their tolerance to others in response to their local environment, in line with contemporary theories from social psychology. We show that adaptive tolerance leads to a polarization in tolerance levels, with distinct modes at either extreme of the distribution. Moreover, agents self-organize into communities of like-tolerance, just as they congregate with those of same colour. Our results are robust not only to variations in free parameters, but also experimental treatments in which migrants are dynamically introduced into the native population. We argue that this model provides one possible parsimonious explanation of the political landscape circa 2016. [ABSTRACT FROM AUTHOR]

Background: Food supplements, and in particular those containing botanicals (plant food supplements, PFS), have in recent decades been of great interest both to consumers and to food/pharmaceutical industries. Objectives: The aim of this paper is to examine replies by Italian consumers to the PlantLIBRA consumers' survey in order to: 1) assess the behaviour of an Italian population with respect to the use of PFS, and to compare it with that of other 5 countries involved in the whole survey; 2) identify different habits in the 4 Italian cities selected according to their geographical distribution; 3) collect independent information on the actual intake of PFS and consumers' behaviour. Subjects/setting: 397 Italian consumers enrolled, 187 males (49.5%) and 191 female (50.5%). The distribution of subjects among the 4 cities included was: Milan 99; Venice 90; Rome 96 and Catania 96. Results: The interest in PFS in Italy is high, the prevalence of "regular" consumers being 22.7%. Some differences were observed between the 4 cities involved: the pattern of use during the year was specific to each city; consumers in Milan reported reasons to use PFS significantly different from those in the whole Italian sample and did not indicate supermarkets as an important place of purchase; respondents from Rome and Catania more frequently used family doctors and pharmacists as a source of recommendation. Some significant difference among cities, sex and age groups were observed when the most frequently used botanicals were ranked. Conclusions: The results provide new insights on the socio-economic characteristics and lifestyle of Italian PFS consumers, on their reasons for and pattern of use, and on their behaviour and expectations. The value of this information is not restricted to the specific country (Italy) but allows for a more general evaluation of the pattern of use, according to habits and geographical area. [ABSTRACT FROM AUTHOR]

It has recently become possible to study the dynamics of information diffusion in techno-social systems at scale, due to the emergence of online platforms, such as Twitter, with millions of users. One question that systematically recurs is whether information spreads according to simple or complex dynamics: does each exposure to a piece of information have an independent probability of a user adopting it (simple contagion), or does this probability depend instead on the number of sources of exposure, increasing above some threshold (complex contagion)? Most studies to date are observational and, therefore, unable to disentangle the effects of confounding factors such as social reinforcement, homophily, limited attention, or network community structure. Here we describe a novel controlled experiment that we performed on Twitter using ‘social bots’ deployed to carry out coordinated attempts at spreading information. We propose two Bayesian statistical models describing simple and complex contagion dynamics, and test the competing hypotheses. We provide experimental evidence that the complex contagion model describes the observed information diffusion behavior more accurately than simple contagion. Future applications of our results include more effective defenses against malicious propaganda campaigns on social media, improved marketing and advertisement strategies, and design of effective network intervention techniques. [ABSTRACT FROM AUTHOR]

With the rapid global proliferation of social media, there has been growing interest in using this existing source of easily accessible ‘big data’ to develop social science knowledge. However, amidst the big data gold rush, it is important that long-established principles of good social research are not ignored. This article critically evaluates Mitchell et al.’s (2013) study, ‘The Geography of Happiness: Connecting Twitter Sentiment and Expression, Demographics, and Objective Characteristics of Place’, demonstrating the importance of attending to key methodological issues associated with secondary data analysis. [ABSTRACT FROM AUTHOR]

OpenStreetMap, a crowdsourced geographic database, provides the only global-level, openly licensed source of geospatial road data, and the only national-level source in many countries. However, researchers, policy makers, and citizens who want to make use of OpenStreetMap (OSM) have little information about whether it can be relied upon in a particular geographic setting. In this paper, we use two complementary, independent methods to assess the completeness of OSM road data in each country in the world. First, we undertake a visual assessment of OSM data against satellite imagery, which provides the input for estimates based on a multilevel regression and poststratification model. Second, we fit sigmoid curves to the cumulative length of contributions, and use them to estimate the saturation level for each country. Both techniques may have more general use for assessing the development and saturation of crowd-sourced data. Our results show that in many places, researchers and policymakers can rely on the completeness of OSM, or will soon be able to do so. We find (i) that globally, OSM is ∼83% complete, and more than 40% of countries—including several in the developing world—have a fully mapped street network; (ii) that well-governed countries with good Internet access tend to be more complete, and that completeness has a U-shaped relationship with population density—both sparsely populated areas and dense cities are the best mapped; and (iii) that existing global datasets used by the World Bank undercount roads by more than 30%. [ABSTRACT FROM AUTHOR]

Achieving high coverage of HIV testing services is critical in many health systems, especially where HIV testing services remain centralized and inconvenient for many. As a result, planning the optimal spatial distribution of HIV testing sites is increasingly important. We aimed to assess the relationship between geographic distance and uptake of HIV testing services among the general population in Guangzhou, China. Utilizing spatial epidemiological methods and stratified household random sampling, we studied 666 adults aged 18–59. Computer-assisted interviews assessed self-reported HIV testing history. Spatial scan statistic assessed the clustering of participants who have ever been tested for HIV, and two-level logistic regression models assessed the association between uptake of HIV testing and the mean driving distance from the participant’s residence to all HIV testing sites in the research sites. The percentage of participants who have ever been tested for HIV was 25.2% (168/666, 95%CI: 21.9%, 28.5%), and the majority (82.7%) of participants tested for HIV in Centres for Disease Control and Prevention, public hospitals or STIs clinics. None reported using self-testing. Spatial clustering analyses found a hotspot included 48 participants who have ever been tested for HIV and 25.8 expected cases (Rate Ratio = 1.86, P = 0.002). Adjusted two-level logistic regression found an inverse relationship between geographic distance (kilometers) and ever being tested for HIV (aOR = 0.90, 95%CI: 0.84, 0.96). Married or cohabiting participants (aOR = 2.14, 95%CI: 1.09, 4.20) and those with greater social support (aOR = 1.04, 95%CI: 1.01, 1.07) were more likely to be tested for HIV. Our findings underscore the importance of considering the geographical distribution of HIV testing sites to increase testing. In addition, expanding HIV testing coverage by introducing non-facility based HIV testing services and self-testing might be useful to achieve the goal that 90% of people living with HIV knowing their HIV status by the year 2020. [ABSTRACT FROM AUTHOR]

Diffusion processes in social networks often cause the emergence of global phenomena from individual behavior within a society. The study of those global phenomena and the simulation of those diffusion processes frequently require a good model of the global network. However, survey data and data from online sources are often restricted to single social groups or features, such as age groups, single schools, companies, or interest groups. Hence, a modeling approach is required that extrapolates the locally restricted data to a global network model. We tackle this Missing Data Problem using Link-Prediction techniques from social network research, network generation techniques from the area of Social Simulation, as well as a combination of both. We found that techniques employing less information may be more adequate to solve this problem, especially when data granularity is an issue. We validated the network models created with our techniques on a number of real-world networks, investigating degree distributions as well as the likelihood of links given the geographical distance between two nodes. [ABSTRACT FROM AUTHOR]

Aggressive behavior can be defined as any behavior intended to hurt another person, and it is associated with many individual and social factors. This study examined the relationship between emotional regulation and inhibitory control in predicting aggressive behavior. Seventy-eight participants (40 males) completed self-report measures (Negative Mood Regulation Scale and Buss-Perry Aggression Questionnaire), a stop signal task, and engaged in a modified version of Taylor Aggression Paradigm (TAP) exercise, in which the outcome was used as a measure of direct physical aggression. We used a hierarchical, mixed-model multiple regression analysis test to examine the effects of emotion regulation and inhibitory control on physical reactive aggression. Results indicated an interaction between emotion regulation and inhibitory control on aggression. For participants with low inhibitory control only, there was a significant difference between high and low emotion regulation on aggression, such that low emotion regulation participants registered higher aggression than high emotion regulation participants. This difference was not found among participants with high inhibitory control. These results have implications for refining and targeting training and rehabilitation programs aimed at reducing aggressive behavior. [ABSTRACT FROM AUTHOR]

Being able to characterise the patterns of communications between individuals across different time scales is of great importance in understanding people’s social interactions. Here, we present a detailed analysis of the community structure of the network of mobile phone calls in the metropolitan area of Milan revealing temporal patterns of communications between people. We show that circadian and weekly patterns can be found in the evolution of communities, presenting evidence that these cycles arise not only at the individual level but also at that of social groups. Our findings suggest that these trends are present across a range of time scales, from hours to days and weeks, and can be used to detect socially relevant events. [ABSTRACT FROM AUTHOR]

It is commonly assumed that how individuals identify on the political spectrum–whether liberal, conservative, or moderate–has a universal meaning when it comes to policy stances and voting behavior. But, does political identity mean the same thing from place to place? Using data collected from across the U.S. we find that even when people share the same political identity, those in “bluer” locations are more likely to support left-leaning policies and vote for Democratic candidates than those in “redder” locations. Because the meaning of political identity is inconsistent across locations, individuals who share the same political identity sometimes espouse opposing policy stances. Meanwhile, those with opposing identities sometimes endorse identical policy stances. Such findings suggest that researchers, campaigners, and pollsters must use caution when extrapolating policy preferences and voting behavior from political identity, and that animosity toward the other end of the political spectrum is sometimes misplaced. [ABSTRACT FROM AUTHOR]

High fertility rates among disadvantaged subgroups are a public health problem because fertility levels significantly affect socioeconomic conditions and a population’s welfare. This paper aims to analyze the sociodemographic, behavioral, and reproductive factors associated with fertility rates among Brazilian women aged between 15–49 years. A Poisson regression was used to analyze data from the 2006 PNDS (Pesquisa Nacional de Demografia e Saúde da Criança e da Mulher), which evaluates socioeconomic, demographic, geographic, reproductive, behavioral, and chronic disease variables. The results show that the following characteristics are positively associated with an increase in the number of children born: being aged 20–24, residing in the North, being nonwhite, not being in paid employment, having lower education levels, having lower socioeconomic status, being in a stable union, having the first sexual intercourse before the age of 16 and having the first child before the age of 20. Thus, it is important to implement efficient family planning policies targeting these subgroups in order to improve life conditions, reduce inequalities and avoid the adverse outcomes of high fertility. [ABSTRACT FROM AUTHOR]

Social networking sites (SNS) are used for social and professional interaction with people. SNS popularity has encouraged researchers to analyze the relationship of activities performed on SNS with user behavior. In doing so, the term “user behavior” is rather used ambiguously with different interpretations, which makes it difficult to identify studies on user behavior in relation to SNS. This phenomenon has encouraged this thorough research on the characteristics of user behavior being discussed in the literature. Therefore, in this study, we aim to identify, analyze, and classify the characteristics associated with user behavior to answer the research questions designed to conduct this research. A mapping study (also called scoping study), which is a type of systematic literature review, is employed to identify potential studies from digital databases through a developed protocol. Thematic analysis is carried out for the classification of user behavior. We identified 116 primary studies for full analysis. This study found seven characteristics associated with behavior that have direct influence on SNS use and nine factors that have an indirect effect. All studies were conducted largely under seven areas that set the context of these studies. Findings show that the research on SNS is still in its early stage. The range of topics covered in the analyzed studies is quite expansive, although the depth in terms of number of studies under each topic is quite limited. This study reports that activities performed on SNS are either associated with user behavior or reflect personality characteristics. The findings of this study could be used by practitioners to evaluate their SNS platforms and develop more user-centered applications. These studies can also help organizations to understand better the needs of their employees. [ABSTRACT FROM AUTHOR]

Individual behavior is influenced by factors intrinsic to the decision-maker but also associated with other individuals and their ownerships with such relationship intensified by geographic proximity. The land management literature is scarce in the spatially integrated analysis of biophysical and socio-economic data. Localized land management decisions are likely driven by spatially-explicit but often unobserved resource conditions, influenced by an individual’s own characteristics, proximal lands and fellow owners. This study examined stated choices over the management of family-owned forests as an example of a resource that captures strong pecuniary and non-pecuniary values with identifiable decision makers. An autoregressive model controlled for spatially autocorrelated willingness-to-harvest (WTH) responses using a sample of residential and absentee family forest owners from the U.S. State of Missouri. WTH responses were largely explained by affective, cognitive and experience variables including timber production objectives and past harvest experience. Demographic variables, including income and age, were associated with WTH and helped define socially-proximal groups. The group of closest identity was comprised of resident males over 55 years of age with annual income of at least $50,000. Spatially-explicit models showed that indirect impacts, capturing spillover associations, on average accounted for 14% of total marginal impacts among statistically significant explanatory variables. We argue that not all proximal family forest owners are equal and owners-in-absentia have discernible differences in WTH preferences with important implications for public policy and future research. [ABSTRACT FROM AUTHOR]

How the spatial expansion of a species changes at a human time scale is a process difficult to determine. We studied the dispersal pattern of the French white stork population, using a 21-year ringing/resighting dataset. We used the graph-theory to investigate the strength of links between 5 populations (North-East, North-West, Centre, West, and South) and to determine factors important for the birds’ movements. Two clusters of populations were identified within the metapopulation, with most frequent movements of individuals between North-Eastern and Centre populations, and between North-Western and Western populations. Exchanges of individuals between populations were asymmetrical, where North-Eastern and North-Western populations provided more emigrants than they received immigrants. Neither the geographical distance between populations, nor the difference in densities influenced the number of individuals exchanging between populations. The graph-theory approach provides a dynamic view of individual movements within a metapopulation and might be useful for future population studies in the context of conservation. [ABSTRACT FROM AUTHOR]

Cultural orientation is defined as an individual’s cultural preferences when encountering imported culture while still living in the native culture. Data was analyzed from 1305 Chinese university students attending universities in Beijing, Kunming, and Wuhan. Cultural orientation was assessed with the Chinese Cultural Orientation Questionnaire, which assesses both Western and Traditional Chinese cultural orientations. The analysis used hierarchical logistic regression with nondrinkers as the reference group and controlling for demographic factors (age, gender, and urban/rural background). Western cultural orientation was found to significantly increase the odds of recent drinking. The results indicated that higher Western cultural orientation was, after gender, the second most important factor associated with Chinese college student drinking frequency. Traditional Chinese cultural orientation was not associated with drinking frequency. This study highlights an unexpected outcome of globalization on students who have not left their home cultures. [ABSTRACT FROM AUTHOR]

Time spent fishing is the effort metric often studied in fisheries but it may under-represent the effort actually expended by fishers. Entire fishing trips, from the time vessels leave port until they return, may prove more useful for examining trends in fleet dynamics, fisher behavior, and fishing costs. However, such trip information is often difficult to resolve. We identified ~30,000 trips made by vessels that targeted walleye pollock (Gadus chalcogrammus) in the Eastern Bering Sea from 2008–2014 by using vessel monitoring system (VMS) and landings data. We compared estimated trip durations to observer data, which were available for approximately half of trips. Total days at sea were estimated with < 1.5% error and 96.4% of trip durations were either estimated with < 5% error or they were within expected measurement error. With 99% accuracy, we classified trips as fishing for pollock, for another target species, or not fishing. This accuracy lends strong support to the use of our method with unobserved trips across North Pacific fisheries. With individual trips resolved, we examined potential errors in datasets which are often viewed as “the truth.” Despite having > 5 million VMS records (timestamps and vessel locations), this study was as much about understanding and managing data errors as it was about characterizing trips. Missing VMS records were pervasive and they strongly influenced our approach. To understand implications of missing data on inference, we simulated removal of VMS records from trips. Removal of records straightened (i.e., shortened) vessel trajectories, and travel distances were underestimated, on average, by 1.5–13.4% per trip. Despite this bias, VMS proved robust for trip characterization and for improved quality control of human-recorded data. Our scrutiny of human-reported and VMS data advanced our understanding of the potential utility and challenges facing VMS users globally. [ABSTRACT FROM AUTHOR]

Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially. [ABSTRACT FROM AUTHOR]

The question of whether any species except humans exhibits culture has generated much debate, partially due to the difficulty of providing conclusive evidence from observational studies in the wild. A starting point for demonstrating the existence of culture that has been used for many species including chimpanzees and orangutans is to show that there is geographic variation in the occurrence of particular behavioral traits inferred to be a result of social learning and not ecological or genetic influences. Gorillas live in a wide variety of habitats across Africa and they exhibit flexibility in diet, behavior, and social structure. Here we apply the ‘method of exclusion’ to look for the presence/absence of behaviors that could be considered potential cultural traits in well-habituated groups from five study sites of the two species of gorillas. Of the 41 behaviors considered, 23 met the criteria of potential cultural traits, of which one was foraging related, nine were environment related, seven involved social interactions, five were gestures, and one was communication related. There was a strong positive correlation between behavioral dissimilarity and geographic distance among gorilla study sites. Roughly half of all variation in potential cultural traits was intraspecific differences (i.e. variability among sites within a species) and the other 50% of potential cultural traits were differences between western and eastern gorillas. Further research is needed to investigate if the occurrence of these traits is influenced by social learning. These findings emphasize the importance of investigating cultural traits in African apes and other species to shed light on the origin of human culture. [ABSTRACT FROM AUTHOR]

Background: Age-disparate partnerships are hypothesized to increase HIV-risk for young women. However, the evidence base remains mixed. Most studies have focused only on unprotected sex among women in the partnership. Consequently, little is known about other risky behaviours, such as transactional sex, alcohol use, and concurrency, as well as the behaviours of the men who partner with young women. We therefore examined differences in various sexual behaviours of both young women and their male partners by partnership age difference. Methods: We used nationally representative data from South Africa (2012) on partnerships reported by 16–24 year old black African women (n = 818) and by black African men in partnerships with 16–24 year old women (n = 985). We compared sexual behaviours in age-disparate partnerships and age-similar partnerships, using multiple logistic regression to control for potential confounders and to assess rural/urban differences. Results: Young women in age-disparate partnerships were more likely to report unprotected sex than young women in similar-aged partnerships (aOR:1.51; p = 0.014; 95%CI:1.09–2.11). Men in partnerships with young women were more likely to report unprotected sex (aOR:1.92; p<0.01; 95%CI:1.31–2.81), transactional sex (aOR:2.73; p<0.01; 95%CI:1.64–4.56), drinking alcohol before sex (aOR:1.60; p = 0.062; 95%CI:0.98–2.61), and concurrency (aOR:1.39; p = 0.097; 95%CI:0.94–2.07) when their partners were five or more years younger. The association between age-disparate partnerships and transactional sex (aOR:4.14; p<0.01; 95%CI: 2.03–8.46) and alcohol use (aOR:2.24; p<0.013; 95%CI:1.20–4.19) was only found in urban areas. Conclusions: Results provide evidence that young women’s age-disparate partnerships involve greater sexual risk, particularly through the risky behaviours of their male partners, with the risk amplified for young women in urban areas. [ABSTRACT FROM AUTHOR]

Recent advances in multimedia and mobile technologies have facilitated large volumes of travel photos to be created and shared online. Although previous studies have utilized geotagged photos to model travel patterns at individual locations, there is limited research on how these datasets can model international travel behavior and inter-country travel flows—a crucial indicator to quantify the interactions between countries in tourism economics. Realizing the necessity to investigate the potential of geotagged photos in tourism geography, this research investigates international travel patterns from two perspectives: 1) We apply a series of indicators (radius of gyration (ROG), number of countries visited, and entropy) to measure the descriptive characteristics of international travel in different countries; 2) By constructing a gravity model of trade, we investigate how distance decay influences the magnitude of international travel flow between geographic entities, and whether (or how much) the popularity of a given destination (defined as the percentage of tourist income in national gross domestic product (GDP)) affects travel choices in different countries. The results provide valuable input to various commercial applications such as individual travel planning and destination suggestions. [ABSTRACT FROM AUTHOR]

Each animal population has its own acoustic signature which facilitates identification, communication and reproduction. The sonar signals of bats can convey social information, such as species identity and contextual information. The goal of this study was to determine whether bats adjust their echolocation call structures to mutually recognize and communicate when they encounter the bats from different colonies. We used the intermediate leaf-nosed bats (Hipposideros larvatus) as a case study to investigate the variations of echolocation calls when bats from one colony were introduced singly into the home cage of a new colony or two bats from different colonies were cohabitated together for one month. Our experiments showed that the single bat individual altered its peak frequency of echolocation calls to approach the call of new colony members and two bats from different colonies adjusted their call frequencies toward each other to a similar frequency after being chronically cohabitated. These results indicate that the ‘compromise’ in echolocation calls might be used to ensure effective mutual communication among bats. [ABSTRACT FROM AUTHOR]

Background: Provision and scale-up of high quality, evidence-based services is essential for successful international HIV prevention interventions in order to generate and maintain intervention uptake, study integrity and participant trust, from both health service delivery and diplomatic perspectives. Methods: We developed quality assurance (QAC) procedures to evaluate staff fidelity to a cluster-randomized trial of the NIMH Project Accept (HPTN 043) assessing the effectiveness of a community-based voluntary counseling and testing strategy. The intervention was comprised of three components—Mobile Voluntary Counseling and Testing (MVCT), Community Mobilization (CM) and Post-Test Support Services (PTSS). QAC procedures were based on standardized criteria, and were designed to assess both provider skills and adherence to the intervention protocol. Supervisors observed a random sample of 5% to 10% of sessions each month and evaluated staff against multiple criteria on scales of 1–5. A score of 5 indicated 100% adherence, 4 indicated 95% adherence, and 3 indicated 90% adherence. Scores below 3 were considered unsatisfactory, and protocol deviations were discussed with the respective staff. Results: During the first year of the intervention, the mean scores of MVCT and CM staff across the 5 study sites were 4 (95% adherence) or greater and continued to improve over time. Mean QAC scores for the PTSS component were lower and displayed greater fluctuations. Challenges to PTSS staff were identified as coping with the wide range of activities in the PTSS component and the novelty of the PTSS process. QAC fluctuations for PTSS were also associated with new staff hires or changes in staff responsibilities. Through constant staff monitoring and support, by Year 2, QAC scores for PTSS activities had reached those of MVCT and CM. Conclusions: The implementation of a large-sale, evidence based HIV intervention requires extensive QAC to ensure implementation effectiveness. Ongoing appraisal of study staff across sites ensures consistent and high quality delivery of all intervention components, in keeping with the goals of the study protocol, while also providing a forum for corrective feedback, additional supervision and retraining of staff. QAC ensures staff fidelity to study procedures and is critical to the successful delivery of multi-site HIV prevention interventions, as well as the delivery of services scaled up in programmatic situations. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BC) is the most common female malignant tumor. Previous studies have suggested a big incidence disparity among different cities in China. The present work selected a typical city, Hangzhou, to study BC incidence disparity within the city. Methods: Totally, 8784 female breast cancer cases were obtained from the Hangzhou Center for Disease Control and Prevention during the period 2008–2012. Analysis of Variance and Poisson Regression were the statistical tools implemented to compare incidence disparity in the space-time domain (reference group: township residents during 2008, area: subdistrict, town, and township, time frame: 2008–2012), space-time scan statistics was employed to detect significant spatiotemporal clusters of BC compared to the null hypothesis that the probability of cases diagnosed at a particular location was equal to the probability of cases diagnosed in the whole study area. Geographical Information System (GIS) was used to generate BC spatial distribution and cluster maps at the township level. Results: The subdistrict populations were found to have the highest and most stable BC incidence. Although town and township populations had a relatively low incidence, it displayed a significant increasing trend from 2008 to 2012. The BC incidence distribution was spatially heterogeneous and clustered with a trend-surface from the southwest low area to the northeast high area. High clusters were located in the northeastern Hangzhou area, whereas low clusters were observed in the southwestern area during the time considered. Conclusions: Better healthcare service and lifestyle changes may be responsible for the increasing BC incidence observed in towns and townships. One high incidence cluster (Linping subdistrict) and two low incidence clusters (middle Hangzhou) were detected. The low clusters may be attributable mainly to developmental level disparity, whereas the high cluster could be associated with other risk factors, such as environmental pollution. [ABSTRACT FROM AUTHOR]

Background: Identifying geographic areas with significantly high risks of stroke is important for informing public health prevention and control efforts. The objective of this study was to investigate geographic and temporal patterns of stroke hospitalization and mortality risks so as to identify areas and seasons with significantly high burden of the disease in Florida. The information obtained will be useful for resource allocation for disease prevention and control. Methods: Stroke hospitalization and mortality data from 1992 to 2012 were obtained from the Florida Agency for Health Care Administration. Age-adjusted stroke hospitalization and mortality risks for time periods 1992–94, 1995–97, 1998–2000, 2001–03, 2004–06, 2007–09 and 2010–12 were computed at the county spatial scale. Global Moran’s I statistics were computed for each of the time periods to test for evidence of global spatial clustering. Local Moran indicators of spatial association (LISA) were also computed to identify local areas with significantly high risks. Results: There were approximately 1.5 million stroke hospitalizations and over 196,000 stroke deaths during the study period. Based on global Moran’s I tests, there was evidence of significant (p<0.05) global spatial clustering of stroke mortality risks but no evidence (p>0.05) of significant global clustering of stroke hospitalization risks. However, LISA showed evidence of local spatial clusters of both hospitalization and mortality risks with significantly high risks being observed in the north while the south had significantly low risks of stroke deaths. There were decreasing temporal trends and seasonal patterns of both hospitalization and mortality risks with peaks in the winter. Conclusions: Although stroke hospitalization and mortality risks have declined in the past two decades, disparities continue to exist across Florida and it is evident from the results of this study that north Florida may, in fact, be part of the stroke belt despite not being in any of the traditional stroke belt states. These findings are useful for guiding public health efforts to reduce/eliminate inequities in stroke outcomes and inform policy decisions. There is need to continually identify populations with significantly high risks of stroke to better guide the targeting of limited resources to the highest risk populations. [ABSTRACT FROM AUTHOR]

Background: Previous research has shown that environments with features that encourage walking are associated with increased physical activity. Existing methods to assess the built environment using geographical information systems (GIS) data, direct audit or large surveys of the residents face constraints, such as data availability and comparability, when used to study communities in countries in diverse parts of the world. The aim of this study was to develop a method to evaluate features of the built environment of communities using a standard set of photos. In this report we describe the method of photo collection, photo analysis instrument development and inter-rater reliability of the instrument. Methods/Principal Findings: A minimum of 5 photos were taken per community in 86 communities in 5 countries according to a standard set of instructions from a designated central point of each community by researchers at each site. A standard pro forma derived from reviewing existing instruments to assess the built environment was developed and used to score the characteristics of each community. Photo sets from each community were assessed independently by three observers in the central research office according to the pro forma and the inter-rater reliability was compared by intra-class correlation (ICC). Overall 87% (53 of 60) items had an ICC of ≥0.70, 7% (4 of 60) had an ICC between 0.60 and 0.70 and 5% (3 of 60) items had an ICC ≤0.50. Conclusions/Significance: Analysis of photos using a standardized protocol as described in this study offers a means to obtain reliable and reproducible information on the built environment in communities in very diverse locations around the world. The collection of the photographic data required minimal training and the analysis demonstrated high reliability for the majority of items of interest. [ABSTRACT FROM AUTHOR]

Background: Google Trends is a novel, freely accessible tool that allows users to interact with Internet search data, which may provide deep insights into population behavior and health-related phenomena. However, there is limited knowledge about its potential uses and limitations. We therefore systematically reviewed health care literature using Google Trends to classify articles by topic and study aim; evaluate the methodology and validation of the tool; and address limitations for its use in research. Methods and Findings: PRISMA guidelines were followed. Two independent reviewers systematically identified studies utilizing Google Trends for health care research from MEDLINE and PubMed. Seventy studies met our inclusion criteria. Google Trends publications increased seven-fold from 2009 to 2013. Studies were classified into four topic domains: infectious disease (27% of articles), mental health and substance use (24%), other non-communicable diseases (16%), and general population behavior (33%). By use, 27% of articles utilized Google Trends for casual inference, 39% for description, and 34% for surveillance. Among surveillance studies, 92% were validated against a reference standard data source, and 80% of studies using correlation had a correlation statistic ≥0.70. Overall, 67% of articles provided a rationale for their search input. However, only 7% of articles were reproducible based on complete documentation of search strategy. We present a checklist to facilitate appropriate methodological documentation for future studies. A limitation of the study is the challenge of classifying heterogeneous studies utilizing a novel data source. Conclusion: Google Trends is being used to study health phenomena in a variety of topic domains in myriad ways. However, poor documentation of methods precludes the reproducibility of the findings. Such documentation would enable other researchers to determine the consistency of results provided by Google Trends for a well-specified query over time. Furthermore, greater transparency can improve its reliability as a research tool. [ABSTRACT FROM AUTHOR]

In the wake of urbanisation processes and the constitution of metropolitan regions, the role of the city's rural surroundings is receiving more attention from researchers and planners as rural areas offer various (cultural) ecosystem services for the urban population. Urban dwellers increasingly desire recreation and landscape experience. Although this need for recreation is generally recognized, few studies have focused on the question of people's preferences for certain types and characteristics of outdoor recreation areas in relation to the frequency of use. In order to acquire baseline data on this subject, the main objectives of this study were to explore recreation preferences of urban dwellers and the relation between actual use and perceived value of recreation areas in a case study in the Hamburg Metropolitan Region (Germany). In a social survey, Hamburg residents (n = 400) were asked about their preferences and use of four important regional recreation areas with different landscape characteristics in face-to-face interviews in different locations in the city. We found that both outdoor recreation within and outside of the city were fairly or very important for more than 70% of the questioned urban dwellers. Interestingly, the preference for a recreation area outside of the city did not depend on the frequency of use, which indicates that certain recreation areas had a symbolic value besides their use value. When people were questioned on the characteristics of recreation areas, perceived naturalness was found to be strongly related to preference. Respondents considered the diversity, uniqueness, and naturalness of the landscape to be far more important than the accessibility of the recreation areas and the provision of service facilities. [ABSTRACT FROM AUTHOR]

Background: Relationships between the neighborhood environment and children’s physical activity have been well documented in Western countries but are less investigated in ultra-dense Asian cities. The aim of this study was to identify the environmental facilitators and barriers of physical activity behaviors among Hong Kong Chinese children using nominal group technique. Methods: Five nominal groups were conducted among 34 children aged 10–11 years from four types of neighborhoods varying in socio-economic status and walkability in Hong Kong. Environmental factors were generated by children in response to the question “What neighborhood environments do you think would increase or decrease your willingness to do physical activity?” Factors were prioritized in order of their importance to children’s physical activity. Results: Sixteen unique environmental factors, which were perceived as the most important to children’s physical activity, were identified. Factors perceived as physical activity-facilitators included “Sufficient lighting”, “Bridge or tunnel”, “Few cars on roads”, “Convenient transportation”, “Subway station”, “Recreation grounds”, “Shopping malls with air conditioning”, “Fresh air”, “Interesting animals”, and “Perfume shop”. Factors perceived as physical activity-barriers included “People who make me feel unsafe”, “Crimes nearby”, “Afraid of being taken or hurt at night”, “Hard to find toilet in shopping mall”, “Too much noise”, and “Too many people in recreation grounds”. Conclusions: Specific physical activity-related environmental facilitators and barriers, which are unique in an ultra-dense city, were identified by Hong Kong children. These initial findings can inform future examinations of the physical activity-environment relationship among children in Hong Kong and similar Asian cities. [ABSTRACT FROM AUTHOR]

Landscape patterns and chimpanzee (Pan troglodytes schweinfurthii) densities in Kibale National Park show important variation among communities that are geographically close to one another (from 1.5 to 5.1 chimpanzees/km2). Anthropogenic activities inside the park (past logging activities, current encroachment) and outside its limits (food and cash crops) may impact the amount and distribution of food resources for chimpanzees (frugivorous species) and their spatial distribution within the park. Spatial and temporal patterns of fruit availability were recorded over 18 months at Sebitoli (a site of intermediate chimpanzee density and higher anthropic pressure) with the aim of understanding the factors explaining chimpanzee density there, in comparison to results from two other sites, also in Kibale: Kanyawara (low chimpanzee density) and Ngogo (high density, and furthest from Sebitoli). Because of the post-logging regenerating status of the forest in Sebitoli and Kanyawara, smaller basal area (BA) of fruiting trees most widely consumed by the chimpanzees in Kanyawara and Sebitoli was expected compared to Ngogo (not logged commercially). Due to the distance between sites, spatial and temporal fruit abundance in Sebitoli was expected to be more similar to Kanyawara than to Ngogo. While species functional classes consumed by Sebitoli chimpanzees (foods eaten during periods of high or low fruit abundance) differ from the two other sites, Sebitoli is very similar to Kanyawara in terms of land-cover and consumed species. Among feeding trees, Ficus species are particularly important resources for chimpanzees at Sebitoli, where their basal area is higher than at Kanywara or Ngogo. Ficus species provided a relatively consistent supply of food for chimpanzees throughout the year, and we suggest that this could help to explain the unusually high density of chimpanzees in such a disturbed site. [ABSTRACT FROM AUTHOR]

Objective: The adoption of pro-environmental behaviours reduces anthropogenic environmental impacts and subsequent human health effects. This study developed composite indices measuring adoption of pro-environmental behaviours at the household level in Canada. Methods: The 2007 Households and the Environment Survey conducted by Statistics Canada collected data on Canadian environmental behaviours at households' level. A subset of 55 retained questions from this survey was analyzed by Multiple Correspondence Analysis (MCA) to develop the index. Weights attributed by MCA were used to compute scores for each Canadian province as well as for socio-demographic strata. Scores were classified into four categories reflecting different levels of adoption of pro-environmental behaviours. Results: Two indices were finally created: one based on 23 questions related to behaviours done inside the dwelling and a second based on 16 questions measuring behaviours done outside of the dwelling. British Columbia, Quebec, Prince-Edward-Island and Nova-Scotia appeared in one of the two top categories of adoption of pro-environmental behaviours for both indices. Alberta, Saskatchewan, Manitoba and Newfoundland-and-Labrador were classified in one of the two last categories of pro-environmental behaviours adoption for both indices. Households with a higher income, educational attainment, or greater number of persons adopted more indoor pro-environmental behaviours, while on the outdoor index, they adopted fewer such behaviours. Households with low-income fared better on the adoption of outdoors pro-environmental behaviours. Conclusion: MCA was successfully applied in creating Indoor and Outdoor composite Indices of pro-environmental behaviours. The Indices cover a good range of environmental themes and the analysis could be applied to similar surveys worldwide (as baseline weights) enabling temporal trend comparison for recurring themes. Much more than voluntary measures, the study shows that existing regulations, dwelling type, households composition and income as well as climate are the major factors determining pro-environmental behaviours. [ABSTRACT FROM AUTHOR]

Background: Every day, around 400 million tweets are sent worldwide, which has become a rich source for detecting, monitoring and analysing news stories and special (disaster) events. Existing research within this field follows key words attributed to an event, monitoring temporal changes in word usage. However, this method requires prior knowledge of the event in order to know which words to follow, and does not guarantee that the words chosen will be the most appropriate to monitor. Methods: This paper suggests an alternative methodology for event detection using space-time scan statistics (STSS). This technique looks for clusters within the dataset across both space and time, regardless of tweet content. It is expected that clusters of tweets will emerge during spatio-temporally relevant events, as people will tweet more than expected in order to describe the event and spread information. The special event used as a case study is the 2013 London helicopter crash. Results and Conclusion: A spatio-temporally significant cluster is found relating to the London helicopter crash. Although the cluster only remains significant for a relatively short time, it is rich in information, such as important key words and photographs. The method also detects other special events such as football matches, as well as train and flight delays from Twitter data. These findings demonstrate that STSS is an effective approach to analysing Twitter data for event detection. [ABSTRACT FROM AUTHOR]

Strontium isotope sourcing has become a common and useful method for assigning sources to archaeological artifacts. In Chaco Canyon, an Ancestral Pueblo regional center in New Mexico, previous studies using these methods have suggested that significant portion of maize and wood originate in the Chuska Mountains region, 75 km to the East. In the present manuscript, these results were tested using both frequentist methods (to determine if geochemical sources can truly be differentiated) and Bayesian methods (to address uncertainty in geochemical source attribution). It was found that Chaco Canyon and the Chuska Mountain region are not easily distinguishable based on radiogenic strontium isotope values. The strontium profiles of many geochemical sources in the region overlap, making it difficult to definitively identify any one particular geochemical source for the canyon's pre-historic maize. Bayesian mixing models support the argument that some spruce and fir wood originated in the San Mateo Mountains, but that this cannot explain all 87Sr/86Sr values in Chaco timber. Overall radiogenic strontium isotope data do not clearly identify a single major geochemical source for maize, ponderosa, and most spruce/fir timber. As such, the degree to which Chaco Canyon relied upon outside support for both food and construction material is still ambiguous. [ABSTRACT FROM AUTHOR]

Objectives: To assess the relationship between proximity to specific sports facilities and participation in the corresponding sports activities for adolescents in Germany. Methods: A sample of 1,768 adolescents aged 11–17 years old and living in 161 German communities was examined. Distances to the nearest sports facilities were calculated as an indicator of proximity to sports facilities using Geographic Information Systems (GIS). Participation in specific leisure-time sports activities in sports clubs was assessed using a self-report questionnaire and individual-level socio-demographic variables were derived from a parent questionnaire. Community-level socio-demographics as covariates were selected from the INKAR database, in particular from indicators and maps on land development. Logistic regression analyses were conducted to examine associations between proximity to the nearest sports facilities and participation in the corresponding sports activities. Results: The logisitic regression analyses showed that girls residing longer distances from the nearest gym were less likely to engage in indoor sports activities; a significant interaction between distances to gyms and level of urbanization was identified. Decomposition of the interaction term showed that for adolescent girls living in rural areas participation in indoor sports activities was positively associated with gym proximity. Proximity to tennis courts and indoor pools was not associated with participation in tennis or water sports, respectively. Conclusions: Improved proximity to gyms is likely to be more important for female adolescents living in rural areas. [ABSTRACT FROM AUTHOR]

Researchers hoping to elucidate the behaviour of species that aren’t readily observed are able to do so using biotelemetry methods. Accelerometers in particular are proving particularly effective and have been used on terrestrial, aquatic and volant species with success. In the past, behavioural modes were detected in accelerometer data through manual inspection, but with developments in technology, modern accelerometers now record at frequencies that make this impractical. In light of this, some researchers have suggested the use of various machine learning approaches as a means to classify accelerometer data automatically. We feel uptake of this approach by the scientific community is inhibited for two reasons; 1) Most machine learning algorithms require selection of summary statistics which obscure the decision mechanisms by which classifications are arrived, and 2) they are difficult to implement without appreciable computational skill. We present a method which allows researchers to classify accelerometer data into behavioural classes automatically using a primitive machine learning algorithm, k-nearest neighbour (KNN). Raw acceleration data may be used in KNN without selection of summary statistics, and it is easily implemented using the freeware program R. The method is evaluated by detecting 5 behavioural modes in 8 species, with examples of quadrupedal, bipedal and volant species. Accuracy and Precision were found to be comparable with other, more complex methods. In order to assist in the application of this method, the script required to run KNN analysis in R is provided. We envisage that the KNN method may be coupled with methods for investigating animal position, such as GPS telemetry or dead-reckoning, in order to implement an integrated approach to movement ecology research. [ABSTRACT FROM AUTHOR]

Industrial agglomerations have long been thought to offer economic and social benefits to firms and people that are only captured by location within their specified geographies. Using the case study of New York City’s garment industry along with data acquired from cell phones and social media, this study set out to understand the discrete activities underpinning the economic dynamics of an industrial agglomeration. Over a two week period, data was collected by employing the geo-locative capabilities of Foursquare, a social media application, to record every movement of fashion workers employed at fashion design firms located both inside and outside the geographical boundaries of New York City’s Garment District. This unique method of studying worker activity exposed the day-to-day dynamics of an industrial district with a precision thus far undocumented in literature. Our work suggests that having access to the cluster provides almost the same agglomeration economies as residing within its borders. [ABSTRACT FROM AUTHOR]

In the Twitter blogosphere, the number of followers is probably the most basic and succinct quantity for measuring popularity of users. However, the number of followers can be manipulated in various ways; we can even buy follows. Therefore, alternative popularity measures for Twitter users on the basis of, for example, users' tweets and retweets, have been developed. In the present work, we take a purely network approach to this fundamental question. First, we find that two relatively distinct types of users possessing a large number of followers exist, in particular for Japanese, Russian, and Korean users among the seven language groups that we examined. A first type of user follows a small number of other users. A second type of user follows approximately the same number of other users as the number of follows that the user receives. Then, we compare local (i.e., egocentric) followership networks around the two types of users with many followers. We show that the second type, which is presumably uninfluential users despite its large number of followers, is characterized by high link reciprocity, a large number of friends (i.e., those whom a user follows) for the followers, followers' high link reciprocity, large clustering coefficient, large fraction of the second type of users among the followers, and a small PageRank. Our network-based results support that the number of followers used alone is a misleading measure of user's popularity. We propose that the number of friends, which is simple to measure, also helps us to assess the popularity of Twitter users. [ABSTRACT FROM AUTHOR]

Local health status and health care use may be negatively influenced by low local socio-economic profile, population decline and population ageing. To support the need for targeted local health care, we explored spatial patterns of type 2 diabetes mellitus (T2DM) drug use at local level and determined its association with local demographic, socio-economic and access to care variables. We assessed spatial variability in these associations. We estimated the five-year prevalence of T2DM drug use (2005–2009) in persons aged 45 years and older at four-digit postal code level using the University of Groningen pharmacy database IADB.nl. Statistics Netherlands supplied data on potential predictor variables. We assessed spatial clustering, correlations and estimated a multiple linear regression model and a geographically weighted regression (GWR) model. Prevalence of T2DM medicine use ranged from 2.0% to 25.4%. The regression model included the extent of population ageing, proportion of social welfare/benefits, proportion of low incomes and proportion of pensioners, all significant positive predictors of local T2DM drug use. The GWR model demonstrated considerable spatial variability in the association between T2DM drug use and above predictors and was more accurate. The findings demonstrate the added value of spatial analysis in predicting health care use at local level. [ABSTRACT FROM AUTHOR]

We investigate the growth dynamics of Greater London defined by the administrative boundary of the Greater London Authority, based on the evolution of its street network during the last two centuries. This is done by employing a unique dataset, consisting of the planar graph representation of nine time slices of Greater London's road network spanning 224 years, from 1786 to 2010. Within this time-frame, we address the concept of the metropolitan area or city in physical terms, in that urban evolution reveals observable transitions in the distribution of relevant geometrical properties. Given that London has a hard boundary enforced by its long standing green belt, we show that its street network dynamics can be described as a fractal space-filling phenomena up to a capacitated limit, whence its growth can be predicted with a striking level of accuracy. This observation is confirmed by the analytical calculation of key topological properties of the planar graph, such as the topological growth of the network and its average connectivity. This study thus represents an example of a strong violation of Gibrat's law. In particular, we are able to show analytically how London evolves from a more loop-like structure, typical of planned cities, toward a more tree-like structure, typical of self-organized cities. These observations are relevant to the discourse on sustainable urban planning with respect to the control of urban sprawl in many large cities which have developed under the conditions of spatial constraints imposed by green belts and hard urban boundaries. [ABSTRACT FROM AUTHOR]

Objective: Commuting provides opportunities for regular physical activity which can reduce the risk of chronic disease. Commuters' mode of travel may be shaped by their environment, but understanding of which specific environmental characteristics are most important and might form targets for intervention is limited. This study investigated associations between mode choice and a range of objectively assessed environmental characteristics. Methods: Participants in the Commuting and Health in Cambridge study reported where they lived and worked, their usual mode of travel to work and a variety of socio-demographic characteristics. Using geographic information system (GIS) software, 30 exposure variables were produced capturing characteristics of areas around participants' homes and workplaces and their shortest modelled routes to work. Associations between usual mode of travel to work and personal and environmental characteristics were investigated using multinomial logistic regression. Results: Of the 1124 respondents, 50% reported cycling or walking as their usual mode of travel to work. In adjusted analyses, home-work distance was strongly associated with mode choice, particularly for walking. Lower odds of walking or cycling rather than driving were associated with a less frequent bus service (highest versus lowest tertile: walking OR 0.61 [95% CI 0.20–1.85]; cycling OR 0.43 [95% CI 0.23–0.83]), low street connectivity (OR 0.22, [0.07–0.67]; OR 0.48 [0.26–0.90]) and free car parking at work (OR 0.24 [0.10–0.59]; OR 0.55 [0.32–0.95]). Participants were less likely to cycle if they had access to fewer destinations (leisure facilities, shops and schools) close to work (OR 0.36 [0.21–0.62]) and a railway station further from home (OR 0.53 [0.30–0.93]). Covariates strongly predicted travel mode (pseudo r-squared 0.74). Conclusions: Potentially modifiable environmental characteristics, including workplace car parking, street connectivity and access to public transport, are associated with travel mode choice, and could be addressed as part of transport policy and infrastructural interventions to promote active commuting. [ABSTRACT FROM AUTHOR]

Can online behaviour be used as a proxy for studying urban mobility? The increasing availability of digital mobility traces has provided new insights into collective human behaviour. Mobility datasets have been shown to be an accurate proxy for daily behaviour and social patterns, and behavioural data from Twitter has been used to predict real world phenomena such as cinema ticket sale volumes, stock prices, and disease outbreaks. In this paper we correlate city-scale urban traffic patterns with online search trends to uncover keywords describing the pedestrian traffic location. By analysing a 3-year mobility dataset we show that our approach, called Location Archetype Keyword Extraction (LAKE), is capable of uncovering semantically relevant keywords for describing a location. Our findings demonstrate an overarching relationship between online and offline collective behaviour, and allow for advancing analysis of community-level behaviour by using online search keywords as a practical behaviour proxy. [ABSTRACT FROM AUTHOR]

Large scale analysis and statistics of socio-technical systems that just a few short years ago would have required the use of consistent economic and human resources can nowadays be conveniently performed by mining the enormous amount of digital data produced by human activities. Although a characterization of several aspects of our societies is emerging from the data revolution, a number of questions concerning the reliability and the biases inherent to the big data “proxies” of social life are still open. Here, we survey worldwide linguistic indicators and trends through the analysis of a large-scale dataset of microblogging posts. We show that available data allow for the study of language geography at scales ranging from country-level aggregation to specific city neighborhoods. The high resolution and coverage of the data allows us to investigate different indicators such as the linguistic homogeneity of different countries, the touristic seasonal patterns within countries and the geographical distribution of different languages in multilingual regions. This work highlights the potential of geolocalized studies of open data sources to improve current analysis and develop indicators for major social phenomena in specific communities. [ABSTRACT FROM AUTHOR]

Objectives: Smoking among migrants is known to differ from the host population, but migrants’ smoking is rarely ever compared to the prevalence of smoking in their country of origin. The goal of this study is to compare the smoking prevalence among migrants to that of both the US-born population and the countries of origin. Further analyses assess the influence of sex, age at time of entry to the US and education level. Methods: Data of 248,726 US-born and migrants from 14 countries were obtained from the Tobacco Use Supplement to the Current Population Survey (TUS-CPS) from 2006–2007. Data on 108,653 respondents from the corresponding countries of origin were taken from the World Health Survey (WHS) from 2002–2005. Results: The prevalence of smoking among migrants (men: 14.2%, women: 4.1%) was lower than both the US-born group (men: 21.4%, women: 18.1%) and countries of origin (men: 39.4%, women: 11.0%). The gender gap among migrants was smaller than in the countries of origin. Age at time of entry to the US was not related to smoking prevalence for migrants. The risk of smoking for high-educated migrants was closer to their US counterparts. Conclusions: The smoking prevalence among migrants is consistently lower than both the country of origin levels and the US level. The theory of segmented assimilation is supported by some results of this study, but not all. Other mechanisms that might influence the smoking prevalence among migrants are the ‘healthy migrant effect’ or the stage of the smoking epidemic at the time of migration. [ABSTRACT FROM AUTHOR]