Disease outbreaks are one of the key threats to great apes and other wildlife. Because the spread of some pathogens (e.g., respiratory viruses, sexually transmitted diseases, ectoparasites) are mediated by social interactions, there is a growing interest in understanding how social networks predict the chain of pathogen transmission. In this study, we built a party network from wild chimpanzees (Pan troglodytes), and used agent-based modeling to test: (i) whether individual attributes (sex, age) predict individual centrality (i.e., whether it is more or less socially connected); (ii) whether individual centrality affects an individual\'s role in the chain of pathogen transmission; and, (iii) whether the basic reproduction number (R0) and infectious period modulate the influence of centrality on pathogen transmission. We show that sex and age predict individual centrality, with older males presenting many (degree centrality) and strong (strength centrality) relationships. As expected, males are more central than females within their network, and their centrality determines their probability of getting infected during simulated outbreaks. We then demonstrate that direct measures of social interaction (strength centrality), as well as eigenvector centrality, strongly predict disease dynamics in the chimpanzee community. Finally, we show that this predictive power depends on the pathogen\'s R0 and infectious period: individual centrality was most predictive in simulations with the most transmissible pathogens and long-lasting diseases. These findings highlight the importance of considering animal social networks when investigating disease outbreaks.

BACKGROUND: Movement links the distribution of habitats with the social environment of animals using those habitats. Despite the links between movement, habitat selection, and socioecology, their integration remains a challenge due to lack of shared vocabulary across fields, methodological gaps, and the implicit (rather than explicit) historical development of theory in the fields of social and spatial ecology. Given these challenges can be addressed, opportunity for further study will provide insight about the links between social, spatial, and movement ecology. Here, our objective was to disentangle the roles of habitat selection and social association as drivers of movement in caribou (Rangifer tarandus).
METHODS: To accomplish our objective, we modelled the relationship between collective movement and selection of foraging habitats using socially informed integrated step selection function (iSSF). Using iSSF, we modelled the effect of social processes, i.e., nearest neighbour distance and social preference, and movement behaviour on patterns of habitat selection.
RESULTS: By unifying social network analysis with iSSF, we identified movement-dependent social association, where individuals took shorter steps in lichen habitat and foraged in close proximity to more familiar individuals.
CONCLUSIONS: Our study demonstrates that social preference is context-dependent based on habitat selection and foraging behaviour. We therefore surmise that habitat selection and social association are drivers of collective movement, such that movement is the glue between habitat selection and social association. Here, we put these concepts into practice to demonstrate that movement is the glue connecting individual habitat selection to the social environment.

BACKGROUND: Communication breakdowns among healthcare providers have been identified as a significant cause of preventable adverse events, including harm to patients. A large proportion of studies investigating communication in healthcare organizations lack the necessary understanding of social networks to make meaningful improvements. Process Improvement in healthcare (systematic approach of identifying, analyzing, and enhancing workflows) is needed to improve quality and patient safety. This review aimed to characterize the use of SNA methods in Process Improvement within healthcare organizations.
METHODS: Relevant studies were identified through a systematic search of seven databases from inception - October 2022. No limits were placed on study design or language. The reviewers independently charted data from eligible full-text studies using a standardized data abstraction form and resolved discrepancies by consensus. The abstracted information was synthesized quantitatively and narratively.
RESULTS: Upon full-text review, 38 unique articles were included. Most studies were published between 2015 and 2021 (26, 68%). Studies focused primarily on physicians and nursing staff. The majority of identified studies were descriptive and cross-sectional, with 5 studies using longitudinal experimental study designs. SNA studies in healthcare focusing on process improvement spanned three themes: Organizational structure (e.g., hierarchical structures, professional boundaries, geographical dispersion, technology limitations that impact communication and collaboration), team performance (e.g., communication patterns and information flow among providers., and influential actors (e.g., key individuals or roles within healthcare teams who serve as central connectors or influencers in communication and decision-making processes).
CONCLUSIONS: SNA methods can characterize Process Improvement through mapping, quantifying, and visualizing social relations, revealing inefficiencies, which can then be targeted to develop interventions to enhance communication, foster collaboration, and improve patient safety.

Studying the spatial-social interface requires tools that distinguish between social and spatial drivers of interactions. Testing hypotheses about the factors determining animal interactions often involves comparing observed interactions with reference or \'null\' models. One approach to accounting for spatial drivers of social interactions in reference models is randomizing animal movement paths to decouple spatial and social phenotypes while maintaining environmental effects on movements. Here, we update a reference model that detects social attraction above the effect of spatial constraints. We explore the use of our \'wrap-around\' method and compare its performance to the previous approach using agent-based simulations. The wrap-around method provides reference models that are more similar to the original tracking data, while still distinguishing between social and spatial drivers. Furthermore, the wrap-around approach results in fewer false-positives than its predecessor, especially when animals do not return to one place each night but change movement foci, either locally or directionally. Finally, we show that interactions among GPS-tracked griffon vultures (Gyps fulvus) emerge from social attraction rather than from spatial constraints on their movements. We conclude by highlighting the biological situations in which the updated method might be most suitable for testing hypotheses about the underlying causes of social interactions. This article is part of the theme issue \'The spatial-social interface: a theoretical and empirical integration\'.

Pig farming in Mexico is critical to the economy and food supply. Mexico has achieved advancements in swine health and established an electronic database that records swine movements (Sistema Nacional de Avisos de Movilización, SNAM). In this study, we characterized swine movement patterns in México between 2017 and 2019 to identify specific areas and periods that require concentrated efforts for effective epidemiological surveillance and disease control. We employed a Social Network Analysis (SNA) methodology to comprehensively describe and analyze the intricate patterns of pig movement. In addition, we sought to integrate swine population density into the analysis. We used metrics to characterize the network structure and identify the most critical nodes in the movement network. Cohesion metrics were used to identify commercial communities characterized by a high level of interconnectivity in swine movements between groups of nodes. Of a cumulative count of 662,255 pig shipments, 95.9% were attributed to slaughterhouse shipments. We observed that 54% of all Mexican municipalities were part of the network; however, the density of the movement network was less than 0.14%. We identified four Swine Production Centers in Mexico with high interconnectivity in the movement network. We detected moderate positive correlations (ρ ≥0.4 and <0.6, p < 0.001) between node metrics and swine population indicators, whereas the number of commercial swine facilities showed weak correlations with the node metrics. We identified six large, geographically clustered commercial communities that aligned with the Swine Production Centers. This study provides a comprehensive overview of swine movement patterns in Mexico and their close association with swine production centers, which play a dual role as producers and traders within the swine industry of Mexico. Our research offers valuable insights for policymakers in developing disease prevention and control strategies.

Few studies examined the social network structures within multicultural volunteer programs for low-income diverse older adults, making it unclear how diverse older adults establish social connections beyond their co-ethnic community. This study aims to identify the social network structures within a Senior Companion Program (SCP), a multicultural low-income volunteer program in a Midwestern Metropolitan area in the United States. Data were collected through surveys during a SCP monthly in-service training in October 2021. Russian, Khmer, Somali, Nepali, and English-speaking older volunteers in the SCP (N = 41) identified friends through a nomination form. Exponential Random Graph Modeling (ERGM) was used to identify statistically significant structural features of the SCP network. Graphs and ERGM results demonstrated that participants tended to form friendships with other volunteers of the same gender (β=3.27, p < 0.001), from the same country (β=2.89, p < 0.001), with the same education level (β=0.71, p < 0.001), and from the same volunteer recruitment site (β=2.77, p < 0.001). Surprisingly, there were few transitive ties (β= -1.01, p < 0.001), the tendency to make friends with a friend of a friend, which is typically common in friendship networks. Relationships among diverse older volunteers are largely driven by homophily in this multicultural volunteer program. Addressing language barriers and assigning volunteers from different countries to the same recruitment site may counteract homophily by nationality. However, more research needs to identify whether the opportunity to interact with people of one\'s same or different cultural backgrounds is a stronger incentive for volunteer engagement and connectedness.

UNASSIGNED: \"Data scientists\" quickly became ubiquitous, often infamously so, but they have struggled with the ambiguity of their novel role. This article studies data science\'s collective definition on Twitter.
UNASSIGNED: The analysis responds to the challenges of studying an emergent case with unclear boundaries and substance through a cultural perspective and complementary datasets ranging from 1,025 to 752,815 tweets. It brings together relations between accounts that tweeted about data science, the hashtags they used, indicating purposes, and the topics they discussed.
UNASSIGNED: The first results reproduce familiar commercial and technical motives. Additional results reveal concerns with new practical and ethical standards as a distinctive motive for constructing data science.
UNASSIGNED: The article provides a sensibility for local meaning in usually abstract datasets and a heuristic for navigating increasingly abundant datasets toward surprising insights. For data scientists, it offers a guide for positioning themselves vis-à-vis others to navigate their professional future.

This study examined five dimensions of attachment network structure in a large sample of adults (n = 930, 57% female) between 24 to 80 years of age. We employed a newly validated diagrammatic measure, the web-based hierarchical mapping technique (WHMT), to measure the attachment strength to participants\' five closest relationships and the physical distance to and between network members. Our first aim was to replicate existing research on the composition of adult attachment networks, exploring variations in network patterns by age, romantic status, and parental status. Our second aim was to explore four new network dimensions, including physical distance to network members, hierarchical patterns, centrality, and density. The results replicated previous work on network composition, highlighting the pivotal role of romantic partners as primary attachment figures through adulthood. The analysis of the new network dimensions revealed a clear divide between adults in romantic relationships and those who are not. Compared to the single adults, the adults in romantic relationships were more hierarchical in their attachment preferences, reported lower emotional connection to friends and parents, and lived farther from their network, which was also more geographically dispersed. In other words, romantically involved adults put more of their attachment eggs in one basket. The results also showed that the older adults tended to live further away from their attachment network and had a more geographically dispersed network compared to the younger adults.

Science communication has diversified in the wake of the digital transformation of communication and media ecosystems. Social media enable universities, but also academics and institutions affiliated with them, to expand their communication. This leads to increasing plurivocality of universities, yet the many different voices remain largely unexplored. This study develops a typology to conceptually distinguish eight voices by their representational role, hierarchical embeddedness, type, and affiliation. Based on a quantitative content and social network analysis of more than 600 Twitter accounts linked to a research university, it identifies six types of voices empirically. The study compares interactions among these voices, showing differences between central and decentral, as well as institutional and individual voices, and highlighting closer exchanges between voices within the same disciplinary communities. It also examines topics and tonality, revealing that decentral institutional voices engage most in science-related topics, and that only current and former students express critical views.

Based on the entropy weight TOPSIS method to measure the development level of \"zero-waste cities\" in China from 2004 to 2021, the social network analysis method and spatial Durbin model were used to explore the spatial correlation network structure and impact mechanism of the development level of \"zero-waste cities.\" The results showed that： ① The development level of \"zero-waste cities\" was generally on the decline in the whole country and the eastern and central regions. However, it was on the rise in the western regions. ② The spatial correlation of the development level of \"zero-waste cities\" presented a core-edge structure, with an overall upward trend in network density and a stable state in the overall network. ③ Beijing, Shanghai, Jiangsu, Zhejiang, Fujian, and Guangdong were at the center and dominant position of the network. ④ Beijing, Tianjin, Shanghai, and Jiangsu belonged to the \"net benefit\" sector； Zhejiang, Fujian, and Guangdong belonged to the \"broker\" sector； and the other provinces belonged to the \"net overflow\" sectors. ⑤ The level of urbanization, economic development, technological innovation, foreign investment, environmental regulations, government intervention, and population size had a significant impact on the development level of \"zero-waste cities\" in local or neighboring provinces, respectively. The research results can provide a reference for the proposal of policies for constructing and coordinating the development of \"zero-waste cities\" in various regions.