Predictors of romantic partner nomination reciprocity in adolescent social networks.

Network data uniquely allow relationships to be multiply reported, creating varying rates of relationship nomination reciprocation. However, what drives such variation is unclear. Variation in reciprocation may reflect substantive information about relationships (e.g., social salience or desirability) or study design (e.g., question wording or capped nominations). We examine predictors of nomination reciprocity in romantic network data from the PROSPER study to analyze individual and dyadic predictors of nomination reciprocity. Results show higher grades predict higher reciprocity, while same-sex relationships and behaviorally discordant dyads are less likely to be reciprocal.

On limitations of uniplex networks for modeling multiplex contagion.

Many network contagion processes are inherently multiplex in nature, yet are often reduced to processes on uniplex networks in analytic practice. We therefore examine how data modeling choices can affect the predictions of contagion processes. We demonstrate that multiplex contagion processes are not simply the union of contagion processes over their constituent uniplex networks. We use multiplex network data from two different contexts-(1) a behavioral network to represent their potential for infectious disease transmission using a "simple" epidemiological model, and (2) users from online social network sites to represent their potential for information spread using a threshold-based "complex" contagion process. Our results show that contagion on multiplex data is not captured accurately in models developed from the uniplex networks even when they are combined, and that the nature of the differences between the (combined) uniplex and multiplex results depends on the specific spreading process over these networks.

Peer Network Processes in Adolescents' Health Lifestyles.

Combining theories of health lifestyles-interrelated health behaviors arising from group-based identities-with those of network and behavior change, we investigated network characteristics of health lifestyles and the role of influence and selection processes underlying these characteristics. We examined these questions in two high schools using longitudinal, complete friendship network data from the National Longitudinal Study of Adolescent to Adult Health. Latent class analyses characterized each school's predominant health lifestyles using several health behavior domains. School-specific stochastic actor-based models evaluated the bidirectional relationship between friendship networks and health lifestyles. Predominant lifestyles remained stable within schools over time, even as individuals transitioned between lifestyles. Friends displayed greater similarity in health lifestyles than nonfriend dyads. Similarities resulted primarily from teens' selection of friends with similar lifestyles but also from teens influencing their peers' lifestyles. This study demonstrates the salience of health lifestyles for adolescent development and friendship networks.

Estimating the Impact of Statewide Policies to Reduce Spread of Severe Acute Respiratory Syndrome Coronavirus 2 in Real Time, Colorado, USA.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic necessitated rapid local public health response, but studies examining the impact of social distancing policies on SARS-CoV-2 transmission have struggled to capture regional-level dynamics. We developed a susceptible-exposed-infected-recovered transmission model, parameterized to Colorado, USA‒specific data, to estimate the impact of coronavirus disease‒related policy measures on mobility and SARS-CoV-2 transmission in real time. During March‒June 2020, we estimated unknown parameter values and generated scenario-based projections of future clinical care needs. Early coronavirus disease policy measures, including a stay-at-home order, were accompanied by substantial decreases in mobility and reduced the effective reproductive number well below 1. When some restrictions were eased in late April, mobility increased to near baseline levels, but transmission remained low (effective reproductive number <1) through early June. Over time, our model parameters were adjusted to more closely reflect reality in Colorado, leading to modest changes in estimates of intervention effects and more conservative long-term projections.

Crafting Mosaics: Person-Centered Religious Influence and Selection in Adolescent Friendships.

This research addresses the intersection of two key domains of adolescents' lives: religion and peer networks. Religion scholars argue that religion is multi-faceted and better understood by focusing on combinations of indicators (i.e. mosaics), versus a variable-centered approach. We adopt this framework and investigate the interplay between religion and peer networks, both in how religious mosaics are shaped by friends and how religious profiles affect friend selection dynamics. With data from two schools in the National Longitudinal Study of Adolescent Health, we estimate religious mosaics using latent class analysis (LCA) to identify profiles consisting of combinations of commonly available survey-based measures of religious attitudes, behaviors, and identities. Finding evidence of theoretically-expected profiles, we then use stochastic actor based models (SABMs) to investigate network dynamics for these LCA-based religious profiles. We demonstrate how the profile data can be integrated within the SABM framework to evaluate processes of friend selection and influence. Results show evidence of adolescents influencing one another's religious mosaics, but not selecting friends on that basis.

Evaluating Sampling Biases from Third-party Reporting as a Method for Improving Survey Measures of Sensitive Behaviors.

Survey participants often misreport their sensitive behaviors (e.g., smoking, drinking, having sex) during interviews. Several studies have suggested that asking respondents to report the sensitive behaviors of their friends or confidants, rather than their own, might help address this problem. This is so because the "third-party reporting" (TPR) approach creates a surrogate sample of alters that may be less subject to social desirability biases. However, estimates of the prevalence of sensitive behaviors based on TPR assume that the surrogate sample of friends is representative of the population of interest. We used sociometric data on social networks in Likoma, Malawi to examine this assumption. Specifically, we use friendship network data to investigate whether friends have similar socio-economic characteristics as index respondents, and to measure possible correlations between the likelihood of inclusion in the surrogate sample and sensitive behaviors. From these results, we suggest approaches to strengthen estimates of the prevalence of sensitive behaviors obtained from TPR.

Epidemic potential by sexual activity distributions.

For sexually transmitted infections like HIV to propagate through a population, there must be a path linking susceptible cases to currently infectious cases. The existence of such paths depends in part on the degree distribution. Here, we use simulation methods to examine how two features of the degree distribution affect network connectivity: Mean degree captures a volume dimension, while the skewness of the upper tail captures a shape dimension. We find a clear interaction between shape and volume: When mean degree is low, connectivity is greater for long-tailed distributions, but at higher mean degree, connectivity is greater in short-tailed distributions. The phase transition to a giant component and giant bicomponent emerges as a positive function of volume, but it rises more sharply and ultimately reaches more people in short-tail distributions than in long-tail distributions. These findings suggest that any interventions should be attuned to how practices affect both the volume and shape of the degree distribution, noting potential unanticipated effects. For example, policies that primarily affect high-volume nodes may not be effective if they simply redistribute volume among lower degree actors, which appears to exacerbate underlying network connectivity.

How Initial Prevalence Moderates Network-based Smoking Change: Estimating Contextual Effects with Stochastic Actor-based Models.

We use an empirically grounded simulation model to examine how initial smoking prevalence moderates the effectiveness of potential interventions designed to change adolescent smoking behavior. Our model investigates the differences that result when manipulating peer influence and smoker popularity as intervention levers. We demonstrate how a simulation-based approach allows us to estimate outcomes that arise (1) when intervention effects could plausibly alter peer influence and/or smoker popularity effects and (2) across a sample of schools that match the range of initial conditions of smoking prevalence in U.S. schools. We show how these different initial conditions combined with the exact same intervention effects can produce substantially different outcomes-for example, effects that produce smoking declines in some settings can actually increase smoking in others. We explore the form and magnitude of these differences. Our model also provides a template to evaluate the potential effects of alternative intervention scenarios.

Scientific consensus, the law, and same sex parenting outcomes.

While the US Supreme Court was considering two related cases involving the constitutionality of same-sex marriage, one major question informing that decision was whether scientific research had achieved consensus regarding how children of same-sex couples fare. Determining the extent of consensus has become a key aspect of how social science evidence and testimony is accepted by the courts. Here, we show how a method of analyzing temporal patterns in citation networks can be used to assess the state of social scientific literature as a means to inform just such a question. Patterns of clustering within these citation networks reveal whether and when consensus arises within a scientific field. We find that the literature on outcomes for children of same-sex parents is marked by scientific consensus that they experience "no differences" compared to children from other parental configurations.

Mapping interdisciplinary fields: efficiencies, gaps and redundancies in HIV/AIDS research.

While interdisciplinarity continues to increase in popularity among funders and other scientific organizations, its potential to promote scientific advances remains under-examined. For HIV/AIDS research, we examine the dynamics of disciplinary integration (or lack thereof) providing insight into a field's knowledge base and those questions that remain unresolved. Drawing on the complete histories of two interdisciplinary journals, we construct bibliographic coupling networks based on overlapping citations to identify segregation into research clusters and estimate topic models of research content. We then compare how readily those bibliographic coupling clusters account for the structuring of topics covered within the field as it evolves over two decades. These comparisons challenge one-dimensional and/or cross-sectional approaches to interdisciplinarity. Some topics are increasingly coordinated across disciplinary boundaries (e.g., vaccine development); others remain relatively segmented into disconnected disciplinary domains for the full period (e.g., drug resistance). This divergence indicates heterogeneity in interdisciplinarity and emphasizes the need for critical approaches to studying the organization of science.

Social networks and smoking: exploring the effects of peer influence and smoker popularity through simulations.

Adolescent smoking and friendship networks are related in many ways that can amplify smoking prevalence. Understanding and developing interventions within such a complex system requires new analytic approaches. We draw on recent advances in dynamic network modeling to develop a technique that explores the implications of various intervention strategies targeted toward micro-level processes. Our approach begins by estimating a stochastic actor-based model using data from one school in the National Longitudinal Study of Adolescent Health. The model provides estimates of several factors predicting friendship ties and smoking behavior. We then use estimated model parameters to simulate the coevolution of friendship and smoking behavior under potential intervention scenarios. Namely, we manipulate the strength of peer influence on smoking and the popularity of smokers relative to nonsmokers. We measure how these manipulations affect smoking prevalence, smoking initiation, and smoking cessation. Results indicate that both peer influence and smoking-based popularity affect smoking behavior and that their joint effects are nonlinear. This study demonstrates how a simulation-based approach can be used to explore alternative scenarios that may be achievable through intervention efforts and offers new hypotheses about the association between friendship and smoking.

Sex, drugs, and race: how behaviors differentially contribute to the sexually transmitted infection risk network structure.

OBJECTIVES: We examined how risk behaviors differentially connect a population at high risk for sexually transmitted infections. METHODS: Starting from observed networks representing the full risk network and the risk network among respondents only, we constructed a series of edge-deleted counterfactual networks that selectively remove sex ties, drug ties, and ties involving both sex and drugs and a comparison random set. With these edge-deleted networks, we have demonstrated how each tie type differentially contributes to the connectivity of the observed networks on a series of standard network connectivity measures (component and bicomponent size, distance, and transitivity ratio) and the observed network racial segregation. RESULTS: Sex ties are unique from the other tie types in the network, providing wider reach in the network in relatively nonredundant ways. In this population, sex ties are more likely to bridge races than are other tie types. CONCLUSIONS: Interventions derived from only 1 mode of transmission at a time (e.g., condom promotion or needle exchange) would have different potential for curtailing sexually transmitted infection spread through the population than would attempts that simultaneously address all risk-relevant behaviors.

Quantifying the Benefits of Link-Tracing Designs for Partnership Network Studies.

Difficult-to-reach populations are frequently sampled through various link-tracing based designs, which rely on interpersonal networks to identify members of the population. This article examines the substantive returns to one such multiple-link tracing design in the Colorado Springs "Project 90" HIV risk networks study. Cross-links were respondents who were targeted for enrollment because of being named as partners by at least two other respondents in the sample. We compare cross-links to other respondents on sociodemographic characteristics and network properties using bivariate and multivariate adjusted statistics. We evaluate their contributions to observed network structure by creating a set of counterfactual networks deleting the information they provided. Results suggest that the link-tracing techniques led to identifying populations that would have otherwise been missed and that their absence would have underestimated potential HIV risk by distorting epidemiologically relevant measures within the network.

The Malawi Religion Project: Data collection and selected analyses.

Scholars have recently become increasingly interested in the role religion plays in the responses to the HIV/AIDS epidemic in sub-Saharan Africa. Here, we present the Malawi Religion Project (MRP), which provides data to examine the relationship between religion and HIV/AIDS through surveys and in-depth interviews with denominational leaders, congregational leaders, and congregation members in three districts of rural Malawi. In the paper, we outline existing perspectives on the religion-HIV/AIDS link, describe the MRP's design, implementation, and subsequent data; provide initial evidence for a series of general research hypotheses; and describe how these data can be used both to extend explorations of these relationships further and as a model for gathering similar data in other contexts. In particular we highlight the unique possibilities this project provides for analyses that link MRP data to the Malawi Diffusion and Ideational Change Project. These linked data produce a multi-level data set covering individuals, congregations and their communities, allowing empirical research on religion, HIV/AIDS risk, related behaviors, attitudes, and norms.

The Malawi Diffusion and Ideational Change Project 2004-06: Data collection, data quality, and analysis of attrition.

In this paper we evaluate the quality of survey data collected by the Malawi Diffusion and Ideational Change Project by investigating four potential sources of bias: sample representativeness, interviewer effects, response unreliability, and sample attrition. We discuss the results of our analysis and implications of our findings for the collection of data in similar contexts.