Search

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

While there are many uncertainties about the ensuing COVID-19 pandemic, scientific mobilization that integrates knowledge from across the wide-ranging intersection of applicable expertise will optimize our response strategy. As we continue to coordinate these efforts, sociological contributions can continue to identify improved social coordination opportunities, even while practicing social distancing.

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., Main text: 12 pages, 3 figures; Supporting information: 5 pages, 5 figures

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.

Buchwald et al discuss the use of infectious disease transmission models to predict, evaluate, and improve understanding of COVID-19 trajectory and interventions COVID-19 has spread rapidly around the world with devastating consequences Large questions loom about how this epidemic will proceed and what interventions can slow the spread Mathematical models of infectious disease transmission serve a key role in guiding government response;they provide a framework for evaluating the potential impact of different policies on the course of the epidemic and on the expected number of lives lost and whether and when hospital capacity may be exceeded Given the critical role of infectious disease models in the pandemic, it is important to understand their strengths and limitations, as well as why different models may yield conflicting results

This chapter provides an overview of social network data collection strategies. We begin by outlining the primary principles of sampling and measurement design, then describing how those combine into what is labeled the “boundary specification problem” for social network research. We accompany these definitions with examples of how these elements are applied across ego, partial, and complete network designs. Next, the chapter turns to the primary ways that network data have been evaluated, highlighting both the implications of those evaluations for their use in network analyses and various strategies for how the identified limitations can be leveraged for optimal data and analytic quality. The chapter concludes by addressing some of the ethical considerations that are unique to the gathering and analyses of social network data.

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 within 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 non-friend 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.

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.

This research addresses the intersection of two key domains of adolescents' lives: religion and peer networks. Religion scholars have argued that religion is multi-faceted and hence better understood by focusing on combinations of indicators (i.e. mosaics), versus a more traditional 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 profiles affect friend selection dynamics. With data from two schools in the National Longitudinal Study of Adolescent Health, we estimate these 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, our second step is to use stochastic actor based models (SABMs) to investigate network dynamics for these LCA-based religious profiles. We demonstrate how the distinct structure of 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.

This chapter provides an overview of social network data collection strategies. We begin by outlining the primary principles of sampling and measurement design, then describing how those combine into what is labeled as the “boundary specification problem” for social network research. We accompany these definitions with examples of how these elements are applied across ego-, partial- and complete- network designs. Next, the chapter turns to the primary ways that network data have been evaluated, highlighting both the implications of those evaluations for their use in network analyses, and various strategies for how the identified limitations can be leveraged for optimal data and analytic quality. The chapter concludes by addressing some of the ethical considerations that are unique to the gathering and analyses of social network data.

During the past 30 years, research on the global AIDS pandemic and on social networks has coevolved. Insights from social networks literature have advanced our understandings of AIDS; simultaneously, key empirical insights from the AIDS literature have furthered the development of social network research—especially methodologically. We elaborate on this reciprocal relationship, identifying some of the key developments and future directions for research on AIDS and on social networks generally. From existing literatures, we discuss how (i) social networks analysis was central to early attempts to understand the spread of HIV through sexual and needle-sharing relationships; (ii) subsequent prevention efforts leveraged similar insights to different ends; (iii) social networks have been crucial in understanding patterns of care for people living with HIV/AIDS; and (iv) the structural composition of networks across international, organizational, and individual levels highlights the epidemic's global implications in ways that extend far beyond epidemiology. We contend that future research must integrate recent developments from both fields in order advance understandings. Among these, we identify as most promising: (i) a move from static modeling approaches toward research emphasizing the dynamic properties of networks; (ii) a shifting focus from single networks in isolation (e.g., sexual transmission networks) to the analysis of multiplex networks (i.e., those involving multiple relationship types represented simultaneously); and (iii) an acknowledgment—conceptual and methodological—of the “vertical” embeddedness of networks. Continued advances in this area will require the gathering of high quality social network data specifically designed to address such questions. Keywords: AIDS ; HIV ; social networks; social support; international aid; NGOs ; multiplexity; network dynamics

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.

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.

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” human immunodeficiency virus (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. The authors compare cross-links to other respondents on sociodemographic characteristics and network properties using bivariate and multivariate adjusted statistics. The authors 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.

In this visualization, we demonstrate how to use radar plots to represent the class-specific posterior response probabilities from latent class analysis results. These plots allow for a simple representation of the class differences in the distributions across the modeled indicators. We demonstrate the utility of this approach with results from a published model of women’s employment and family life circumstances. In doing so, we demonstrate how to avoid some of the pitfalls common to radar plots and provide example code to allow other researchers to readily adapt this approach to present their own results.

The popular image of the African American National Basketball Association (NBA) player as rising from the ‘ghetto’ to international fame and fortune misleads academics and publics alike. This false image is fueled, in part, by critical shortcomings in empirical research on the relationship between race, sport, and occupational mobility: these studies have not adequately examined differences in social class and family structure backgrounds across, and especially within, racial groups. To address this problem, we empirically investigate how the intersection of race, social class and family structure background influences entry into the NBA. Information on social class and family structure background for a subpopulation of NBA players ( N = 155) comes from 245 articles published in local, regional and national newspapers between 1994 and 2004. We find that, after accounting for methodological problems common in newspaper data, most NBA players come from relatively advantaged social origins and African Americans from disadvantaged social origins have lower odds of being in the NBA than African American and white players from relatively advantaged origins. A discussion of the implications of these findings for academics and publics concludes the article.

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.

While women represent the vast majority of participants in religious organizations in the United States, their participation in top leadership positions within Christian congregations remains remarkably low. In this article, the author uses the National Congregations Study to examine the situations that lead to this “stained glass ceiling” effect, prohibiting women from attaining top congregational leadership positions. The author also investigates similar barriers that exist at other levels of congregational leadership. The results suggest that while a queue-like process appears, the specifically religious nature of these organizations produces barriers that are quite different from the traditional glass ceiling conceptualization.

This visualization provides a dynamic representation of the microsteps involved in modeling network and behavior change with a stochastic actor-based model. This video illustrates how (1) observed time is broken up into a series of simulated microsteps and (2) these microsteps serve as the opportunity for actors to change their network ties or behavior. The example model comes from a widely used tutorial, and we provide code to allow for adapting the visualization to one’s own model.

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.

Brewer Potterat Roberts and Brody (BPRB) provide the latest in a series of papers encouraging researchers to explore nonsexual routes of human immunodeficiency virus (HIV) transmission in sub-Saharan Africa (SSA). Whereas recent findings demonstrate that circumcision provides a substantial protective effect against contracting HIV BPRB suggest tempering the enthusiasm for any interventions based on these findings until hygienic means to obtaining circumcisions can be guaranteed. They highlight levels of HIV prevalence among self-reported virgins in several SSA countries and assess variation in these countries in light of male and female circumcision practices - which they suggest add to the mounting evidence supporting iatrogenic transmission routes. We agree that medical practitioners should take care in implementing any new strategies (i.e. hygienic circumcision should be the goal not just circumcision). Furthermore we recognize that identifying routes of HIV transmission in SSA is an empiric question demanding rigorous exploration - that transmission routes should not be a foregone conclusion. But in light of our experience collecting data in this context and assessing data quality we contend that the evidence in BPRB calls for an alternate interpretation. (excerpt)

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 upon 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 co-evolution 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.