Geographical patterns of social cohesion drive disparities in early COVID infection hazard.

The uneven spread of COVID-19 has resulted in disparate experiences for marginalized populations in urban centers. Using computational models, we examine the effects of local cohesion on COVID-19 spread in social contact networks for the city of San Francisco, finding that more early COVID-19 infections occur in areas with strong local cohesion. This spatially correlated process tends to affect Black and Hispanic communities more than their non-Hispanic White counterparts. Local social cohesion thus acts as a potential source of hidden risk for COVID-19 infection.

Comparison of Landmark-Guided Versus Fluoroscopy-Guided Cerebrospinal Fluid Drain-Related Complications After Aortic Repairs.

OBJECTIVE: Cerebrospinal fluid drains (CSFDs) are efficacious in preventing spinal cord injury after thoracic or thoracoabdominal aortic repair with extensive coverage. Increasingly, fluoroscopy is used to guide placement instead of the traditional landmark-based approach, but it is unknown which approach is associated with fewer complications. DESIGN: A retrospective cohort study. SETTING: In the operating room. PARTICIPANTS: Patients having undergone thoracic or thoracoabdominal aortic repair with a CSFD over a 7-year period at a single center. INTERVENTIONS: No intervention. MEASUREMENTS AND MAIN RESULTS: Groups were reviewed and statistically compared with respect to baseline characteristics, ease of CSFD placement, and major and minor complications directly related to placement. A total of 150 CSFDs were placed with landmark guidance as opposed to 95 with fluoroscopy guidance. Compared to the landmark group, patients with fluoroscopy-guided CSFDs were older (p < 0.008), had lower American Society of Anesthesiologists physical status scores (p = 0.008), required fewer CSFD placement attempts (p = 0.011), had the CSFD in place for longer duration (p < 0.001), and had a similar incidence of CSFD-related complications (p > 0.999). Composites of both major (4.5% of cases) and minor CSFD-related complications (6.1% of cases), the primary outcomes of the study, occurred with similar incidences between the 2 groups (p > 0.999 for both comparisons) after adjusting potential confounders. CONCLUSIONS: In patients undergoing thoracic or thoracoabdominal aortic repairs, there were no significant differences in the risk of major and minor CSFD-related complications between fluoroscopic guidance and the landmark approach. Although the authors' institution is a high-volume center for this type of procedure, the study was limited by a small sample size. Hence, regardless of the technique used for the placement of CSFD, the risks related to the placement should be balanced carefully against the potential benefits resulting from spinal cord injury prevention. Fluoroscopy-aided insertion of CSFD requires fewer attempts and, hence, may be better tolerated by patients.

Spatial heterogeneity can lead to substantial local variations in COVID-19 timing and severity.

Standard epidemiological models for COVID-19 employ variants of compartment (SIR or susceptible-infectious-recovered) models at local scales, implicitly assuming spatially uniform local mixing. Here, we examine the effect of employing more geographically detailed diffusion models based on known spatial features of interpersonal networks, most particularly the presence of a long-tailed but monotone decline in the probability of interaction with distance, on disease diffusion. Based on simulations of unrestricted COVID-19 diffusion in 19 US cities, we conclude that heterogeneity in population distribution can have large impacts on local pandemic timing and severity, even when aggregate behavior at larger scales mirrors a classic SIR-like pattern. Impacts observed include severe local outbreaks with long lag time relative to the aggregate infection curve, and the presence of numerous areas whose disease trajectories correlate poorly with those of neighboring areas. A simple catchment model for hospital demand illustrates potential implications for health care utilization, with substantial disparities in the timing and extremity of impacts even without distancing interventions. Likewise, analysis of social exposure to others who are morbid or deceased shows considerable variation in how the epidemic can appear to individuals on the ground, potentially affecting risk assessment and compliance with mitigation measures. These results demonstrate the potential for spatial network structure to generate highly nonuniform diffusion behavior even at the scale of cities, and suggest the importance of incorporating such structure when designing models to inform health care planning, predict community outcomes, or identify potential disparities.

Insight into Selecting Adolescents for Drinking Intervention Programs: a Simulation Based on Stochastic Actor-Oriented Models.

Adolescent drinking remains a prominent public health and socioeconomic issue in the USA with costly consequences. While numerous drinking intervention programs have been developed, there is little guidance whether certain strategies of participant recruitment are more effective than others. The current study aims at addressing this gap in the literature using a computer simulation approach, a more cost-effective method than employing actual interventions. We first estimate stochastic actor-oriented models for two schools from the National Longitudinal Study of Adolescent to Adult Health (Add Health). We then employ different strategies for selecting adolescents for the intervention (either based on their drinking levels or their positions in the school network) and simulate the estimated model forward in time to assess the aggregated level of drinking in the school at a later time point. The results suggest that selecting moderate or heavy drinkers for the intervention produces better results compared to selecting casual or light drinkers. The intervention results are improved further if network position information is taken into account, as selecting drinking adolescents with higher in-degree or higher eigenvector centrality values for intervention yields the best results. Results from this study help elucidate participant selection criteria and targeted network intervention strategies for drinking intervention programs in the USA.

Neighborhood change from the bottom Up: What are the determinants of social distance between new and prior residents?

An important source of neighborhood change occurs when there is a turnover in the housing unit due to residential mobility and the new residents differ from the prior residents based on socio-demographic characteristics (what we term social distance). Nonetheless, research has typically not asked which characteristics explain transitions with higher social distance based on a number of demographic dimensions. We explore this question using American Housing Survey data from 1985 to 2007, and focus on instances in which the prior household moved out and is replaced by a new household. We focus on four key characteristics for explaining this social distance: the type of housing unit, the age of the housing unit, the length of residence of the exiting household, and the crime and social disorder in the neighborhood. We find that transitions in the oldest housing units and for the longest tenured residents result in the greatest amount of social distance between new and prior residents, implying that these transitions are particularly important for fostering neighborhood socio-demographic change. The results imply micro-mechanisms at the household level that might help explain net change at the neighborhood level.

How great and how good?: Third places, neighbor interaction, and cohesion in the neighborhood context.

Though Ray Oldenburg's (1989) notion of "third places", or places conducive to sociality outside of the realms of home and work, has received both scholarly and popular attention over the past several decades, many of the author's central claims remain empirically untested. The present study considers the association between neighborhood third places, cohesion and neighbor interaction. Drawing on various literatures regarding interaction in public space and neighborhood use-value, we consider how the role of third places might vary according to neighborhood socioeconomic context. Using data from Wave I of the Los Angeles Family and Neighborhood Study (LAFANS) and data on third places from the point-based business data of ReferenceUSA, we test the effect of third places on cohesion and neighbor interaction across neighborhood poverty strata. We find support for the hypothesis that third places are associated with greater cohesion and neighbor interaction, and that neighbor interaction mediates the relationship between third places and cohesion in poor neighborhoods.

Fight or flight? Crime as a driving force in business failure and business mobility.

A growing body of research has documented the consequences of neighborhood crime for a myriad of individual, household, and community outcomes. Given that neighborhood businesses figure into the link between neighborhood structure and crime as sources of employment or sites for neighbor interaction, the present study examines the extent to which neighborhood crime is associated with the survival, mobility, and destination locations of businesses in the subsequent year. Using business data from Reference USA (Infogroup, 2015) and crime data from the Southern California Crime Study (SCCS) we assess this question for neighborhoods across cities in the Southern California region. We find that in general, higher violent and property crime are significantly associated with both business failure and mobility, and that higher crime in a destination neighborhood reduces the likelihood that a business locates there. We also present findings specific to industries, and discuss the implications of our findings for future research.

Parks as crime inhibitors or generators: Examining parks and the role of their nearby context.

Although neighborhood studies often focus on the presence of some particular entity and its consequences for a variety of local processes, a frequent limitation is the failure to account more broadly for the local context. This paper therefore examines the role of parks for community crime, but contributes to the literature by testing whether the context of land uses and demographics nearby parks moderate the parks and crime relationship. A key feature of our approach is that we also test how these characteristics explain crime in the park, nearby the park, and in other neighborhoods in the city with data from nine cities across the United States (N = 109,808 blocks). We use multilevel Poisson and negative binomial regressions to test our ideas for six types of street crime. Our findings show that nearby land uses and socio-demographic characteristics are a key driver of crime being located within the park or nearby the park. Our results also show a clear distance decay pattern for the impact of various land uses and socio-demographics nearby parks. The results emphasize a need for research to consider the broader socio-spatial context in which crime generators/inhibitors are embedded.

Growing pains or appreciable gains? Latent classes of neighborhood change, and consequences for crime in Southern California neighborhoods.

This study explored the dynamic nature of neighborhoods using a relatively novel approach and data source. By using a nonparametric holistic approach of neighborhood change based on latent class analysis (LCA), we have explored how changes in the socio-demographic characteristics of residents, as well as home improvement and refinance activity by residents, are related to changes in neighborhood crime over a decade. Utilizing annual home mortgage loan data in the city of Los Angeles from the years 2000-2010, we 1) conducted principle components factor analyses using measures of residential in-migration and home investment activities; 2) estimated LCA models to identify classes of neighborhoods that shared common patterns of change over the decade; 3) described these 11 classes; 4) estimated change-score regression models to assess the relationship of these classes with changing crime rates. The analyses detected six broad types of neighborhood change: 1) stability; 2) urban investors; 3) higher-income home buyers; 4) in-mover oscillating; 5) oscillating refinance; 6) mixed-trait. The study describes the characteristics of each of these classes, and how they are related to changes in crime rates over the decade.

Problems, perceptions and actions: An interdependent process for generating informal social control.

Using two waves of survey data for residents in neighborhoods in Brisbane, this study explores the interdependent relationship between residents' perceptions of neighboring, cohesion, collective efficacy, neighborhood disorder, and the actions they take to address these problems. Our longitudinal results show that residents' perceived severity of a problem helps explain engaging in activity to address the problem. People loitering appeared to be the most galvanizing problem for residents, but had particularly deleterious effects on perceptions of cohesion and collective efficacy. We also find that residents who perceive more neighboring in their local area engage in more public and parochial social control activity and residents who live in collectively efficacious neighborhoods are more likely to engage in parochial social control action. Furthermore, residents who themselves perceive more collective efficacy in the neighborhood engage in more parochial or public social control during the subsequent time period. Importantly, we find strong evidence that residents update their sense of collective efficacy. Perceiving more problems in the neighborhood, and perceiving that these problems are increasing, reduced perceptions of neighboring and collective efficacy over time.

Perceptions as the crucial link? The mediating role of neighborhood perceptions in the relationship between the neighborhood context and neighborhood cohesion.

This study examines the effects of neighborhood racial in-group size, economic deprivation and the prevalence of crime on neighborhood cohesion among U.S. whites. We explore to what extent residents' perceptions of their neighborhood mediate these macro-micro relationships. We use a recent individual-level data set, the American Social Fabric Study (2012/2013), enriched with contextual-level data from the U.S. Census Bureau (2010) and employ multi-level structural equation models. We show that the racial in-group size is positively related to neighborhood cohesion and that neighborhood cohesion is lower in communities with a high crime rate. Individuals' perceptions of the racial in-group size partly mediate the relationship between the objective racial in-group size and neighborhood cohesion. Residents' perceptions of unsafety from crime also appear to be a mediating factor, not only for the objective crime rate but also for the objective racial in-group size. This is in line with our idea that racial stereotypes link racial minorities to crime whereby neighborhoods with a large non-white population are perceived to be more unsafe. Residents of the same neighborhood differ in how they perceive the degree of economic decay of the neighborhood and this causes them to evaluate neighborhood cohesion differently, however perceptions of neighborhood economic decay do not explain the link between the objective neighborhood context and neighborhood cohesion.

Peer Influence, Peer Selection and Adolescent Alcohol Use: a Simulation Study Using a Dynamic Network Model of Friendship Ties and Alcohol Use.

While studies suggest that peer influence can in some cases encourage adolescent substance use, recent work demonstrates that peer influence may be on average protective for cigarette smoking, raising questions about whether this effect occurs for other substance use behaviors. Herein, we focus on adolescent drinking, which may follow different social dynamics than smoking. We use a data-calibrated Stochastic Actor-Based (SAB) Model of adolescent friendship tie choice and drinking behavior to explore the impact of manipulating the size of peer influence and selection effects on drinking in two school-based networks. We first fit a SAB Model to data on friendship tie choice and adolescent drinking behavior within two large schools (n = 2178 and n = 976) over three time points using data from the National Longitudinal Study of Adolescent to Adult Health. We then alter the size of the peer influence and selection parameters with all other effects fixed at their estimated values and simulate the social systems forward 1000 times under varying conditions. Whereas peer selection appears to contribute to drinking behavior similarity among adolescents, there is no evidence that it leads to higher levels of drinking at the school level. A stronger peer influence effect lowers the overall level of drinking in both schools. There are many similarities in the patterning of findings between this study of drinking and previous work on smoking, suggesting that peer influence and selection may function similarly with respect to these substances.

Studying neighborhood crime across different macro spatial scales: The case of robbery in 4 cities.

Whereas there is a burgeoning literature focusing on the spatial distribution of crime events across neighborhoods or micro-geographic units in a specific city, the present study expands this line of research by selecting four cities that vary across two macro-spatial dimensions: population in the micro-environment, and population in the broader macro-environment. We assess the relationship between measures constructed at different spatial scales and robbery rates in blocks in four cities: 1) San Francisco (high in micro- and macro-environment population); 2) Honolulu (high in micro- but low in macro-environment population); 3) Los Angeles (low in micro- but high in macro-environment population); 4) Sacramento (low in micro- and macro-environment population). Whereas the socio-demographic characteristics of residents further than ½ mile away do not impact robbery rates, the number of people up to 2.5 miles away are related to robbery rates, especially in the two cities with smaller micro-environment population, implying a larger spatial scale than is often considered. The results show that coefficient estimates differ somewhat more between cities differing in micro-environment population compared to those differing based on macro-environment population. It is therefore necessary to consider the broader macro-environment even when focusing on the level of crime across neighborhoods or micro-geographic units within an area.

Multiple Imputation for Missing Edge Data: A Predictive Evaluation Method with Application to Add Health.

Recent developments have made model-based imputation of network data feasible in principle, but the extant literature provides few practical examples of its use. In this paper we consider 14 schools from the widely used In-School Survey of Add Health (Harris et al., 2009), applying an ERGM-based estimation and simulation approach to impute the network missing data for each school. Add Health's complex study design leads to multiple types of missingness, and we introduce practical techniques for handing each. We also develop a cross-validation based method - Held-Out Predictive Evaluation (HOPE) - for assessing this approach. Our results suggest that ERGM-based imputation of edge variables is a viable approach to the analysis of complex studies such as Add Health, provided that care is used in understanding and accounting for the study design.

Collective efficacy: How is it conceptualized, how is it measured, and does it really matter for understanding perceived neighborhood crime and disorder?

Building on the insights of the self-efficacy literature, this study highlights that collective efficacy is a collective perception that comes from a process. This study emphasizes that 1) there is updating, as there are feedback effects from success or failure by the group to the perception of collective efficacy, and 2) this updating raises the importance of accounting for members' degree of uncertainty regarding neighborhood collective efficacy. Using a sample of 113 block groups in three rural North Carolina counties, this study finds evidence of updating as neighborhoods perceiving more crime or disorder reported less collective efficacy at the next time point. Furthermore, collective efficacy was only associated with lower perceived disorder at the next time point when it occurred in highly cohesive neighborhoods. Finally, neighborhoods with more perceived disorder and uncertainty regarding collective efficacy at one time point had lower levels of collective efficacy at the next time point, illustrating the importance of uncertainty along with updating.

Simulating Dynamic Network Models and Adolescent Smoking: The Impact of Varying Peer Influence and Peer Selection.

We used a stochastic actor-based approach to examine the effect of peer influence and peer selection--the propensity to choose friends who are similar--on smoking among adolescents. Data were collected from 1994 to 1996 from 2 schools involved in the National Longitudinal Study of Adolescent to Adult Health, with respectively 2178 and 976 students, and different levels of smoking. Our experimental manipulations of the peer influence and selection parameters in a simulation strategy indicated that stronger peer influence decreased school-level smoking. In contrast to the assumption that a smoker may induce a nonsmoker to begin smoking, adherence to antismoking norms may result in an adolescent nonsmoker inducing a smoker to stop smoking and reduce school-level smoking.

Research Note: The consequences of different methods for handling missing network data in Stochastic Actor Based Models.

Although stochastic actor based models (e.g., as implemented in the SIENA software program) are growing in popularity as a technique for estimating longitudinal network data, a relatively understudied issue is the consequence of missing network data for longitudinal analysis. We explore this issue in our research note by utilizing data from four schools in an existing dataset (the AddHealth dataset) over three time points, assessing the substantive consequences of using four different strategies for addressing missing network data. The results indicate that whereas some measures in such models are estimated relatively robustly regardless of the strategy chosen for addressing missing network data, some of the substantive conclusions will differ based on the missing data strategy chosen. These results have important implications for this burgeoning applied research area, implying that researchers should more carefully consider how they address missing data when estimating such models.

Endplate changes following discectomy: natural history and associations between imaging and clinical data.

PURPOSE: Some patients will experience post-operative back pain following lumbar discectomy, and the potential sources for that pain are poorly understood. One potential source is the vertebral endplates. The goal of this study was to document the changes that occur in lumbar endplates following discectomies, and to assess associations between endplate changes and clinical outcomes. METHODS: Changes in lumbar endplates and discs were assessed from X-rays, CT and MRI exams by comparing preoperative imaging with imaging obtained at yearly intervals up to 5 years. 260 endplates in 137 patients with single-level herniation and discectomy were analyzed. The geometry of osseous defects in the endplates was measured from the CT exams, and marrow and disc changes adjacent to endplates were assessed from the MRI exams. Clinical outcome assessments were collected at each time point. Descriptive statistics were used to describe endplate defect sizes, and logistic regression and analysis of variance were used to identify potential associations between endplate and vertebral body changes and clinical outcomes. RESULTS: Approximately 14 % of the endplates had osseous defects prior to surgery. After surgery, 24 % of inferior and 43 % of superior endplates had defects. Change occurred within the first year and remained relatively constant over the next few years. Disc signal intensity worsened and disc height decreased following surgery. New Modic changes were also observed. None of these changes were associated with having achieved a clinically significant improvement in outcome scores. The follow-up rates were low at the later time points and significant associations cannot be ruled out. CONCLUSIONS: This study documents lesion characteristics in detail and supports that osseous defects in the endplates at the level of a lumbar discectomy may be a relatively common finding following surgery, along with disc height loss, loss of disc signal intensity, and Modic changes. The clinical significance of these imaging findings could not be conclusively determined in this study.

Quantitative Analysis of Cervical Flexion-Extension Radiographs in Rheumatoid Arthritis Patients.

STUDY DESIGN: Diagnostic retrospective case series. OBJECTIVE: To evaluate cervical intersegmental motion in rheumatoid arthritis patients using specialized tracking software (QMA) and compare the findings with a previously published cohort of "normal" subjects. SUMMARY OF BACKGROUND DATA: Rheumatoid arthritis follows 3 patterns of cervical involvement, atlantoaxial subluxation, atlantoaxial impaction, and subaxial subluxation. Deformities present are sometimes considered "unstable" to the point where surgery can be recommended based on the interpretation of cervical radiographs. METHODS: Cervical flexion-extension radiographs of 99 subjects with rheumatoid arthritis were evaluated. Angular and translational segmental motions were determined at each level using specialized tracking software. Findings were compared with previously published normative data using the same device. RESULTS: Relative to controls, patients with rheumatoid arthritis demonstrated significantly less overall sagittal motion. Segmental analysis at C1-C2 demonstrated a 10% prevalence of dynamic motion outside the 95% confidence interval for "normal" patients. In contrast, segmental analysis at C2-C7 demonstrated no intersegmental motion outside the 95% confidence interval for "normal" subjects. CONCLUSIONS: In patients with rheumatoid arthritis, abnormal motion at C1-C2 was consistent with truly dynamic deformity and should be closely evaluated. Conversely, subaxial subluxations, although frequently present, were relatively fixed deformities and in most cases, may not represent an unstable condition.

Efficacy of MRI for assessment of spinal trauma: correlation with intraoperative findings.

STUDY DESIGN: Observational diagnostic study on consecutive patients. OBJECTIVE: To assess the efficacy of magnetic resonance imaging (MRI) for detecting spinal soft tissue injury after acute trauma using intraoperative findings as a reference standard. SUMMARY OF BACKGROUND DATA: Recognizing injuries to spinal soft tissue structures is critical for proper decision making and management for blunt trauma victims. Although MRI is considered the gold standard for imaging of soft tissues, its ability to identify specific components of soft tissue damage in acute spine trauma patients is poorly documented and controversial. METHODS: Intraoperative findings were recorded for 21 acute spinal trauma patients (study group) and 14 nontraumatic spinal surgery patients (control group). Preoperative MRI's were evaluated randomly and blindly by 2 neuroradiologists. MRI and intraoperative findings were compared. By using the intraoperative findings as the reference standard, sensitivity, specificity, positive and negative predictive values of MRI in detecting spinal soft tissue injury were determined. RESULTS: MRI was 100% sensitive and specific in detecting injury to the anterior longitudinal ligament. MRI was moderately sensitive (80%) but highly specific (100%) for injury to the posterior longitudinal ligament. In contrast, MRI was highly sensitive but less specific in detecting injury to paraspinal muscles (100%, 77%), intervertebral disk (100%, 71%), and interspinous ligament (100%, 64%). MRI was moderately sensitive and specific in detecting ligamentum flavum injury (80% and 86.7%) but poorly sensitive for facet capsule injury (62.5%). CONCLUSIONS: MRI demonstrated high sensitivity for spinal soft tissue injuries. However, MRI showed a definite trend to overestimate interspinous ligament, intervertebral disk, and paraspinal muscle injuries. On the basis of these results, we would consider MRI to be a useful tool for spine clearance after trauma. Conversely, caution should be applied when using MRI for operative decision making due to its less predictable specificity.