Browsing by Subject "Network analysis"

Background: Reports from the first monkeypox (MPX) active surveillance program in the Democratic Republic of Congo (DRC) in the 1980s determined that the disease was not of epidemic potential, with R0<1. However, during an active surveillance period from 2005-2007, researchers found a 20-fold increase during the last 30 years. The purpose of this study was to analyze the contact data from 2005-07 and compare characteristics to those of the 1980s, and toassess the change in R0 of MPX. Methods: Contact tracing information and samples from active lesions were collected. Samples were screened by PCR and positive cases were ranked by generation and grouped into chains of transmission according to date of rash onset, contact tracing, and location. R0 was determined using calculations provided in the 1980s study and chain size distribution was compared. Results: Of 1407 suspected cases of MPX investigated in 2005-07, 287 provided contact information with an average of 6.22 (range, 1-20) contacts each. Among the 703 positive cases, 408 distinct chains of transmission were identified. Average chain size was 1.75 cases (range, 1-12), with the longest reaching six generations. The crude secondary attack rate (AR) was 0.092, with an effective R0 of 0.576. Discussion: Contact characteristics and types of contacts differed from those of the 1980s program. This analysis found a higher crude secondary attack rate and effective R0. This could be the result of a higher proportion of unvaccinated contacts, or that the virus is better able to transmit between humans with a more limited amount of contact.

Background: Globally, road traffic injury (RTI) is predicted to become the fifth leading cause of mortality by 2030. In addition to the burden of RTI, multimorbidity (MM) is increasingly becoming a health concern across all age groups. If MM is left unaddressed, individuals suffering from RTI will most likely experience delayed recovery and poorer health outcomes. Thus, there is a need to examines the association between RTI and MM in order to inform post-injury care practices.

Methods: This study is a cross-sectional analysis of the 2013 Brazilian National Health Survey. 60,202 individuals, aged 18 and above, were included in this study. Univariate and bivariate analyses were used to explore the relationship between demographic variables, chronic diseases, MM and RTI. Network analysis was used to identify multimorbidity patterns.

Results: Out of those who had experienced RTI (n=1910), 16.50% have reported having a multimorbid condition. Age, gender, risky alcohol use and regions were key predictors of RTI. Risky alcohol use was one of the direct nodes that connected RTI to other morbidities. Within the road traffic injured population, seven multimorbid communities were identified, with two communities being the most central: the cardio-metabolic morbidities and physical-mental morbidities.

Conclusions: Risky use of alcohol was a key predictor of RTI and a potential mediator in the association between RTI and other morbidities. Given that the temporal association between RTI and MM could not be established in this study, additional studies are needed to further assess the direction of the association between RTI and MM.

In situations of armed violence and insecurity, how do civilians influence the political environment around them? In this dissertation, I present three different studies that broadly engage this question. In concert, the papers presented herein offer new insights on civilians' relationship to armed conflict through a focus on victimization, participation, attitudes on resistance, and the effects of civilian resistance on aggregate levels of violence.

The first study explores the effects of victimization on political participation. I argue that previous answers to this question have overlooked a key variable for predicting civilian behavior: individual level social context. As a step forward in connecting social support networks to behavioral outcomes, I present the kinship network as a novel measure that captures an individual's valuable and private social interactions. I find that survivors of criminal violence with strong ties to kinship networks are most likely to attend political meetings. By highlighting variation in behavior across victims, I challenge previous work which only examines differences in participation between victims and non-victims.

Motivated by the assumption that attitudes are a precursor to action, my second study examines civilian attitudes on the efficacy of resistance in regions of protracted violence. Using an original survey fielded in Mexico, I explore the conditions under which civilians are likely to view nonviolent or violent methods as useful tools for change. I first test whether several demographic factors--age, gender, income, knowledge about civil resistance, and media consumption--influence attitudes toward resistance. Moving beyond these variables, I then test whether perceptions about government responsibility affect these attitudes. Specifically, I argue that civilian attitudes towards resistance methods are informed by which political actor civilians view as responsible for their security problems. I find that the predicted probability of viewing nonviolent action as more effective than violent action increases by 20.8% for those who attribute security responsibility to local authorities, compared to other actors. Using an embedded survey experiment, I then address the empirically relevant question of whether these attitudes about resistance correlate with action. I find that compared to those who do not view resistance as useful, respondents who view nonviolence as effective are "supportive types'' who are more willing than others to support local resistance groups, regardless of the methods these groups employ. Together, these analyses provide important information for civilian organizers seeking to mobilize latent support for resistance. Moreover, they enrich our understanding of the ways in which communities can reduce violence in order to reclaim political control during armed conflicts.

Last, I present an aggregated analysis on the evolution of armed conflict in Mexico. The criminal war in Mexico is extremely complex: Drug Trafficking Organizations, citizens, government agents, amongst others, are all relevant actors within the dynamic evolution of the conflict. Existing research, however, typically ignores the interdependencies inherent to these networks. Using a new collection of machine-coded event data, I generate conflict networks for each year from 2004 to 2010. In doing so, I make three major contributions. First, I offer insights into the potential promise and pitfalls of using machine-coded data for country-level analysis. Next, after cleaning and improving upon the original data, I generate yearly networks, which capture a wide range of violent-related actors. Importantly, I demonstrate how these networks illustrate the interdependent nature of the Mexican conflict and present new insights, such as how government coordination changes in response to cartel violence over time. Finally, I use a latent space approach to identify previously unobservable violence between government actors, criminal groups, and civilians. This research design serves as a platform for future research to investigate the effects of major civilian-led events--such as mass protests--on the evolution of armed conflict.

Ostensibly, BITs are the ideal international treaty. First, until just recently, they almost uniformly came with explicit dispute resolution mechanisms through which countries could face real costs for violation (Montt 2009). Second, the signing, ratification, and violation of them are easily accessible public knowledge. Thus countries presumably would face reputational costs for violating these agreements. Yet, these compliance devices have not dissuaded states from violating these agreements. Even more interestingly, in recent years, both developed and developing countries have moved towards modifying the investor-friendly provisions of these agreements. These deviations from the expectations of the credible commitment argument raise important questions about the field's assumptions regarding the ability of international treaties with commitment devices to effectively constrain state behavior.

The emergence and persistence of communities has long been of interest to social scientists, and the increasingly digital landscape in which these communities exist present some important theoretical and methodological challenges and opportunities. In this dissertation, I develop methods for identifying and characterizing communities on Twitter and examine the kinds of interactions that affect social cohesion. Using the Fat Liberation community as a case study, I find that there is a core set of users engaged in conversations around criticizing conceptions of Fatness, and I observe partitions in the community differentiated by stylistic approaches to discussion rather than topical focus. I next operationalize hypotheses from Randall Collins' Interaction Ritual Chain theory using novel methods for measuring the effects of engaging in particular types of interactions. I find support for several hypotheses generated directly from this theory in online settings and further find that high-status users play a particularly important role in producing group cohesion - a perhaps underplayed aspect of the theory that may be particularly important in online settings. Finally, I build on conflict theories to hypothesize that exposure to toxic interactions will affect social cohesion - particularly when they involve other high-status users. I do not find support for these hypotheses, however, suggesting further work should investigate the role of toxic behavior by accounting for the situational dynamics produced by interactions.

The Arab Spring has renewed scholarly interest in popular protests and nonviolent mobilization against authoritarian rulers. Over the past decade, the bulk of the literature has focused on examining the impact of protest movements on regime transition, while lesser attention was paid to explain why protests emerge initially. Social movements literature has documented rich materials on contentious politics; however, as Tilly, Tarrow, and McAdam (2001) indicated in their seminal work, these traditional approaches work better to explain contention in democracies but less well when it comes to explaining protests in nondemocratic contexts. My dissertation, a suite of three related papers, aims to fill this gap by asking several important questions: Why do citizens risk their lives to protest against the authoritarian governments under the threats of state repression? How does mobilization behaviors interact with state responses (e.g. state repression)? Why do opposition parties participate and mobilize protesters in authoritarian elections? Using new protest event data, I first show that in authoritarian China, politically motivated officials are encouraged to compete in the economic field by extracting local resources, and these efforts often contribute to local protests. Additional evidence also indicates that land expropriation by local governments has become the main source of social grievance in contemporary China. Second, I show that mobilization behaviors and state responses are intrinsically interdependent to each other. I propose a network method to model this interdependence and interactive repertoires of contention. I find that the nodes-as-actions framework I introduce improves our ability to forecast different types of state repression against protesters and helps us examine the processes of conflict escalation and a mutual spiral effect in authoritarian elections. Lastly, I find that anti-government protest mobilization is an oft-used electoral campaign strategy by the opposition to mobilize supporters, gain visibility in state censorship, and signal their strength and commitment to unseating autocratic rulers in authoritarian elections. When the authoritarian incumbent suffers from declining popularity among citizens, it provides a window of opportunity for the opposition candidates to defeat the authoritarian ruler on the ballot by mobilizing anti-regime protesters and encouraging voter turnout. Overall, this dissertation introduces novel theoretical framework and empirical methods to advance our understanding of protest emergence in authoritarian regimes.