Concern Regarding the HIV/AIDS epidemic and Individual Childbearing

I examine if and how rural Malawians alter their childbearing as a consequence of concern regarding the HIV/AIDS epidemic. The paper is motivated by the debate which opposes two ideas regarding the childbearing effect of high HIV infection rates and heightened AIDS mortality: one, the acceleration of childbearing as individuals find themselves under time pressure to meet their reproductive goals and two, the decrease in childbearing as parents opt to avoid the risk of transmitting the virus. I find some evidence to support the hypothesis of reduced childbearing in the presence of high levels of worry regarding HIV/AIDS. However, this finding does not seem to apply to younger women, who are perhaps subject to relatively stronger childbearing promoting norms.Africa - South of the Sahara, AIDS/HIV, childbearing, concern, fertility, Malawi, self-perceptions, worry

Close kin influences on fertility behavior

Family members are uniquely situated to influence the decision-making of their kin in nearly every facet of life. We examine the importance of social interactions in fertility outcomes by assessing family members’ scope of influence on their fellow kin’s fertility behavior. With the unique KASS genealogical dataset from eight countries in Europe, we study the effects of family members’ fertility outcomes on individual fertility to assess the presence and the extent of inter-generational transmission of fertility behaviors and siblings’ influences on fertility outcomes. We find only limited evidence of the inter-generational transmission of fertility behaviors, but a relatively important effect of siblings for individual fertility. Rather than parents, siblings’ influences appear to constitute the largest share of familial influences on fertility outcomes. We also find that among siblings, women’s fertility is more subject to the influences of their sisters. These findings indicate the relative importance of close kin influences on individual fertility and demonstrate the consequences of family structure for fertility change.Europe, family demography, family size, fertility, kinship, sisters

Youth Incarceration, Health, and Length of Stay

For youth from marginalized communities, the pathway into the juvenile justice system occurs against a backdrop of disproportionately high levels of stress, complex trauma, and adverse childhood experiences. Despite overall reductions in the percentage of youth in confinement from recent state-level reforms, the lengths of stay for many youth often exceed evidence-based timelines, as well as a state’s own guidelines and criteria. This occurs despite a large and growing body of empirical research that documents the health status of system-involved youth and the association between incarceration during adolescence and the range of subsequent health and mental health outcomes in adulthood. Presently, advocates for length of stay reform rely on two primary arguments: recidivism and costs of confinement. This Article argues that this framing misses a critical component, as a better understanding of the linkages between length of stay, health, and mental health are essential for achieving the foundational goals of the juvenile justice system—i.e., rehabilitation, decreased recidivism, and improved community reintegration. Through an examination of juvenile sentencing typologies, release decision-making, and empirical research on the health and mental health needs of at-risk and system-involved youth, this Article aims to fill this gap and expand current lines of debate, discourse, and advocacy.

Disrupting Illicit Supply Networks: New Applications of Operations Research and Data Analytics to End Modern Slavery

Report from a 2017 National Science Foundation workshop on promising research directions for applications of operations research and data analytics toward the disruption of illicit supply networks like human trafficking. The workshop was funded by the NSF’s Operations Engineering (ENG) and the Law & Social Sciences Program (SBE) under grant # CMMI-1726895. The report addresses the opportunity to apply advances from the fields of operations research, management science, analytics, machine learning, and data science toward the development of disruptive interventions against illicit networks. Such an extension of the current research agenda for trafficking would move understanding of such dynamic systems from descriptive characterization and predictive estimation toward improved dynamic operational control.Bureau of Business Researc

A new approach to hierarchical data analysis: Targeted maximum likelihood estimation for the causal effect of a cluster-level exposure

We often seek to estimate the impact of an exposure naturally occurring or randomly assigned at the cluster-level. For example, the literature on neighborhood determinants of health continues to grow. Likewise, community randomized trials are applied to learn about real-world implementation, sustainability, and population effects of interventions with proven individual-level efficacy. In these settings, individual-level outcomes are correlated due to shared cluster-level factors, including the exposure, as well as social or biological interactions between individuals. To flexibly and efficiently estimate the effect of a cluster-level exposure, we present two targeted maximum likelihood estimators (TMLEs). The first TMLE is developed under a non-parametric causal model, which allows for arbitrary interactions between individuals within a cluster. These interactions include direct transmission of the outcome (i.e. contagion) and influence of one individual's covariates on another's outcome (i.e. covariate interference). The second TMLE is developed under a causal sub-model assuming the cluster-level and individual-specific covariates are sufficient to control for confounding. Simulations compare the alternative estimators and illustrate the potential gains from pairing individual-level risk factors and outcomes during estimation, while avoiding unwarranted assumptions. Our results suggest that estimation under the sub-model can result in bias and misleading inference in an observational setting. Incorporating working assumptions during estimation is more robust than assuming they hold in the underlying causal model. We illustrate our approach with an application to HIV prevention and treatment

Social Networks

We survey the literature on social networks by putting together the economics, sociological and physics/applied mathematics approaches, showing their similarities and differences. We expose, in particular, the two main ways of modeling network formation. While the physics/applied mathematics approach is capable of reproducing most observed networks, it does not explain why they emerge. On the contrary, the economics approach is very precise in explaining why networks emerge but does a poor job in matching real-world networks. We also analyze behaviors on networks, which take networks as given and focus on the impact of their structure on individuals’ outcomes. Using a game-theoretical framework, we then compare the results with those obtained in sociology.random graph, game theory, centrality measures, network formation, weak and strong ties

Women and health and well-being

The paper argues broadly for recognition of a number of principles essential to establishing a firm basis upon which to redress health inequities for women: It is impossible to understand women’s health outcomes without also understanding the social context of women’s lives; International human rights and cultural conventions are a powerful mechanism for mobilising action on women’s health and well-being; Gender power relations impact on social and health outcomes for women; The factor of gender accounts for the fundamental differences between women’s and men’s experience of health issues. As such, improvement of women’s health care necessitates affording high priority to gender issues in all aspects of health care; In determining health and illness outcomes, health systems have a responsibility to acknowledge the importance of gendered social relations, social factors, and conditions of living; Understanding the ways in which gender impacts on chronic health conditions will be enhanced by explicitly mainstreaming gender in the process of informing gender-specific services; It is vital to infuse gender analysis, gender sensitive research, women’s perspectives, and gender equity goals into policies, projects and institutional ways of working

Social Networks

We survey the literature on social networks by putting together the economics, sociological and physics/applied mathematics approaches, showing their similarities and differences. We expose, in particular, the two main ways of modeling network formation. While the physics/applied mathematics approach is capable of reproducing most observed networks, it does not explain why they emerge. On the contrary, the economics approach is very precise in explaining why networks emerge but does a poor job in matching real-world networks. We also analyze behaviors on networks, which take networks as given and focus on the impact of their structure on individuals’ outcomes. Using a game-theoretical framework, we then compare the results with those obtained in sociology.Random Graph; Game Theory; Centrality Measures; Network Formation; Weak