Correlations and forecast of death tolls in the Syrian conflict

The Syrian armed conflict has been ongoing since 2011 and has already caused thousands of deaths. The analysis of death tolls helps to understand the dynamics of the conflict and to better allocate resources and aid to the affected areas. In this article, we use information on the daily number of deaths to study temporal and spatial correlations in the data, and exploit this information to forecast events of deaths. We found that the number of violent deaths per day in Syria varies more widely than that in England in which non-violent deaths dominate. We have identified strong positive auto-correlations in Syrian cities and non-trivial cross-correlations across some of them. The results indicate synchronization in the number of deaths at different times and locations, suggesting respectively that local attacks are followed by more attacks at subsequent days and that coordinated attacks may also take place across different locations. Thus the analysis of high temporal resolution data across multiple cities makes it possible to infer attack strategies, warn potential occurrence of future events, and hopefully avoid further deaths

Random Convex Hulls and Extreme Value Statistics

In this paper we study the statistical properties of convex hulls of $N$ random points in a plane chosen according to a given distribution. The points may be chosen independently or they may be correlated. After a non-exhaustive survey of the somewhat sporadic literature and diverse methods used in the random convex hull problem, we present a unifying approach, based on the notion of support function of a closed curve and the associated Cauchy's formulae, that allows us to compute exactly the mean perimeter and the mean area enclosed by the convex polygon both in case of independent as well as correlated points. Our method demonstrates a beautiful link between the random convex hull problem and the subject of extreme value statistics. As an example of correlated points, we study here in detail the case when the points represent the vertices of $n$ independent random walks. In the continuum time limit this reduces to $n$ independent planar Brownian trajectories for which we compute exactly, for all $n$, the mean perimeter and the mean area of their global convex hull. Our results have relevant applications in ecology in estimating the home range of a herd of animals. Some of these results were announced recently in a short communication [Phys. Rev. Lett. {\bf 103}, 140602 (2009)].Comment: 61 pages (pedagogical review); invited contribution to the special issue of J. Stat. Phys. celebrating the 50 years of Yeshiba/Rutgers meeting

Can mental health treatments help prevent or reduce intimate partner violence in low- and middle-income countries? A systematic review

Background Epidemiological research suggests an interrelationship between mental health problems and the (re)occurrence of intimate partner violence (IPV). However, little is known about the impact of mental health treatments on IPV victimization or perpetration, especially in low- and middle-income countries (LMIC). Methods We conducted a systematic review to identify prospective, controlled studies of mental health treatments in LMIC. We defined ‘mental health treatment’ as an intervention for individuals experiencing mental ill health (including substance misuse) including a substantial psychosocial or pharmacological component. Studies had to measure a mental health and IPV outcome. We searched across multi-disciplinary databases using a structured search strategy. Screening of title/abstracts and full-text eligibility assessments were conducted by two researchers independently, data were extracted using a piloted spreadsheet, and a narrative synthesis was generated. Results We identified seven studies reported in 11 papers conducted in five middle-income countries. With the exception of blinding, studies overall showed acceptable levels of risk of bias. Four of the seven studies focused on dedicated mental health treatments in various populations, including: common mental disorders in earthquake survivors; depression in primary care; alcohol misuse in men; and alcohol misuse in female adult sex workers. The dedicated mental health treatments targeting depression or alcohol misuse consistently reduced levels of these outcomes. The two studies targeting depression also reduced short-term IPV, but no IPV benefits were identified in the two alcohol-focused studies. The other three studies evaluated integrated interventions, in which a focus on substance misuse was part of efforts to reduce HIV/AIDS and violence against particularly vulnerable women. In contrast to the dedicated mental health interventions, the integrated interventions did not consistently reduce mental ill health or alcohol misuse compared to control conditions. Conclusions Too few studies have been conducted to judge whether mental health treatments may provide a beneficial strategy to prevent or reduce IPV in LMIC. Key future research questions include: whether promising initial evidence on the effects of depression interventions on reducing IPV hold more broadly, the required intensity of mental health components in integrated interventions, and the identification of mechanisms of IPV that are amenable to mental health intervention

Myopic Misery: Maternal Depression, Child Investments, and the Neurobiological Poverty Trap

In this paper, I explore in an overlapping generations framework, a mechanism motivating a neurobiological poverty trap. Poverty causes stress and depression in individuals susceptible to depression. Poor and depressed individuals discount the future at a higher rate and invest less in the human capital of their children than mentally healthy or rich individuals. This gene-environment interaction generates a vicious cycle in which poor individuals inherit not only susceptibility to depression but also stress and poverty. I show that a successful one-time intervention has the power to permanently eliminate the neurobiological poverty trap

Socioeconomic mobility and talent utilization of workers from poorer backgrounds: The overlooked importance of within-organization dynamics

Socioeconomic mobility, or the ability of individuals to improve their socioeconomic standing through merit-based contributions, is a fundamental ideal of modern societies. The key focus of societal efforts to ensure socioeconomic mobility has been on the provision of educational opportunities. We review evidence that even with the same education and job opportunities, being born into a poorer family undermines socioeconomic mobility due to processes occurring within organizations. The burden of poorer background might, ceteris paribus, be economically comparable to the gender gap. We argue that in the societal and scientific effort to promote socioeconomic mobility, the key context in which mobility is supposed to happen—organizations—as well as the key part of the life of people striving toward socioeconomic advancement—that as working adults—have been overlooked. We integrate the organizational literature pointing to key within-organizational processes impacting objective (socioeconomic) success with research, some emergent in organizational sciences and some disciplinary, on when, why, and how people from poorer backgrounds behave or are treated by others in the relevant situations. Integrating these literatures generates a novel and useful framework for identifying issues people born into poorer families face as employees, systematizes extant evidence and makes it more accessible to organizational scientists, and allows us to lay the agenda for future organizational scholarshi