Search

Background: Large numbers of young people die yearly due to homicide, but little is known about homicide during adolescence. Research primarily focuses on youth violence among young men and masks important gender-related factors inherent in the adolescent age group. Although young women are less likely to be victims of homicide, violence against women is an important form of violence experienced during adolescence. In this paper, we describe the prevalence of and gender difference in adolescent homicide in South Africa in 2009. Methods: We conducted a retrospective national mortuary-based study to identify all child homicides (boys and girls < 18 years) in 2009 in a proportionate sample of mortuaries. Victim, perpetrator and crime data were collected in three phases: cases were identified from the mortuary register, the autopsy report and from police interviews. In this paper we focus on the adolescent group, aged 10 to 17 years. Findings: We identified 674 (95% CI: 520–823) adolescent homicides for 2009, with more male (520) than female (154) homicides. This gender disparity increased as children aged, with the male homicide rate 27.9/100 000 population (95% CI: 20.3–35.5), nearly 5 times the female rate (4.5:1) of 6.5/ 100 000 population (95% CI: 4.7–8.2) in older adolescents (15–17 year old). Adolescent males were significantly more likely (61.2%) to die in a public space compared to female adolescents (39.3%) but more adolescent females (48.4%) died at home compared to adolescent males (32.9%). Adolescent females (42.1%) were mainly killed by a family member or intimate partner while adolescent males were predominantly (58%) killed by an acquaintance. Conclusion: We found a distinct gender pattern for adolescent homicide in South Africa. This pattern appears to be driven by gender norms that support violence. South Africa requires an investment in developing evidence informed interventions to reduce violence. [ABSTRACT FROM AUTHOR]

TB is rated as one of the world’s deadliest diseases and South Africa ranks 9th out of the 22 countries with hardest hit of TB. Although many pieces of research have been carried out on this subject, this paper steps further by inculcating past knowledge into the model, using Bayesian approach with informative prior. Bayesian statistics approach is getting popular in data analyses. But, most applications of Bayesian inference technique are limited to situations of non-informative prior, where there is no solid external information about the distribution of the parameter of interest. The main aim of this study is to profile people living with TB in South Africa. In this paper, identical regression models are fitted for classical and Bayesian approach both with non-informative and informative prior, using South Africa General Household Survey (GHS) data for the year 2014. For the Bayesian model with informative prior, South Africa General Household Survey dataset for the year 2011 to 2013 are used to set up priors for the model 2014. [ABSTRACT FROM AUTHOR]