Although a growing body of literature emphasizes the role of friendship networks and peer relations for youth involvement in violence and delinquency, little research has examined the role of friendship networks in understanding the varying involvement of different racial‐ethnic groups in violence. Using data from approximately 13,000 respondents to the first two waves of the National Longitudinal Study of Adolescent Health (Add Health), we explore the ability of friendship networks to account for the differential rates of violence among racial‐ethnic groups. In addition, we evaluate whether race moderates the degree to which friendship characteristics predict adolescent violence. Findings indicate significant differences in the structure and behavioral orientation of friendship networks across racial‐ethnic identities. Moreover, incorporating characteristics of friendship networks into multivariate analyses accounts for greater involvement in violence among black and Hispanic youths. Network racial heterogeneity and friends' popularity also emerge as particular network characteristics that operate differently for black and white youth.
Introduction
HIV planning requires granular estimates for the number of people living with HIV (PLHIV), antiretroviral treatment (ART) coverage and unmet need, and new HIV infections by district, or equivalent subnational administrative level. We developed a Bayesian small‐area estimation model, called Naomi, to estimate these quantities stratified by subnational administrative units, sex, and five‐year age groups.
Methods
Small‐area regressions for HIV prevalence, ART coverage and HIV incidence were jointly calibrated using subnational household survey data on all three indicators, routine antenatal service delivery data on HIV prevalence and ART coverage among pregnant women, and service delivery data on the number of PLHIV receiving ART. Incidence was modelled by district‐level HIV prevalence and ART coverage. Model outputs of counts and rates for each indicator were aggregated to multiple geographic and demographic stratifications of interest. The model was estimated in an empirical Bayes framework, furnishing probabilistic uncertainty ranges for all output indicators. Example results were presented using data from Malawi during 2016–2018.
Results
Adult HIV prevalence in September 2018 ranged from 3.2% to 17.1% across Malawi's districts and was higher in southern districts and in metropolitan areas. ART coverage was more homogenous, ranging from 75% to 82%. The largest number of PLHIV was among ages 35 to 39 for both women and men, while the most untreated PLHIV were among ages 25 to 29 for women and 30 to 34 for men. Relative uncertainty was larger for the untreated PLHIV than the number on ART or total PLHIV. Among clients receiving ART at facilities in Lilongwe city, an estimated 71% (95% CI, 61% to 79%) resided in Lilongwe city, 20% (14% to 27%) in Lilongwe district outside the metropolis, and 9% (6% to 12%) in neighbouring Dowa district. Thirty‐eight percent (26% to 50%) of Lilongwe rural residents and 39% (27% to 50%) of Dowa residents received treatment at facilities in Lilongwe city.
Conclusions
The Naomi model synthesizes multiple subnational data sources to furnish estimates of key indicators for HIV programme planning, resource allocation, and target setting. Further model development to meet evolving HIV policy priorities and programme need should be accompanied by continued strengthening and understanding of routine health system data.
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