HIV Infection-Related Care Outcomes among U.S.-Born and Non-U.S.-Born Blacks with Diagnosed HIV in 40 U.S. Areas: The National HIV Surveillance System, 2016.
Hanna B DemekeAnna S JohnsonHong ZhuZanetta GantWayne A DuffusHazel D DeanPublished in: International journal of environmental research and public health (2018)
HIV care outcomes must be improved to reduce new human immunodeficiency virus (HIV) infections and health disparities. HIV infection-related care outcome measures were examined for U.S.-born and non-U.S.-born black persons aged ≥13 years by using National HIV Surveillance System data from 40 U.S. areas. These measures include late-stage HIV diagnosis, timing of linkage to medical care after HIV diagnosis, retention in care, and viral suppression. Ninety-five percent of non-U.S.-born blacks had been born in Africa or the Caribbean. Compared with U.S.-born blacks, higher percentages of non-U.S.-born blacks with HIV infection diagnosed during 2016 received a late-stage diagnoses (28.3% versus 19.1%) and were linked to care in ≤1 month after HIV infection diagnosis (76.8% versus 71.3%). Among persons with HIV diagnosed in 2014 and who were alive at year-end 2015, a higher percentage of non-U.S.-born blacks were retained in care (67.8% versus 61.1%) and achieved viral suppression (68.7% versus 57.8%). Care outcomes varied between African- and Caribbean-born blacks. Non-U.S.-born blacks achieved higher care outcomes than U.S.-born blacks, despite delayed entry to care. Possible explanations include a late-stage presentation that requires immediate linkage and optimal treatment and care provided through government-funded programs.
Keyphrases
- antiretroviral therapy
- human immunodeficiency virus
- hiv infected
- healthcare
- hiv positive
- gestational age
- hiv testing
- low birth weight
- quality improvement
- hepatitis c virus
- palliative care
- hiv aids
- affordable care act
- men who have sex with men
- public health
- pain management
- preterm infants
- dna methylation
- health insurance
- sars cov
- machine learning
- genome wide
- risk assessment
- mental health
- gene expression
- metabolic syndrome
- type diabetes
- chronic pain
- insulin resistance
- combination therapy
- high density