Challenges in evaluating the use of viral sequence data to identify HIV transmission networks for public health.
Rami KantorJohn P FultonJon SteingrimssonVladimir NovitskyMark HowisonFizza GillaniYuanning LiAkarsh ManneZoanne ParilloMatthew SpenceTheodore MarakPhilip ChanCasey W DunnThomas BertrandUtpala BandyNicole Alexander-ScottJoseph W HoganPublished in: Statistical communications in infectious diseases (2020)
Great efforts are devoted to end the HIV epidemic as it continues to have profound public health consequences in the United States and throughout the world, and new interventions and strategies are continuously needed. The use of HIV sequence data to infer transmission networks holds much promise to direct public heath interventions where they are most needed. As these new methods are being implemented, evaluating their benefits is essential. In this paper, we recognize challenges associated with such evaluation, and make the case that overcoming these challenges is key to the use of HIV sequence data in routine public health actions to disrupt HIV transmission networks.
Keyphrases
- public health
- antiretroviral therapy
- hiv positive
- hiv testing
- hiv infected
- human immunodeficiency virus
- hepatitis c virus
- hiv aids
- men who have sex with men
- electronic health record
- big data
- physical activity
- healthcare
- south africa
- mental health
- machine learning
- emergency department
- artificial intelligence
- amino acid
- global health
- quality improvement