Abstract:
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The HIV care cascade is a conceptual model describing the stages of care leading to long-term viral suppression of those with HIV. Distinct stages include case identification, linkage to care, initiation of antiviral treatment, and eventual viral suppression. After entering care, individuals are subject to disengagement from care, dropout, and mortality. Operationally, the care cascade has a state space representation, and modeling approaches can be used to parameterize state transition rates or duration times. Owing to the complexity of the cascade, evaluation of efficacy and cost effectiveness of specific policies has primarily relied on simulation-based approaches of mathematical models, where model parameters may be informed by multiple data sources that come from different populations or samples. The growing availability of large longitudinal cohorts of HIV-infected individuals presents an opportunity for a more unified approach using statistical models of the cascade. We describe these models, compare them to more widely used mathematical models, and describe how they can be used to estimate causal policy effects.
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