Optimizing HIV Treatment Monitoring under Resource Constraints
The effectiveness of HIV antiretroviral therapy (ART) depends on regular monitoring of key indicators such as CD4 cell count and plasma viral load (VL). Some patients can experience treatment failure, indicated by elevated viral load or development of ART resistance, and need to switch to second- or third-line treatments. Correct and early diagnosis of treatment failure is essential for durable response to therapy, prevention of morbidity and mortality, and optimal use of therapeutic options. Owing to financial and infrastructure constraints, many HIV treatment programs in the developing world do not have access to viral load and resistance tests, or can apply them only on a limited basis. Our project has four aims: (i) develop the statistical framework required to discover optimally targeted allocation of patient diagnostics such as viral load and drug resistance testing when testing capacity is limited; (ii) use cohort data from both the US and Kenya to develop and validate optimal test allocation algorithms; (iii) develop methods for pooled testing for viral load and drug resistance; and (iv) implement these methods in the reference laboratory of a PEPFAR-funded HIV care program. We are developing open-source software to promote implementation of the methods.