Particle swarm optimization based estimation of HIV-1 viral load in resource limited settings

Viral load (VL) testing is highly important for diagnosis and staging of HIV-1 infection and for initiating antiretroviral treatment in AIDS patients. However, due to the cost and availability of viral load testing instruments, VL testing is not being performed in many developing and underdeveloped countries. Such countries depend on CD4 tests as an alternative. In this work, a method for estimating the HIV-1 viral load from CD4 cell counts, using Particle Swarm Optimization (PSO) technique was proposed. The efficiency of the proposed method was evaluated using error analysis and correlation analysis. The average error in estimation of HIV-1 viral load was found to be 3.317%. Further, an average correlation value (R) of 0.99 was found between the actual and estimated values of HIV-1 viral load. This work seems to be of high clinical significance, since efficient and low cost strategies for estimation of HIV-1 viral load is required for proper diagnosis and staging of the disease.