DEA Based Anti-HIV Immunotherapy Model

In the text, the Data Envelopment Analysis (DEA) method is applied into thetreatment strategy of anti-HIV immunotherapy, as is significant practically in the anti-HIV treatment. DEA methods are utilized to describe the drug treatment strategies,and two prediction models are constructed respectively according to the given inputsand the given outputs. Moreover, the optimal treatment strategy of anti-HIVimmunotherapy is solved by the relative efficiency of DMUs.In the text, DEA models based on inputs with undesirable outputs are utilized todescribe the drug treatment strategies of anti-HIV immunotherapy and the efficiencyof treatment strategies is solved. The critical step is how to build the DMUs tomeasure the efficiency of each treatment period. More over, the medical meaning ofassessing the relative efficiency of DMUs is significant: If the endurance of thepatient permits, the immune system can produce more T cells and less HIV virus at aless body cost. Traditionally, the differential equation method is used to set up theanti-HIV immunotherapy models and the optimal controlled solutions are explored.However, through calculating of DEA method, it is indicated that not every optimalsolutions of the differential equation method is DEA efficient.Furthermore, Prediction models are designed to predict the efficient unknownoutputs according to the given inputs and to predict the efficient unknown inputsaccording to the given outputs. It is used together with some medical simulated modelto predict the efficiency of the treatment periods. In the text, the efficient unknownvariables are obtained by the DEA prediction model and then validated by somemedical simulated model, and then the efficient predict values are obtained.