Anti Retroviral Life-Saving Therapy

Abstract

Objectives: Effective implementation of mathematical and statistical modelsmaximizes the likelihood of understanding the trajectory, level and pattern of incurable diseasesand their therapies, so that precise demand strategies for costly lifesaving therapies for future,resource allocation and timely intervention could be ensured, a significant concern for lessdeveloped countries like Pakistan. Methods: The record of monthly number of patients onlifesaving anti-Retroviral Therapy for more than 18 HIV treatment centers in Pakistan wasacquired for the period January 2011 to July 2013.A set of eleven curve fitting models namelylinear, quadratic, cubic, logarithmic, inverse ,exponential growth model, logistics-curve andcompound models was carried out for prediction. Results: After the execution of various curvefitting models by taking the ANOVA approach along with coefficient of determination and theforecast accuracy measures namely, mean percentage error (MAPE), mean absolute error(MAE) and mean square error (MSE) in the selection of final efficient model. Cubic model wasselected for forecasting the monthly anti-retroviral therapy cases for all categories i.e. overall,male female and children. On the basis of final selected model 3% increment is expectednumber of paticuts on anti-retroviral therapy annually in HIV treatment center in all Pakistan.Male patients are expected to increase 14% who will get lifesaving anti-retroviral therapies.While the annually expected reduction of 17% and 42% in female and children cases takinganti-retroviral therapy is expcted in future respectively. Conclusions: The overall number ofpeople on anti-retroviral therapy are expected to increase in Pakistan. Males are expected tohave greater risk as compared to female and children in Pakistan.