Medication correlation analysis for outbreak prediction

Abstract

Outbreak prediction is a way to predict the epidemic potentials of diseases using the pattern of medication sales values. Successful prediction might result in being cautious of the outbreak of diseases and taking necessary measures to prevent the predicted outcome. As medication sales values are too random, the analysis of medication correlation is one of the most interesting and challenging parts for the researchers. The major objective of this proposed research method is to analyze medication drug sales values for a certain period of a pharmaceutical company using statistical methods. It is also the intent of this research to make a comparative analysis of the output generated by the deep learning model with the real sales values of a month. Our method successfully predicts the outbreak potential of diseases with competent accuracy, so that we will have enough time to take precautions and prevent future pandemics through precautionary measures.