A Markovian Analysis of Low Back Pain on Jute Mill Workers

Abstract

Jute industry which employs around 3,50,000 labors, is a large contributor to India’s economy. With the prevalence of chronic low back pain among jute mill workers being 55%, the paper proposes a Markov model-based approach to analyze the probabilistic trend for increment or decrement in the population size of jute mill workers suffering from the ailment in next five years till 2025. The proposed model is designed with three states to effectively capture the changes occurred in two consecutive years in the size of jute mill population involved in different types of jute processing tasks. The results of the Markov model show that the size of the LBP population comprising the workers involved mostly in the spinning and weaving processes is likely to get increased in next five years. On the other hand, the population having workers associated with the jute finishing process is likely to have less no. of individuals having the pain over the time. Having this alarming prediction on jute mill workers, the paper proposes an outline of an Artificial Intelligence based medical expert system to offer reliable, affordable, and available healthcare solution to a wider range of population suffering from low back pain.