Fuzzy ELECTRE and TOPSIS method to analyze the risk factors of tuberculosis

Abstract

Tuberculosis (TB) is an infectious disease that mainly affects the lungs and it is caused by Mycobacterium tuberculosis bacteria. WHO reported that nearly 1.4 million people died of TB in 2019 and TB is one of the top 10 causes of death in the world. Over 95% of cases and deaths are occurring in developing countries and a lot of factors such as diabetes, immune problem, malnutrition, alcohol, active smoking, crowded places, HIV infection, air pollution, kidney diseases, cancer and tuberculosis treatment workers are linked to TB. So, it is our utmost interest is to analyze the risk factors of TB. Therefore, this present study intended to combine the salient features of ELECTRE and TOPSIS methods under a fuzzy environment to analyze the risk factors of TB. Moreover, the comparative analysis is demonstrated to find the most influencing risk factors of TB. Finally, the sensitivity analysis is also performed using the entropy method to verify the results.