Sensitivity Analysis of a General Lung Diseases Progression Stochastic Model Considering Two Types of Diagnostic Tests

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Keywords:

Keywords. Lung disease, Mean sojourn time, Mean survival time, Markov process, Regenerative point technique, Sensitivity analysis.

Abstract

Abstract. Lung is a vital organ in the human body that is affected by many diseases each with different causes, symptoms, and treatments. In the present paper, a general stochastic model for   lung diseases has been developed considering various stages of progression of the disease. In the model, two types of diagnostic tests viz. normal and advance diagnostic tests have been taken into account. For the survival analysis purpose, mean sojourn times and mean survival time have been calculated for the model using concepts of Markov process and regenerative point techniques. Sensitivity and relative sensitivity analyses have also been performed to find out how the variation in parameters affect the mean survival time under certain specific conditions.

Keywords. Lung disease, Mean sojourn time, Mean survival time, Markov process, Regenerative point technique, Sensitivity analysis.

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Published

13-08-2025

How to Cite

suman, S., & Kumar, R. (2025). Sensitivity Analysis of a General Lung Diseases Progression Stochastic Model Considering Two Types of Diagnostic Tests. Communications in Mathematics and Applications, 16(1). Retrieved from https://www.journals.rgnpublications.com/index.php/cma/article/view/2996

Issue

Vol. 16 No. 1 (2025)

Section

Research Article

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