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Pleural effusion is an interruption of a pleural cavity in the lung wall. The lung and chest wall reversal process leads to pleural fluid aggregation in the pleural space. The parietal lymphatic expansion occurs because of increased pleural fluid. This model has been developed to obtain new results of respiratory tract infections, and also investigated the reaction of injection on an unstable free and forced convection flow of visceral pleural fluid transports in two different vertical porous regions. Finally, the model gives an impact of COVID-19 in the human respiratory tract, as it helps to anticipate early summary of establishing current pandemic infection. Results are computed analytically and plotted graphically for various physical parameters. The main highlights of this paper are mixed convection has been investigated mathematically in porous media, the effect of temperature and velocity field of pleural fluid was analyzed based on human lung mechanism, heat exchange associates with mucus layer and pleural fluid layer corresponding to thermal radiation and heat absorption, contribution of injection parameter over the region’s mucus and pleural phase, it has shown high sensitivity flow in diagnosis of COVID-19 due to pleural effusion.

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The influence of pulsatile flow on the oscillatory motion of an incompressible conducting boundary layer mucus fluid flowing through porous media in a channel with elastic walls is investigated. The oscillatory flow is treated as a cyclical time-dependent flux. The Laplace transform method using the Womersley number is used to solve non-linear equations controlling the motion through porous media under the influence of an electromagnetic field. The theoretical pulsatile flow of two liquid phase concurrent fluid streams, one kinematic and the other viscoelastic, is investigated in this study. To extend the model for various physiological fluids, we postulate that the viscoelastic fluid has several distinct periods. We also apply our analytical findings to mucus and airflow in the airways, identifying the wavelength that increases dynamic mucus permeability. The microorganism’s thickness, velocity, energy, molecular diffusion, skin friction, Nusselt number, Sherwood number, and Hartmann number are evaluated. Discussion is also supplied in various sections to investigate the mucosal flow process.