Novel coronavirus SARS-CoV-2 (Covid-19) dynamics inside the human body.

A knowledge-based cybernetic framework model representing the dynamics of SARS-CoV-2 inside the human body has been studied analytically and in silico to explore the pathophysiologic regulations. The following modeling methodology was developed as a platform to introduce a predictive tool supporting a therapeutic approach to Covid-19 disease. A time-dependent nonlinear system of ordinary differential equations model was constructed involving type-I cells, type-II cells, SARS-CoV-2 virus, inflammatory mediators, interleukins along with host pulmonary gas exchange rate, thermostat control, and mean pressure difference. This formalism introduced about 17 unknown parameters. Estimating these unknown parameters requires a mathematical association with the in vivo sparse data and the dynamic sensitivities of the model. The cybernetic model can simulate a dynamic response to the reduced pulmonary alveolar gas exchange rate, thermostat control, and mean pressure difference under a very critical condition based on equilibrium (steady state) values of the inflammatory mediators and system parameters. In silico analysis of the current cybernetical approach with system dynamical modeling can provide an intellectual framework to help experimentalists identify more active therapeutic approaches.

A fluid mechanics explanation of the effectiveness of common materials for respiratory masks.

OBJECTIVES: Face masks are an important component of personal protection equipment employed in preventing the spread of diseases such as COVID-19. As the supply of mass-produced masks has decreased, the use of homemade masks has become more prevalent. It is important to quantify the effectiveness of different types of materials to provide useful information, which should be considered for homemade masks. METHODS: Filtration effects of different types of common materials were studied by measuring the aerosol droplet concentrations in the upstream and downstream regions. Flow-field characteristics of surrounding regions of tested materials were investigated using a laser-diagnostics technique, i.e., particle image velocimetry. The pressure difference across the tested materials was measured. RESULTS: Measured aerosol concentrations indicated a breakup of large-size particles into smaller particles. Tested materials had higher filtration efficiency for large particles. Single-layer materials were less efficient, but they had a low pressure-drop. Multilayer materials could produce greater filtering efficiency with an increased pressure drop, which is an indicator of comfort level and breathability. The obtained flow-fields indicated a flow disruption downstream of the tested materials as the velocity magnitude noticeably decreased. CONCLUSIONS: The obtained results provide an insight into flow-field characteristics and filtration efficiency of different types of household materials commonly used for homemade masks. This study allows comparison with mass-produced masks under consistent test conditions while employing several well-established techniques.