Microplastics have become omnipresent in the environment, including the air we inhale, the water we consume, and the food we eat. Despite limited research, the accumulation of microplastics within the human respiratory system has garnered considerable interest because of its potential implications for health. This review offers a comprehensive examination of the impacts stemming from the accumulation of microplastics on human lung airways and explores the computational benefits and challenges associated with studying this phenomenon. The existence of microplastics in the respiratory system can lead to a range of adverse effects. Research has indicated that microplastics can induce inflammation, oxidative stress, and impaired lung function. Furthermore, the small size of microplastics allows them to penetrate deep into the lungs, reaching the alveoli, where gas exchange takes place. This raises concerns about long-term health consequences, such as the development of respiratory diseases and the potential for translocation to other organs. Computational approaches have been instrumental in understanding the impact of microplastic deposition on human lung airways. Computational models and simulations enable the investigation of particle dynamics, deposition patterns, and interaction mechanisms at various levels of complexity. However, studying microplastics in the lung airways using computational methods presents several challenges. The complex anatomy and physiological processes of the respiratory system require accurate representation in computational models. Obtaining relevant data for model validation and parameterization remains a significant hurdle. Additionally, the diverse nature of microplastics, including variations in size, shape, and chemical composition, poses challenges in capturing their full range of behaviours and potential toxicological effects.

Schematic illustration of various kinds of geometries used for inertial microfluidics.

The understanding of complex inhalation and transport processes of pollutant particles through the human respiratory system is important for investigations into dosimetry and respiratory health effects in various settings, such as environmental or occupational health. The studies over the last few decades for micro- and nanoparticle transport and deposition have advanced the understanding of drug-aerosol impacts in the mouth-throat and the upper airways. However, most of the Lagrangian and Eulerian studies have utilized the non-realistic symmetric anatomical model for airflow and particle deposition predictions. Recent improvements to visualization techniques using high-resolution computed tomography (CT) data and the resultant development of three dimensional (3-D) anatomical models support the realistic representation of lung geometry. Yet, the selection of different modelling approaches to analyze the transitional flow behavior and the use of different inlet and outlet conditions provide a dissimilar prediction of particle deposition in the human lung. Moreover, incorporation of relevant physical and appropriate boundary conditions are important factors to consider for the more accurate prediction of transitional flow and particle transport in human lung. This review critically appraises currently available literature on airflow and particle transport mechanism in the lungs, as well as numerical simulations with the aim to explore processes involved. Numerical studies found that both the Euler–Lagrange (E-L) and Euler–Euler methods do not influence nanoparticle (particle diameter ≤50 nm) deposition patterns at a flow rate ≤25 L/min. Furthermore, numerical studies demonstrated that turbulence dispersion does not significantly affect nanoparticle deposition patterns. This critical review aims to develop the field and increase the state-of-the-art in human lung modelling.

Genetic variants of severe acute respiratory syndrome coronavirus (SARS-CoV-2) have been globally surging and devastating many countries around the world. There are at least eleven reported variants dedicated with inevitably catastrophic consequences. In 2021, the most dominant Delta and Omicron variants were estimated to lead to more severity and deaths than other variants. Furthermore, these variants have some contagious characteristics involving high transmissibility, more severe illness, and an increased mortality rate. All outbreaks caused by the Delta variant have been rapidly skyrocketing in infection cases in communities despite tough restrictions in 2021. Apart from it, the United States, the United Kingdom and other high-rate vaccination rollout countries are still wrestling with this trend because the Delta variant can result in a significant number of breakthrough infections. However, the pandemic has changed since the latest SARS-CoV-2 variant in late 2021 in South Africa, Omicron. The preliminary data suggest that the Omicron variant possesses 100-fold greater than the Delta variant in transmissibility. Therefore, this paper aims to review these characteristics based on the available meta-data and information from the first emergence to recent days. Australia and the five most affected countries, including the United States, India, Brazil, France, as well as the United Kingdom, are selected in order to review the transmissibility, severity and fatality due to Delta and Omicron variants. Finally, the vaccination programs for each country are also reviewed as the main factor in prevention.