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This paper is devoted to the multidisciplinary modelling of a pandemic initiated by an aggressive virus, specifically the so-called SARS–CoV–$2$ Severe Acute Respiratory Syndrome, corona virus n.$2$. The study is developed within a multiscale framework accounting for the interaction of different spatial scales, from the small scale of the virus itself and cells, to the large scale of individuals and further up to the collective behaviour of populations. An interdisciplinary vision is developed thanks to the contributions of epidemiologists, immunologists and economists as well as those of mathematical modellers. The first part of the contents is devoted to understanding the complex features of the system and to the design of a modelling rationale. The modelling approach is treated in the second part of the paper by showing both how the virus propagates into infected individuals, successfully and not successfully recovered, and also the spatial patterns, which are subsequently studied by kinetic and lattice models. The third part reports the contribution of research in the fields of virology, epidemiology, immune competition, and economy focussed also on social behaviours. Finally, a critical analysis is proposed looking ahead to research perspectives.

The development of anti-COVID-19 drugs has become the top priority since the outbreak of the epidemic, and Traditional Chinese medicine plays an important role in reducing mortality. Here, hesperidin and its glycosylation product, glucosyl hesperidin were selected to determine their antiviral activity against SARS-CoV-2 due to their structural specificity as reported. To be specific, their binding ability with ACE2, M, S, RBD and N proteins were verified with both in silico and wet lab methods, i.e., molecular docking and binding affinity tests, including biolayer interferometry assay (BLI) and isothermal titration calorimetry assay (ITC). Moreover, systematic pharmacological analysis was conducted to reveal their pharmacological mechanism in treating COVID-19. Finally, their antiviral activity against SARS-CoV-2 was determined in vitro in a biosafety level 3 (BSL3) laboratory. The results demonstrated their outstanding binding affinity with ACE2, M, S and RBD proteins, while showed barely unobserved binding with N protein, indicating their key roles in influencing the invasion and early replication phase of SARS-CoV-2. In addition, both hesperidin and glucosyl hesperidin were shown to have a great impact on immune, inflammation and virus infection induced by COVID-19 according to the systematic pharmacological analysis. Moreover, the IC50s of hesperidin and glucosyl hesperidin against SARS-CoV-2 were further determined (51.5 $\mu$M and 5.5 mM, respectively) with cell-based in vitro assay, suggesting their great anti-SARS-CoV-2 activity. All in all, present research was the first to verify the binding ability of hesperidin and glucosyl hesperidin with SARS-CoV-2 proteins with both in silico and wet-lab methods and proposed the possibility of applying hesperidin and glucosyl hesperidin to treat COVID-19.

The outbreak of COVID-19 resulted in high death tolls all over the world. The aim of this paper is to show how a simple SEIR model was used to make quick predictions for New Jersey in early March 2020 and call for action based on data from China and Italy. A more refined model, which accounts for social distancing, testing, contact tracing and quarantining, is then proposed to identify containment measures to minimize the economic cost of the pandemic. The latter is obtained taking into account all the involved costs including reduced economic activities due to lockdown and quarantining as well as the cost for hospitalization and deaths. The proposed model allows one to find optimal strategies as combinations of implementing various non-pharmaceutical interventions and study different scenarios and likely initial conditions.

The coronavirus disease 2019 (COVID-19) spreads and rages around the world and threatens human life. It is disappointing that there are no specific drugs until now. The combination of traditional Chinese medicine (TCM) and western medication seems to be the current more effective treatment strategy for COVID-19 patients in China. In this review, we mainly discussed the relationship between COVID-19 and gut microbiota (GM), as well as the possible impact of TCM combined with western medication on GM in the treatment of COVID-19 patients, aiming to provide references for the possible role of GM in TCM against COVID-19. The available data suggest that GM dysbiosis did occur in COVID-19 patients, and the intervention of GM could ameliorate the clinical condition of COVID-19 patients. In addition, TCMs (e.g., Jinhua Qinggan granule, Lianhua Qingwen capsule, Qingfei Paidu decoction, Shufeng Jiedu capsule, Qingjin Jianghuo decoction, Toujie Quwen granules, and MaxingShigan) have been proven to be safe and effective for the treatment of COVID-19 in Chinese clinic. Among them, Ephedra sinica, Glycyrrhiza uralensis, Bupleurum chinense, Lonicera japonica,Scutellaria baicalensi, and Astragalus membranaceus are common herbs and have a certain regulation on GM, immunity, and angiotensin converting enzyme 2 (ACE2). Notably, Qingfei Paidu decoction and MaxingShigan have been demonstrated to modulate GM. Finally, the hypothesis of GM-mediated TCM treatment of COVID-19 is proposed, and more clinical trials and basic experiments need to be initiated to confirm this hypothesis.

From origin in Wuhan city of China, a highly communicable and deadly virus is spreading in the entire world and is known as COVID-19. COVID-19 is a new species of coronavirus which is affecting respiratory system of human. The virus is known as severe acute respiratory syndrome (SARS) coronavirus 2 abbreviated as SARS-CoV-2 and generally known as coronavirus disease COVID-19. This is growing day by day in countries. The symptoms include fever, cough and difficulty in breathing. As there is no vaccine made for this virus and COVID-19 tests are not readily available, this is causing panic. Various Artificial Intelligence-based algorithms and frameworks are being developed to detect this virus, but it has not been tested. People are taking advantages of others by providing duplicate COVID-19 test kits. A work is carried out with deep learning to detect presence of COVID 19. With the use of Convolutional Neural networks, the model is trained with dataset of COVID-19 positive and negative X-Rays. The accuracy of training model is 99% and the confusion matrix shows 98% values that are predicted truly. Hence, the model is able to detect the presence of COVID-19.

Viral respiratory infections have plagued mankind over its known history. Unfortunately, there has been a lack of meaningful progress in preventing the spread of viral respiratory infections globally. The central dogma appears to be that viruses are the villains. This framing focuses on a viral load balance (VLB) in the air. It follows that physical dilution through various means have been the primary focus of attempts to reduce the spread of infections. The problem of obesity provides a good example of how paradigm blindness can slow down progress in a field. Obesity has been framed as an energy balance disorder that blames overeating and lack of exercise for weight gain. Reframing obesity as a disorder of fat metabolism and storage caused by the quantity and quality of carbohydrates in the diet, referred to as the carbohydrate-insulin model (CIM), opened an alternative line of questioning with a testable hypothesis. Similarly, we postulate an alternative way to frame the spread of viral respiratory infections that would lead to new insights and potentially new ways to prevent infections.

It has long been recognized that viral respiratory infections show a pronounced seasonal variation, referred to as seasonal forging, such that they increase in the winter but decrease or virtually disappear in the summer. In temperate regions, people spend over 90% of their time indoors. This is, therefore, where most respiratory infections are expected to occur. Evidence has been accumulating for decades on the strong correlation between variations in indoor relative humidity (RH) and variations in infection rates. Within a RH Goldilocks zone of 40%-60%, encapsulated viruses like influenza and SARS are optimally inactivated outside the infected host. Below 40% and above 80%, viruses can survive for extended periods in the air or on surfaces. This may explain in part the seasonality of infections as the indoor level of RH in winter is typically about 20% and above 40% in summer in temperate regions. However, the mechanism for the inactivation at midrange RH (in summer) is not well understood. This paper offers a hypothesis that could explain these observations.

We have demonstrated that H₂O₂ and other reactive oxygen species (ROS) are formed spontaneously at the water-air interface of pure water microdroplets. Using only water and a nebulizing gas in the presence of oxygen, we have demonstrated the significant disinfectant potential of pure water microdroplets caused by the activity of H₂O₂ and other ROS. We postulate that spontaneous H₂O₂ and ROS formation in viruses containing exhaled microdroplets have a similar virucidal effect at mid-range RH. The droplet evaporation rate is sufficient to concentrate the solutes and provide enough time for reactions to occur at significantly higher rates than in bulk solutions. The concentration of H₂O₂ has also been shown to be positively correlated to RH. In addition, several other ROS/RNS may be present or formed through interactions with H₂O₂ that may act as even more effective virucide disinfectants to inactivate the virus. Below RH 40% evaporation happens too rapidly for these reactions to make an impact before the droplet is desiccated, and above RH 80% the solutes remain too diluted. Rapid inactivation of viruses at midrange RH may therefore play a greater role in preventing infections than physical dilution of virus load in the air through excessive mechanical ventilation. Similar to obesity, we suggest that a new paradigm that considers virus infectivity outside the host rather than the virus load balance in the air alone could greatly contribute to our understanding of respiratory infections. The proposed new “Relative Humidity Infectivity” RHI paradigm could explain the causal mechanisms underlying seasonal respiratory infections. This can point to better prevention strategies that avoid further distortion of our indoor environment and create conditions within which humans can thrive and be optimally protected. We need more focus on testing the various hypotheses and more data to determine which of the two paradigms will lead us in the right direction or how to use the best of both in an optimal combination. The stakes cannot be higher, and the potential for eradicating future viral respiratory pandemics with nature-based solutions may be right under our noses, literally.

SARS-CoV-2, which causes COVID-19 disease, has proven to be a disastrous pandemic due to its contagious nature. This study has been planned to theoretically explore some antidotes against this virus from natural compounds. A total of 150 compounds from the shogaol class and shogaol derivatives (SDs) have been screened whereas 50 among those, which obeyed Lipinski’s Rule of Five (Ro5), have further been investigated using molecular docking techniques. Furthermore, reference antiviral drug chloroquine (ChQ) and Co-Crystallized inhibitor have also been studied against M^pro of SARS-CoV-2 for comparing the potential of our docked ligands. Surprisingly, 78% of our docked ligands have shown binding energies and inhibition constants lower than ChQ and all ligands showed these values lower than an inhibitor. We further visualized the nature of intermolecular interactions for the best docked six ligands, which have shown higher binding affinities. We have also assessed ADMET properties for three ligands that displayed visually the best intermolecular interactions. Quantum analysis of three selected ligands L4, L5, and L9 has proved their reactivity and kinetic stability. Moreover, molecular dynamic simulations over 60ns have been run for free M^pro and its selected three ligand-protein complexes for evaluating conformational stability and residual flexibility of docked complexes. Furthermore, 100ns the MD simulations have been performed for two ligand complexes L4, L5 (with negative binding free energy), and inhibitor. Available parameters suggest stable complexes for our ligands and could be active drugs against SARS-CoV-2 in near future.

SARS-CoV-2 is a deadly virus that has affected human life since late 2019. Between all the countries that have reported the cases of patients with SARS-CoV-2 disease (COVID-19), the United States of America has the highest number of infected people and mortality rate. Since different states in the USA reported different numbers of patients and also death cases, analyzing the difference of SARS-CoV-2 between these states has great importance. Since the generated RNA walk from the SARS-CoV-2 genome includes complex random fluctuations that also contain information, in this study, we employ the complexity and information theories to investigate the variations of SARS-CoV-2 genome between different states in the USA for the first time. The results of our analysis showed that the fractal dimension and Shannon entropy of genome walk significantly change between different states. Based on these results, we can conclude that the SARS-CoV-2 genomic structure significantly changes between different states, which is resulted from the virus evolution. Therefore, developing a vaccine for SARS-CoV-2 is very challenging since it should be able to fight various structures of the virus in different states.

The ongoing coronavirus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) has serious influences on human health and economy. The available clinical data suggest that patients infected by SARS-CoV-2 have the possibility of simultaneous infection of bacteria. In this study, we present a data-driven mathematical model for coinfection of SARS-CoV-2 and bacteria to investigate the dynamics of COVID-19 progress. Specifically, based on the statistical analysis of different clinical data from China and some other countries, a system model with ordinary differential equations (ODEs) in four variables, i.e. SARS-CoV-2, bacteria, neutrophils and lymphocytes, is established. We further validate our model through theoretical analysis and fitting of different clinical data. Moreover, through numerical simulations and bifurcation analysis, we find that bacterial infection and immune-related parameters in certain ranges lead to the system transitions among three steady states, i.e. mild, severe and death. We also analyzed the influence of the time it takes for patients to switch from a high-risk area to a low-risk area on the recovery time. These results reveal that the coinfection of viruses and bacteria can explain the changes in neutrophils and lymphocytes, and that initial bacterial infection and immune-related parameters have great influences on the severity degree and mortality in COVID-19 patients. Together, our model and quantitative analysis suggest that preventing bacterial infection and enhancing immune ability during the early phase of infections could be a potential treatment option for high-risk COVID-19 patients.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causes COVID-19, a disease currently spreading around the world. Some drugs are underway or being used to combat this disease. Several proteins of the virus can be targeted in therapeutic approaches. Two structural proteins, membrane (M), envelope (E) have critical roles in virus life cycle, such as assembly, budding, envelope formation and pathogenesis. Here, we employed the in silico strategies to identify and evaluate the selected potential compounds against M and E proteins. For this, the structures of proteins were modeled and then several groups of compounds as FDA approved, natural products or under clinical trials were screened from DrugBank and ZINC databases. The selected dockings were analyzed and the ligands with best binding affinity scores were subjected to evaluate drug-likeness and medicinal chemistry friendliness through prediction of ADMET properties. Normal mode analyses were also performed for six selected complexes to explore the collective motions of proteins. Molecular dynamic (MD) simulation was also performed to calculate the stability of two docked protein–ligand complexes. The results revealed that several compounds had high affinity to the proteins along with some acceptable profiles of mobility and deformability, especially, for M protein.

The COVID-19 pandemic lit a fire under researchers who have subsequently raced to build models which capture various physical aspects of both the biology of the virus and its mobility throughout the human population. These models could include characteristics such as different genders, ages, frequency of interactions, mutation of virus, etc. Here, we propose two mathematical formulations to include virus mutation dynamics. The first uses a compartmental epidemiological model coupled with a discrete-time finite-state Markov chain. If one includes a nonlinear dependence of the transition matrix on current infected, the model is able to reproduce pandemic waves due to different variants. The second approach expands such an idea to a continuous state-space leveraging a combination of ordinary differential equations with an evolution equation for measure. This approach allows to include reinfections with partial immunity with respect to variants genetically similar to that of first infection.

The current COVID-19 pandemic mainly affects the upper respiratory tract. People with COVID-19 report a wide range of symptoms, some of which are similar to those of common flu, such as sore throat and rhinorrhea. Additionally, COVID-19 shares many clinical symptoms with severe pneumonia, including fever, fatigue, dry cough, and respiratory distress. Several diagnostic strategies, such as the real-time polymerase chain reaction technique and computed tomography imaging, which are more costly than chest radiography, are employed as diagnostic tools. The purpose of this paper is to describe the role of the d-summable information dimension of X-ray images in differentiating several lesions and lung illnesses better than both fractal and information dimensions. The statistical analysis shows that the d-summable information dimension model better describes the information obtained from the X-ray images. Therefore, it is a more precise measure of complexity than the information and box-counting dimension. The results also show that the X-ray images of COVID-19 pneumonia reveal greater damage than those of tuberculosis, pneumonia, and various lung lesions, where the damage is minor or much focused. Because the d-summable information dimension increases as the image complexity decreases, it could pave the way to formulate a new measure to quantify the lung damage and assist the clinical diagnosis based on the area under the d-summable information model. In addition, the physical meaning of the $\nu$ parameter in the d-summable information dimension is given.

COVID-19 is the last disease caused by SARS-CoV-2 associated with a severe immune response and lung damage. The main protease (M^pro) has a vital role in SARS-CoV-2 proliferation. Moreover, humans lack homologous M^pro, which makes the M^pro a suitable drug target for the development of SARS-CoV-2 drugs. The purchasable L5000 library (Selleckchem Inc) includes 99,040 compounds that were used for virtual screening. After molecular docking and ADME studies, we selected a compound (WAY-604395) with a potent binding affinity to the M^pro active site and acceptable ADME properties compared to the reference drug (nelfinavir). Molecular dynamics (MD) simulation outcomes have proved that the M^pro-WAY604395 complex possesses a considerable value of flexibility, stability, compactness and binding energy. Our Molecular Mechanics Poisson–Boltzmann Surface Area (MM-PBSA) calculation demonstrates that WAY-604395 is more potent ($-$272.19kcal mol${}^{-1}$) in comparison with nelfinavir ($-$173.39kcalmol${}^{-1}$) against SARS-CoV-2 M^pro. In conclusion, we suggest that WAY-604395 has the potential for the treatment of SARS-CoV-2 by inhibition of the M^pro.

In December 2019, a novel coronavirus SARS-CoV-2, causing the disease COVID-19, spread from Wuhan throughout China and has infected people over 200 countries. Thus far, more than 3,400,000 cases and 240,000 deaths have occurred worldwide, and the coronavirus pandemic continues to grip the globe. While numbers of cases in China have been steadying, the number of infections outside China is increasing at a worrying pace. We face an urgent need to control the spread of the COVID-19 epidemic, which is currently expanding to a global pandemic. Efforts have focused on testing antiviral drugs and vaccines, but there is currently no treatment specifically approved. Traditional Chinese medicine (TCM) is grounded in empirical observations and the Chinese people use TCM to overcome these sorts of plagues many times in thousands of years of history. Currently, the Chinese National Health Commission recommended a TCM prescription of Qing-Fei-Pai-Du-Tang (QFPDT) in the latest version of the “Diagnosis and Treatment guidelines of COVID-19” which has been reported to provide reliable effects for COVID-19. While doubts about TCM still exist today, this review paper will describe the rationalities that QFPDT is likely to bring a safe and effective treatment of COVID-19.

SARS-CoV-2 has posed a threat to the health of people around the world because of its strong transmission and high virulence. Currently, there is no specific medicine for the treatment of COVID-19. However, for a wide variety of medicines used to treat COVID-19, traditional Chinese medicine (TCM) plays a major role. In this paper, the effective treatment of COVID-19 using TCM was consulted first, and several Chinese medicines that were frequently used apart from their huge role in treating it were found. Then, when exploring the active ingredients of these herbs, it was discovered that most of them contained flavonoids. Therefore, the structure and function of the potential active substances of flavonoids, including flavonols, flavonoids, and flavanes, respectively, are discussed in this paper. According to the screening data, these flavonoids can bind to the key proteins of SARS-CoV-2, 3CLpro, PLpro, and RdRp, respectively, or block the interface between the viral spike protein and ACE2 receptor, which could inhibit the proliferation of coronavirus and prevent the virus from entering human cells. Besides, the effects of flavonoids on the human body systems are expounded on in this paper, including the respiratory system, digestive system, and immune system, respectively. Normally, flavonoids boost the body’s immune system. However, they can suppress the immune system when over immunized. Ultimately, this study hopes to provide a reference for the clinical drug treatment of COVID-19 patients, and more TCM can be put into the market accordingly, which is expected to promote the development of TCM on the international stage.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the most dangerous type of coronavirus and has infected over 25.3 million people around the world (including causing 848,000 deaths). In this study, we investigated the similarity between the genome walks of coronaviruses in various animals and those of human SARS-CoV-2. Based on the results, although bats show a similar pattern of coronavirus genome walks to that of SARS-CoV-2 in humans, decoding the complex structure of coronavirus genome walks using sample entropy and fractal theory showed that the complexity of the pangolin coronavirus genome walk has a 94% match with the complexity of the SARS-CoV-2 genome walk in humans. This is the first reported study that found a similarity between the hidden characteristics of pangolin coronavirus and human SARS-CoV-2 using complexity-based analysis. The results of this study have great importance for the analysis of the origin and transfer of the virus.

The ongoing eruption of the COVID-19 pandemic instigated by severe-acute-respiratory-syndrome-coronavirus 2 (SARS-CoV-2) has produce enormous damage to the world. The need of the hour is to stop this pandemic by inhibiting the main protease (M^Pro) of SARS-CoV-2, which is primarily involved in viral replication. Our study aims to find potential inhibitors for M^Pro by docking marine fungi-based 90 antiviral compounds against SARS-CoV-2. Among these, 11 antiviral compounds (obeying Lipinski RO5) are selected from 90 docked antiviral compounds on the basis of binding energy range ($-$6.4kcal/mol to $-$9kcal/mol) and low inhibition constant values (0.23$\mu$M to 2.5$\mu$M) as compared with remdesivir (reference compound) toward M^Pro of SARS-CoV-2. Tryptoquivaline F, arisugacin B, and arisugacin A antiviral compounds exhibited effective hydrogen and hydrophobic (alkyl, $\pi$-alkyl, and $\pi$-anion) interactions and are expected to be potential protease inhibitors. Drug-likeness of these lead compounds are elaborated by boiled-egg and bioavailability radar map. The toxicity profile showed that the lead compounds L1, L2, and L3 have no AMES toxicity, skin sensitization, and cardiac toxicity. The RMSD graph proposed that all the complexes, i.e. L1, L2, and L3 are in the adequate RMSD range with the average value of 2.1Å. All the complex systems of L1, L2, and L3 showed fluctuations in the acceptable RMSF range of 1.5Å to 3Å. The molecular dynamics simulation proved the stability of docked complexes L1, L2, and L3 in the binding pocket of main protease. The average hydrogen count of all complexes is $\mathrm{\text{L1}}=69.5$, $\mathrm{\text{L2}}=67.7$, and $\mathrm{\text{L3}}=68.6$ H-bonds. The complexes L1-M^Pro, L2-M^Pro, and L3-M^Pro have an average value of $R_g$ as 22.44Å, 22.63Å, and 22.50Å, respectively. The lead compounds L1 (tryptoquivaline F), L2 (arisugacin b), and l3 (arisugacin A) in this study are the most promising inhibitors of SARS-CoV-2 main protease M^Pro, which are not reported in ealier studies. Our findings will evoke the scientific interest for their further in vitro and in vivo experimental studies.

This study aimed to investigate the efficacy of Traditional Chinese Medicine (TCM) decoction with different intervention timepoints in the treatment of coronavirus disease 2019 (COVID-19) patients. We retrospectively collected the medical records and evaluated the outcomes of COVID-19 patients that received TCM decoction treatment at different timepoints. A total of 234 COVID-19 patients were included in this study. Patients who received TCM decoction therapy within 3 days or 7 days after admission could achieve shorter hospitalization days and disease periods compared to those who received TCM decoction $\ge$ 7 days after admission (all $p<0.05$). Patients who received TCM decoction therapy within 3 days had significantly fewer days to negative SARS-CoV-2 from nasopharyngeal/oral swab and days to negative SARS-CoV-2 from urine/stool/blood samples compared to those received TCM decoction $\ge 7$ days after admission (all $p<0.05$). Patients who received TCM decoction therapy on the 3rd to 7th day after admission had a faster achievement of negative SARS-CoV-2 from urine/stool/blood samples compared to those who received TCM decoction $\ge 7$ days after admission ($p<0.05$). Logistic models revealed that more days from TCM decoction to admission $\ge 7$ days might be a risk factor for long hospitalization days, disease period, and slower negative-conversion of SARS-CoV-2 (all $p<0.01$). Conclusively, our results suggest that TCM decoction therapy should be considered at the early stage of COVID-19 patients.

A novel coronavirus named SARS-CoV-2 is causing the severe acute pneumonia (COVID-19) and rapid spread nationally and internationally, resulting in a major global health emergency. Chinese governments and scientists have implemented a series of rigorous measures and scientific research to prevent and control the SARS-CoV-2 infection. However, there is still no specific antiviral drug or vaccine against SARS-CoV-2. It has been proven that traditional Chinese medicine (TCM) exerts an important role in the prevention and treatment of the COVID-19 caused by SARS-CoV-2 during the outbreak. Although the therapeutic effects of these TCM formulas are attractive, the molecular mechanism of action has not been fully elucidated. An emerging strategy of systems pharmacology has been proposed to be a promising method to interpret drug action in complex biological systems and quickly screen out the bioactive compounds from TCM to treat treatment of COVID-19 caused by SARS-CoV-2. Therefore, in this study, the epidemiology, TCM therapy, and the systems pharmacology-based method for TCM are reviewed for COVID-19 to provide a perspective for the prevention and treatment of SARS-CoV-2 infection. Further efforts should be made to reduce disease burden and improve the ability to design antiviral drugs and vaccines, which will benefit the health care system, economic development and even social stability.

Andrographolide (APE) has been used for COVID-19 treatment in various clinical settings in South-East Asia due to its benefits on reduction of viral clearance and prevention of disease progression. However, the limitation of APE clinical use is the high incidence of adverse events. The objective of this study was to find the optimal dosage regimens of APE for COVID-19 treatment. The whole-body physiologically-based pharmacokinetic (PBPK) models were constructed using data from the published articles and validated against clinical observations. The inhibitory effect of APE was determined for the potency of drug efficacy. For prevention of pneumonia, multiple oral doses such as 120mg for three doses, followed by 60mg three times daily for 4 consecutive days, or 200mg intravenous infusion at the rate of 20 mg/h once daily is advised in patients with mild COVID-19. For prevention of pneumonia and reduction of viral clearance time, the recommended dosage regimen is 500mg intravenous infusion at the rate of 25mg/h once daily in patients with mild-to-moderate COVID-19. One hundred virtual populations (50 males and 50 females) were simulated for oral and intravenous infusion formulations of APE. The eligible PBPK/PD models successfully predicted optimal dosage regimens and formulations of APE for prevention of disease progression and/or reduction of viral clearance time. Additionally, APE should be co-administered with other antiviral drugs to enhance therapeutic efficacy for COVID-19 treatment.