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In this paper, we introduce a SEIR-type COVID-19 model where the infected class is further divided into subclasses with individuals in intensive care (ICUs) and ventilation units. The model is calibrated with the symptomatic COVID-19 cases, deaths, and the number of patients in ICUs and ventilation units as reported by Republic of Turkey, Ministry of Health for the period 11 March 2020 through 30 May 2020 when the nationwide lockdown is in order. COVID-19 interventions in Turkey are incorporated into the model to detect the future trend of the outbreak accurately. We tested the effect of underreporting and we found that the peaks of the disease differ significantly depending on the rate of underreporting, however, the timing of the peaks remains constant. The lockdown is lifted on 1 June, and the model is modified to include a time-dependent transmission rate which is linked to the effective reproduction number ${{ℛ}}_t$ through basic reproduction number ${{ℛ}}_0$. The modified model captures the changing dynamics and peaks of the outbreak successfully. With the onset of vaccination on 13 January 2021, we augment the model with the vaccination class to investigate the impact of vaccination rate and efficacy. We observe that vaccination rate is a more critical parameter than the vaccine efficacy to eliminate the disease successfully.

SARS-CoV-2, the new coronavirus variant, has been a worldwide health crisis that may outbreak at any time in the future. Over spans of human history, preparations derived from natural products have always been recognized as a preliminary source of medications. Taking into account the SARS-CoV-2 main protease (Mpro) as the essential element of the viral cycle and as a main target, herein we highlight a computer-aided comprehensive virtual screening for a focused chemical list of 14 laulimalides marine macrolides against SARS-CoV-2 Mpro using a set of integrated modern computational techniques including molecular docking (MDock), molecule dynamic simulations (MDS) and structure–activity relationships (SARs). Based on their remarkable ligand-protein energy scores and relevant binding affinities with SARS-CoV-2 (Mpro) pocket residues, two promising macrolides [laulimalides LA4 (6) and LA18 (13)] are selected as proposed inhibitor compounds. Consequently, they are thermodynamically investigated by deciphering their MD simulations at 100 ns, where they show noticeable stability within the accommodated (Mpro) pockets. Moreover, in-depth SARs studies suggest crucial roles for C-23 substituted side chain and C-20 methoxy as essential pharmacophoric structural features for activity. Further in vitro/vivo examinations of the selected marine macrolides would pave the way towards developing effective antiviral drugs from natural resources.

We investigate the spreading of SARS-CoV-2 in the state of Alagoas, northeast of Brazil, via an adaptive susceptible-infected-removed (SIR) model featuring dynamic recuperation and propagation rates. Input parameters are defined based on data made available by Alagoas Secretary of Health from April 19, 2020 on. We provide with the evolution of the basic reproduction number $R_0$ and reproduce the historical series of the number of confirmed cases with less than $10\%$ error. We offer predictions, from November 16 forward, over the epidemic situation in the near future and show that it will keep decelerating. Furthermore, the same model can be used to study the epidemic dynamics in other countries with great easiness and accuracy.

Amid growing debate between scientists and policymakers on the trade-off between public safety and reviving economy during the COVID-19 pandemic, the government of Bangladesh decided to relax the countrywide lockdown restrictions from the beginning of June 2020. Instead, the Ministry of Public Affairs officials have declared some parts of the capital city and a few other districts as red zones or high-risk areas based on the number of people infected in the late June 2020. Nonetheless, the COVID-19 infection rate had been increasing in almost every other part of the country. Ironically, rather than ensuring rapid tests and isolation of COVID-19 patients, from the beginning of July 2020, the Directorate General of Health Services restrained the maximum number of tests per laboratory. Thus, the health experts have raised the question of whether the government is heading toward achieving herd immunity instead of containing the COVID-19 pandemic. In this paper, the dynamics of the pandemic due to SARS-CoV-2 in Bangladesh is analyzed with integrated the Unscented Kalman Filter (UKF) in the SIRD model. We demonstrate that the herd immunity threshold can be reduced to 31% than that of 60% by considering age group cluster analysis resulting in a total of 53.0 million susceptible populations. With the data of COVID-19 cases till January, 2021, the time-varying reproduction numbers are used to explain the nature of the pandemic. Based on the estimations of active, severe and critical cases, we discuss a set of policy recommendations to improve the current pandemic control methods in Bangladesh.

Different epidemiological compartmental models have been presented to predict the transmission dynamics of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we have proposed a fuzzy rule-based Susceptible-Exposed-Infectious-Recovered-Death ($SEIRD$) compartmental model considering a new dynamic transmission possibility variable as a function of time and three different fuzzy linguistic intervention variables to delineate the intervention and transmission heterogeneity on SARS-CoV-2 viral infection. We have analyzed the datasets of active cases and total death cases of China and Bangladesh. Using our model, we have predicted active cases and total death cases for China and Bangladesh. We further presented the correspondence of different intervention measures in relaxing the transmission possibility. The proposed model delineates the correspondence between the intervention measures as fuzzy subsets and the predicted active cases and total death cases. The prediction made by our system fitted the collected dataset very well while considering different fuzzy intervention measures. The integration of fuzzy logic in the classical compartmental model also produces more realistic results as it generates a dynamic transmission possibility variable. The proposed model could be used to control the transmission of SARS-CoV-2 as it deals with the intervention and transmission heterogeneity on SARS-CoV-2 transmission dynamics.

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.

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.

The SARS-CoV-2 outbreak in 2019 highlighted the fact that no specific medications providing effective treatment have been identified and approved. We explored the possibilities for COVID-19 by systematically reviewing evidence on the efficacy and safety of glycyrrhizin preparations for SARS and MERS. Electronic databases were systematically searched from inception to February 2020 for eligible studies that evaluated the efficacy and safety of glycyrrhizin preparations for SARS and MERS. A quantitative analysis or descriptive analysis was applied. Five retrospective cohort studies were included, and NOS scores ranged from 5–7 points. The clinical symptoms of dry cough, chest distress and dyspnoea improved quickly, and elevated serum levels of aminotransferase decreased after compound glycyrrhizin treatment. The SARS-CoV antibody appeared earlier in the treated group than in the control group ($-2.9\pm 2.8$d). Compared to that with conventional medications, the average period from peak to 50% improvement of lesions, in terms of X-ray manifestations, was shorter with compound glycyrrhizin treatment ($-$2.1d), and treatment reduced the dosage ($-75.7\pm 42.8$mg/d) and duration of the corticosteroids used, without other serious adverse reactions. Based on the available evidence regarding glycyrrhizin preparations for treating SARS and MERS, we infer that compound glycyrrhizin could be an optional therapeutic strategy for SARS-CoV-2 infections, especially those complicated with liver damage. Further research using well-designed randomized clinical trials (RCTs) is warranted to determine the dosage and duration of use of compound glycyrrhizin and to monitor its specific adverse effects.

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.

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.

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.

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.

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.

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.

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 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 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 SARS-CoV-2 leads to a worldwide COVID-19 pandemic, which has caused tremendous damage to the world. In this paper, we develop a dynamic model in vivo, fitting and estimating parameters for T lymphocytes and pro-inflammatory cytokines IL-6 in patients with mild and severe COVID-19 at Yale New Haven Hospital through the GWMCMC algorithm. Meanwhile, we also analyze the structural identifiability and practical identifiability of the model. Further, we add time-varying parameters to the model, using the least squares method to perform data fitting and parameter estimation on survivors and non-survivors of the Italian infectious disease hospital. Then analyze the similarities and differences in immune response mechanisms between the two countries. Finally, we demonstrate the existence and stability of the equilibrium state of the model and analyze the Hopf bifurcation at the positive equilibrium state by using the central manifold theory and normal form theory. This result may explain the recurrence of infection in some COVID-19 patients.

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.

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.