Study on potential common action and mechanism of Reduning Injection against SARS, MERS and COVID-19 based on network pharmacology and molecular docking technology.

Objective To explore the potential common mechanism and active ingredients of Reduning Injection against SARS, MERS and COVID-19 through network pharmacology and molecular docking technology. Methods The TCMSP database was used to retrieve the chemical components and targets of Artemisiae Annuae Herba, Lonicerae Japonicae Flos and Gardeniae Fructus in Reduning Injection. The gene corresponding to the target was searched by UniProt database, and Cytoscape 3.8.2 was used to build a medicinal material-compound-target (gene) network. Three coronavirus-related targets were collected in the Gene Cards database with the key words of "SARS""MERS" and "COVID-19", and common target of three coronavirus infection diseases were screened out through Venny 2.1.0 database. The common targets of SARS, MERS and COVID-19 were intersected with the targets of Reduning Injection, and the common targets were selected as research targets. Protein-protein interaction (PPI) network map were constructed by Cytoscape3.8.2 software after importing the common targets into the STRING database to obtain data. R language was used to carry out GO biological function enrichment analysis and KEGG signaling pathway enrichment analysis, histograms and bubble charts were drew, and component-target-pathway network diagrams was constructed. The key compounds in the component-target-pathway network were selected for molecular docking with important target proteins, novel coronavirus (SARS-CoV-2) 3CL hydrolase, and angiotensin-converting enzyme II (ACE2). Results 31 active compounds and 207 corresponding targets were obtained from Reduning Injection. 2 453 SARS-related targets, 805 MERS-related targets, 2 571 COVID-19-related targets, and 786 targets for the three diseases. 11 common targets with Reduning Injection: HSPA5, CRP, MAPK1, HMOX1, TGFB1, HSP90AA1, TP53, DPP4, CXCL10, PLAT, PRKACA. GO function enrichment analysis revealed 995 biological processes (BP), 71 molecular functions (MF), and 31 cellular components (CC). KEGG pathway enrichment analysis screened 99 signal pathways (P < 0.05), mainly related to prostate cancer, fluid shear stress and atherosclerosis, hepatocellular carcinoma, proteoglycans in cancer, lipid and atherosclerosis, human T-cell leukemia virus 1 infection, MAPK signaling pathway, etc. The molecular docking results showed that the three core active flavonoids of quercetin, luteolin, and kaempferol in Reduning Injection had good affinity with key targets MAPK1, PRKACA, and HSP90AA1, and the combination of the three active compounds with SARS-CoV-2 3CL hydrolase and ACE2 was less than the recommended chemical drugs. Conclusion Reduning Injection has potential common effects on the three diseases of SARS, MERS and COVID-19. This effect may be related to those active compounds such as quercetin, luteolin, and kaempferol acting on targets such as MAPK1, PRKACA, HSP90AA1 to regulate multiple signal pathways and exert anti-virus, suppression of inflammatory storm, and regulation of immune function.Copyright © 2022 Drug Evaluation Research. All rights reserved.

A Review on the Effect of COVID-19 in Pregnant Women

Coronavirus Disease 2019 (COVID-19) is an emerging disease with a rapid increase in cases and deaths since its first discovery in December 2019, in Wuhan, China. Limited data are available on COVID-19 effects during pregnancy;however, information on diseases associated with other highly pathogenic coronaviruses (i.e. Severe Acute Respiratory Syndrome [SARS] and the Middle East respiratory syndrome [MERS]) may provide insight into the effects of COVID-19 during pregnancy. Coronaviruses cause illnesses ranging from the common cold to severe respiratory disease and death. The data indicate an average of 5 days incubation period (range: 2-14 days). The average age range of the hospitalized patients was 49-56 years, and a third to half of them have an underlying illness. Children were rarely mentioned. Within hospitalized cases, men were more frequent (54%-73%). Fever, cough, myalgia, vomiting, and diarrhea are common symptoms. This review aims at giving an in-depth understanding of COVID-19 by comparing its effects with SARS and MERS to evaluate its severity in pregnant women1. The results of varied studies show that COVID-19 affects pregnant women seriously and there is an alarming need to look into this aspect to prevent its harmful effects on the fetus.Copyright © 2020

Rational Repurposing of Drugs, Clinical Trial Candidates, and Natural Products for SARS-CoV-2 Therapy

In the last 20 years, the world has been threatened with coronavirus (CoV) pandemic threats from severe acute respiratory syndrome coronavirus (SARS-CoV) in 2002, Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012 and finally COVID-19 due to SARS-CoV-2 in 2019. These viruses posed serious global pandemic threats, with estimated case fatality rates of 15% for SARS-CoV, 34% for MERS-CoV, and 1-3% for SARS-CoV-2. With the current pandemic still far from over there is an urgent need to find new drug treatments for COVID-19. We can assume that this will not be the last coronavirus to threaten humanity, so we need better tools to identify drugs active against past but also future coronavirus threats. In this Chapter we describe in silico computer modeling and screening approaches that can rapidly identify drugs from existing drug libraries that could be repurposed to treat COVID-19 infections. We also describe how this computational screening pipeline can be expanded in the future to identify drugs with broad spectrum activity against a wide diversity of coronaviruses. A significant concern is that the protection against CoVs provided by single drugs protection may be short-lived because viruses rapidly mutate to develop drug resistance. We know from other viruses such as HIV that drugs hitting multiple targets within the virus provide better protection against the development of resistance. This Chapter describes the current state of development of in silico CoV drug repurposing, the challenges and pitfalls of these approaches, and our predictions of how these methods could be used to develop drugs for future pandemics before they occur. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Convalescent plasma transfusion in severe or critically ill COVID 19 patients: a rapid systematic review

Currently, there is no availability of any proven specific treatment or prevention strategy to fight against COVID-19. Convalescent plasma (CP) therapy is expected to increase survival rates in COVID-19 as in the case of emerging viral infection (SARS-CoV and MERS-CoV). To collect all the studies relevant to CP therapy in critically ill or severe COVID-19 patients and summarize the findings. The systematic review was conducted according to the PRISMA consensus statement. A systematic search was performed in PubMed, Scopus, Web of Science, and Cochrane databases on April 25, 2020. A total of six studies (28 patients) relevant to CP therapy in severe or critical COVID-19 are considered for inclusion. Two authors extracted the data about study characteristics, demographics, symptoms, co-morbidities, clinical classification of COVID-19, drug therapies, oxygen therapy, laboratory results, chest CT, neutralizing antibody titer, SARS-CoV-2 RNA load, aal outcome. The review findings revealed that CP therapy increases lymphocyte count, reduced s serum inflammatory markers (CRP, IL-6, Procalcitonin) and liver enzyme levels (AST or ALT). There was a rise in serum neutralizing antibody titers in 10 of 14 patients after CP transfusion. In 4 of 14 patients, the titer levels remain unchanged after CP transfusion. All 28 cases (100%) achieved negative to the SARS-CoV-2 RNA after CP transfusion. The convalescent plasma transfusion can improve neutralizing antibody titers and reduces the viral load in severe/critical COVID-19 patients. The review recommends a well-controlled trial design is required to give a definite statement on the safety and efficacy of convalescent plasma therapy in severe/critical COVID-19.

Impact of Early Termination of Lockdown and Maintaining Social Distancing: COVID-19

A novel corona-virus named COVID-19 has spread rapidly and has caused a global outbreak of respiratory illness. It has been confirmed that the bats are the source host of SARS, and camels act as a source for MERS. However, the source host of the COVID-19 remains unknown. All three kinds of pneumonia show human-to-human transmissions. Among which, COVID-19 shows a longer incubation period. The routes for the human to human transmission are common, respiratory droplets, contact, and aerosol. In which, the new form is Aerosol transmission. In which, integration of the air with droplets will occur during transmission that leads to the formation of Droplet Nucleus. It can lead to infection after inhalation. Because of this, the virus has already spread to South Korea, Japan, Iran, Italy, and other countries. The objective of this chapter is to address the impact and list the suggestion to handle COVID-19 safely. The methodology followed in drafting this chapter is to provide answers to the following questions: Q1: The clinical manifestation of COVID-19? Q2: How to prevent the transmission of this disease and protect themselves? Q3: The outcome of COVID-19 pneumonia. Q4: How to diagnose COVID-19? Q5: The effects of COVID-19 pneumonia on pregnancy: Q6: Coronavirus pneumonia in children. Q7: The response strategies against the COVID-19 in China. Q8: Therapeutic Strategy for COVID-19. Q9: Consequences of COVID-19 in Human Daily Life. Q10: How to deal with the novel Coronavirus disease calmly? Q11: The COVID-19 prevention among students. Q12: Plan to return to the campus. Q13: Home-based self-care in climacteric women Q14: Strategies to climacteric women's psychological problems during COVID-19 pandemic. The outcome of the present research is to provide suggestions to the humankind towards handling the epidemic safely. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Modeling the epidemic trend of middle eastern respiratory syndrome coronavirus with optimal control

Since the outbreak of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in 2012 in the Middle East, we have proposed a deterministic theoretical model to understand its transmission between individuals and MERS-CoV reservoirs such as camels. We aim to calculate the basic reproduction number (R0) of the model to examine its airborne transmission. By applying stability theory, we can analyze and visualize the local and global features of the model to determine its stability. We also study the sensitivity of R0 to determine the impact of each parameter on the transmission of the disease. Our model is designed with optimal control in mind to minimize the number of infected individuals while keeping intervention costs low. The model includes time -dependent control variables such as supportive care, the use of surgical masks, government campaigns promoting the importance of masks, and treatment. To support our analytical work, we present numerical simulation results for the proposed model.

Identification of host factors that bind to the 5 ' end of the MERS-CoV RNA genome

Plain language summaryMERS-CoV is a virus that causes a severe illness in the nose, mouth and throat of humans. It is a zoonotic virus, which means that it can spread from animals to humans. MERS-CoV was first found in Saudi Arabia in 2012 and continues to pose a threat to public health. Interactions between the virus and human cells and proteins are important to establishing infection. Understanding these interactions is important for the development of drugs to treat viral infections. Here, we have identified some proteins that interact with MERS-CoV. Tweetable A proteomic approach for the identification of cellular proteins that interact with the 5 '-terminal region of MERS-CoV RNA genome. #MERS-CoV #RNA_viruses. Aim: The aim of this study was to identify host factors that interact with the 5 ' end of the MERS-CoV RNA genome. Materials & methods: RNA affinity chromatography followed by mass spectrometry analysis was used to identify the binding of host factors in Vero E6 cells. Results: A total of 59 host factors that bound the MERS-CoV RNA genome in non-infected Vero E6 cells were identified. Most of the identified cellular proteins were previously reported to interact with the genome of other RNA viruses. We validated our mass spectrometry results using western blotting. Conclusion: These data enhance our knowledge about the RNA-host interactions of coronaviruses, which could serve as targets for developing antiviral therapeutics against MERS-CoV.

A resource of human coronavirus protein-coding sequences in a flexible, multipurpose Gateway Entry clone collection.

The COVID-19 pandemic has catalyzed unprecedented scientific data and reagent sharing and collaboration, which enabled understanding the virology of the SARS-CoV-2 virus and vaccine development at record speed. The pandemic, however, has also raised awareness of the danger posed by the family of coronaviruses, of which 7 are known to infect humans and dozens have been identified in reservoir species, such as bats, rodents, or livestock. To facilitate understanding the commonalities and specifics of coronavirus infections and aspects of viral biology that determine their level of lethality to the human host, we have generated a collection of freely available clones encoding nearly all human coronavirus proteins known to date. We hope that this flexible, Gateway-compatible vector collection will encourage further research into the interactions of coronaviruses with their human host, to increase preparedness for future zoonotic viral outbreaks.

A comprehensive insight on the challenges for COVID-19 vaccine: A lesson learnt from other viral vaccines.

The aim of this study is to comprehensively analyze previous viral vaccine programs and identify potential challenges and effective measures for the COVID-19 vaccine program. Previous viral vaccine programs, such as those for HIV, Zika, Influenza, Ebola, Dengue, SARS, and MERS, were evaluated. Paramount challenges were identified, including quasi-species, cross-reactivity, duration of immunity, revaccination, mutation, immunosenescence, and adverse events related to viral vaccines. Although a large population has been vaccinated, mutations in SARS-CoV-2 and adverse events related to vaccines pose significant challenges. Previous vaccine programs have taught us that predicting the final outcome of the current vaccine program for COVID-19 cannot be determined at a given state. Long-term follow-up studies are essential. Validated preclinical studies, long-term follow-up studies, alternative therapeutic approaches, and alternative vaccines are necessary.

A Comprehensive Review on COVID-19: Emphasis on Current Vaccination and Nanotechnology Aspects.

COVID-19, caused by SARS-CoV-2 virus, has been expanding. SARS-CoV caused an outbreak in early 2000, while MERS-CoV had a similar expansion of illness in early 2010. Nano-technology has been employed for nasal delivery of drugs to conquer a variety of challenges that emerge during mucosal administration. The role of nanotechnology is highly relevant to counter this "virus" nano enemy. This technique directs the safe and effective distribution of accessible therapeutic choices using tailored nanocarriers, as well as the interruption of virion assembly, by preventing the early contacts of viral spike glycoprotein with host cell surface receptors. This study summarises what we know about earlier SARS-CoV and MERS-CoV illnesses, with the goal of better understanding the recently discovered SARS-CoV-2 virus. It also explains the progress made so far in creating COVID-19 vaccines/ treatments using existing methods. Furthermore, we studied nanotechnology-based vaccinations and therapeutic medications that are now undergoing clinical trials and other alternatives.

MICaFVi: A Novel Magnetic Immuno-Capture Flow Virometry Nano-Based Diagnostic Tool for Detection of Coronaviruses.

COVID-19 has resulted in a pandemic that aggravated the world's healthcare systems, economies, and education, and caused millions of global deaths. Until now, there has been no specific, reliable, and effective treatment to combat the virus and its variants. The current standard tedious PCR-based tests have limitations in terms of sensitivity, specificity, turnaround time, and false negative results. Thus, an alternative, rapid, accurate, and sensitive diagnostic tool that can detect viral particles, without the need for amplification or viral replication, is central to infectious disease surveillance. Here, we report MICaFVi (Magnetic Immuno-Capture Flow Virometry), a novel precise nano-biosensor diagnostic assay for coronavirus detection which combines the MNP-based immuno-capture of viruses for enrichment followed by flow-virometry analysis, enabling the sensitive detection of viral particles and pseudoviruses. As proof of concept, virus-mimicking spike-protein-coated silica particles (VM-SPs) were captured using anti-spike-antibody-conjugated MNPs (AS-MNPs) followed by detection using flow cytometry. Our results showed that MICaFVi can successfully detect viral MERS-CoV/SARS-CoV-2-mimicking particles as well as MERS-CoV pseudoviral particles (MERSpp) with high specificity and sensitivity, where a limit of detection (LOD) of 3.9 µg/mL (20 pmol/mL) was achieved. The proposed method has great potential for designing practical, specific, and point-of-care testing for rapid and sensitive diagnoses of coronavirus and other infectious diseases.

Classification of Highly Divergent Viruses from DNA/RNA Sequence Using Transformer-Based Models.

Viruses infect millions of people worldwide each year, and some can lead to cancer or increase the risk of cancer. As viruses have highly mutable genomes, new viruses may emerge in the future, such as COVID-19 and influenza. Traditional virology relies on predefined rules to identify viruses, but new viruses may be completely or partially divergent from the reference genome, rendering statistical methods and similarity calculations insufficient for all genome sequences. Identifying DNA/RNA-based viral sequences is a crucial step in differentiating different types of lethal pathogens, including their variants and strains. While various tools in bioinformatics can align them, expert biologists are required to interpret the results. Computational virology is a scientific field that studies viruses, their origins, and drug discovery, where machine learning plays a crucial role in extracting domain- and task-specific features to tackle this challenge. This paper proposes a genome analysis system that uses advanced deep learning to identify dozens of viruses. The system uses nucleotide sequences from the NCBI GenBank database and a BERT tokenizer to extract features from the sequences by breaking them down into tokens. We also generated synthetic data for viruses with small sample sizes. The proposed system has two components: a scratch BERT architecture specifically designed for DNA analysis, which is used to learn the next codons unsupervised, and a classifier that identifies important features and understands the relationship between genotype and phenotype. Our system achieved an accuracy of 97.69% in identifying viral sequences.

Enhancing immune protection against MERS-CoV: the synergistic effect of proteolytic cleavage sites and the fusion peptide and RBD domain targeting VLP immunization.

Introduction: The Middle East Respiratory Syndrome Coronavirus (MERS-CoV) is a zoonotic infectious virus that has caused significant outbreaks in the Middle East and beyond. Due to a highly mortality rate, easy transmission, and rapid spread of the MERS-CoV, it remains as a significant public health treat. There is currently no licensed vaccine available to protect against MERS-CoV. Methods: In this study, we investigated whether the proteolytic cleavage sites and fusion peptide domain of the MERS-CoV spike (S) protein could be a vaccine target to elicit the MERS-CoV S protein-specific antibody responses and confer immune protection against MERS-CoV infection. Our results demonstrate that immunization of the proteolytic cleavage sites and the fusion peptide domain using virus-like particle (VLP) induced the MERS-CoV S protein-specific IgG antibodies with capacity to neutralize pseudotyped MERS-CoV infection in vitro. Moreover, proteolytic cleavage sites and the fusion peptide VLP immunization showed a synergistic effect on the immune protection against MERS-CoV infection elicited by immunization with VLP expressing the receptor binding domain (RBD) of the S protein. Additionally, immune evasion of MERS-CoV RBD variants from anti-RBD sera was significantly controlled by anti-proteolytic cleavage sites and the fusion peptide sera. Conclusion and discussion: Our study demonstrates the potential of VLP immunization targeting the proteolytic cleavage sites and the fusion peptide and RBD domains of the MERS-CoV S protein for the development of effective treatments and vaccines against MERS-CoV and related variants.

Luteolin Isolated from Juncus acutus L., a Potential Remedy for Human Coronavirus 229E.

The COVID-19 pandemic, caused by SARS-CoV-2, addressed the lack of specific antiviral drugs against coronaviruses. In this study, bioguided fractionation performed on both ethyl acetate and aqueous sub-extracts of Juncus acutus stems led to identifying luteolin as a highly active antiviral molecule against human coronavirus HCoV-229E. The apolar sub-extract (CH2Cl2) containing phenanthrene derivatives did not show antiviral activity against this coronavirus. Infection tests on Huh-7 cells, expressing or not the cellular protease TMPRSS2, using luciferase reporter virus HCoV-229E-Luc showed that luteolin exhibited a dose-dependent inhibition of infection. Respective IC50 values of 1.77 µM and 1.95 µM were determined. Under its glycosylated form (luteolin-7-O-glucoside), luteolin was inactive against HCoV-229E. Time of addition assay showed that utmost anti-HCoV-229E activity of luteolin was achieved when added at the post-inoculation step, indicating that luteolin acts as an inhibitor of the replication step of HCoV-229E. Unfortunately, no obvious antiviral activity for luteolin was found against SARS-CoV-2 and MERS-CoV in this study. In conclusion, luteolin isolated from Juncus acutus is a new inhibitor of alphacoronavirus HCoV-229E.

Secondary Structures of MERS-CoV, SARS-CoV, and SARS-CoV-2 Spike Proteins Revealed by Infrared Vibrational Spectroscopy.

All coronaviruses are characterized by spike glycoproteins whose S1 subunits contain the receptor binding domain (RBD). The RBD anchors the virus to the host cellular membrane to regulate the virus transmissibility and infectious process. Although the protein/receptor interaction mainly depends on the spike's conformation, particularly on its S1 unit, their secondary structures are poorly known. In this paper, the S1 conformation was investigated for MERS-CoV, SARS-CoV, and SARS-CoV-2 at serological pH by measuring their Amide I infrared absorption bands. The SARS-CoV-2 S1 secondary structure revealed a strong difference compared to those of MERS-CoV and SARS-CoV, with a significant presence of extended ß-sheets. Furthermore, the conformation of the SARS-CoV-2 S1 showed a significant change by moving from serological pH to mild acidic and alkaline pH conditions. Both results suggest the capability of infrared spectroscopy to follow the secondary structure adaptation of the SARS-CoV-2 S1 to different environments.

Reddit and Google Activity Related to Non-COVID Epidemic Diseases Surged at Start of COVID-19 Pandemic: Retrospective Study.

BACKGROUND: Resources such as Google Trends and Reddit provide opportunities to gauge real-time popular interest in public health issues. Despite the potential for these publicly available and free resources to help optimize public health campaigns, use for this purpose has been limited. OBJECTIVE: The purpose of this study is to determine whether early public awareness of COVID-19 correlated with elevated public interest in other infectious diseases of public health importance. METHODS: Google Trends search data and Reddit comment data were analyzed from 2018 through 2020 for the frequency of keywords "chikungunya," "Ebola," "H1N1," "MERS," "SARS," and "Zika," 6 highly publicized epidemic diseases in recent decades. After collecting Google Trends relative popularity scores for each of these 6 terms, unpaired 2-tailed t tests were used to compare the 2020 weekly scores for each term to their average level over the 3-year study period. The number of Reddit comments per month with each of these 6 terms was collected and then adjusted for the total estimated Reddit monthly comment volume to derive a measure of relative use, analogous to the Google Trends popularity score. The relative monthly incidence of comments with each search term was then compared to the corresponding search term's pre-COVID monthly comment data, again using unpaired 2-tailed t tests. P value cutoffs for statistical significance were determined a priori with a Bonferroni correction. RESULTS: Google Trends and Reddit data both demonstrate large and statistically significant increases in the usage of each evaluated disease term through at least the initial months of the pandemic. Google searches and Reddit comments that included any of the evaluated infectious disease search terms rose significantly in the first months of 2020 above their baseline usage, peaking in March 2020. Google searches for "SARS" and "MERS" remained elevated for the entirety of the 2020 calendar year, as did Reddit comments with the words "Ebola," "H1N1," "MERS," and "SARS" (P<.001, for each weekly or monthly comparison, respectively). CONCLUSIONS: Google Trends and Reddit can readily be used to evaluate real-time general interest levels in public health-related topics, providing a tool to better time and direct public health initiatives that require a receptive target audience. The start of the COVID-19 pandemic correlated with increased public interest in other epidemic infectious diseases. We have demonstrated that for 6 distinct infectious causes of epidemics over the last 2 decades, public interest rose substantially and rapidly with the outbreak of COVID-19. Our data suggests that for at least several months after the initial outbreak, the public may have been particularly receptive to dialogue on these topics. Public health officials should consider using Google Trends and social media data to identify patterns of engagement with public health topics in real time and to optimize the timing of public health campaigns.

Combining virtual screening with cis-/trans-cleavage enzymatic assays effectively reveals broad-spectrum inhibitors that target the main proteases of SARS-CoV-2 and MERS-CoV.

The main protease (Mpro) of SARS-CoV-2 is essential for viral replication, which suggests that the Mpro is a critical target in the development of small molecules to treat COVID-19. This study used an in-silico prediction approach to investigate the complex structure of SARS-CoV-2 Mpro in compounds from the United States National Cancer Institute (NCI) database, then validate potential inhibitory compounds against the SARS-CoV-2 Mpro in cis- and trans-cleavage proteolytic assays. Virtual screening of ∼280,000 compounds from the NCI database identified 10 compounds with highest site-moiety map scores. Compound NSC89640 (coded C1) showed marked inhibitory activity against the SARS-CoV-2 Mpro in cis-/trans-cleavage assays. C1 strongly inhibited SARS-CoV-2 Mpro enzymatic activity, with a half maximal inhibitory concentration (IC50) of 2.69 µM and a selectivity index (SI) of >74.35. The C1 structure served as a template to identify structural analogs based on AtomPair fingerprints to refine and verify structure-function associations. Mpro-mediated cis-/trans-cleavage assays conducted with the structural analogs revealed that compound NSC89641 (coded D2) exhibited the highest inhibitory potency against SARS-CoV-2 Mpro enzymatic activity, with an IC50 of 3.05 µM and a SI of >65.57. Compounds C1 and D2 also displayed inhibitory activity against MERS-CoV-2 with an IC50 of <3.5 µM. Thus, C1 shows potential as an effective Mpro inhibitor of SARS-CoV-2 and MERS-CoV. Our rigorous study framework efficiently identified lead compounds targeting the SARS-CoV-2 Mpro and MERS-CoV Mpro.

Relationship between Knowledge and Anxiety about Covid-19 among Nurses in Iran: A Cross-sectional Study

The level of knowledge people have about Covid-19 can affect their anxiety and worry about this disease. The present study was conducted to assess the relationship between knowledge and anxiety about Covid-19 in nurses at Guilan University of Medical Sciences, north of Iran. This cross-sectional study was conducted on 270 nurses working in selected hospitals of Guilan University of Medical Sciences in northern Iran using a questionnaire that included demographic characteristics, knowledge (21 questions), and anxiety about Covid-19 (18 questions with two components of physical and mental). The data were analysed in SPSS ver. 21 using descriptive and analytical statistics. The mean score of knowledge of subjects about Covid-19 was 18.65 +/- 1.5 (range: 021);the mean score of physical symptoms of anxiety was 3.31 +/- 4.77 (range: 027);and the mean score of mental symptoms was 10.77 +/- 5.61 (range: 0-27). The mean of general anxiety about Covid-19 was 14.08 +/- 9.54 (range: 0-54) and most participants had sufficient knowledge and mild anxiety about Covid-19. In the present study, there was no significant relationship between the level of knowledge and the level of anxiety about Covid-19. It was found in the present study that nurses were well aware of Covid-19 and mildly anxious about it, but there were mental anxiety symptoms present. It is more critical than ever to engage nurses in educational and practical programmes provided by disparate institutions, primarily educational departments of hospitals, in different domains of mental health.

Three dimensional epidemic model with non-monotonic incidence and saturated treatment: A case study of SARS infection of Hong Kong 2003 scenario

In this paper, we have proposed a mathematical compartmental model with non-monotonic incidence and saturated treatment and we have validated the model with SARS infection in Hong Kong, 2003. We have analysed the stability of disease free and endemic equilibria as well as different bifurcations. We have shown that the epidemic disappears if the cure rate of treatment crosses a threshold value. We have obtained a necessary and sufficient condition for backward bifurcation, which shows the basic reproduction number less than unity is not sufficient to eradicate the disease completely. Saddle–node and Hopf bifurcation with respect to awareness factor have been investigated, which shows that the awareness factor is effective to change the disease dynamics. The model has been fitted to SARS cases in Hong Kong. The most effective parameters for controlling infections have been identified through sensitivity analysis. Moreover, we have investigated how the number of infected cases reduces if there was some vaccination polices in SARS infection. Finally, the model has been also used as an optimal control problem as vaccination and treatment controls are time dependent functions.