Computational design of candidate multi-epitope vaccine against SARS-CoV-2 targeting structural (S and N) and non-structural (NSP3 and NSP12) proteins.

The COVID-19 pandemic caused by SARS-CoV-2 virus has created a global damage and has exposed the vulnerable side of scientific research towards novel diseases. The intensity of the pandemic is huge, with mortality rates of more than 6 million people worldwide in a span of 2 years. Considering the gravity of the situation, scientists all across the world are continuously attempting to create successful therapeutic solutions to combat the virus. Various vaccination strategies are being devised to ensure effective immunization against SARS-CoV-2 infection. SARS-CoV-2 spreads very rapidly, and the infection rate is remarkably high than other respiratory tract viruses. The viral entry and recognition of the host cell is facilitated by S protein of the virus. N protein along with NSP3 is majorly responsible for viral genome assembly and NSP12 performs polymerase activity for RNA synthesis. In this study, we have designed a multi-epitope, chimeric vaccine considering the two structural (S and N protein) and two non-structural proteins (NSP3 and NSP12) of SARS-CoV-2 virus. The aim is to induce immune response by generating antibodies against these proteins to target the viral entry and viral replication in the host cell. In this study, computational tools were used, and the reliability of the vaccine was verified using molecular docking, molecular dynamics simulation and immune simulation studies in silico. These studies demonstrate that the vaccine designed shows steady interaction with Toll like receptors with good stability and will be effective in inducing a strong and specific immune response in the body.Communicated by Ramaswamy H. Sarma.

Colchicine and aspirin in community patients with COVID-19 (ACT): an open-label, factorial, randomised, controlled trial.

BACKGROUND: The large number of patients worldwide infected with the SARS-CoV-2 virus has overwhelmed health-care systems globally. The Anti-Coronavirus Therapies (ACT) outpatient trial aimed to evaluate anti-inflammatory therapy with colchicine and antithrombotic therapy with aspirin for prevention of disease progression in community patients with COVID-19. METHODS: The ACT outpatient, open-label, 2 × 2 factorial, randomised, controlled trial, was done at 48 clinical sites in 11 countries. Patients in the community aged 30 years and older with symptomatic, laboratory confirmed COVID-19 who were within 7 days of diagnosis and at high risk of disease progression were randomly assigned (1:1) to receive colchicine 0·6 mg twice daily for 3 days and then 0·6 mg once daily for 25 days versus usual care, and in a second (1:1) randomisation to receive aspirin 100 mg once daily for 28 days versus usual care. Investigators and patients were not masked to treatment allocation. The primary outcome was assessed at 45 days in the intention-to-treat population; for the colchicine randomisation it was hospitalisation or death, and for the aspirin randomisation it was major thrombosis, hospitalisation, or death. The ACT outpatient trial is registered at ClinicalTrials.gov, NCT04324463 and is ongoing. FINDINGS: Between Aug 27, 2020, and Feb 10, 2022, 3917 patients were randomly assigned to colchicine or control and to aspirin or control; after excluding 36 patients due to administrative reasons 3881 individuals were included in the analysis (n=1939 colchicine vs n=1942 control; n=1945 aspirin vs 1936 control). Follow-up was more than 99% complete. Overall event rates were 5 (0·1%) of 3881 for major thrombosis, 123 (3·2%) of 3881 for hospitalisation, and 23 (0·6%) of 3881 for death; 66 (3·4%) of 1939 patients allocated to colchicine and 65 (3·3%) of 1942 patients allocated to control experienced hospitalisation or death (hazard ratio [HR] 1·02, 95% CI 0·72-1·43, p=0·93); and 59 (3·0%) of 1945 of patients allocated to aspirin and 73 (3·8%) of 1936 patients allocated to control experienced major thrombosis, hospitalisation, or death (HR 0·80, 95% CI 0·57-1·13, p=0·21). Results for the primary outcome were consistent in all prespecified subgroups, including according to baseline vaccination status, timing of randomisation in relation to onset of symptoms (post-hoc analysis), and timing of enrolment according to the phase of the pandemic (post-hoc analysis). There were more serious adverse events with colchicine than with control (34 patients [1·8%] of 1939 vs 27 [1·4%] of 1942) but none in either group that led to discontinuation of study interventions. There was no increase in serious adverse events with aspirin versus control (31 [1·6%] vs 31 [1·6%]) and none that led to discontinuation of study interventions. INTERPRETATION: The results provide no support for the use of colchicine or aspirin to prevent disease progression or death in outpatients with COVID-19. FUNDING: Canadian Institutes for Health Research, Bayer, Population Health Research Institute, Hamilton Health Sciences Research Institute, and Thistledown Foundation. TRANSLATIONS: For the Portuguese, Russian and Spanish translations of the abstract see Supplementary Materials section.

A fractional-order mathematical model for COVID-19 outbreak with the effect of symptomatic and asymptomatic transmissions.

The purpose of this paper is to investigate the transmission dynamics of a fractional-order mathematical model of COVID-19 including susceptible ( S ), exposed ( E ), asymptomatic infected ( I 1 ), symptomatic infected ( I 2 ), and recovered ( R ) classes named SEI 1 I 2 R model, using the Caputo fractional derivative. Here, SEI 1 I 2 R model describes the effect of asymptomatic and symptomatic transmissions on coronavirus disease outbreak. The existence and uniqueness of the solution are studied with the help of Schaefer- and Banach-type fixed point theorems. Sensitivity analysis of the model in terms of the variance of each parameter is examined, and the basic reproduction number ( R 0 ) to discuss the local stability at two equilibrium points is proposed. Using the Routh-Hurwitz criterion of stability, it is found that the disease-free equilibrium will be stable for R 0 < 1 whereas the endemic equilibrium becomes stable for R 0 > 1 and unstable otherwise. Moreover, the numerical simulations for various values of fractional-order are carried out with the help of the fractional Euler method. The numerical results show that asymptomatic transmission has a lower impact on the disease outbreak rather than symptomatic transmission. Finally, the simulated graph of total infected population by proposed model here is compared with the real data of second-wave infected population of COVID-19 outbreak in India.

A Cross-Sectional Survey of Knowledge, Attitude, and Practices of University Students in Pakistan Regarding COVID-19.

The COVID-19 pandemic is striking the world with serious public health and socioeconomic complications. The pandemic has influenced all forms of daily life, including educational institutions. Therefore, this cross-sectional survey was conducted to understand knowledge, attitudes, and practices related to COVID-19 among the students of the University of Veterinary and Animal Sciences, Lahore. The data was collected using an online self-directed questionnaire. The survey form includes six items about sociodemographic characteristics, 14 knowledge-based questions, seven questions on attitude, and eight questions on practices. The sample number was calculated using the Raosoft sample size calculator. A total number of 3,854 students, including 1,823 men and 2,031 women, were engaged in this survey, having student representation from all the provinces in the country. The data were analyzed using a chi-square test. A total of 97% of the students knew that the etiological agent of COVID-19 is a virus and that it is a disease of the respiratory system (94%). Many students kept visiting their relatives during the lockdown (45%), and their relatives kept visiting them at home (59%). The responses from the students varied a lot on specific questions about the transmission of the virus. Women tended to have less information regarding precautionary travel measures (p < 0.01), but supplemental knowledge of prevention of disease transmission from positive patients (p < 0.01). Conclusively, the majority of the university students surveyed had imperative knowledge, a good attitude, and active practice in response to the COVID-19 outbreak. Moreover, the KAP scores have varied by demography, gender, and the number of family members. Therefore, continuous awareness of preventative behaviors should be disseminated regularly in emergencies.

DYNAMICS OF SIR MATHEMATICAL MODEL FOR COVID-19 OUTBREAK IN PAKISTAN UNDER FRACTAL-FRACTIONAL DERIVATIVE

There are still mathematical predictions in the fight against epidemics. Speedy expansion, ways and procedures for the pandemic control require early understanding when solutions with better computer-based mathematical modeling and prognosis are developed. Despite high uncertainty in each of these models, one of the important tools for public health management system is epidemiology models. The fractional order is shown to be more effective in modeling epidemic diseases, in relation to the memory effects. Notably, recently founded calculus tools, called fractal-fractional calculus, having a fractional order and fractal dimension, enable us to study the behavior of a real-world problem under both fractal and fractional tools. This paper is about the dynamical behavior of a new mathematical model of novel corona disease (COVID-19) under the fractal-fractional Atangana–Baleanu derivative. The considered model has three compartments, namely, susceptible, infected and recovered or removed (SIR). The existence and uniqueness of the model’s solution will be proved via Krasnoselskii’s and Banach’s fixed point theorems, respectively. The stability of the solution in the sense of Hyers–Ulam (HU) will be built up by nonlinear functional analysis. Moreover, the numerical simulations for different values of isolation parameters corresponding to various fractal-fractional orders are analyzed using fractional Adams–Bashforth (AB) method with two-step Lagrange polynomial. Finally, the obtained simulation results are applied to the real data of disease spread from Pakistan. The graphical interpretations demonstrate that increasing the isolation parameters which is caused by strict precautionary measures will reduce the disease infection transmission in society. [ABSTRACT FROM AUTHOR] Copyright of Fractals is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Qualitative Analysis of Fractal-Fractional order COVID-19 Mathematical Model with Case Study of Wuhan

In this manuscript, a qualitative analysis of the mathematical model of novel coronavirus (COVID-19) involving anew devised fractal-fractional operator in the Caputo sense having the fractional-order q and the fractal dimension p is considered. The concerned model is composed of eight compartments: susceptible, exposed, infected, super-spreaders, asymptomatic, hospitalized, recovery and fatality. Under the new derivative the existence and uniqueness of the solution for considered model are proved using Schaefer’s and Banach type fixed point approaches. Additionally, with the help of nonlinear functional analysis, the condition for Ulam’s type of stability of the solution to the considered model is established. For numerical simulation of proposed model, a fractional type of two-step Lagrange polynomial known as fractional Adams-Bashforth (AB) method is applied to simulate the results. At last, the results are tested with real data from COVID-19 outbreak in Wuhan City, Hubei Province of China from 4 January to 9 March 2020, taken from a source [42]. The Numerical results are presented in terms of graphs for different fractional-order q and fractal dimensions p to describe the transmission dynamics of disease infection.