The ecological theory of species interactions rests largely on the competition, interference, and predator-prey models. In this paper, we propose and investigate a three-species predator-prey model to inspect the mutual interference between predators. We analyze boundedness and Kolmogorov conditions for the non-spatial model. The dynamical behavior of the system is analyzed by stability and Hopf bifurcation analysis. The Turing instability criteria for the Spatio-temporal system is estimated. In the numerical simulation, phase portrait with time evolution diagrams shows periodic and chaotic oscillations. Bifurcation diagrams show the very rich and complex dynamical behavior of the non-spatial model. We calculate the Lyapunov exponent to justify the dynamics of the non-spatial model. A variety of patterns like interference, spot, and stripe are observed with special emphasis on Beddington-DeAngelis function response. These complex patterns explore the beauty of the spatio-temporal model and it can be easily related to real-world biological systems.

To investigate the characteristic findings between laboratory-confirmed and clinically suspected patients with COVID-19. In this retrospective study, we included patients admitted to the Xiangya Hospital from Jan 24 to Feb 10, 2020. Two researchers separately collected and sorted out the patients' epidemiological, demographic, clinical, laboratory, and radiologic findings. SPSS was performed to analyze the collected data. 241 patients were admitted, including 28 (45.5; IQR, 34.0-52.5) confirmed and 213 (42.0; IQR, 30.0-57.0) suspected patients. The prevalence of COVID-19 disease in males was significantly higher than in females (64.3% vs. 35.7%,  = 0.033). Before admission of the confirmed and suspected undiagnosed cases, the onset of symptoms is often manifested as respiratory symptoms such as fever (35.7% vs. 27.7%) and cough (30.7% vs. 32.1%). Twenty patients (71.4%) had an exposure history to high-risk areas, and 14 patients (50.0%) traveled or lived in a high-risk area in the confirmed group, which was significantly different from the suspected group. The pulmonary imaging of the patients in the confirmed group was primarily manifested as ground-glass opacity (89.3%). A total of 499 nucleic acid testing (NAT) was performed to determine the 28 COVID-19 positive throat swabs among the 241 patients. Whether there is a history of high-risk area exposure in the epidemiological investigation is essential in distinguishing the suspected patients from the confirmed patients. Multiple nucleic acid tests were used as the basis for the diagnosis of COVID-19, and during CT examination, ground-glass opacity was used as a COVID-19 indicator. Trail registration number. 202012195, Date of registration: 2020.12.22 "retrospectively registered".

In this contribution, a first-order time scheme is proposed for finding solutions to partial differential equations (PDEs). A mathematical model of the COVID-19 epidemic is modified where the recovery rate of exposed individuals is also considered. The linear stability of the equilibrium states for the modified COVID-19 model is given by finding its Jacobian and applying Routh-Hurwitz criteria on characteristic polynomial. The proposed scheme provides the first-order accuracy in time and second-order accuracy in space. The stability of the proposed scheme is given using the von Neumann stability criterion for standard parabolic PDEs. The consistency for the proposed scheme is also given by expanding the involved terms in it using the Taylor series. The scheme can be used to obtain the condition of getting a positive solution. The stability region of the scheme can be enlarged by choosing suitable values of the contained parameter. Finally, a comparison of the proposed scheme is made with the existing non-standard finite difference method. The results indicate that the non-standard classical technique is incapable of preserving the unique characteristics of the model's epidemiologically significant solutions, whereas the proposed approaches are capable of doing so. A computational code for the proposed discrete model scheme may be made available to readers upon request for convenience.

In this article, we investigate a diffusive two-strain epidemic model with non-monotone incidence rate and virus mutation. The positivity, existence and uniform boundedness of the solutions of the model system are studied. It is found that the system has three equilibrium points, namely the infection-free equilibrium point, the strain-2 endemic equilibrium point and both the strain-1 and strain-2 endemic equilibrium points. The global asymptotic stability analysis of the diffusive model system near all the equilibrium points is carried out by constructing appropriate Lyapunov functional. It is found that the system has no strain-1 endemic equilibrium point possibly due to the virus mutation. So, in this type of diseases, the infection due to strain-1 cannot be persistent in the community.

In this paper, we consider an SEIR model that describes the dynamics of the COVID-19 pandemic. Subject to this model with vaccination and treatment as controls, we formulate a control problem that aims to reduce the number of infectious individuals to zero. The novelty of this work consists of considering a more realistic control problem by adding mixed constraints to take into account the limited vaccines supply. Furthermore, to solve this problem, we use a set-valued approach combining a Lyapunov function defined in the sense of viability theory with some results from the set-valued analysis. The expressions of the control variables are given via continuous selection of an adequately designed feedback map. The main result of our study shows that even though there are limits of vaccination resources, the combination of treatment and vaccination strategies can significantly reduce the number of exposed and infectious individuals. Some numerical simulations are proposed to show the efficiency of our set-valued approach and to validate our theoretical results.

SARS-CoV-2 is a newly emerged coronavirus that has been widely transmitted since late 2019. It has caused a pandemic and infected roughly 450 million people globally.Hitherto, there is no approved anti-COVID-19 treatment, and vaccination is the only experienced preventive strategy. It mainly promotes the immune system, which is vital as a barrier against COVID-19. Humoral immunity (antibody-mediated immunity), among the various functions of the immune system against the coronavirus, plays an outstanding role in preventing infection. Consequently, we intended to assess IgG and IgM antibodies, 3 and 6 months after infection, to trend their titer and see how long COVID-19 antibodies remained in the human body. According to the research-designed criteria, only 98 patients out of 4500 suspected cases of SARS-CoV-2 infection remained for analysis. Blood samples were taken in three time periods (Day Zero ( ), 3 and 6 months post-infection) and examined for COVID-19's IgG and IgM antibodies titration using the ELISA platform. Though both IgG and IgM were still detectable for some subjects at the end of the period, the decline in their levels (from 14.45 ± 5.88 to 2.52 ± 2.33 for IgG [85% decline of antibody titer] and 8.3 ± 0.99 to 0.37 ± 0.14 for IgM [95.5% decline of antibody titer]) was statistically significant ( value 0.0001). There was no correlation between gender and IgG and IgM levels. Although the levels of both antibodies were overall higher in the senior group (≥ 60 years old), statistical analysis showed a significantly higher level just for IgM in this group ( value: 0.005). Following the results, although anti-SARS-CoV-2 IgM and IgG antibodies can persist in the blood for 6 months post-infection, their levels steeply declined over time. Therefore, relying on humoral immunity as a trustworthy barrier against SARS-CoV-2 infection calls for more extensive research.

This study aims to explore the clinical characteristics of the patients with novel coronavirus pneumonia (COVID-19) during rehabilitation. One hundred and twelve confirmed patients were enrolled, while 72 were females (64.3%) and 40 were males (35.7%). The age of the patients was 51.63 ± 4.07 years old. Those patients were divided into mild group, moderate group and severe group based on lesion volume and proportion of total lesion on CT images. The age, gender, past medical history, finger pulse oxygen (SPO2), heart rate (HR) and body temperature and other clinical characteristics of patients were collected. Lesion volume was measured by CT. Compared with mild group, age, lesion volume and total lesion proportion in moderate group were significantly higher. Age, lesion volume and total lesion proportion in severe group were also higher than those in moderate group. Age and past medical history were the risk factors for the lesion volume of COVID-19. Older the patient has larger CT lesion range ( = 0.232,  = 0.045). Without past medical history or combination of post-medical history, the COVID-19 patients had smaller CT lesion ranges, and the history of previous cardiovascular disease and pulmonary disease was important risk factors for the larger CT lesion ranges. The patients who were older or combined with chronic diseases, especially cardiovascular diseases, respiratory disease and diabetes, tended to have the larger lesions. Age and past medical history of patients with COVID-19 period are significantly related to the lesion volume and total lesion proportion on CT images.

In any outbreak of infectious disease, the timely quarantine of infected individuals along with preventive measures strategy are the crucial methods to control new infections in the population. Therefore, this study aims to provide a novel fractional Caputo derivative-based susceptible-infected-quarantined-recovered-susceptible epidemic mathematical model along with a nonmonotonic incidence rate of infection. A new quarantined individual compartment is incorporated into the susceptible-infected-recovered-susceptible compartmental model by dividing the total population into four subpopulations. The nonmonotonic incidence rate of infection is considered as Monod-Haldane functional type to understand the psychological effects in the population. Qualitative analysis of the study shows that the model solutions are well-posed i.e., they are nonnegative and bounded in an attractive region. It is revealed that the model has two equilibria, namely, disease-free (DFE) and endemic (EE). The stability analysis of equilibria is investigated for local as well as global behaviors. Mathematical analysis of the model reveals that DFE is locally asymptotically stable when the basic reproduction number is lower than one. The basic reproduction number is computed using the next-generation matrix method. The existence of EE is shown and it is investigated that EE is locally asymptotically stable when under some appropriate conditions. Moreover, the global stability behaviors of DFE and EE are analyzed under some conditions using . Finally, some numerical simulations are performed to interpret the theoretical findings.

COVID-19 patients in critical conditions are hospitalized and treated with various protocols including antiviral drugs, which have been updated repeatedly. This study was aimed to analyze the demographics, costs, and outcomes of drug regimens in COVID-19 patients hospitalized in "Ali Asghar" hospital, affiliated with Shiraz University of Medical Sciences, from March 2019 to December 2020 as a retrospective study, approved by the ethics committee of Shiraz University of Medical Sciences (IR.SUMS.REC.1399.1003) on Dec. 28, 2020. Using hospital information system (HIS) data, 2174 patients receiving favipiravir, remdesivir, interferon-, and Kaletra were analyzed. Descriptive, univariate, and regression analyses were used. The costs and consequences of different drug regimens were significantly different ( value < 0.05); the highest and lowest costs belonged to remdesivir and Kaletra, respectively. The highest and lowest mean length of stay and mortality were related to remdesivir and favipiravir, respectively. Mortality did not differ significantly with various regimens. Length of stay was significantly shorter with favipiravir and Kaletra than interferon-. Remdesivir had significantly the highest cost. Age presented a significantly positive relationship with mortality and length of stay. Besides, ICU admission significantly increased mortality, length of stay, and costs. Underlying diseases and low blood oxygen saturation contributed to mortality. COVID-19 correlation with age and underlying diseases is accordant with the published data. Given the highest costs and broad usage of remdesivir, besides controversies regarding its outcomes and side effects, a stricter evaluation of remdesivir benefits seems essential. Totally, COVID-19 therapeutic protocols should be selected carefully to optimize costs and outcomes.

The COVID-19 pandemic has crippled the world population. Our present work aims to formulate a model to analyze the change in normal health conditions due to COVID-19 infection. For this purpose, we have collected data of seven parameters, namely, age, systolic pressure (SP), diastolic paper (DP), respiratory distress (RD), fasting blood sugar (FBS), cholesterol (CHL), and insomnia (INS) of 156 persons of Birnagar municipality, Nadia, India; before and after COVID-19 infection. Ultimately, using an adaptive neuro-fuzzy inference system (ANFIS), we have formulated our desired model, a Takagi-Sugeno fuzzy inference system. Further, with the help of this model, we have established one's change in health condition with age due to COVID-19 infection. Finally, we have derived that older people are more affected by COVID-19 infection than younger people.

The treatment of COVID-19 disease has been one of the most critical essential concerns of researchers in recent years. One of the most exciting and potential therapeutic targets for SARS-CoV-2 therapy progression is RNA-dependent RNA polymerase (RdRP), a viral enzyme for viral RNA replication throughout host cells. According to some research, Remdesivir suppresses RdRp. The nucleoside medication remdesivir has been authorized under an Emergency Use Authorization to treat COVID-19. Given the role of this enzyme in virus replication, our scientific question is whether Remdesivir is the most appropriate antiviral drug to inhibit this enzyme or not. Accordingly, this study aimed to repurpose antiviral drugs to inhibition of RdRp using virtual screening and Molecular Dynamics simulation methods. Five FDA-approved antiviral medications, including Elbasvir, Glecaprevir, Ledipasvir, Paritaprevir, and Simeprevir, had good interaction potential with RdRp. Also, the results show that the number of H-bonds and contacts and ∆ interactions between the protein and ligand in the Remdesivir complex is less than those of other complexes. According to the given data which shows the tendency of binding with RdRp for Paritaprevir, Simeprevir, Glecaprevir, and Ledipasvir and Elbasvir is more than Remdesivir and due to the fact that these five drugs have a high tendency to bind to other targets in the SARS-CoV-2, the use of Remdesivir as an antiviral drug in the treatment of COVID-19 should be considered more sensitively.

Although several drugs have been proposed and used to treat the COVID-19 virus, but recent clinical trials have concentrated on ivermectin. It appears that ivermectin can potentially act against COVID-19 and stop the development in its infancy. The purpose of this study was to determine the effect of ivermectin on the recovery of outpatients with COVID-19. In this cross-sectional study, we compared the symptoms reduction in COVID-19 disease in two groups of patients by administering ivermectin. A total of 347 mild outpatients in the Iranian provinces of Qazvin and Khuzestan with a confirmed PCR were enrolled. The symptoms of outpatients with COVID-19 were analyzed using SPSS (V23). In this cross-sectional study, the sex ratio was 0.64 (female/male: 37.9/59.8) and most patients were under 50 years old (72.8%). The results of this study demonstrated a significant decrease in several COVID-19 disease symptoms, including fever, chills, dyspnea, headache, cough, fatigue, and myalgia in the group administered ivermectin compared to the control group. In addition, the odds ratio of the above symptoms was significantly lower in patients who received ivermectin than in patients who did not receive the drug (OR = 0.16, 95% CI = 0.09, 0.27).

In this paper, we have studied a fractional-order eco-epidemiological model incorporating fear, treatment, and hunting cooperation effects to explore the memory effect in the ecological system through Caputo-type fractional-order derivative. We have studied the behavior of different equilibrium points with the memory effect. The proposed system undergoes through Hopf bifurcation with respect to the memory parameter as the bifurcation parameter. We perform numerical simulations for different values of the memory parameter and some of model parameters. In the numerical results, it appears that the system is exhibiting a stable behavior from a period or chaotic nature with the increase in the memory effect. The system also exhibits two transcritical bifurcations with respect to the growth rate of the prey. At low values of prey's growth, all species go to extinction, at moderate values of prey's growth, only preys (susceptible and infected) can survive, and at higher values of prey's growth, all species survive simultaneously. The paper ended with some recommendations.

In this paper, we analyze the complexity of an eco-epidemiological model for phytoplankton-zooplankton system in presence of toxicity and time delay. Holling type II function response is incorporated to address the predation rate as well as toxic substance distribution in zooplankton. It is also presumed that infected phytoplankton does recover from the viral infection. In the absence of time delay, stability and Hopf-bifurcation conditions are investigated to explore the system dynamics around all the possible equilibrium points. Further, in the presence of time delay, conditions for local stability are derived around the interior equilibria and the properties of the periodic solution are obtained by applying normal form theory and central manifold arguments. Computational simulation is performed to illustrate our theoretical findings. It is explored that system dynamics is very sensitive corresponding to carrying capacity and toxin liberation rate and able to generate chaos. Further, it is observed that time delay in the viral infection process can destabilize the phytoplankton density whereas zooplankton density remains in its old state. Incorporation of time delay also gives the scenario of double Hopf-bifurcation. Some control parameters are discussed to stabilize system dynamics. The effect of time delay on (i) growth rate of susceptible phytoplankton shows the extinction and double Hopf-bifurcation in the zooplankton population, (ii) a sufficiently large value of carrying capacity stabilizes the chaotic dynamics or makes the whole system chaotic with further increment.

In the pathophysiology of COVID-19, immunomodulatory factors play a vital role. Viruses have epigenetic effects on various genes, particularly methylation. Explaining the changes in immunological factor methylation levels during viral infections requires substantial consideration. HLA-C is a crucial determinant of immune function and NK cell activity and is primarily implicated in viral infections. This research focused on studying HLA-C methylation in COVID-19 patients with different severity. Peripheral blood samples were collected from 470 patients (235 men and 235 women) with RT-qPCR-confirmed COVID-19 test and classified into moderate, severe, and critical groups based on WHO criteria. Also, one hundred (50 men and 50 women) healthy subjects were selected as the control group. Peripheral blood mononuclear cells were used for DNA extraction, and the methylation-specific PCR (MSP) method and gel electrophoresis were used to determine the methylation status of the HLA-C. Significant statistical differences in HLA-C methylation were observed among cases and controls and various stages of the disease. HLA-C methylation in men and women has decreased in all stages ( < 0.05). In comparison with control, HLA-C methylation in both genders were as follows: moderate (women: 41.0%, men: 52.33%), severe (women: 43.42%, men: 64.86%), critical (women: 42.33%, men: 60.07%), and total patients (women: 45.52%, men: 56.97%). Furthermore, the methylation levels in men were higher than in women in all groups ( < 0.05). Significantly, among all groups, the severe group of men participants showed the highest methylation percentage ( < 0.05). No significant differences were detected for different disease severity in the women group ( > 0.1). This study found that HLA-C methylation was significantly lower in COVID-19 patients with different disease severity. There were also significant differences in HLA-C methylation between men and women patients with different severity. Therefore, during managing viral infections, particularly COVID-19, it is critical to consider patient gender and disease severity.

Hand, foot and mouth disease is a common viral infectious disease caused by enteroviruses, including coxsackie A16 (CVA16) and enterovirus 71 (EV71). HFMD can cause severe symptoms in children which can be fatal. Human scavenger receptor class B member 2 (SCARB2) is a cellular receptor for EV71 and CVA16, providing a potential approach for preventing EV71 infection and transmission. In this present study, we constructed and assessed the potential of recombinant SCARB2, using expression system. To generate this construct, gene was cloned into pET22b vector and expressed in BL21 (DE3). The expression of SCARB2 was induced by 0.1 mM IPTG and analyzed using SDS-PAGE, followed by Western blot. Expressed SCARB2 was in inclusion bodies and refolded to obtain the soluble form with recovery efficacy of 100%. This recombinant protein was then validated for binding with EV71 via indirect ELISA in two different pHs (7.4 and 5.5), which partially revealed the mechanism of virus-receptor interaction. These results envisaged potential applications for utilizing recombinant SCARB2 in preventing the virus transmission.

In this paper, we introduce a new stationary first-order integer-valued autoregressive process (INAR) with zero-and-one-inflated geometric innovations that is useful for modeling medical practical data. Basic probabilistic and statistical properties of the model are discussed. Conditional least squares and maximum likelihood estimators are proposed to estimate the model parameters. The performance of the estimation methods is assessed by some Monte Carlo simulation experiments. The zero-and-one-inflated INAR process is subsequently applied to analyze two medical series that include the number of new COVID-19-infected series from Barbados and Poliomyelitis data. The proposed model is compared with other popular competing zero-inflated and zero-and-one-inflated INAR models on the basis of some goodness-of-fit statistics and selection criteria, where it shows to provide better fitting and hence can be considered as another important commendable model in the class of INAR models.

Månsson and Shukur (Econ Model 28:1475-1481, 2011) proposed a Poisson ridge regression estimator (PRRE) to reduce the negative effects of multicollinearity. However, a weakness of the PRRE is its relatively large bias. Therefore, as a remedy, Türkan and Özel (J Appl Stat 43:1892-1905, 2016) examined the performance of almost unbiased ridge estimators for the Poisson regression model. These estimators will not only reduce the consequences of multicollinearity but also decrease the bias of PRRE and thus perform more efficiently. The aim of this paper is twofold. Firstly, to derive the mean square error properties of the Modified Almost Unbiased PRRE (MAUPRRE) and Almost Unbiased PRRE (AUPRRE) and then propose new ridge estimators for MAUPRRE and AUPRRE. Secondly, to compare the performance of the MAUPRRE with the AUPRRE, PRRE and maximum likelihood estimator. Using both simulation study and real-world dataset from the Swedish football league, it is evidenced that one of the proposed, MAUPRRE ( ) performed better than the rest in the presence of high to strong (0.80-0.99) multicollinearity situation.

The continuing coronavirus pandemic has come up with considerable questions in front of the world. Presently, India is among concerned countries in Asia. Even though the recovery rate is more than the death rate, it is affecting human lives and experiencing losses to the market. Several methods were employed to study the spread of novel coronavirus. Mathematical modeling is one of the prominent techniques to evaluate the dynamics of novel coronavirus. In this work, we extend the mathematical model SEIAQRDT by incorporating environmental transmission to analyze the transmission of coronavirus in India. The notable aspect of the model incorporates asymptomatic population, quarantine individuals, and environmental transmission factors. These factors have enormous significance in the ongoing COVID-19 outbreak. The basic reproduction number is calculated theoretically. Bifurcation analysis of is also done analytically. The existence and stability analysis of disease-free equilibrium (DFE) and endemic equilibrium (EE) points are established. The impact of environmental factors in spreading COVID-19 pandemic is deliberated. The case study for India and Italy is presented and compared with real data, and the results are in accordance with the real situation.