Design, Synthesis and Biological Activities of N-（Furan-2-ylmethyl）-lH-indole-3-carboxamide Derivatives as Epidemal Growth Factor Receptor Inhibitors and Anticancer Agents

A series ofN-（furan-2-ylmethyl）-lH-indole-3-carboxamide derivatives（6a--6p） was designed and synthe- sized for developing novel indole scaffolds as anticancer agents targeting the epidemal growth factor receptor （EGFR）, and the cytotoxic activities of the target compounds were evaluated against three EGFR high-expressed cancer cell lines[human lung adenocarcinoma cell line（A549）, Henrietta Lacks strain of cancer cell line（HeLa） and human colorectal cancer cell line（SW480）], one EGFR low-expressed cell line（human liver cancer cell line, HepG2） and one human liver normal cell line（HL7702） using 3-（4,5-dimethylthiazol-2-yl）-2,5-diphenyl tetrazolium bromide （MTT） assay, Some target compounds exhibited potent anficancer activities against A549, HeLa, SW480 and weak activities on HepG2, which signifies that the target compounds are likely to be EGFR inhibitors as expected. And they showed weak cytotoxic effects on HL7702, which implies the target compounds are probably to be of low toxicity against normal cells. Among them, the target compound 1-ethyl-N-（fttran-2-ylmethyl）-5-{2-{ [2-（2-methoxy- phenoxy）ethyl]amino}-2-oxoethoxy}-2-methyl-1H-indole-3-carboxamide（6p） with 2-{[2-（2-methoxyphenoxy）ethyl]- amino}-2-oxoethoxy group at the C5 position of the N-（furan-2-ylmethyl）-lH-indole-3-carboxamide scaffold exhibited the most potent anticancer activity. Also the binding interaction of the target compound 6p with EGFR was explored by molecular docking. Conclusively, the novel indole scaffold may be beneficial to investigate new anticancer agents for targeting the EGFR.

Assessing healthcare workers’knowledge and confidence in the diagnosis,management and prevention of Monkeypox

BACKGROUND Monkeypox(Mpox),is a disease of global public health concern,as it does not affect only countries in western and central Africa.AIM To assess Burundi healthcare workers(HCWs)s’level of knowledge and confidence in the diagnosis and management of Mpox.METHODS We conducted a cross-sectional study via an online survey designed mainly from the World Health Organization course distributed among Burundi HCWs from June-July 2023.The questionnaire comprises 8 socioprofessional-related questions,22 questions about Mpox disease knowledge,and 3 questions to assess confidence in Mpox diagnosis and management.The data were analyzed via SPSS software version 25.0.A P value<0.05 was considered to indicate statistical significance.RESULTS The study sample comprised 471 HCWs who were mainly medical doctors(63.9%)and nurses(30.1%).None of the 22 questions concerning Mpox knowledge had at least 50%correct responses.A very low number of HCWs(17.4%)knew that Mpox has a vaccine.The confidence level to diagnose(21.20%),treat(18.00%)or prevent(23.30%)Mpox was low among HCWs.The confidence level in the diagnosis of Mpox was associated with the HCWs’age(P value=0.009),sex(P value<0.001),work experience(P value=0.002),and residence(P value<0.001).The confidence level to treat Mpox was significantly associated with the HCWs’age(P value=0.050),sex(P value<0.001),education(P value=0.033)and occupation(P value=0.005).The confidence level to prevent Mpox was associated with the HCWs’education(P value<0.001),work experience(P value=0.002),residence(P value<0.001)and type of work institution(P value=0.003).CONCLUSION This study revealed that HCWs have the lowest level of knowledge regarding Mpox and a lack of confidence in the ability to diagnose,treat or prevent it.There is an urgent need to organize continuing medical education programs on Mpox epidemiology and preparedness for Burundi HCWs.We encourage future researchers to assess potential hesitancy toward Mpox vaccination and its associated factors.

Construction of a Computational Scheme for the Fuzzy HIV/AIDS Epidemic Model with a Nonlinear Saturated Incidence Rate

This work aimed to construct an epidemic model with fuzzy parameters.Since the classical epidemic model doesnot elaborate on the successful interaction of susceptible and infective people,the constructed fuzzy epidemicmodel discusses the more detailed versions of the interactions between infective and susceptible people.Thenext-generation matrix approach is employed to find the reproduction number of a deterministic model.Thesensitivity analysis and local stability analysis of the systemare also provided.For solving the fuzzy epidemic model,a numerical scheme is constructed which consists of three time levels.The numerical scheme has an advantage overthe existing forward Euler scheme for determining the conditions of getting the positive solution.The establishedscheme also has an advantage over existing non-standard finite difference methods in terms of order of accuracy.The stability of the scheme for the considered fuzzy model is also provided.From the plotted results,it can beobserved that susceptible people decay by rising interaction parameters.

Novel Investigation of Stochastic Fractional Differential Equations Measles Model via the White Noise and Global Derivative Operator Depending on Mittag-Leffler Kernel

Because of the features involved with their varied kernels,differential operators relying on convolution formulations have been acknowledged as effective mathematical resources for modeling real-world issues.In this paper,we constructed a stochastic fractional framework of measles spreading mechanisms with dual medication immunization considering the exponential decay and Mittag-Leffler kernels.In this approach,the overall population was separated into five cohorts.Furthermore,the descriptive behavior of the system was investigated,including prerequisites for the positivity of solutions,invariant domain of the solution,presence and stability of equilibrium points,and sensitivity analysis.We included a stochastic element in every cohort and employed linear growth and Lipschitz criteria to show the existence and uniqueness of solutions.Several numerical simulations for various fractional orders and randomization intensities are illustrated.

Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic outbreaks.This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance.Since,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by SM.This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic outbreaks.DL has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation results.In recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM analysis.This paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM analysis.Finally,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

High Diversity in Genotypes of Human Rhinovirus Contributes to High Prevalence in Beijing,2018-2022:A Retrospective Multiple-Center Epidemiological Study

Objective To comprehensively examine the molecular epidemiological characteristics of human rhinovirus(HRV)in Beijing.Methods A total of 7,151 children and adults with acute respiratory tract infections(ARTIs)were recruited from 35 sentinel hospitals in Beijing between 2018 and 2022.Their respiratory samples were obtained,and epidemiological and clinical data were collected.Nucleic acid testing for 11 respiratory pathogens,including HRV,was performed on the specimens.We sequenced VP4/VP2 or 5’UTR of HRV isolates to identify their genotypes using phylogenetic analyses.Results HRV was detected in 462(6.5%)cases.A total of 105 HRV genotypes were successfully identified in 359(77.7%)specimens,comprising 247(68.8%)with HRV-A,42(11.7%)with HRV-B,and 70(19.5%)with HRV-C.No predominant genotype was observed.HRV was prevalent year-round with two weak peaks in spring and autumn.HRV detection declined gradually between 2018 and 2022,with seven genotypes disappearing and five genotypes emerging.HRV detection rate decreased by age without resurge among old people.HRV-C was more common among children aged less than 5 years with severe community-acquired pneumonia compared to HRV-A and HRV-B.Adults infected with HRV-B had higher rates of hospitalization,intensive care unit admission,and complications than those infected with HRV-A and HRV-C.Conclusion HRV epidemics in Beijing were highly dispersed in genotypes,which probably resulted in a high prevalence of HRV infection,attenuated its seasonality,and made it more difficult to establish effective population immunity.

A Dynamical Study of Modeling the Transmission of Typhoid Fever throughDelayed Strategies

This study analyzes the transmission of typhoid fever caused by Salmonella typhi using a mathematical model thathighlights the significance of delay in its effectiveness.Time delays can affect the nature of patterns and slow downthe emergence of patterns in infected population density.The analyzed model is expanded with the equilibriumanalysis,reproduction number,and stability analysis.This study aims to establish and explore the non-standardfinite difference(NSFD)scheme for the typhoid fever virus transmission model with a time delay.In addition,the forward Euler method and Runge-Kutta method of order 4(RK-4)are also applied in the present research.Some significant properties,such as convergence,positivity,boundedness,and consistency,are explored,and theproposed scheme preserves all the mentioned properties.The theoretical validation is conducted on how NSFDoutperforms other methods in emulating key aspects of the continuous model,such as positive solution,stability,and equilibrium about delay.Hence,the above analysis also shows some of the limitations of the conventional finitedifference methods,such as forward Euler and RK-4 in simulating such critical behaviors.This becomes moreapparent when using larger steps.This indicated that NSFD is beneficial in identifying the essential characteristicsof the continuous model with higher accuracy than the traditional approaches.

Individual dynamics and local heterogeneity provide a microscopic view of the epidemic spreading

The COVID-19 pandemic has caused severe global disasters,highlighting the importance of understanding the details and trends of epidemic transmission in order to introduce efficient intervention measures.While the widely used deterministic compartmental models have qualitatively presented continuous “analytical” insight and captured some transmission features,their treatment usually lacks spatiotemporal variation.Here,we propose a stochastic individual dynamical(SID)model to mimic the random and heterogeneous nature of epidemic propagation.The SID model provides a unifying framework for representing the spatiotemporal variations of epidemic development by tracking the movements of each individual.Using this model,we reproduce the infection curves for COVID-19 cases in different areas globally and find the local dynamics and heterogeneity at the individual level that affect the disease outbreak.The macroscopic trend of virus spreading is clearly illustrated from the microscopic perspective,enabling a quantitative assessment of different interventions.Seemingly,this model is also applicable to studying stochastic processes at the “meter scale”,e.g.,human society’s collective dynamics.

Impact of different interaction behavior on epidemic spreading in time-dependent social networks

We investigate the impact of pairwise and group interactions on the spread of epidemics through an activity-driven model based on time-dependent networks.The effects of pairwise/group interaction proportion and pairwise/group interaction intensity are explored by extensive simulation and theoretical analysis.It is demonstrated that altering the group interaction proportion can either hinder or enhance the spread of epidemics,depending on the relative social intensity of group and pairwise interactions.As the group interaction proportion decreases,the impact of reducing group social intensity diminishes.The ratio of group and pairwise social intensity can affect the effect of group interaction proportion on the scale of infection.A weak heterogeneous activity distribution can raise the epidemic threshold,and reduce the scale of infection.These results benefit the design of epidemic control strategy.

Boundedness and Positivity Preserving Numerical Analysis of a Fuzzy-Parameterized Delayed Model for Foot and Mouth Disease Dynamics

Foot-and-mouth disease(FMD)is a viral disease that affects cloven-hoofed animals including cattle,pigs,and sheep,hence causing export bans among others,causing high economic losses due to reduced productivity.The global effect of FMD is most felt where livestock rearing forms an important source of income.It is therefore important to understand the modes of transmission of FMD to control its spread and prevent its occurrence.This work intends to address these dynamics by including the efficacy of active migrant animals transporting the disease from one area to another in a fuzzy mathematical modeling framework.Historical models of epidemics are determinable with a set of deterministic parameters and this does not reflect on real-life scenarios as observed in FMD.Fuzzy theory is used in this model as it permits the inclusion of uncertainties in the model;this makes the model more of a reality regarding disease transmission.A time lag,in this case,denotes the incubation period and other time-related factors affecting the spread of FMD and,therefore,is added to the current model for FMD.To that purpose,the analysis of steady states and the basic reproduction number are performed and,in addition,the stability checks are conveyed in the fuzzy environment.For the numerical solution of the model,we derive the Forward Euler Method and the fuzzy delayed non-standard finite difference(FDNSFD)method.Analytical studies of the FDNSFD scheme are performed for convergence,non-negativity,boundedness,and consistency analysis of the numerical projection to guarantee that the numerical model is an accurate discretization of the continuous dynamics of FMD transmission over time.In the following simulation study,we show that the FDNSFD method preserves the characteristics of the constant model and still works if relatively large time steps are employed;this is a bonus over the normal finite difference technique.The study shows how valuable it is to adopt fuzzy theory and time delays when simulating the transmission of the epidemic,especially for such diseases as FMD where uncertainty and migration have a defining role in transmission.This approach gives more sound and flexible grounds for analyzing and controlling the outbreak of FMD in various situations.

Epidemic threshold influenced by non-pharmaceutical interventions in residential university environments

The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.

Projecting the Dynamic Trends of Human Immunodeficiency Virus/Acquired Immunodeficiency Syndrome:Modeling the Epidemic in Sichuan Province, China

Objective Our study aimed to provide a comprehensive overview of the current status and dynamic trends of the human immunodeficiency virus(HIV)prevalence in Sichuan,the second most heavily affected province in China,and to explore future interventions.Methods The epidemiological,behavioral,and population census data from multiple sources were analyzed to extract inputs for an acquired immunodeficiency syndrome(AIDS)epidemic model(AEM).Baseline curves,derived from historical trends in HIV prevalence,were used,and the AEM was employed to examine future intervention scenarios.Results In 2015,the modeled data suggested an adult HIV prevalence of 0.191%in Sichuan,with an estimated 128,766 people living with HIV/AIDS and 16,983 individuals with newly diagnosed infections.Considering current high-risk behaviors,the model predicts an increase in the adult prevalence to 0.306%by 2025,projecting an estimated 212,168 people living with HIV/AIDS and 16,555 individuals with newly diagnosed infections.Conclusion Heterosexual transmission will likely emerge as the primary mode of AIDS transmission in Sichuan.Furthermore,we anticipate a stabilization in the incidence of AIDS with a concurrent increase in prevalence.Implementing comprehensive intervention measures aimed at high-risk groups could effectively alleviate the spread of AIDS in Sichuan.

Current updates on the epidemiology,pathogenesis and development of small molecule therapeutics for the treatment of Ebola virus infections

Ebola virus disease(EVD)is a rare,highly contagious and a deadly disease with a variable fatality rate ranging from 30%to 90%.Over the past two decades,Ebola pandemic has severely affected the sub-Sahara region including Democratic Republic of the Congo(DRC),and Uganda.The causative agents of the most EVD cases are three distinct species out of six Ebolaviruses namely Zaire Ebolavirus(ZEBOV),Sudan Ebolavirus(SUDV)and Bundibugyo Ebolavirus(BDBV).In recent years,significant strides have been made in therapeutic interventions.Notably,the US Food and Drug Administration has approved two monoclonal antibodies:InmazebTM(REGN-EB3)and Ansuvimab or EbangaTM.Additionally,many small molecules are currently in the developmental stage,promising further progress in medical treatment.Addressing the critical need for preventive measures,this review provides an in-depth analysis of the licensed Ebola vaccines-Ervebo and the combination of Zabdeno(Ad26.ZEBOV)and Mvabea(MVA-BN-Filo)as well as the vaccines which are currently being tested for their efficacy and safety in clinical studies.These vaccines might play an important role in curbing the spread and mitigating the impact of this lethal disease.The current treatment landscape for EVD encompasses both nutritional(supportive)and drug therapies.The review comprehensively details the origin,pathogenesis,and epidemiology of EVD,shedding light on the ongoing efforts to combat this devastating disease.It explores small molecules in various stages of the development,discusses patents filed or granted,and delves into the clinical and supportive therapies that form the cornerstone of EVD management.This review aims to provide the recent developments made in the design and synthesis of small molecules for scientific community to facilitate a deeper understanding of the disease and fostering the development of effective strategies for prevention,treatment,and control of EVD.

Relationship Between Individuals’Epidemic Risk Perception Within Living Space and Subjective Well-Being:Empirical Evidence from China after the First Wave of COVID-19

It is common to observe the epidemic risk perception(ERP)and a decline in subjective well-being(SWB)in the context of public health events,such as Corona Virus Disease 2019(COVID-19).However,there have been few studies exploring the impact of individuals’ERP within living space on their SWB,especially from a geographical and daily activity perspective after the resumption of work and other activities following a wave of the pandemic.In this paper,we conducted a study with 789 participants in urban China,measuring their ERP within living space and examining its influence on their SWB using path analysis.The results indicated that individuals’ERP within their living space had a significant negative effect on their SWB.The density of certain types of facilities within their living space,such as bus stops,subway stations,restaurants,fast food shops,convenience shops,hospitals,and public toilets,had a significantly negative impact on their SWB,mediated by their ERP within living space.Additionally,participation in out-of-home work and other activities not only increased individuals’ERP within living space,but also strengthened its negative effect on their SWB.

Epidemic Characteristics and Spatio-Temporal Patterns of HFRS in Qingdao City,China,2010-2022

Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingdao City from 2010 to 2022.Descriptive epidemiologic,seasonal decomposition,spatial autocorrelation,and spatio-temporal cluster analyses were performed.Results A total of 2,220 patients with HFRS were reported over the study period,with an average annual incidence of 1.89/100,000 and a case fatality rate of 2.52%.The male:female ratio was 2.8:1.75.3%of patients were aged between 16 and 60 years old,75.3%of patients were farmers,and 11.6%had both“three red”and“three pain”symptoms.The HFRS epidemic showed two-peak seasonality:the primary fall-winter peak and the minor spring peak.The HFRS epidemic presented highly spatially heterogeneous,street/township-level hot spots that were mostly distributed in Huangdao,Pingdu,and Jiaozhou.The spatio-temporal cluster analysis revealed three cluster areas in Qingdao City that were located in the south of Huangdao District during the fall-winter peak.Conclusion The distribution of HFRS in Qingdao exhibited periodic,seasonal,and regional characteristics,with high spatial clustering heterogeneity.The typical symptoms of“three red”and“three pain”in patients with HFRS were not obvious.

Evolutionary Safe Padé Approximation Scheme for Dynamical Study of Nonlinear Cervical Human Papilloma Virus Infection Model

This study proposes a structure-preserving evolutionary framework to find a semi-analytical approximate solution for a nonlinear cervical cancer epidemic(CCE)model.The underlying CCE model lacks a closed-form exact solution.Numerical solutions obtained through traditional finite difference schemes do not ensure the preservation of the model’s necessary properties,such as positivity,boundedness,and feasibility.Therefore,the development of structure-preserving semi-analytical approaches is always necessary.This research introduces an intelligently supervised computational paradigm to solve the underlying CCE model’s physical properties by formulating an equivalent unconstrained optimization problem.Singularity-free safe Padérational functions approximate the mathematical shape of state variables,while the model’s physical requirements are treated as problem constraints.The primary model of the governing differential equations is imposed to minimize the error between approximate solutions.An evolutionary algorithm,the Genetic Algorithm with Multi-Parent Crossover(GA-MPC),executes the optimization task.The resulting method is the Evolutionary Safe PadéApproximation(ESPA)scheme.The proof of unconditional convergence of the ESPA scheme on the CCE model is supported by numerical simulations.The performance of the ESPA scheme on the CCE model is thoroughly investigated by considering various orders of non-singular Padéapproximants.

A Collocation Technique via Pell-Lucas Polynomials to Solve Fractional Differential EquationModel for HIV/AIDS with Treatment Compartment

In this study,a numerical method based on the Pell-Lucas polynomials(PLPs)is developed to solve the fractional order HIV/AIDS epidemic model with a treatment compartment.The HIV/AIDS mathematical model with a treatment compartment is divided into five classes,namely,susceptible patients(S),HIV-positive individuals(I),individuals with full-blown AIDS but not receiving ARV treatment(A),individuals being treated(T),and individuals who have changed their sexual habits sufficiently(R).According to the method,by utilizing the PLPs and the collocation points,we convert the fractional order HIV/AIDS epidemic model with a treatment compartment into a nonlinear system of the algebraic equations.Also,the error analysis is presented for the Pell-Lucas approximation method.The aim of this study is to observe the behavior of five populations after 200 days when drug treatment is applied to HIV-infectious and full-blown AIDS people.To demonstrate the usefulness of this method,the applications are made on the numerical example with the help of MATLAB.In addition,four cases of the fractional order derivative(p=1,p=0.95,p=0.9,p=0.85)are examined in the range[0,200].Owing to applications,we figured out that the outcomes have quite decent errors.Also,we understand that the errors decrease when the value of N increases.The figures in this study are created in MATLAB.The outcomes indicate that the presented method is reasonably sufficient and correct.

Fentanyl and xylazine crisis:Crafting coherent strategies for opioid overdose prevention

The United States is in the throes of a severe opioid overdose epidemic,primarily fueled by the pervasive use of fentanyl and the emerging threat of xylazine,a veterinary sedative often mixed with fentanyl.The high potency and long duration of fentanyl is compounded by the added risks from xylazine,heightening the lethal danger faced by opioid users.Measures such as enhanced surveillance,public awareness campaigns,and the distribution of fentanylxylazine test kits,and naloxone have been undertaken to mitigate this crisis.Fentanyl-related overdose deaths persist despite these efforts,partly due to inconsistent policies across states and resistance towards adopting harm reduction strategies.A multifaceted approach is imperative in effectively combating the opioid overdose epidemic.This approach should include expansion of treatment access,broadening the availability of medications for opioid use disorder,implementation of harm reduction strategies,and enaction of legislative reforms and diminishing stigma associated with opioid use disorder.

Identification,Isolation and Genomic Characterization of Porcine Astrovirus in Shandong Province,China in 2021-2023

[Objective]The paper was to identify,isolate,and characterize porcine astrovirus in Shandong Province between 2021 and 2023.[Method]A total of 1025 samples of porcine diarrhea samples were collected from various regions of Shandong Province between January 2021 and October 2023.The samples were tested by RT-PCR,followed by sequencing and phylogenetic analyses of the polymerase.[Result]The total positive rate of PAstV was 34.6%(355/1025).The respective proportions of individuals infected with PAstV-1,PAstV-2,PAstV-4 and PAstV-5 were 25.4%(90/355),28.2%(100/355),35.2%(125/355)and 22.5%(80/355),respectively.Additionally,mixed infection was observed.Meanwhile,849 samples of healthy pigs were tested by RT-PCR,and the results demonstrated that the total positive rate of PAstV was 8.13%(69/849).Of these,the proportion of PAstV-1,PAstV-2 and PAstV-4 infection was 27.5%(19/69),37.7%(26/69)and 40.6%(28/69),and a mixed infection also existed.Further sequencing and characterization of some the selected isolates revealed low sequence identities(56.2%)with known PAstV strains,indicating the presence of novel types or genotypes of PAstVs.Furthermore,the isolation conditions of porcine astrovirus were optimized,resulting in the purification of a pure PAstV-4 strain(designated PAstV-4-GRF1).The virus was found to exhibit typical astroviral morphology,with nucleotide identity ranging from 89.9 to 95.4%with previously published PAstV-4 strains.Then,macrovirus transcriptome sequencing showed that 88.30%of the CRF1 samples were mammalian astroviruses.By species classification,PAstV 4 and PAstV 2 accounted for 21.79%and 0.32%,respectively.Phylogenetic tree analysis showed that the c15050 fragment was identical to the GRF-1 sequencing fragment of the isolated strain,and exhibited the highest homology with the Hunan PAstV-4 sequence MK460231 in China.[Conclusion]As the inaugural isolated PAstV-4 strain,it furnishes pivotal materialfor the investigation ofthe biological and pathogenic properties of this virus as well as for the prospectivedevelopment of relevant biological and diagnostic reagents.

An Analysis of the Impact of Stay-at-Home Measures on the Occurrence of Vaccine Shortages

COVID-19, a contagious respiratory disease, presents immediate and unforeseen challenges to people worldwide. Moreover, its transmission rapidly extends globally due to its viral transmissibility, emergence of novel strains (variants), absence of immunity, and human unawareness. This framework introduces a revised epidemic model, drawing upon mathematical principles. This model incorporates a modified vaccination and lockdown approach to comprehensively depict an epidemics transmission, containment, and decision-making processes within a community. This study aims to provide policymakers with precise information on real-world situations to assist them in making informed decisions about the implementation of lockdown strategies, maintenance variables, and vaccine availability. The suggested model has conducted stability analysis, strength number analysis, and first and second-order derivative analysis of the Lyapunov function and has established the existence and uniqueness of solutions of the proposed models. We examine the combined effects of an effective vaccination campaign and non-pharmaceutical measures such as lockdowns and states of emergency. We rely on the results of this research to assist policymakers in various countries in eradicating the illness by developing more innovative measures to control the outbreak.