Steady States in SIRS Epidemical Model of Mobile Individual

We consider an epidemical model within soclally interacting mobile individuals to study the behaviors of steady states of epidemic propagation in 2D networks. Using mean-field approximation and large scale simulations, we recover the usual epidemic behavior with critical thresholds δc and pc below which infectious disease dies out. For the population density δ far above δc it is found that there is linear relationship between contact rate λ and the population density δ in the main. At the same time, the result obtained from mean-field approximation is compared with our numerical result, and it is found that these two results are similar by and large but not completely the same.

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.

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.

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.

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.

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.

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.

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.

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.

Research on the Control Cover against Solenopsis invicta and Rapid Extinguishment of Its Epidemic

Based on the biological characteristics of Solenopsis invicta and the structural characteristics of its ant nest,a fast and efficient closed treatment device was developed.Compared with the simple chemical treatment commonly used at present,the developed treatment device(the ant nest control cover)is a fast and efficient method to exterminate S.invicta in 7 d,featured by short course,quick results and good effect.

Exploring the Contribution of Pharmacists in Addressing the Opioid Crisis through Naloxone Prescriptions and Pharmacist-Led Interventions

The opioid epidemic in the United States continues to take the lives of many individuals, with overdoses continuing to rise every year. Naloxone is an opioid antagonist that is efficacious in temporarily reversing opioid overdoses. Pharmacists play an important role in the accessibility and education of naloxone in both the community and health system settings. Recent efforts, such as co-dispensing naloxone with opioid prescriptions, naloxone training programs, and approval of naloxone to be over-the-counter, have been implemented in hopes to better control the opioid epidemic. Despite the efforts to make naloxone more accessible, there are still some barriers to overcome such as lack of training, cost, stigma, and patient refusal. This review aims to explore the contributions pharmacists have made thus far and define the barriers that still have to be resolved.

Ozone Sterilizer for Treatment and Health Care

Ozone is a green broad-spectrum bactericidal disinfectant, and a trace amount of ozone in the atmosphere makes many viruses and bacteria lose their biochemical activity and infectivity. Nature produces trace amounts of ozone in the air through lightning to purify the ecological environment. The product of ozone decomposition is oxygen, without secondary pollution. Ozone sterilizer is widely used in the epidemic prevention and control of intensive breeding farms and achieved remarkable results. If the concentration and action time of ozone can be accurately controlled, then ozone can quickly eliminate pathogens, without harming the normal cells in the human body. How to use medical ozone for epidemic prevention, treatment and health care is a subject worthy of serious study, which should arouse the attention of the experts in the field.

Analysis on the Changes of Research Hotspots in the Prevention and Treatment of COVID-19 by Traditional Chinese Medicine Based on Knowledge Graph

Objective: To grasp the changing trend of research hotspots of traditional Chinese medicine in the prevention and treatment of COVID-19, and to better play the role of traditional Chinese medicine in the prevention and treatment of COVID-19 and other diseases. Methods: The research literature from 2020 to 2022 was searched in the CNKI database, and CiteSpace software was used for visual analysis. Results: The papers on the prevention and treatment of COVID-19 by traditional Chinese medicine changed from cases, overviews, reports, and efficacy studies to more in-depth mechanism research, theoretical exploration, and social impact analysis, and finally formed a theory-clinical-society Influence-institutional change and other multi-dimensional achievement systems. Conclusion: Analyzing the changing trends of TCM hotspots in the prevention and treatment of COVID-19 can fully understand the important value of TCM, take the coordination of TCM and Western medicine as an important means to deal with public health security incidents, and promote the exploration of the potential efficacy of TCM, so as to enhance the role of TCM in Applications in social stability, emergency security, clinical practice, etc.