Studying the co-evolution of information diffusion,vaccination behavior and disease transmission in multilayer networks with local and global effects

Today,with the rapid development of the internet,a large amount of information often accompanies the rapid transmission of disease outbreaks,and increasing numbers of scholars are studying the relationship between information and the disease transmission process using complex networks.In fact,the disease transmission process is very complex.Besides this information,there will often be individual behavioral measures and other factors to consider.Most of the previous research has aimed to establish a two-layer network model to consider the impact of information on the transmission process of disease,rarely divided into information and behavior,respectively.To carry out a more in-depth analysis of the disease transmission process and the intrinsic influencing mechanism,this paper divides information and behavior into two layers and proposes the establishment of a complex network to study the dynamic co-evolution of information diffusion,vaccination behavior,and disease transmission.This is achieved by considering four influential relationships between adjacent layers in multilayer networks.In the information layer,the diffusion process of negative information is described,and the feedback effects of local and global vaccination are considered.In the behavioral layer,an individual's vaccination behavior is described,and the probability of an individual receiving a vaccination is influenced by two factors:the influence of negative information,and the influence of local and global disease severity.In the disease layer,individual susceptibility is considered to be influenced by vaccination behavior.The state transition equations are derived using the micro Markov chain approach(MMCA),and disease prevalence thresholds are obtained.It is demonstrated through simulation experiments that the negative information diffusion is less influenced by local vaccination behavior,and is mainly influenced by global vaccination behavior;vaccination behavior is mainly influenced by local disease conditions,and is less influenced by global disease conditions;the disease transmission threshold increases with the increasing vaccination rate;and the scale of disease transmission increases with the increasing negative information diffusion rate and decreases with the increasing vaccination rate.Finally,it is found that when individual vaccination behavior considers both the influence of negative information and disease,it can increase the disease transmission threshold and reduce the scale of disease transmission.Therefore,we should resist the diffusion of negative information,increase vaccination proportions,and take appropriate protective measures in time.

Dynamics of information diffusion and disease transmission in time-varying multiplex networks with asymmetric activity levels

While the interaction between information and disease in static networks has been extensively investigated,many studies have ignored the characteristics of network evolution.In this study,we construct a new two-layer coupling model to explore the interactions between information and disease.The upper layer describes the diffusion of disease-related information,and the lower layer represents the disease transmission.We then use power-law distributions to examine the influence of asymmetric activity levels on dynamic propagation,revealing a mapping relationship characterizing the interconnected propagation of information and diseases among partial nodes within the network.Subsequently,we derive the disease outbreak threshold by using the microscopic Markov-chain approach(MMCA).Finally,we perform extensive Monte Carlo(MC)numerical simulations to verify the accuracy of our theoretical results.Our findings indicate that the activity levels of individuals in the disease transmission layer have a more significant influence on disease transmission compared with the individual activity levels in the information diffusion layer.Moreover,reducing the damping factor can delay disease outbreaks and suppress disease transmission,while improving individual quarantine measures can contribute positively to disease control.This study provides valuable insights into policymakers for developing outbreak prevention and control strategies.

Prediction of Disease Transmission Risk in Universities Based on SEIR and Multi-hidden Layer Back-propagation Neural Network Model

Against the background of regular epidemic prevention and control,in order to ensure the return of teachers to work,students to return to school and safe operation of schools,the risk of disease transmission is analyzed in key areas such as university canoons,auditoriums,teaching buildings and dormitories.The risk model of epidemic transmission in key regions of universities is established based on the improved SEIR model,considering the four groups of people,namely susceptible,latent,infected and displaced,and their mutual transformation relationship.After feature post-processing,the selected feature parameters are processed with monotone non-decreasing and smoothing,and used as noise-free samples of stacked sparse denoising automatic coding network to train the network.Then,the feature vectors after dimensionality reduction of the stacked sparse denoising automatic coding network are used as the input of the multi-hidden layer back-propagation neural network,and these features are used as tags to carry out fitting training for the network.The results show that the implementation of control measures can reduce the number of contacts between infected people and susceptible people,reduce the transmission rate of single contact,and reduce the peak number of infected people and latent people by 61%and 72%respectively,effectively controlling the disease spread in key regions of universities.Our method is able to accurately predict the number of infections.

Impact of asymmetric activity on interactions between information diffusion and disease transmission in multiplex networks

Disease is a serious threat to human society.Understanding the characteristics of disease transmission is helpful for people to effectively control disease.In real life,it is natural to take various measures when people are aware of disease.In this paper,a novel coupled model considering asymmetric activity is proposed to describe the interactions between information diffusion and disease transmission in multiplex networks.Then,the critical threshold for disease transmission is derived by using the micro-Markov chain method.Finally,the theoretical results are verified by numerical simulations.The results show that reducing the activity level of individuals in the physical contact layer will have a continuous impact on reducing the disease outbreak threshold and suppressing the disease.In addition,the activity level of individuals in the virtual network has little impact on the transmission of the disease.Meanwhile,when individuals are aware of more disease-related information,the higher their awareness of prevention will be,which can effectively inhibit the transmission of disease.Our research results can provide a useful reference for the control of disease transmission.

Mitochondrial replacement techniques or therapies (MRTs) to improve embryo development and to prevent mitochondrial disease transmission

The mitochondrion which contains its own double-stranded circular DNA is a semi-independent organelle that plays critical roles in cell activity. Mitochondrial DNA （mtDNA） is maternally inherited through several mechanisms that have been proposed （Luo et al., 2013） and, if mitochondrial mutations are inherited to the offspring, it is possible to cause mitochondrial diseases such as neuropathy, cardiomyopathy, myopathy, and liver failure.

Aerosol transmission of human pathogens:From miasmata to modern viral pandemics and their preservation potential in the Anthropocene record

Ongoing uncertainty over the relative importance of aerosol transmission of COVID-19 is in part rooted in the history of medical science and our understanding of how epidemic diseases can spread through human populations. Ancient Greek medical theory held that such illnesses are transmitted by airborne pathogenic emanations containing particulate matter(“miasmata”). Notable Roman and medieval scholars such as Varro, Ibn al-Khatib and Fracastoro developed these ideas, combining them with early germ theory and the concept of contagion. A widely held but vaguely defined belief in toxic miasmatic mists as a dominant causative agent in disease propagation was overtaken by the science of 19th century microbiology and epidemiology, especially in the study of cholera, which was proven to be mainly transmitted by contaminated water. Airborne disease transmission came to be viewed as burdened by a dubious historical reputation and difficult to demonstrate convincingly. A breakthrough came with the classic mid-20th century work of Wells, Riley and Mills who proved how expiratory aerosols(their “droplet nuclei”)could transport still-infectious tuberculosis bacteria through ventilation systems. The topic of aerosol transmission of pathogenic respiratory diseases assumed a new dimension with the mid-late 20th century “Great Acceleration” of an increasingly hypermobile human population repeatedly infected by different strains of zoonotic viruses, and has taken centre stage this century in response to outbreaks of new respiratory infections that include coronaviruses. From a geoscience perspective, the consequences of pandemic-status diseases such as COVID-19, produced by viral pathogens utilising aerosols to infect a human population currently approaching 8 billion, are far-reaching and unprecedented. The obvious and sudden impacts on for example waste plastic production, water and air quality and atmospheric chemistry are accelerating human awareness of current environmental challenges. As such, the “anthropause”lockdown enforced by COVID-19 may come to be seen as a harbinger of change great enough to be preserved in the Anthropocene stratal record.

Risk assessment of hepatitis E transmission through tissue allografts

Hepatitis E virus(HEV)is a small non-enveloped single stranded RNA virus whose genotypes 3 and 4 have been associated with zoonotic transmission in industrialized countries.HEV infection is considered the main cause of acute hepatitis worldwide.In some cases,transfusion of blood components or organ transplantation have been reported as the source of infection.We have conducted a literature review on the risk of transmission through cell and tissue allografts.Although no case was found,measures to control this risk should be taken when donor profile(based upon geographical and behavioural data)recommended it.Issues to be considered in donor screening and tissue processing to assess and to reduce the risk of HEV transmission are approached.

A Leslie-Gower Holling Type-II Predator-Prey Mathematical Model with Disease in Prey Population Incorporating a Prey Refuge

We formulate and analyze a predator-prey model followed by Leslie-Gower model in which the prey population is infected by disease. We assume that the disease can only spread over prey population. As a result prey population has been classified into two categories, namely susceptible prey, infected prey where as the predator population remains free from infection. To investigate the behaviour of prey population we incorporate prey refuge in this model. Since the prey refuge decreases the predation rate then it has an important effect in our predator-prey interaction model. We have discussed the existence of various equilibrium points and local stability analysis at those equilibrium points. We investigate the Hopf-bifurcation analysis about the interior equilibrium point by taking the rate of infection parameter and the prey refuge parameter as bifurcation parameters. The numerical analysis is carried out to support the analytical results and to discuss some interesting results that our model exhibits.

Brain-derived neurotropic factor and GABAergic transmission in neurodegeneration and neuroregeneration

Neurotoxicity induced by stress,radiation,chemicals,or metabolic diseases,is commonly associated with excitotoxicity,oxidative stress,and neuroinflammation.The pathological process of neurotoxicity induces neuronal death,interrupts synaptic plasticity in the brain,and is similar to that of diverse neurodegenerative diseases.Animal models of neurotoxicity have revealed that clinical symptoms and brain lesions can recover over time via neuroregenerative processes.Specifically,brain-derived neurotropic factor（BDNF） and gamma-aminobutyric acid（GABA）-ergic transmission are related to both neurodegeneration and neuroregeneration.This review summarizes the accumulating evidences that suggest a pathogenic role of BDNF and GABAergic transmission,their underlying mechanisms,and the relationship between BDNF and GABA in neurodegeneration and neuroregeneration.This review will provide a comprehensive overview of the underlying mechanisms of neuroregeneration that may help in developing potential strategies for pharmacotherapeutic approaches to treat neurotoxicity and neurodegenerative disease.

Demographic and risk characteristics of healthcare workers infected with SARS-CoV-2 from two tertiary care hospitals in the United Arab Emirates

BACKGROUND Understanding the transmission dynamics of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection among healthcare workers(HCWs)and their social contacts is crucial to plan appropriate risk-reduction measures.AIM To analyze the socio-demographic risk factors and transmission of SARS-CoV-2 infection among HCWs in two tertiary care hospitals in Dubai,United Arab Emirates.METHODS The demographic and clinical characteristics were available for all HCWs in both facilities from the human resources department.A cross-sectional survey was conducted from January-April 2022 among HCWs who tested positive through Reverse Transcriptase Polymerase Chain Reaction of the nasopharyngeal swab for SARS-CoV-2 between March 2020 and August 2021 in two tertiary-level hospitals.The survey included questions on demographics,work profile,characteristics of coronavirus disease 2019(COVID-19),and infection among their household or co-workers.The survey also checked the knowledge and perception of participants on the infection prevention measures related to SARS-CoV-2.RESULTS Out of a total of 346 HCWs infected with SARS-CoV-2,286(82.7%)HCWs consented to participate in this study.From the sample population,150(52.5%)of participants were female,and a majority(230,80.4%)were frontline HCWs,including 121 nurses(121,42.4%).Only 48(16.8%)participants were fully vaccinated at the time of infection.Most infected HCWs(85%)were unaware of any unprotected exposure and were symptomatic at the time of testing(225,78.7%).Nearly half of the participants(140,49%)had co-infection among household,and nearly one-third(29.5%)had coinfection among three or more household.Another 108(37.8%)participants reported crossinfection among co-workers.The frontline HCWs were significantly more infected(25.1%vs 8.6%,P<0.001)compared to non-frontline HCWs.Another significant risk factor for a high infection rate was male sex(P<0.001).Among the infected frontline HCWs,a significantly higher proportion were male and shared accommodation with family(P<0.001).COVID-19 vaccination significantly reduced the infection rate(83.2%vs 16.8,P<0.001)among HCWs.Most participants(99.3%)were aware about importance of appropriate use of personal protective equipment.However,only 70%agreed with the efficacy of the COVID-19 vaccination in preventing an infection and severe disease.CONCLUSION The risk profiling of the HCWs infected with SARS-CoV-2 found that working at frontline and being male increase the rate of infection.COVID-19 vaccination can effectively reduce the rate of transmission of SARS-CoV-2 among HCWs.

Transmission matrices used in epidemiologic modelling

Mixing matrices are included in infectious disease models to reflect transmission opportunities between population strata.These matrices were originally constructed on the basis of theoretical considerations and most of the early work in this area originates from research on sexually transferred diseases in the 80s,in response to AIDS.Later work in the 90s populated these matrices on the basis of survey data gathered to capture transmission risks for respiratory diseases.We provide an overview of developments in the construction of matrices for capturing transmission opportunities in populations.Such transmission matrices are useful for epidemiologic modelling to capture within and between stratum transmission and can be informed from theoretical mixing assumptions,informed by empirical evidence gathered through investigation as well as generated on the basis of data.Links to summary measures and threshold conditions are also provided.

The transmission mechanism theory of disease dynamics:Its aims,assumptions and limitations

Most of the progress in the development of single scale mathematical and computational models for the study of infectious disease dynamics which now span over a century is build on a body of knowledge that has been developed to address particular single scale descriptions of infectious disease dynamics based on understanding disease transmission process.Although this single scale understanding of infectious disease dynamics is now founded on a body of knowledge with a long history,dating back to over a century now,that knowledge has not yet been formalized into a scientific theory.In this article,we formalize this accumulated body of knowledge into a scientific theory called the transmission mechanism theory of disease dynamics which states that at every scale of organization of an infectious disease system,disease dynamics is determined by transmission as the main dynamic disease process.Therefore,the transmission mechanism theory of disease dynamics can be seen as formalizing knowledge that has been inherent in the study of infectious disease dynamics using single scale mathematical and computational models for over a century now.The objective of this article is to summarize this existing knowledge about single scale modelling of infectious dynamics by means of a scientific theory called the transmission mechanism theory of disease dynamics and highlight its aims,assumptions and limitations.

Studies on the integration of hepatitis B virus DNA sequence in human sperm chromosomes

Aim: To study the integration of hepatitis B virus (HBV) DNA into sperm chromosomes in hepatitis B patients and the features of its integration. Methods: Sperm chromosomes of 14 subjects (5 healthy controls and 9 HB patients, including 1 acute hepatitis B, 2 chronic active hepatitis B, 4 chronic persistent hepatitis B, 2 HBsAg chronic carriers with no clinical symptoms) were prepared using interspecific in vitro fertilization between zona-free hamster oocytes and human spermatozoa. Fluorescence in situ hybridization (FISH) to sperm chromosome spreads was carried out with biotin-labeled full length HBV DNA probe to detect the specific HBV DNA sequences in the sperm chromosomes. Results: Specific fluorescent signal spots for HBV DNA were seen in sperm chromosomes of one patient with chronic persistent hepatitis B. In 9(9/42) sperm chromosome complements containing fluorescent signal spots, one presented 5 obvious FISH spots and the others 2 to 4 signals. The fluorescence intensity showed significant difference among the signal spots. The distribution of signal sites among chromosomes seems to be random. Conclusion: HBV could integrate into human sperm chromosomes. Results suggest that the possibility of vertical transmission of HBV via the germ line to the next generation is present.

An Outbreak of SARS in a Diabetes Room of a General Hospital without Infected Medical Staff

Objective To investigate the epidemiologic features of an outbreak of SARS that occurred in a single diabetes room of a general hospital in Beijing in late March 2003.Methods Field investigation was carried out in the ward,the nursing log and the hospitalization medical record of correlative patients were consulted.SARS-CoV in serum specimen from SARS patient was detected by PCR.Results The room where SARS outbreak occurred was on the 13th floor of the 16-story main ward building.There were 6 beds in the room,living with 6 female patients(aged 45-67)who were all hospitalized due to type2 diabetes.On March 24,2003,Patient 1 began to have a fever and cough,chest X-ray showed pneumonia.Five and six days later,Patient 2 and Patient 3 began to have a fever,respectively.Finally,all of these 3 patients died.Their beds were all at the same side of the room,and the other 3 patients at the opposite side were not infected.Serum SARS CoV-RNA of the Patient 3 was positive by nest-PCR.The daughter-in-law of Patient 1who accompanied Patient 1 by the bedside several days,mainly near the window,upwind of Patient 1,was not infected.Medical staff,family members and visitors of the 6 patients were not infected.Conclusions This outbreak was not transmitted by aerosol.The distance droplets travels could be up to 3.43 meters.Droplet spread has direction,and the droplets direction of propagation is closely related with the wind direction and speed.Those at the downwind position of SARS patients were susceptible to be infected.Medical staff wore face masks and good natural ventilation of this ward building may be important reasons for the prevention of infection.

The effect of changing COVID-19 restrictions on the transmission rate in a veterinary clinic

With the declaration of the COVID-19 pandemic by the World Health Organization on March 11,2020,the University of Tennessee College of Veterinary Medicine(UTCVM),like other institutions,restructured their services to reduce the potential spread of the COVID-19 virus while simultaneously providing critical and essential veterinary services.A mathematical model was developed to predict the change in the level of possible COVID-19 infections due to the increased number of potential contacts within the UTCVM hospital.A system of ordinary differential equations with different compartments for UTCVM individuals and the Knox county population was formulated to show the dynamics of transmission and the number of confirmed cases.Key transmission rates in the model were estimated using COVID-19 case data from the surrounding county and UTCVM personnel.Simulations from this model show the increasing number of COVID-19 cases among UTCVM personnel as the number of daily clients and the number of veterinary staff in the clinic are increased.We also investigate how changes within the Knox county community impact the UTCVM hospital.These scenarios show the importance of understanding the effects of re-opening scenarios in veterinary teaching hospitals.

Effect of delivery mode on maternal-infant transmission of hepatitis B virus by immunoprophylaxis

OBJECTIVE: To study the effect of different delivery modes on immunoprophylaxis efficacy so as to clarify whether or not cesarean section reduces immunoprophylaxis failure. METHODS: Mothers with positive hepatitis B surface antigen (HBsAg) were selected in the third trimester of pregnancy. Their babies were inoculated with hepatitis B immunoglobulin at birth and hepatitis B vaccine at 1, 2 and 7 months of age. HBsAg and its antibodies (anti-HBs) were tested at 1, 4, 7, and 12 months of age, then followed up yearly. RESULTS: A total of 301 babies entered the study, including 144 born by normal spontaneous vaginal delivery, 40 by obstetric forceps or vacuum extraction, and 117 by cesarean section. The incidence of mother's HBeAg positivity or baby's gender constitution was comparable between the three groups. There were no significant differences in the positive rate of anti-HBs or HBsAg at follow-up periods among the three groups. At 12 months of age, anti-HBs could be detected in 78.9% of the babies born by normal vaginal delivery, 84.6% of the babies by forceps or vacuum extraction, and 86.4% of the babies by cesarean section. The positive rate of HBsAg was 8.1%, 7.7%, 9.7%, and chronic HBV infection incidence was 7.3%, 7.7%, 6.8% respectively. CONCLUSIONS: There are no significant effects of delivery mode on the interruption of HBV maternal-baby transmission by immunoprophylaxis. Cesarean section does not reduce the incidence of immunoprophylaxis failure.

The Global Leprosy Assessment Index(GLAI):A new approach for measuring the severity of disease in Brazil

Background:In Brazil,the Ministry of Health(MH)monitors leprosy using 15 indicators,with the aim of imple-menting and evaluating evidence-based public policies.However,an excessive number of variables can compli-cate the definition of objectives and verification of epidemiological goals.Methods:In this paper,we develop the Global Leprosy Assessment Index(GLAI),a composite measure that integrates two key dimensions for the control the disease:epidemiological and operational.Using a confirmatory factor analysis model to examine 2020 state-level data,we have standardized GLAI to a range of 0 to 1.Results:Higher values within this range indicate a greater severity of the disease.The mean value of the GLAI was 0.67,with a standard deviation of 0.22.Roraima has the highest value,followed by Paraíba with 0.88 while Tocantins records the lowest value of the indicator,followed by Mato Grosso with 0.14.The epidemiological and operational indicators have a positive but statistically insignificant correlation(r=0.25;p-value=0.20).Conclusions:The development of evidence-based public policies depends on the availability of valid and reliable indicators.The GLAI presented in this paper is easily reproducible and can be used to monitor the disease with disaggregated information.Furthermore,the GLAI has the potential to serve as a more robust parameter for evaluating the impact of actions designed to eradicate leprosy in Brazil.

Effect of delivery mode on maternal-infant transmission of hepatitis B virus by immunoprophylaxis

To study the effect of different delivery modes on immunoprophylaxis efficacy so as to clarify whether or not cesarean section reduces immunoprophylaxis failure Methods Mothers with positive hepatitis B surface antigen (HBsAg) were selected in the third trimester of pregnancy Their babies were inoculated with hepatitis B immunoglobulin at birth and hepatitis B vaccine at 1, 2 and 7 months of age HBsAg and its antibodies (anti HBs) were tested at 1, 4, 7, and 12 months of age, then followed up yearly Results A total of 301 babies entered the study, including 144 born by normal spontaneous vaginal delivery, 40 by obstetric forceps or vacuum extraction, and 117 by cesarean section The incidence of mother’s HBeAg positivity or baby’s gender constitution was comparable between the three groups There were no significant differences in the positive rate of anti HBs or HBsAg at follow up periods among the three groups At 12 months of age, anti HBs could be detected in 78 9% of the babies born by normal vaginal delivery, 84 6% of the babies by forceps or vacuum extraction, and 86 4% of the babies by cesarean section The positive rate of HBsAg was 8 1%, 7 7%, 9 7%, and chronic HBV infection incidence was 7 3%, 7 7%, 6 8% respectively Conclusions There are no significant effects of delivery mode on the interruption of HBV maternal baby transmission by immunoprophylaxis Cesarean section does not reduce the incidence of immunoprophylaxis failure

Optimal control analysis of Ebola disease with control strategies of quarantine and vaccination

Background:The 2014 Ebola epidemic is the largest in history,affecting multiple countries in West Africa.Some isolated cases were also observed in other regions of the world.Method:In this paper,we introduce a deterministic SEIR type model with additional hospitalization,quarantine and vaccination components in order to understand the disease dynamics.Optimal control strategies,both in the case of hospitalization(with and without quarantine)and vaccination are used to predict the possible future outcome in terms of resource utilization for disease control and the effectiveness of vaccination on sick populations.Further,with the help of uncertainty and sensitivity analysis we also have identified the most sensitive parameters which effectively contribute to change the disease dynamics.We have performed mathematical analysis with numerical simulations and optimal control strategies on Ebola virus models.Results:We used dynamical system tools with numerical simulations and optimal control strategies on our Ebola virus models.The original model,which allowed transmission of Ebola virus via human contact,was extended to include imperfect vaccination and quarantine.After the qualitative analysis of all three forms of Ebola model,numerical techniques,using MATLAB as a platform,were formulated and analyzed in detail.Our simulation results support the claims made in the qualitative section.Conclusion:Our model incorporates an important component of individuals with high risk level with exposure to disease,such as front line health care workers,family members of EVD patients and Individuals involved in burial of deceased EVD patients,rather than the general population in the affected areas.Our analysis suggests that in order for R0(i.e.,the basic reproduction number)to be less than one,which is the basic requirement for the disease elimination,the transmission rate of isolated individuals should be less than one-fourth of that for non-isolated ones.Our analysis also predicts,we need high levels of medication and hospitalization at the beginning of an epidemic.Further,optimal control analysis of the model suggests the control strategies that may be adopted by public health authorities in order to reduce the impact of epidemics like Ebola.

Spatial transmission of avian influenza (type H5) in birds

Highly pathogenic avian influenza(HPAI)H5N1 continues to threaten domestic and wild birds,as well as human health.However,the mechanism of spatial transmission of HPAI is still unclear.We analyzed the current distribu-tion of HPAI occurrences based on World Organization for Animal Health reported data from 3049 sites in the world from December 2003 to June 2006,and found that these sites were spaced at distances with a frequency peak of 100–200 km.We built a cellular automata model to simulate the spatial transmission process of HPAI as a function of transmission distance,variance of the transmission distance,infection rate,and transmission times(how many times HPAI transmits from one host to another before suppression).We determined that the transmis-sion distance between HPAI occurrences is approximately 100 km on the basis of historical HPAI occurrences from 2003 to 2006 in both wild and domestic birds.To effectively reduce the long-distance spreading of HPAI,preventing close contact between domestic birds and waterfowl within a radius of 100 km around HPAI occur-rence sites is essential.