Brucellosis Model Research Articles

Dynamics of a Stochastic Brucellosis Model with Vaccination and Environmental Pollution Transmission

Dynamics of a Stochastic Brucellosis Model with Vaccination and Environmental Pollution Transmission

Stability of a stochastic brucellosis model with semi-Markovian switching and diffusion.

To explore the influence of state changes on brucellosis, a stochastic brucellosis model with semi-Markovian switchings and diffusion is proposed in this paper. When there is no switching, we introduce a critical value and obtain the exponential stability in mean square when by using the stochastic Lyapunov function method. Sudden climate changes can drive changes in transmission rate of brucellosis, which can be modelled by a semi-Markov process. We study the influence of stationary distribution of semi-Markov process on extinction of brucellosis in switching environment including both stable states, during which brucellosis dies out, and unstable states, during which brucellosis persists. The results show that increasing the frequencies and average dwell times in stable states to certain extent can ensure the extinction of brucellosis. Finally, numerical simulations are given to illustrate the analytical results. We also suggest that herdsmen should reduce the densities of animal habitation to decrease the contact rate, increase slaughter rate of animals and apply disinfection measures to kill brucella.

Numerical threshold stability of an unconditionally positivity-preserving numerical method for a nonlinear age-structured reaction–diffusion brucellosis model

Numerical threshold stability of an unconditionally positivity-preserving numerical method for a nonlinear age-structured reaction–diffusion brucellosis model

Exponential stability and optimal control of a stochastic brucellosis model with spatial diffusion and nonlocal transmission

In this paper, a stochastic brucellosis model with nonlocal transmission and spatial diffusion is established. Existence, uniqueness and positivity of mild solution to the model are obtained by adopting a truncation method. To ensure the Mean Square Exponential Stability (MSES) of the solution, sufficient conditions are given by employing the inequality techniques and the stability implies that the brucellosis die out in a short period of time. Moreover, we introduce elimination of infected animals and disinfection of brucella to the model as control strategies. Necessary conditions are given to obtain the optimal control which best balance the outcomes and costs of the control by applying Pontryagin’s maximum principle. Finally, the theoretical results are demonstrated by the numerical simulations.

Development of a Plant-Expressed Subunit Vaccine against Brucellosis.

Brucellosis is an important bacterial disease of livestock and the most common zoonotic disease. The current vaccines are effective but unsafe, as they result in animal abortions and are pathogenic to humans. Virus-like particles are being investigated as molecular scaffolds for foreign antigen presentation to the immune system. Here, we sought to develop a new-generation vaccine by presenting selected Brucella melitensis T cell epitopes on the surface of Orbivirus core-like particles (CLPs) and transiently expressing these chimeric particles in Nicotiana benthamiana plants. We successfully demonstrated the assembly of five chimeric CLPs in N. benthamiana plants, with each CLP presenting a different T cell epitope. The safety and protective efficacy of three of the highest-yielding CLPs was investigated in a mouse model of brucellosis. All three plant-expressed chimeric CLPs were safe when inoculated into BALB/c mice at specific antigen doses. However, only one chimeric CLP induced protection against the virulent Brucella strain challenge equivalent to the protection induced by the commercial Rev1 vaccine. Here, we have successfully shown the assembly, safety and protective efficacy of plant-expressed chimeric CLPs presenting B. melitensis T cell epitopes. This is the first step in the development of a safe and efficacious subunit vaccine against brucellosis.

A Review on the Methodology and Use of the Pregnant Mouse Model in the Study of Brucella Reproductive Pathogenesis and Its Abortifacient Effect.

Brucellosis is one of the most common and widespread bacterial zoonoses and is caused by Gram-negative bacteria belonging to the genus Brucella. These organisms are able to infect and replicate within the placenta, resulting in abortion, one of the main clinical signs of brucellosis. Although the mouse model is widely used to study Brucella virulence and, more recently, to evaluate the protection of new vaccines, there is no clear consensus on the experimental conditions (e.g., mouse strains, doses, routes of inoculation, infection/pregnancy time) and the natural host reproducibility of the pregnant mouse model for reproductive brucellosis. This lack of consensus calls for a review that integrates the major findings regarding the effect of Brucella wild-type and vaccine strains infections on mouse pregnancy. We found sufficient evidence on the utility of the pregnant mouse model to study Brucella-induced placentitis and abortion and propose suitable experimental conditions (dose, time of infection) and pregnancy outcome readouts for B. abortus and B. melitensis studies. Finally, we discuss the utility and limitations of the pregnant mouse as a predictive model for the abortifacient effect of live Brucella vaccines.

Brucella-driven host N-glycome remodeling controls infection

Many powerful methods have been employed to elucidate the global transcriptomic, proteomic, or metabolic responses to pathogen-infected host cells. However, the host glycome responses to bacterial infection remain largely unexplored, and hence, our understanding of the molecular mechanisms by which bacterial pathogens manipulate the host glycome to favor infection remains incomplete. Here, we address this gap by performing a systematic analysis of the host glycome during infection by the bacterial pathogen Brucella spp. that cause brucellosis. We discover, surprisingly, that a Brucella effector protein (EP) Rhg1 induces global reprogramming of the host cell N-glycome by interacting with components of the oligosaccharide transferase complex that controls N-linked protein glycosylation, and Rhg1 regulates Brucella replication and tissue colonization in a mouse model of brucellosis, demonstrating that Brucella exploits the EP Rhg1 to reprogram the host N-glycome and promote bacterial intracellular parasitism, thereby providing a paradigm for bacterial control of host cell infection.

Global dynamics of a periodic brucellosis model with time delay and environmental factors

In China, brucellosis has always been a significant public health issue, especially in the pastoral regions of northern provinces where animal husbandry is well-developed. However, the impact of control measures, breeding characteristics and temperature fluctuations on the transmission dynamics of brucellosis outbreaks remains unclear. We construct a periodic mechanism-driven dynamic model with latent delay coupled with the regional breeding and temperature characteristics of Xinjiang Region. Theoretically, the global dynamics of periodic solutions are demonstrated by the theory of monotone dynamical system. In the application, the monthly human brucellosis cases and average temperature data of Xinjiang from 2015 to 2020 are fitted, and the basic reproduction number of brucellosis transmission is evaluated as 0.6691. Nonetheless, it is yet unable to attain the national control standards in the short term. The findings suggest that: 1. Interactions of periodic fluctuations in Brucella survival time and sheep shearing are key factors leading to the periodic outbreaks of brucellosis. 2. Improving the frequency of environmental disinfection could quickly eliminate the brucellosis epidemic. Specifically, when the disinfection frequency was once a month, the national control standard could be reached 5 years ahead of schedule. 3. In extreme cases, when the immunization rate κ=0 or the detection rate γ=0, the basic reproduction number might still be less than 1. From an epidemiological perspective, non-immunization control measures may be implemented with the reduction of brucellosis cases. The aforementioned statement may also bear resemblance to the preventive and control measures implemented in our country.

Development of auxiliary early predicting model for human brucellosis using machine learning algorithm

Using machine learning algorithms to construct an early prediction model of brucellosis to improve the diagnosis efficiency of Brucellosis. This study was a case-control study. 2 381 brucellosis patients from Beijing Ditan Hospital affiliated to Capital Medical University were retrospectively collected as case group, and healthy people from Beijing Chaoyang Hospital affiliated to Capital Medical University were collected as control group from May 9, 2011 to November 29, 2021. The relevant clinical information and full blood count results of 13 257 data were collected and five algorithms of machine learning were used to construct an early predication model of brucellosis by using machine learning: random forest, Naive Bayes, decision tree, logistic regression and support vector machine;14 074 data (2 143 cases incase group and 11 931 cases in control group) were used to establish the early predication model of brucellosis, and 1 564 (238 cases in case group and 1 326 cases in control group) data were used to test the predication efficiency of the brucellosis model. The results showed that the support vector machine algorithm has the best predication performance by comparing the five machine learning models. The area under receiver curve (AUC) of receiver operating characteristic (ROC) was 0.991, and the accuracy, precision, specificity and Recall were 95.6%, 95.5%, 95.4% and 95.9%, respectively. Based on the SHAP plot, platelet distribution width (PDW) and basophil relative value (BASO%) results were low, and men with high coefficient of variation (R-CV), erythrocyte hemoglobin concentration (MCHC), and platelet volume (MPV) were predicted to be at high risk of brucellosis. Platelet distribution width (PDW) contributed the most to the prediction model, followed by red blood cell distribution width coefficient of variation (R-CV). In conclusion, the establishment of a high-precision early predication method of brucellosis based on machine learning may be of great significance for the early detection and treatment of brucellosis patients.

Epidemiology Study of Brucellosis in Polewali Mandar District, Indonesia

<p>This research aims to determine the prevalence rate of brucellosis in the Polman District, examine the risk factors associated with seropositive diagnoses of brucellosis, and also to determine the brucellosis case model at the farm level. This research was carried out through a cross-sectional study and obtained a sample size of 395 serum. Samples were tested<em> </em>through the RBT and CFT. Identification of risk factors is based on questionnaire data conducted on around 113 breeders spread across Polman Regency. The data were analyzed using univariate and bivariate descriptive statistics, chi-square, and odds ratio (OR). The brucellosis model at the farm level was analyzed by multivariate logistic regression. The results of this study indicate the prevalence of brucellosis in Polman Regency is 27.1%. Risk factors associated with diagnosis of brucellosis in Polman Regency included the history of abortion (p=0.000; OR=128), handling of aborted animal (p=0.000; OR=94.667), abortion at the end of pregnancy (p=0.000; OR=62.333), knowledge about brucellosis (p=0.000; OR=9.841), handling of residual abortions (p=0.003; OR=8,471), high grazing density (p=0.000; OR=6.861), introduction of new livestock (p=0.006; OR=5.833), dirty cage (p=0.003; OR=3.600), and grazing method (p=0.005; OR=3.167). Models of diagnosis brucellosis in Polman Regency is = -2,48923 + 3,38734 history of abortion + 2,06312 abortions at the end of pregnancy. The model shows that the history of abortion (β=+3.387; OR=29.588) and the incidence of abortion at the end of pregnancy (β=+2.205; OR = 7.871) can increase the seropositive diagnosis of brucellosis at the farm level<em>.</em></p>

Analysis of a fractional order Bovine Brucellosis disease model with discrete generalized Mittag–Leffler kernels

Bovine Brucellosis, a zoonotic disease, can infect cattle in tropical and subtropical areas. It remains a critical issue for both human and animal health in many parts of the world, especially those where livestock is an important source of food and income. An efficient method for monitoring the illness’s increasing prevalence and developing low-cost prevention strategies for both its effects and recurrence is brucellosis disease modeling. We create a fractional-order model of Bovine Brucellosis using a discrete modified Atangana–Baleanu fractional difference operator of the Liouville–Caputo type. An analysis of the suggested system’s well-posedness and a qualitative investigation are both conducted. The examination of the Volterra-type Lyapunov function for global stability is supported by the first and derivative tests. The Lipschitz condition is also used for the model in order to meet the criterion of the uniqueness of the exact solution. We created an endemic and disease-free equilibrium. Solutions are built in the discrete generalized form of the Mittag-Leffler kernel in order to analyze the effect of the fractional operator with numerical simulations and emphasize the effects of the sickness due to the many factors involved. The capacity of the suggested model to forecast an infectious disease like brucellosis can help researchers and decision-makers take preventive actions.

A TLR4 agonist liposome formulation effectively stimulates innate immunity and enhances protection from bacterial infection.

Stimulation of innate immunity can protect against infectious insult and could be used in combination with other therapies. Since antibiotic resistance is an increasing concern, strategies to reduce the dose or eliminate the need for these drugs are warranted. Lipo-CRX is a formulation in which the TLR4 agonist CRX-527 is incorporated into lipid membranes in liposomes. Lipo-CRX is less inflammatory than either CRX-527 or LPS, but retains unique capacity to enhance host defense responses. We compared lipo-CRX to other agonists in vitro using mammalian cells and in vivo in mice, and assessed indicators of innate immune responses and protection from bacterial infection. Lipo-CRX is similar to E. coli LPS in its capacity to activate bovine γδ T cells and to recruit neutrophils into mouse lungs, but with less reactivity in the LAL assay. However, lipo-CRX uniquely induced the production of systemic innate immune cytokines. In the mouse model of brucellosis, delivery of lipo-CRX to the lungs reduced the dissemination of B. abortus. While lipo-CRX or the antibiotic ampicillin alone did not alter B. abortus burdens in the lung, the combination had a synergistic beneficial effect. Our data suggest that stimulating the innate immune system with lipo-CRX, either alone or when combined with antibiotics, can enhance bacterial clearance in the mouse model of brucellosis.

Insights for brucellosis eradication in Italy through a model-based spread evaluation in grazing livestock - Sicily case study.

Brucellosis is one of the world's major zoonotic pathogens and is responsible for enormous economic losses as well as considerable human morbidity in endemic areas. Definitive control of human brucellosis requires control of brucellosis in livestock through practical solutions that can be easily applied to the field. In Italy, brucellosis remains endemic in several southern provinces, particularly in Sicily Region. The purpose of this paper is to describe the developed brucellosis model and its applications, trying to reproduce as faithfully as possible the complex transmission process of brucellosis accounting for the mixing of grazing animals. The model focuses on the contaminated environment rather than on the infected animal, uses real data from the main grazing areas of the Sicily Region, and aims to identify the best control options for minimizing the spread (and the prevalence) and to reach the eradication within the concerned areas. Simulation results confirmed the efficacy of an earlier application of the controls, showed the control should take place 30 days after going to pasture, and the culling time being negligible. Moreover, results highlighted the importance of the timing of both births and grazing pastures (and their interaction) more than other factors. As these factors are region‑specific, the study encourages the adoption of different and new eradication tools, tuned on the grazing and commercial behavior of each region. This study will be further extended to improve the model's adaptability to the real world, with the purpose of making the model an operational tool able to help decision makers in accelerating brucellosis eradication in Italy.

Dynamics of a stochastic multi-stage sheep brucellosis model with incomplete immunity

This paper considered a multi-stage sheep brucellosis model with incomplete immunity. First, we established a deterministic model, calculated the basic reproduction number [Formula: see text], set out the conditions for the global stability of the disease-free equilibrium and endemic equilibrium. Second, considering the influence of environmental white noise on brucellosis infection, we further established the stochastic version of the model. By constructing a suitable Lyapunov function, we proved the existence and uniqueness of the global positive solution. Further, we got the sufficient conditions for disease extinction and the existence of ergodic stationary distribution. Finally, we carried out some numerical simulations to verify the theoretical results.

Threshold dynamics of an age-space structured brucellosis model with nonlinear incidence rate on a heterogeneous environment

We propose an age-space structured brucellosis model that includes diffusion with heterogeneous coefficients and a general nonlinear incidence rate. The renewal process is used to calculate the next generation operator, and the basic reproduction number R0 is defined by the spectral radius of the next generation operator. We prove that R0 governs the threshold dynamics of the brucellosis model: when R0 < 1 the disease dies out, and when R0 > 1 the disease persists.

Dynamic analysis of sheep Brucellosis model with environmental infection pathways.

We develop a mathematical model for the transmission of brucellosis in sheep taking into account external inputs, immunity, stage structure and other factors. We find the the basic reproduction number $ R_0 $ in terms of the model parameters, and prove the global stability of the disease-free equilibrium. Then, the existence and global stability of the endemic equilibrium is proven. Finally, sheep data from Yulin, China are employed to fit the model parameters for three different environmental infection exposure conditions. The variability between different models in terms of control measures are analyzed numerically. Results show that the model is sensitive to the control parameters for different environmental infection exposure functions. This means that in practical modeling, the selection of environmental infection exposure functions needs to be properly considered.

Optimal control strategy analysis for an human-animal brucellosis infection model with multiple delays

Firstly, we consider an animal-human infection model of brucellosis with three distributed delays, representing the latent period of brucellosis in infected animal and human population and the survival time of brucella in the environment, respectively. The equilibrium points and basic reproduction number R0 are calculated. By building appropriate Lyapunov functionals and applying LaSalle's invariance principle, the sufficient conditions for global asymptotic stability of two equilibria are given. Secondly, by introducing four control variables, we set the corresponding optimal control model and drive the first order necessary conditions for the existence of optimal control solution. Finally, we perform several numerical simulations to validate our theoretical results and show effects of different control strategies.

A delayed stage-structure brucellosis model with interaction among seasonality, time-varying incubation and density-dependent growth

In this paper, a class of brucellosis transmission model with seasonal alternation, density-dependent growth, stage-structure, maturation delay, time-varying incubation is established. The basic reproduction number [Formula: see text] is derived, by which we find that the brucellosis is uniformly persistent if [Formula: see text], while the disease-free periodic solution is globally attractive if [Formula: see text]. The theoretical results are illustrated by numerical simulation, from which we find that the brucellosis transmission would be overestimated (or underestimated) if we ignore the influence of time-varying incubation or maturation delay. If density-dependent growth of animals is ignored, the risk of brucellosis may be far underestimated, the extinction of brucellosis can be obtained by numerical simulation under the same conditions. Seasonality significantly affects the long-term dynamic behavior of brucellosis, and the inconsistency of parameter periods results in complex dynamic behavior.

Stationary distribution and extinction of a stochastic cattle brucellosis model

In this paper, we propose a deterministic cattle brucellosis model and analyze the global stability of disease-free equilibrium and the persistence of the disease. Secondly, we consider environmental perturbations and present a stochastic version of the model, study the existence and uniqueness of positive solution, investigate the sufficient conditions for the existence of ergodic stationary distribution and extinction of the model. Finally, we use numerical simulation to observe the influence of the disturbance term on the original model.

Stationary Distribution and Extinction of a Stochastic Brucellosis Model with Standard Incidence

In this paper, we proposed a stochastic SVEI brucellosis model with stage structure by introducing the effect of environmental white noise on transmission dynamics of brucellosis. By Has'minskii theory and constructing suitable Lyapunov functions, we established sufficient conditions on the existence of ergodic stationary distribution for the considered model. Moreover, we also established sufficient condition for extinction of the disease. Finally, two examples with numerical simulations are given to illustrate the main results of this paper.