Mathematical Biosciences最新文献

Assessing the influence of HIV on the spread of Mpox disease 评估艾滋病毒对痘病传播的影响

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-29 DOI: 10.1016/j.mbs.2025.109499

Arsène Jaurès Ouemba Tassé , Yibetal Terefe , Jean Lubuma

{"title":"Assessing the influence of HIV on the spread of Mpox disease","authors":"Arsène Jaurès Ouemba Tassé , Yibetal Terefe , Jean Lubuma","doi":"10.1016/j.mbs.2025.109499","DOIUrl":"10.1016/j.mbs.2025.109499","url":null,"abstract":"<div><div>Mpox, originating primarily in African rodents, has led to human outbreaks over recent years. This study presents a mathematical model for Mpox, distinguishing between individuals with and without HIV who are susceptible. We explore scenarios involving both rodent-to-human transmission and those without it. In the absence of this transmission route, the model undergoes a backward bifurcation, suggesting that reducing the basic reproduction number below one would not eliminate the disease unless further control strategies are used. With the account of rodent-to-human transmission, if Mpox is endemic in the rodent population, a unique interior equilibrium, globally asymptotically stable, exists, requiring targeted interventions like quarantine or vaccination for people with HIV (PWH) for disease control. Model validation using USA case data (May 2022–July 2024) shows that both human-to-human and rodent-to-human transmissions prevail in the population, but the disease is not endemic. Projections indicate that the outbreak will be overcome by May 2027, with a total of 35,811 cases. We design a nonstandard finite difference (NSFD) scheme which is dynamically consistent with respect to the qualitative properties of the continuous model. Numerical simulations demonstrate that reducing the recruitment rate of PWH is essential, and rodent-to-human transmission is identified as highly influential in increasing the number of Mpox cases.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109499"},"PeriodicalIF":1.9,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bifurcation analysis of tumor-immune dynamics under the dual Allee effects 双Allee效应下肿瘤免疫动力学的分岔分析。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-23 DOI: 10.1016/j.mbs.2025.109483

Eymard Hernandez-Lopez, Xiunan Wang

引用次数: 0

Recurrent patterns of disease spread post the acute phase of a pandemic: Insights from a coupled system of a differential equation for disease transmission and a delayed algebraic equation for behavioral adaptation 大流行急性期后疾病传播的复发模式：来自疾病传播微分方程和行为适应延迟代数方程耦合系统的见解

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-21 DOI: 10.1016/j.mbs.2025.109480

Tianyu Cheng, Jianhong Wu

{"title":"Recurrent patterns of disease spread post the acute phase of a pandemic: Insights from a coupled system of a differential equation for disease transmission and a delayed algebraic equation for behavioral adaptation","authors":"Tianyu Cheng, Jianhong Wu","doi":"10.1016/j.mbs.2025.109480","DOIUrl":"10.1016/j.mbs.2025.109480","url":null,"abstract":"<div><div>We introduce a coupled system of a disease transmission differential equation and a behavioral adaptation algebraic renewal equation to understand the mechanisms of nonlinear oscillations post-acute phase of a pandemic. This extends the Zhang–Scarabel–Murty–Wu model, which was formulated and analyzed to describe multi-wave patterns observed at the early stage during the acute phase of the COVID-19 pandemic. Our extension involves the depletion of susceptible population due to infection and contains a nonlinear disease transmission term to reflect the recovery and temporal immunity in the infected population past the acute phase of the pandemic. Examining whether and how incorporating this depletion of susceptible population impacts interwoven disease transmission dynamics and behavioral adaptation is the objective of our current research. We introduce some prototypical risk aversion functions to characterize behavioral responses to perceived risks and show how the risk aversion behaviors and the logistic delay in implementation of behavioral adaptation combined contribute to a dynamic equilibrium state described by a periodic oscillatory wave. We also link the period between two consecutive peaks to basic epidemic parameters, the community flexibility to behavioral change, and the population’s tolerance to perceived risks.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109480"},"PeriodicalIF":1.9,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144478349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimation of time-varying recovery and death rates from epidemiological data: A new approach 从流行病学数据估计时变的恢复率和死亡率：一种新方法。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-09 DOI: 10.1016/j.mbs.2025.109479

Samiran Ghosh , Malay Banerjee , Subhra Sankar Dhar , Siuli Mukhopadhyay

{"title":"Estimation of time-varying recovery and death rates from epidemiological data: A new approach","authors":"Samiran Ghosh , Malay Banerjee , Subhra Sankar Dhar , Siuli Mukhopadhyay","doi":"10.1016/j.mbs.2025.109479","DOIUrl":"10.1016/j.mbs.2025.109479","url":null,"abstract":"<div><div>The time-to-recovery or time-to-death for various infectious diseases can vary significantly among individuals, influenced by several factors such as demographic differences, immune strength, medical history, age, pre-existing conditions, and infection severity. To capture these variations, time-since-infection dependent recovery and death rates offer a detailed description of the epidemic. However, obtaining individual-level data to estimate these rates is challenging, while aggregate epidemiological data (such as the number of new infections, number of active cases, number of new recoveries, and number of new deaths) are more readily available. In this article, a new methodology is proposed to estimate time-since-infection dependent recovery and death rates using easily available data sources, accommodating irregular data collection timings reflective of real-world reporting practices. The Nadaraya–Watson estimator is utilized to derive the number of new infections. This model improves the accuracy of epidemic progression descriptions and provides clear insights into recovery and death distributions. The proposed methodology is validated using COVID-19 data and its general applicability is demonstrated by applying it to some other diseases like measles and typhoid.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109479"},"PeriodicalIF":1.9,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277096","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mathematical study of the spread and blocking in inflammatory bowel disease 炎症性肠病扩散和阻塞的数学研究。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-07 DOI: 10.1016/j.mbs.2025.109481

Saoussen Latrach , Eric Ogier-Denis , Nicolas Vauchelet , Hatem Zaag

引用次数: 0

Stochastic model of siRNA endosomal escape mediated by fusogenic peptides 融合肽介导siRNA内体逃逸的随机模型。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-05 DOI: 10.1016/j.mbs.2025.109476

Nisha Yadav , Jessica Boulos , Angela Alexander-Bryant , Keisha Cook

{"title":"Stochastic model of siRNA endosomal escape mediated by fusogenic peptides","authors":"Nisha Yadav , Jessica Boulos , Angela Alexander-Bryant , Keisha Cook","doi":"10.1016/j.mbs.2025.109476","DOIUrl":"10.1016/j.mbs.2025.109476","url":null,"abstract":"<div><div>Gene silencing via small interfering RNA (siRNA) represents a transformative tool in cancer therapy, offering specificity and reduced off-target effects compared to conventional treatments. A crucial step in siRNA-based therapies is endosomal escape, the release of siRNA from endosomes into the cytoplasm. Quantifying endosomal escape is challenging due to the dynamic nature of the process and limitations in imaging and analytical techniques. Traditional methods often rely on fluorescence intensity measurements or manual image processing, which are time-intensive and fail to capture continuous dynamics. This paper presents a novel computational framework that integrates automated image processing to analyze time-lapse fluorescent microscopy data of endosomal escape, hierarchical Bayesian inference, and stochastic simulations. Our method employs image segmentation techniques such as binary masks, Gaussian filters, and multichannel color quantification to extract precise spatial and temporal data from microscopy images. Using a hierarchical Bayesian approach, we estimate the parameters of a compartmental model that describes endosomal escape dynamics, accounting for variability over time. These parameters inform a Gillespie stochastic simulation algorithm, ensuring realistic simulations of siRNA release events over time. By combining these techniques, our framework provides a scalable and reproducible method for quantifying endosomal escape. The model captures uncertainty and variability in parameter estimation, and endosomal escape dynamics. Additionally, synthetic data generation allows researchers to validate experimental findings and explore alternative conditions without extensive laboratory work. This integrated approach not only improves the accuracy of endosomal escape quantification but also provides predictive insights for optimizing siRNA delivery systems and advancing gene therapy research.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109476"},"PeriodicalIF":1.9,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144251660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Patient-specific prediction of glioblastoma growth via reduced order modeling and neural networks 通过降阶模型和神经网络对胶质母细胞瘤生长的患者特异性预测

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-03 DOI: 10.1016/j.mbs.2025.109468

D. Cerrone , D. Riccobelli , S. Gazzoni , P. Vitullo , F. Ballarin , J. Falco , F. Acerbi , A. Manzoni , P. Zunino , P. Ciarletta

{"title":"Patient-specific prediction of glioblastoma growth via reduced order modeling and neural networks","authors":"D. Cerrone , D. Riccobelli , S. Gazzoni , P. Vitullo , F. Ballarin , J. Falco , F. Acerbi , A. Manzoni , P. Zunino , P. Ciarletta","doi":"10.1016/j.mbs.2025.109468","DOIUrl":"10.1016/j.mbs.2025.109468","url":null,"abstract":"<div><div>Glioblastoma is among the most aggressive brain tumors in adults, characterized by patient-specific invasion patterns driven by the underlying brain microstructure. In this work, we present a proof-of-concept for a mathematical model of GBL growth, enabling real-time prediction and patient-specific parameter identification from longitudinal neuroimaging data.</div><div>The framework exploits a diffuse-interface mathematical model to describe the tumor evolution and a reduced-order modeling strategy, relying on proper orthogonal decomposition, trained on synthetic data derived from patient-specific brain anatomies reconstructed from magnetic resonance imaging and diffusion tensor imaging. A neural network surrogate learns the inverse mapping from tumor evolution to model parameters, achieving significant computational speed-up while preserving high accuracy.</div><div>To ensure robustness and interpretability, we perform both global and local sensitivity analyses, identifying the key biophysical parameters governing tumor dynamics and assessing the stability of the inverse problem solution. These results establish a methodological foundation for future clinical deployment of patient-specific digital twins in neuro-oncology.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109468"},"PeriodicalIF":1.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144223529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bistability between acute and chronic states in a Model of Hepatitis B Virus Dynamics 乙型肝炎病毒动力学模型中急性和慢性状态的双稳定性。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-05-31 DOI: 10.1016/j.mbs.2025.109467

Nazia Afrin , Stanca M. Ciupe , Jessica M. Conway , Hayriye Gulbudak

{"title":"Bistability between acute and chronic states in a Model of Hepatitis B Virus Dynamics","authors":"Nazia Afrin , Stanca M. Ciupe , Jessica M. Conway , Hayriye Gulbudak","doi":"10.1016/j.mbs.2025.109467","DOIUrl":"10.1016/j.mbs.2025.109467","url":null,"abstract":"<div><div>Understanding the mechanisms responsible for different clinical outcomes following hepatitis B infection requires a systems investigation of dynamical interactions between the virus and the immune system. To help elucidate mechanisms of protection and those responsible from transition from acute to chronic disease, we developed a deterministic mathematical model of hepatitis B infection that accounts for cytotoxic immune responses resulting in infected cell death, non-cytotoxic immune responses resulting in infected cell cure and protective immunity from reinfection, and cell proliferation. We analyzed the model and presented outcomes based on three important disease markers: the basic reproduction number <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span>, the infected cells death rate <span><math><mi>δ</mi></math></span> (describing the effect of cytotoxic immune responses), and the liver carrying capacity <span><math><mi>K</mi></math></span> (describing the liver susceptibility to infection). Using asymptotic and bifurcation analysis techniques, we determined regions where virus is cleared, virus persists, and where clearance-persistence is determined by the size of viral inoculum. These results can guide the development of personalized intervention.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109467"},"PeriodicalIF":1.9,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144210592","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effect of demographic and seasonal variability on an influenza epidemic in a metapopulation model 人口统计学和季节变化对亚人口模型中流感流行的影响。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-05-28 DOI: 10.1016/j.mbs.2025.109465

Dan Li, Ying Liu, Longxing Qi

{"title":"Effect of demographic and seasonal variability on an influenza epidemic in a metapopulation model","authors":"Dan Li, Ying Liu, Longxing Qi","doi":"10.1016/j.mbs.2025.109465","DOIUrl":"10.1016/j.mbs.2025.109465","url":null,"abstract":"<div><div>Meteorological factors such as temperature and humidity significantly affect the transmission efficiency of influenza viruses in temperate regions. School-age children aged 5 to 14 years are more susceptible to influenza A virus infection than other age groups. To reveal the impact of seasonal fluctuations in meteorological factors on the spread of influenza and the role of school-age children in disease transmission, we first develop a metapopulation ordinary differential equation model with the seasonal variation of infection probability upon contacting an infectious individual. The basic reproduction number <span><math><msub><mrow><mi>R</mi></mrow><mrow><mn>0</mn></mrow></msub></math></span> is obtained. To incorporate demographic variability, a time-nonhomogeneous Markov chain model is reformulated on the basis of the deterministic model. An analytic estimate for the probability of a disease outbreak, as well as an explicit expression for the mean(variance) of the disease extinction time in the absence of an outbreak, is derived. Finally, in the case where the population is divided into two subgroups based on age: school-age children aged 5 to 14 years and individuals of other age groups, our model is applied to study seasonal outbreaks of influenza A viruses in temperate regions. Numerical simulations suggest that: (i) the probability of a disease outbreak depends on the number of reported and unreported infections introduced for the first time, the timing of introduction, and their age group; (ii) the impact of demographic stochasticity on the final size and time until extinction after a disease outbreak depends mainly on the timing of influenza virus introduction; (iii) regardless of the season in which an unreported infected individual is introduced, timely treatment of infected school-age children can help reduce the likelihood of disease outbreaks and lower the mean final size after an outbreak.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"386 ","pages":"Article 109465"},"PeriodicalIF":1.9,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144188737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mathematical modelling of carbohydrate and protein metabolism in muscle 肌肉中碳水化合物和蛋白质代谢的数学模型

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-05-21 DOI: 10.1016/j.mbs.2025.109455

Bandar Muidh Alharbi , Hannah E. Williams , Tim Parr , John M Brameld , Christopher Fallaize , Jonathan A.D. Wattis

{"title":"Mathematical modelling of carbohydrate and protein metabolism in muscle","authors":"Bandar Muidh Alharbi , Hannah E. Williams , Tim Parr , John M Brameld , Christopher Fallaize , Jonathan A.D. Wattis","doi":"10.1016/j.mbs.2025.109455","DOIUrl":"10.1016/j.mbs.2025.109455","url":null,"abstract":"<div><div>We propose a mathematical model based on coupled ordinary differential equations (ODEs) for metabolite concentrations with the aim of investigating how modifications to the rates affects outputs from a regulatory network. Our aim is to model the relationships between energy metabolism and the biosynthesis of non-essential amino acids, such as serine. We consider a network of cytosolic glycolysis, the mitochondrial TCA cycle, and the associated serine synthesis pathway, with the aim of modelling the role of metabolic reprogramming as a mechanism to enhance protein synthesis and growth, particularly in skeletal muscle. Our objective is to explore the consequences of overexpressing two key enzymes, phosphoenolpyruvate carboxykinase 2 (PCK2), and phosphoglycerate dehydrogenase (PHGDH), on the TCA cycle and on serine production. We investigate how the rate of serine synthesis is affected by upregulating both enzymes simultaneously, or each one individually. We find a range of steady-states which depend upon input fluxes into the network. As input fluxes are altered, steady states cease to exist due to a bifurcation to one of two states in which some metabolites grow linearly in time whilst others decay to zero. Asymptotic analysis provides approximations for steady-state solutions near these bifurcation points, and conditions on parameter values which determine where in parameter space the system’s behaviour changes. We also perform a parameter sensitivity analysis to determine the effect of perturbations to rate constants and input rates. Our numerical simulations show that the up-regulation of PHGDH, the initial rate limiting enzyme in the serine-synthesis pathway, causes an increase in serine production but that, contrary to our hypothesis, increased expression of PCK2 has no effect. This model aids our understanding of both the effects of drugs and changes in enzyme expression or activities which upregulate one or more reactions in a pathway.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"386 ","pages":"Article 109455"},"PeriodicalIF":1.9,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0