Mathematical Biosciences and Engineering最新文献

{"title":"Data-driven modeling of imported malaria in Morocco and the impact of population migration.","authors":"Hamza Toufga, Ghassane Benrhmach, Mustapha Lhous, Abdessamad Tridane","doi":"10.3934/mbe.2026042","DOIUrl":"10.3934/mbe.2026042","url":null,"abstract":"<p><p>Malaria remains a very critical health-threatening issue worldwide, and increasingly, migration is viewed as a cause of re-emergence in malaria-free zones. This study proposes a data-driven, deterministic compartmental model that explicitly accounts for human immigration when modeling malaria transmission from humans to mosquito populations. The human host is categorized into susceptible, asymptomatic, infected, and recovered classes, while the vector population is stratified into susceptible and infected compartments. The paper presents a rigorous mathematical analysis to prove the positivity and uniqueness of solutions, and further demonstrates that the model only admits a globally stable endemic equilibrium. Using Morocco as a case study, key parameters are estimated using three complementary methods: least-squares fit, Extended Kalman Filter, and Long Short-Term Memory (LSTM) neural networks, which where applied to imported malaria data from 1990 through 2023. To identify the best control measures to prevent the possible re-establishment of malaria in Morocco, we investigate an optimal control problem that includes awareness, prophylactic treatment, treatment of the infected population, and vector control with insecticide. The goal is to identify the optimal effectiveness of these controls. Numerical results show a significant reduction in human and vector infections through a combination of control strategies, thus underscoring the importance of surveillance and control policies that account for migration. Therfore, it serves as a practical, flexible framework to analyze imported malaria and other vector-borne diseases across similarly high-mobility areas.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 4","pages":"1121-1155"},"PeriodicalIF":2.6,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147647102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling infectious disease transmission dynamics in conference environments: An agent-based approach.","authors":"Xue Liu, Yue Deng, Jingying Huang, Yuhong Zhang, Jinzhi Lei","doi":"10.3934/mbe.2026041","DOIUrl":"10.3934/mbe.2026041","url":null,"abstract":"<p><p>The looming threat of infectious diseases perpetually challenges the global public health landscape. Central to addressing this concern is the imperative to prevent and manage disease transmission during pandemics, particularly in unique settings. This study addresses the transmission dynamics of infectious diseases within conference venues by presenting a computational model that simulates transmission processes over a condensed timeframe (one day), beginning with sporadic cases. Our model captures the activities of individual attendees within the conference venue, including meetings, rest breaks, and meal breaks. While meetings entail proximity seating, rest and lunch periods allow attendees to interact with diverse individuals. Moreover, the restroom environment poses an additional avenue for potential infection transmission. Employing an agent-based model, we meticulously replicated the transmission dynamics of infectious diseases, with a specific emphasis on close-contact interactions between infected and susceptible individuals. Through comprehensive analysis of model simulations, we elucidated the intricacies of disease transmission dynamics within conference settings and assessed the efficacy of control strategies to curb disease dissemination. Ultimately, our study provides a numerical framework for assessing the risk of infectious disease transmission during short-duration conferences, furnishing conference organizers with valuable insights to inform the implementation of targeted prevention and control measures.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 4","pages":"1096-1120"},"PeriodicalIF":2.6,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147647247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mathematical modeling of the effects of screening and treatment of gastric ulcers as a control strategy for gastric cancer.","authors":"Glory Kawira Mutua, Musyoka Kinyili, Dominic Makaa Kitavi","doi":"10.3934/mbe.2026040","DOIUrl":"10.3934/mbe.2026040","url":null,"abstract":"<p><p>Gastric cancer is among the most common cancers in the world, and it has a significant negative impact on the health and economies of different countries, led by those that are developing. This study formulates a deterministic model for the transmission dynamics of gastric cancer through gastric ulcers, incorporating screening and treatment strategies. The model is thoroughly analyzed both quantitatively, qualitatively, and numerically. The key properties considered in the model analysis are positivity, invariant region, equilibria, stabilities, and bifurcation analysis. We compute the control reproduction number $ mathcal R_{C} $ using the next-generation matrix approach. This enables us to prove that the model has a unique disease-free equilibrium (DFE) and admits a unique endemic equilibrium, which are locally and globally asymptotically stable whenever $ mathcal R_{C} < 1 $ and $ mathcal R_{C} > 1 $, respectively. Sensitivity analysis indicates that increasing the rate of screening decreases the control reproduction number, consequently reducing the rate of transmission of infections. Simulation results demonstrate that the combination of screening and treatment is the most effective intervention in reducing infection transmission. Furthermore, a combination of early screening and treatment proves more effective than a combination of late screening and treatment of gastric ulcers. Screening the infected population alone is identified as the least effective strategy for curtailing transmission of infection in the susceptible population. The findings of this study will guide public health officers in making decisions regarding the screening and treatment of exposed individuals with <i>Helicobacter pylori</i> infection and gastric ulcer patients, therefore aiding in fighting gastric ulcers and their progression to gastric cancer.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 4","pages":"1067-1095"},"PeriodicalIF":2.6,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147647225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immune dysregulation in COVID-19: Mathematical modeling of the within-host dynamics.","authors":"Keopagnapech Ngoun, Nicolas Alvarez, Ayesh Awad, Hwayeon Ryu","doi":"10.3934/mbe.2026038","DOIUrl":"10.3934/mbe.2026038","url":null,"abstract":"<p><p>The COVID-19 pandemic has spurred extensive research into viral transmission and control, yet the mechanisms of the human immune response to SARS-CoV-2 remain incompletely understood, particularly the role of natural killer (NK) cells and cytokine regulation in disease severity. Mathematical modeling provides a powerful approach to bridge this gap by linking viral dynamics with immune interactions. In this work, we developed a mechanistic within-host model, formulated in a system of coupled ordinary and delayed differential equations, to investigate the contributions of NK cell activity, interferon signaling, and pro-inflammatory cytokines to viral clearance and disease outcome. Model parameters were estimated from experimental data, and computational simulations were used to explore how dysregulated NK responses and cytokine feedback loops may drive divergent clinical outcomes. Local sensitivity analysis identified the most influential parameters shaping host-pathogen dynamics, highlighting potential control points for intervention. In addition, knockdown simulations were performed to mimic potential therapeutic interventions, allowing us to evaluate their advantages and limitations <i>in silico</i>. These findings provided mechanistic insights into COVID-19 immune dynamics and offered a foundation for guiding the design of future treatment strategies.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 4","pages":"987-1049"},"PeriodicalIF":2.6,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147647108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global boundedness and large time behavior in a forager-exploiter model of parabolic-parabolic-elliptic type.","authors":"Yifeng Xiong, Lu Xu","doi":"10.3934/mbe.2026039","DOIUrl":"https://doi.org/10.3934/mbe.2026039","url":null,"abstract":"<p><p>This paper deals with the parabolic-parabolic-elliptic forager-exploiter model under homogeneous Neumann boundary conditions. It is shown that if the taxis effects of exploiters are suitably weak, its classical solution is globally bounded in arbitrary dimensions. Moreover, the foragers and exploiters will approach spatially homogeneous distributions in the large time limit.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 4","pages":"1050-1066"},"PeriodicalIF":2.6,"publicationDate":"2026-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147647167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling neural dynamics with optical nonlinearity: From classical models to optogenetic approaches.","authors":"Svetlana A Gerasimova, Alexander N Pisarchik","doi":"10.3934/mbe.2026037","DOIUrl":"10.3934/mbe.2026037","url":null,"abstract":"<p><p>Optogenetic experiments in vivo face fundamental limitations in real-time optical stimulation and biophotonic signal processing, constraining the efficiency and adaptability of neural circuit interrogation. This review establishes how photonic neuromorphic systems, operating at ultrafast speeds and with high energy efficiency, can overcome these barriers by forming a closed-loop optically driven interface with neural tissue. We present a comprehensive analysis of mathematical and computational models that describe neural dynamics in optical neuromorphic devices, bridging classical neuronal frameworks with optogenetic control paradigms. Emphasis is placed on how nonlinear dynamical modeling and data-driven approaches enable the design of photonic neurons and synapses capable of seamless integration with tapered fibers, fiber photometry, and computational optical control systems. Such integration allows real-time signal processing and adaptive feedback within optogenetic experiments, thereby enhancing precision and bidirectionality in living neural circuit interactions. By converging mathematical theory, photonic hardware, and neurobiology, this work provides a roadmap for next-generation neural interfaces that leverage optical neuromorphic computing to advance both intelligent neuroengineering and biomedical diagnostics.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 4","pages":"940-986"},"PeriodicalIF":2.6,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147647267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ambiguity in identifying parameters of an SIR model when fitting epidemic incidence data.","authors":"B Shayak, Sana Jahedi, James A Yorke","doi":"10.3934/mbe.2026036","DOIUrl":"10.3934/mbe.2026036","url":null,"abstract":"<p><p>When a new pathogen emerges, determining the key transmission parameters plays a crucial role in formulating public health policies and controlling the spread of the pathogen. It is important to note that not every parameter is \"identifiable\". A parameter of a model is said to be globally structurally identifiable from some kind of perfect data if it can be determined uniquely. Whether that parameter is identifiable depends on what kind of perfect data is available. In this work, we developed a new mathematical concept, the \"decay-growth ratio\", and using it, we prove that the basic reproduction number is \"globally structurally identifiable\" from the knowledge of this ratio, and with a bit more information, the duration of infectiousness can be determined as well. That, however, assumes perfect, noise-free data which in reality is unattainable. A parameter is said to be \"practically identifiable\" if it can be reliably estimated from finite, noisy data. Practical identifiability is inherently dependent on both the nature of the available data and the inferential methodology employed. We proved that neither the basic reproduction number nor the duration of infectiousness is practically identifiable from the common summary statistics of an outbreak, specifically its mean, standard deviation, and amplitude. In fact, we showed that given any outbreak, and given any value greater than one for the basic reproduction, there is an SIR solution with the same mean and standard deviation as the outbreak's. We further demonstrated how this result can be extended to more complex multi-compartment epidemic models. Moreover, we provided indistinguishable fits to real epidemic data with extremely different parameter choices. This insensitivity of fit quality to parameter choices means that traditional curve-fitting cannot reliably infer the key outbreak parameters from case data alone. Taken together, our results highlight fundamental limits on estimating epidemic parameters from incidence data, i.e., the rate of new cases, or from prevalence data, i.e., the number of infected people at a given time.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 4","pages":"913-939"},"PeriodicalIF":2.6,"publicationDate":"2026-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147647180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of insecticides on bee ecosystems: A mathematical approach using piecewise smooth dynamical systems.","authors":"Carlos Andrés Trujillo-Salazar, Oscar Emilio Molina-Díaz","doi":"10.3934/mbe.2026035","DOIUrl":"10.3934/mbe.2026035","url":null,"abstract":"<p><p>Honey bees (<i>Apis mellifera</i>) are key pollinators in agroecological systems and are crucial to ensuring global food security. However, apiculture is currently facing a crisis due to the proliferation of pests and diseases, with the ectoparasitic mite <i>Varroa destructor</i> posing the most significant threat. By feeding on the hemolymph of honey bees, this mite reduces their lifespan and acts as a vector for lethal viruses, potentially leading to the collapse of the entire beekeeping ecosystem. In this context, we propose a novel mathematical model based on a nonlinear system of ordinary differential equations to describe the interaction between the honey bee population and the <i>Varroa destructor</i> mite population, along with the temporal evolution of honey production. The model identifies the equilibrium states and examines their biological feasibility and stability in relation to key ecological thresholds. Numerical simulations are then conducted to illustrate the system's dynamics and to interpret, from an agroecological perspective, the impact of chemical control applied to crops situated in close proximity to the beekeeping environment. Subsequently, a switching mechanism is incorporated into the mite population equation, transforming the system in a piecewise smooth model. This mechanism activates or deactivates chemical control, depending on whether the ratio of mites to bees exceeds a predefined critical threshold. This approach captures the abrupt transitions induced by technical monitoring in apicultural practice, providing a more realistic framework for representing discontinuous control strategies. This work thus enables the evaluation of the differential impact of chemical pressure arising from neighboring crops and from targeted mite control, demonstrating, within the framework of ecological theory, how such interventions influence a population's viability and the long-term sustainability of the apicultural ecosystem.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 4","pages":"884-912"},"PeriodicalIF":2.6,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147647175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Darwinian dynamics of Host-Pathogen interactions.","authors":"Anuraag Bukkuri, Sabrina Streipert, Yun Kang","doi":"10.3934/mbe.2026034","DOIUrl":"10.3934/mbe.2026034","url":null,"abstract":"<p><p>Epizootic hemorrhagic disease (EHD) causes varied clinical outcomes across ruminants and geographical locations. Northern white-tailed deer experience infrequent, high-mortality outbreaks; southern white-tailed deer experience seasonal, lower-mortality infections; and African cattle experience endemic, subclinical infections. These observations provide a natural setting to explore how environmental exposure impacts the evolution of host defense strategies. In this paper, we develop a Darwinian pathogen-epidemic model that couples host-pathogen population dynamics with the evolution of resistance (recovery from pathogen) and tolerance (minimizing the effects of infection) traits. We obtain the basic reproduction number $ mathcal{R}_0 $ and show that the unique disease-free equilibrium is locally asymptotically stable if $ mathcal{R}_0 < 1 $ and unstable if $ mathcal{R}_0 > 1 $, consistent with the corresponding purely ecological model. However, we also identify key differences between the models, as the evolution of traits can have a stabilizing effect and may promote bistability. Numerical simulations reveal that high pathogen burden and transmission favor the evolution of tolerance, whereas low pathogen burden promotes the evolution of resistance. Host-intrinsic factors, such as natural death rates and density-dependent suppression of growth, lead to resistance evolution, whereas high host reproductive rates lead to tolerance. Applying our model to EHD shows that intermittent exposure in northern deer leads to no evolved defense, seasonal exposure in southern deer results in the evolution of resistance, and endemic exposure in African cattle selects for tolerance. Furthermore, we demonstrate that continuous vs. periodic control of the disease vector population can lead to the evolution of different defense mechanisms. These findings highlight how environmental and host-pathogen factors shape the evolution of defense strategies, thereby informing disease management and control in wildlife and livestock populations affected by pathogens, such as the EHD virus.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 4","pages":"845-883"},"PeriodicalIF":2.6,"publicationDate":"2026-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147647149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A deep learning and metaheuristic optimization algorithm based on Parkinson's disease classification from MRI images.","authors":"V Balamurugan, K Sivasankari","doi":"10.3934/mbe.2026033","DOIUrl":"10.3934/mbe.2026033","url":null,"abstract":"<p><p>Parkinson's disease (PD) is the second most common neurodegenerative disorder, characterized by the gradual deterioration of dopamine-producing neurons. The main challenge of diagnosing this disease is that physical changes in the brain begin before the patient shows outward symptoms. This leads to the necessity of developing early methods for the detection of this disease. Therefore, with the proposed model, we aimed to significantly improve the early classification of PD using MRI scans by capitalizing on advanced Artificial Intelligence (AI) and Deep Learning (DL) techniques. Our goal of the proposed model was to develop a robust medical decision-support system that enhances the diagnostic precision and supports prompt clinical intervention strategies. The method proposed was a modified EfficientNet DL model combined with the reinforcement learning optimization. This approach enabled a dynamic adjustment of model parameters to effectively minimize the misclassification rates while differentiating MRI scans of PD patients and healthy individuals. Certain performance metrics were used to calculate the performance of the proposed detection model. The results showed that the research achieved high precision, recall, and F1-score values with 98% accuracy for both classes. In the patients (class 0), the precision rate was 95%, the recall rate was 96%, and the F1-score was 98%. Similarly, for healthy individuals (class 1), the precision rate was 93%, the recall rate was 97%, and the F1-Score was 96%. Thus, the proposed EfficientNet model revealed significant enhancements in the diagnostic performance compared to the standard methods. The innovations outlined in this study emphasize the transformative power of AI in enhancing diagnostic predictions. Moreover, the convergence of a DL based EfficientNet model and reinforcement learning based metaheuristic optimization establishes a prospective implementation of predictive analytics in managing high-risk PD with the defined objective of optimizing the patient outcomes within the field of neurology.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"23 4","pages":"813-844"},"PeriodicalIF":2.6,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147647146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}