Mathematical Biosciences最新文献

{"title":"A new method for the estimation of stochastic epidemic descriptors reinforced by Kalman-based dynamic parameter estimation. Application to mpox data","authors":"Vasileios E. Papageorgiou ,&nbsp;Georgios Vasiliadis ,&nbsp;George Tsaklidis","doi":"10.1016/j.mbs.2024.109365","DOIUrl":"10.1016/j.mbs.2024.109365","url":null,"abstract":"<div><div>In the realm of epidemiology, it is essential to accurately assess epidemic phenomena through the adoption of innovative techniques that yield reliable predictions. This article introduces an advanced method that merges the Extended Kalman Filter approach with recursive algorithms to compute critical stochastic attributes important for evaluating epidemics. A new three-dimensional discrete Markov chain is presented, according to which the total number of infections, deaths, and the duration of epidemic outbreaks are estimated. This approach represents a notable improvement over the standard estimation procedure, which relies on Markov-based stochastic models with fixed parameters. Furthermore, it constitutes a real-time estimation process, as opposed to the standard method, which is more suitable for offline applications. The proposed methodology marks an original attempt to integrate computational techniques for modeling stochastic epidemic characteristics with dynamic parameter estimation procedures. An additional advantage is the reduction of noise in the system's states enhancing the overall precision. The method's performance is thoroughly assessed through 3 simulated epidemic instances. Furthermore, its application to the actual 2022 monkeypox (mpox) data from the Czech Republic demonstrates promising effectiveness. In comparison to the standard methodology, our approach yields estimates with deviations of only 4.383 weeks, 3.542 infections, and 0.266 deaths, as opposed to the standard method where we observe deviations of 15.372 weeks, 5.786 infections, and 0.501 deaths. Overall, the proposed estimation procedure proves to be a valuable tool for investigating epidemic phenomena characterized by fluctuating dynamics, potentially providing valuable insights for addressing the associated public health challenges.</div></div><div><h3>MSC</h3><div>62M20, 60J22, 65C40, 62G30, 62P10</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"381 ","pages":"Article 109365"},"PeriodicalIF":1.9,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142823039","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}

{"title":"A spatiotemporal model for the effects of toxicants on the competitive dynamics of aquatic species","authors":"Xiumei Deng ,&nbsp;Qihua Huang ,&nbsp;Zhi-An Wang","doi":"10.1016/j.mbs.2024.109341","DOIUrl":"10.1016/j.mbs.2024.109341","url":null,"abstract":"<div><div>In this paper, we develop a reaction–diffusion model with negative toxicant–taxis that incorporates spatiotemporally inhomogeneous toxicant input to investigate the impact of toxicants on the competitive dynamics of two species in a polluted aquatic environment. Here the negative toxicant–taxis models the evasive movement of avoiding toxicants by species. We establish the global well-posedness of the model, analyze the existence and stability of spatially homogeneous steady states, and derive sufficient conditions for species extinction and coexistence. Through linear stability analysis, we identify sufficient conditions on model parameters that destabilize spatially homogeneous steady states under spatiotemporally uniform toxicant input. Numerical experiments reveal the influence of key toxicant-related factors (input rate, taxis intensity, and diffusivity) on competition outcomes and species distributions. Notably, strong negative toxicant–taxis can induce spatial aggregation and segregation patterns between the species and the toxicant under uniform toxicant input. Our findings suggest that toxicant–taxis may promote population persistence and coexistence, particularly when the toxicant input is not uniform in space and time and the toxicant does not diffuse fast (i.e. weak diffusivity). However, strong toxicant diffusion can diminish the impact of taxis, adversely affecting population persistence and species coexistence.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"379 ","pages":"Article 109341"},"PeriodicalIF":1.9,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142718113","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}

{"title":"Spatio-temporal model of combining chemotherapy with senolytic treatment in lung cancer","authors":"Teddy Lazebnik ,&nbsp;Avner Friedman","doi":"10.1016/j.mbs.2024.109342","DOIUrl":"10.1016/j.mbs.2024.109342","url":null,"abstract":"<div><div>Senescent cells are cells that stop dividing but sustain viability. Cellular senescence is the hallmark of aging, but senescence also appears in cancer, triggered by cells stress, tumor suppression of gene activation, and oncogene activity. In lung cancer, senescent cancer cells secrete VEGF, which initiates a process of angiogenesis, enabling the cancer to grow and proliferate. Chemotherapy kills cancer cells, but some cancer cells become senescent. Hence, a senolytic drug, a drug that eliminates senescent cells, should significantly improve the efficacy of chemotherapy. In this paper, we developed a mathematical spatio-temporal model of combination chemotherapy with senolytic drug in treatment of lung cancer. Model’s simulations of tumor volume growth are shown to agree with mouse experiments in the case where cyclophosphamide is combined with the senolytic drug fisetin. It is then shown how the model can be used to assess the benefits of treatments with different combinations and different schedules of the two drugs in order to achieve optimal tumor volume reduction.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"379 ","pages":"Article 109342"},"PeriodicalIF":1.9,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142718115","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}

{"title":"A theory for viral rebound after antiviral treatment: A study case for SARS-CoV-2","authors":"Mara Perez ,&nbsp;Marcelo Actis ,&nbsp;Ignacio Sanchez ,&nbsp;Esteban A. Hernandez-Vargas ,&nbsp;Alejandro H. González","doi":"10.1016/j.mbs.2024.109339","DOIUrl":"10.1016/j.mbs.2024.109339","url":null,"abstract":"<div><div>A fraction of individuals infected with SARS-CoV-2 experienced rebounds when treated with effective antivirals such as Nirmatrelvir/Ritonavir (Paxlovid). Although this phenomenon has been studied from biological and statistical perspectives, the underlying dynamical mechanism is not yet fully understood. In this work, we characterize the dynamic behavior of a target-cell model to explain post-treatment rebounds from the perspective of set-theoretic stability analysis. Without relying on the effects of the adaptive immune system or the resistance through viral mutations, we develop mathematical conditions for antiviral treatments to avoid viral rebound. Simulation results illustrate the critical role of dosage (i.e., the doses and timing of administration) in taking advantage of highly effective drugs and tailoring therapies.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"379 ","pages":"Article 109339"},"PeriodicalIF":1.9,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142693996","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}

{"title":"Green behavior propagation analysis based on statistical theory and intelligent algorithm in data-driven environment","authors":"Linhe Zhu ,&nbsp;Yi Ding ,&nbsp;Shuling Shen","doi":"10.1016/j.mbs.2024.109340","DOIUrl":"10.1016/j.mbs.2024.109340","url":null,"abstract":"<div><div>The correlation between green behavior and energy efficiency is growing due to the heightened focus on energy efficiency among individuals. This paper introduces a three-layer network model to analyze the relationships among information diffusion, awareness and green behavior spreading. We have analyzed the probability tree of state transfer across 12 states by using Microscopic Markov Chain Approach (MMCA) and derived the state transfer equations for each state to compute the state transition threshold. In addition, we use the reaction–diffusion system to model the interaction between space and time changes for each state in the green behavior propagation layer. The equilibrium point of the system is defined, and the criteria for Turing bifurcation are identified. The optimal control approach achieves parameter identification, and this study validates the theory through several numerical simulations. Meanwhile, the effectiveness of parameter identification based on the convolutional neural network (CNN) and optimal control is compared. The data on China’s electrical energy generation is predicted and compared by using three neural networks and an autoregressive integrated moving average (ARIMA) model. Further, considering clean energy generation as a green behavior, we fit the data on the percentage of clean energy generation by applying a Microscopic Markov Chain model and a reaction–diffusion system.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"379 ","pages":"Article 109340"},"PeriodicalIF":1.9,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142690159","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}

{"title":"A Parrondo paradox in susceptible-infectious-susceptible dynamics over periodic temporal networks","authors":"Maisha Islam Sejunti ,&nbsp;Dane Taylor ,&nbsp;Naoki Masuda","doi":"10.1016/j.mbs.2024.109336","DOIUrl":"10.1016/j.mbs.2024.109336","url":null,"abstract":"<div><div>Many social and biological networks periodically change over time with daily, weekly, and other cycles. Thus motivated, we formulate and analyze susceptible-infectious-susceptible (SIS) epidemic models over temporal networks with periodic schedules. More specifically, we assume that the temporal network consists of a cycle of alternately used static networks, each with a given duration. We observe a phenomenon in which two static networks are individually above the epidemic threshold but the alternating network composed of them renders the dynamics below the epidemic threshold, which we refer to as a Parrondo paradox for epidemics. We find that network structure plays an important role in shaping this phenomenon, and we study its dependence on the connectivity between and number of subpopulations in the network. We associate such paradoxical behavior with anti-phase oscillatory dynamics of the number of infectious individuals in different subpopulations.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"378 ","pages":"Article 109336"},"PeriodicalIF":1.9,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142635463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling the interplay between disease spread, behaviors, and disease perception with a data-driven approach","authors":"Alessandro De Gaetano ,&nbsp;Alain Barrat ,&nbsp;Daniela Paolotti","doi":"10.1016/j.mbs.2024.109337","DOIUrl":"10.1016/j.mbs.2024.109337","url":null,"abstract":"<div><div>Individuals’ perceptions of disease influence their adherence to preventive measures, shaping the dynamics of disease spread. Despite extensive research on the interaction between disease spread, human behaviors, and interventions, few models have incorporated real-world behavioral data on disease perception, limiting their applicability. In this study, we propose an approach to integrate survey data on contact patterns and disease perception into a data-driven compartmental model, by hypothesizing that perceived severity is a determinant of behavioral change. We explore scenarios involving a competition between a COVID-19 wave and a vaccination campaign, where individuals’ behaviors vary based on their perceived severity of the disease. Results indicate that behavioral heterogeneities influenced by perceived severity affect epidemic dynamics, in a way depending on the interplay between two contrasting effects. On the one hand, longer adherence to protective measures by groups with high perceived severity provides greater protection to vulnerable individuals, while premature relaxation of behaviors by low perceived severity groups facilitates virus spread. Differences in behavior across different population groups may impact strongly the epidemiological curves, with a transition from a scenario with two successive epidemic peaks to one with only one (higher) peak and overall more numerous severe outcomes and deaths. The specific modeling choices for how perceived severity modulates behavior parameters do not strongly impact the model’s outcomes. Moreover, the study of several simplified models indicate that the observed phenomenology depends on the combination of data describing age-stratified contact patterns and of the feedback loop between disease perception and behavior, while it is robust with respect to the lack of precise information on the distribution of perceived severity in the population. Sensitivity analyses confirm the robustness of our findings, emphasizing the consistent impact of behavioral heterogeneities across various scenarios. Our study underscores the importance of integrating risk perception into infectious disease transmission models and gives hints on the type of data that further extensive data collection should target to enhance model accuracy and relevance.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"378 ","pages":"Article 109337"},"PeriodicalIF":1.9,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142607445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Existence and stability criteria for global synchrony and for synchrony in two alternating clusters of pulse-coupled oscillators updated to include conduction delays","authors":"Ananth Vedururu Srinivas,&nbsp;Carmen C. Canavier","doi":"10.1016/j.mbs.2024.109335","DOIUrl":"10.1016/j.mbs.2024.109335","url":null,"abstract":"<div><div>Phase Response Curves (PRCs) have been useful in determining and analyzing various phase-locking modes in networks of oscillators under pulse-coupling assumptions, as reviewed in Mathematical Biosciences, 226:77–96, 2010. Here, we update that review to include progress since 2010 on pulse coupled oscillators with conduction delays. We then present original results that extend the derivation of the criteria for stability of global synchrony in networks of pulse-coupled oscillators to include conduction delays. We also incorporate conduction delays to extend previous studies that showed how an alternating firing pattern between two synchronized clusters could enforce within-cluster synchrony, even for clusters unable to synchronize themselves in isolation. To obtain these results, we used self-connected neurons to represent clusters. These results greatly extend the applicability of the stability analyses to networks of pulse-coupled oscillators since conduction delays are ubiquitous and strongly impact the stability of synchrony. Although these analyses only strictly apply to identical oscillators with identical connections to other oscillators, the principles are general and suggest how to promote or impede synchrony in physiological networks of neurons, for example. Heterogeneity can be interpreted as a form of frozen noise, and approximate synchrony can be sustained despite heterogeneity. The pulse-coupled oscillator model can not only be used to describe biological neuronal networks but also cardiac pacemakers, lasers, fireflies, artificial neural networks, social self-organization, and wireless sensor networks.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"378 ","pages":"Article 109335"},"PeriodicalIF":1.9,"publicationDate":"2024-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142570795","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}

{"title":"Two-step global sensitivity analysis of a non-local integro-differential model for Cancer-on-Chip experiments","authors":"Elio Campanile ,&nbsp;Annachiara Colombi ,&nbsp;Gabriella Bretti","doi":"10.1016/j.mbs.2024.109330","DOIUrl":"10.1016/j.mbs.2024.109330","url":null,"abstract":"<div><div>The present work focuses on a non-local integro-differential model reproducing Cancer-on-chip experiments where tumor cells, treated with chemotherapy drugs, secrete chemical signals stimulating the immune response. The reliability of the model in reproducing the phenomenon of interest is investigated through a global sensitivity analysis, rather than a local one, to have global information about the role of parameters, and by examining potential non-linear effects in greater detail. Focusing on a region in the parameter space, the effect of 13 model parameters on the <em>in silico</em> outcome is investigated by considering 11 different target outputs, properly selected to monitor the spatial distribution and the dynamics of immune cells along the period of observation. In order to cope with the large number of model parameters to be investigated and the computational cost of each numerical simulation, a two-step global sensitivity analysis is performed. First, the screening Morris method is applied to rank the effect of the 13 model parameters on each target output and it emerges that all the output targets are mainly affected by the same 6 parameters. The extended Fourier Amplitude Sensitivity Test (eFAST) method is then used to quantify the role of these 6 parameters. As a result, the proposed analysis highlights the feasibility of the considered space of parameters, and indicates that the most relevant parameters are those related to the chemical field and cell-substrate adhesion. In turn, it suggests how to possibly improve the model description as well as the calibration procedure, in order to better capture the observed phenomena and, at the same time, reduce the complexity of the simulation algorithm. On one hand, the model could be simplified by neglecting cell–cell alignment effects unless clear empirical evidences of their importance emerge. On the other hand, the best way to increase the accuracy and reliability of our model predictions would be to have experimental data/information to reduce the uncertainty of the more relevant parameters.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"378 ","pages":"Article 109330"},"PeriodicalIF":1.9,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142564636","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}

{"title":"Self-financing model for cabbage crops with pest management","authors":"Aurelien Kambeu Youmbi ,&nbsp;Suzanne Touzeau ,&nbsp;Frédéric Grognard ,&nbsp;Berge Tsanou","doi":"10.1016/j.mbs.2024.109332","DOIUrl":"10.1016/j.mbs.2024.109332","url":null,"abstract":"<div><div>Smallholder farmers rely on their farm earnings to cover operating costs and generate income. That is not an easy task because of the pests, which reduce yields and generate plant protection costs. The farm yield and plant protection depend on the budget capacity of the farmer. In this work, we want to explore conditions for a sustainable and self-financing cabbage farm. We propose then a non-linear mathematical model for cabbage crops by considering the current account of the plantation as a dynamic variable. We assume that this variable increases due to the sale of cabbages, and provides for the seedling purchase, the plant protection costs, and the grower’s income. In the first part, we analyze the model without pest management. We determine how the budget must be spent and we show the existence of a double transcritical bifurcation. We quantify the seasonal yield and income, and estimate the damage due to pest herbivory. In the second part, we analyze a slightly simplified version of our model and obtain the existence of a backward bifurcation. Furthermore, we show that botanical pesticides can be used to prevent pest spread with relatively low plant protection costs.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"378 ","pages":"Article 109332"},"PeriodicalIF":1.9,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142564563","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}