MATHEMATICAL BIOSCIENCES 发表使用数学模型提供新概念或对生物系统的新理解的工作，或可能适用于多个生物系统的方法论文章。预计论文将提出对生物科学或数学生物学具有广泛意义的重大研究发现。数学生物科学欢迎原创研究文章、信件、评论和观点。

The journal Mathematical Biosciences publishes research that uses mathematical models to provide new concepts or insights into biological systems, as well as methodological articles applicable to multiple biological systems. The journal expects submissions to present significant research findings that have broad implications for the biological sciences or mathematical biology. Mathematical Biosciences welcomes original research articles, letters, reviews, and perspectives.

《Mathematical Biosciences》期刊发表利用数学模型提供新概念或对生物系统的新理解的研究成果，以及适用于多个生物系统的方法论文章。期刊期待论文能够提出对生物科学或数学生物学具有广泛意义的重要研究发现。数学生物科学欢迎原创研究文章、信件、评论和观点。

Mathematical Biosciences

Cholera remains a major public health problem that threatens human health worldwide and its severity is continuing. In this paper, an edge-based model for cholera transmission on random networks is proposed and investigated. The model assumes that two communities share a common water source and includes three transmission routes, namely intra- and inter-community human-to-human transmission as well as water-to-human transmission. Intra-community human-to-human contacts are modeled through a random contact network, while both inter-community and water-to-human transmission are modeled through external nodes that reach each individual in the network to the same extent. The basic reproduction number and the equations of the final epidemic size are obtained. In addition, our study considers the cholera situation in Banadir, which is one of the most severely infected regions in Somalia, during the period (2019-2021). According to the geographical location, two adjacent districts are selected and our model fits well with the real data on the monthly cumulative cholera cases of these two districts during the above-mentioned period. From the perspective of network topology, cutting off high-risk contacts by supervising, isolating, quarantining and closing places with high-degree cholera-infected individuals to reduce degree heterogeneity is an effective measure to control cholera transmission. Our findings might offer some useful insights on cholera control.

Xinxin Cheng

Yi Wang

Gang Huang

Mathematical biosciences

Math Biosci

Edge-based compartmental modeling for the spread of cholera on random networks: A case study in Somalia.

The transmission dynamics of infectious diseases and human responses are intertwined, forming complex feedback loops. However, many epidemic models fail to endogenously represent human behavior change. In this study, we introduce a novel behavioral epidemic model that incorporates various behavioral phenomena into SEIR models, including risk-response dynamics, shifts in containment policies, adherence fatigue, and societal learning, alongside disease transmission dynamics. By testing our model against data from 8 countries, where extensive behavioral data were available, we simultaneously replicate death rates, mobility trends, fatigue levels, and policy changes, both in-sample and out-of-sample. Our model offers a comprehensive depiction of changes in multiple behavioral measures along with the spread of the disease. We assess the explanatory power of each model mechanism in capturing data variability. Our findings demonstrate that the comprehensive model that includes all mechanisms provides the most insightful perspective for understanding the influence of human behavior during pandemics.

Ann Osi

Navid Ghaffarzadegan

A Simultaneous Simulation of Human Behavior Dynamics and Epidemic Spread: A Multi-Country Study Amidst the COVID-19 Pandemic

人类行为动态与疫情传播的同步模拟：新冠疫情期间的多国研究

In this paper, we propose a vascular tumor growth model that combines a phase-field tumor model with a phase-field angiogenesis model. By incorporating various tumor cell species, we capture the instabilities of the tumor in the presence of evolving neovasculature. The model not only considers different dynamics of tumor cell phase conversions, movement, and pressure effects but also provides a comprehensive representation of angiogenesis, encompassing chemotaxis of endothelial cells, sprouting, anastomoses, and blood flow in capillaries. This study evaluates the impact of chemotaxis on tumor cell movement in both avascular and vascular tumor growth scenarios. The results highlight the acceleration of tumor growth when angiogenesis is stimulated. Additionally, the investigation explores various initial distances of the tumor from neighboring vessels, revealing a critical threshold distance beyond which the angiogenesis factor fails to stimulate angiogenesis, resulting in the tumor maintaining a stable state. The integration of chemotaxis into the growth model induces instabilities, leading to increased nutrient availability and faster growth for the tumor. Furthermore, the study considers anti-angiogenesis therapy as an ideal approach, assuming complete inhibition of angiogenesis from the early stages. In this scenario, the tumor persists in a steady state, adhering to the avascular size limit in the absence of neovasculature. Conversely, when considering chemotaxis, anti-angiogenesis therapy loses efficiency, enabling unrestrained tumor growth towards neighboring vessels. This work sheds light on the intricate interplay among chemotaxis, angiogenesis, and anti-angiogenesis therapy in the context of vascular tumor growth, providing valuable insights for the development of targeted treatment strategies.

Soroosh Arshadi

Ahmadreza Pishevar

Mahdi Javanbakht

Shaghayegh Haghjooy Javanmard

Chemotaxis Effects on the Vascular Tumor Growth: Phase-field Model and Simulations

化学趋化作用对血管肿瘤生长的影响：相场模型与模拟

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 process 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 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. MSC: 62M20, 60J22, 65C40, 62G30, 62P10.

Vasileios E Papageorgiou

Georgios Vasiliadis

George Tsaklidis

A new method for the estimation of stochastic epidemic descriptors reinforced by Kalman-based dynamic parameter estimation. Application to mpox data.

一种基于卡尔曼滤波动态参数估计增强的随机传染病特征估计新方法。应用于猴痘数据。

Pablo Saez

Pallavi U. Shirke

Jyoti R. Seth

Jorge Alegre-Cebollada

Abhijit Majumder

Competing elastic and viscous gradients determine directional cell migration

弹性梯度和粘性梯度的竞争决定了细胞的定向迁移

Jiangzhuo Chen

Baltazar Espinoza

Jingyuan Chou

Abba B. Gumel

Simon A. Levin

Madhav Marathe

A simple model of coupled individual behavior and its impact on epidemic dynamics

耦合个体行为的简单模型及其对流行病动态的影响

Abbreviation	Math. Biosci.
Journal Impact	1.83
Quartiles(Global)	MATHEMATICAL & COMPUTATIONAL BIOLOGY(Q3)

ISSN	0025-5564, 1879-3134
h-index	109

Publication Information	Publisher: Elsevier Inc.，Publishing cycle: Monthly，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 1967，Proportion of original research papers: 100.00%，Self Citation Rate:5.30%， Gold OA Rate: 37.61%
Average review cycle	网友分享经验：较慢,6-12周来源Elsevier官网：平均15.4周
Average recruitment ratio	网友分享经验：容易

Mathematical Biosciences

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Edge-based compartmental modeling for the spread of cholera on random networks: A case study in Somalia.

A Simultaneous Simulation of Human Behavior Dynamics and Epidemic Spread: A Multi-Country Study Amidst the COVID-19 Pandemic

Chemotaxis Effects on the Vascular Tumor Growth: Phase-field Model and Simulations

A new method for the estimation of stochastic epidemic descriptors reinforced by Kalman-based dynamic parameter estimation. Application to mpox data.

Competing elastic and viscous gradients determine directional cell migration

A Simultaneous Simulation of Human Behavior Dynamics and Epidemic Spread: A Multi-Country Study Amidst the COVID-19 Pandemic

Chemotaxis Effects on the Vascular Tumor Growth: Phase-field Model and Simulations

A new method for the estimation of stochastic epidemic descriptors reinforced by Kalman-based dynamic parameter estimation. Application to mpox data.

Competing elastic and viscous gradients determine directional cell migration

A simple model of coupled individual behavior and its impact on epidemic dynamics