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Communication in Biomathematical Sciences
Published by Indonesian Biomathematical Society
ISSN : -     EISSN : 25492896     DOI : 10.5614/cbms
Core Subject : Social,
Social Sciences
Full research articles in the area of Applications of Mathematics in biological processes and phenomena
Arjuna Subject : Matematika - Matematika Terapan
Articles 131 Documents
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A Novel Mathematical Model for Overweight, Obesity, and Their Impact on Diabetes and Hypertension Delgado Moya, Erick Manuel; Rodriguez, Ranses Alfonso; Pietrus, Alain; Bernard, Severine
Communication in Biomathematical Sciences Vol. 8 No. 2 (2025)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2025.8.2.5

Abstract

In this paper, we present a new mathematical model describing the dynamics of overweight and obesity and their impact on diabetes and hypertension. In constructing the model, we consider negative and positive interactions among individuals with normal weight, overweight, and obesity, as well as social factors influencing overweight and hypertension diagnoses. As a novel contribution to transmission dynamics, we interpret the basic reproduction number from two perspectives: negative and positive interactions. Focusing on parameters linked to social factors and their health impact, we present theoretical results characterizing their influence on the basic reproduction number and compute corresponding sensitivity indices. Additionally, we perform a global sensitivity analysis of model parameters using first- and total-order Sobol’ indices with various methods and sampling techniques, concluding that parameters associated with social factors are among the most influential. We conduct computational simulations of the basic reproduction number and model’s compartments to examine the influence of social-factor parameters on overweight and hypertension. Our findings indicate the need to explore strategies to prevent the rise of overweight, obesity, and diabetes in the population. Social factors associated with overweight and hypertension diagnosis have a substantial impact on the progression of these dynamics. Recognizing this influence enables the identification of the most vulnerable groups and the design of more precise and effective interventions.
Mathematical Modelling of Carbon Dioxide Emissions in Agricultural Systems Mor, Ashish; Das, Kalyan; Srinivas, M.N.
Communication in Biomathematical Sciences Vol. 8 No. 2 (2025)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2025.8.2.2

Abstract

This study formulates a dynamic mathematical model to investigate the interplay between human activities and CO2 emissions within the context of agriculture. The model incorporates a system of differential equations describing the interactions among human population growth (H1), human economic activities (H2), atmospheric CO2 concentration (H3), forest biomass density (H4), and vehicle population (H5). Key processes include the effects of deforestation, economic activities, and vehicle emissions on CO2 levels, as well as the mitigating role of forest biomass.The model parameters account for natural growth rates, carrying capacities, and interaction coefficients that represent both the exacerbation and alleviation of CO2 emissions. The delay parameter τ captures the temporal lag in the effects of population growth and deforestation. This framework aims to provide insights into the dynamic interactions and feedback loops influencing CO2 emissions, with a particular emphasis on sustainable practices and policies to mitigate environmental degradation in agricultural contexts.
Modeling COVID-19 Dynamics with a Medical Treatment Strategy: A Case Study of Thailand Chen, Yinghui; Modnak, Chairat
Communication in Biomathematical Sciences Vol. 8 No. 2 (2025)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2025.8.2.6

Abstract

Since 2020, Thailand has been impacted by the COVID-19 pandemic, which continues to persist into 2025. In response, the country has implemented various disease control measures, including public health campaigns and vaccination programs. While these strategies are still in place, they are now applied with less intensity, allowing people to return to a more normal way of life. However, this relaxed approach can contribute to continued disease transmission. In this study, we shift focus from conventional control measures-such as vaccination, mask-wearing, and social distancing-to strategies aimed at coexisting with the disease while minimizing its spread. Specifically, we investigate the impact of treating symptomatic and severe patients to reduce their infectiousness and thereby lower the risk of transmission to others. To achieve this, we develop a mathematical model of COVID-19 transmission dynamics and apply it using Thailand's 2025 data. We analyze the stability of both the disease-free and endemic equilibrium points and explore an optimal control problem related to medical treatment strategies. Our findings suggest that reducing the infectiousness of symptomatic and severe cases through effective treatment can help slow down the spread of COVID-19, supporting safer coexistence in a society returning to normalcy.
A Fractional SIR Model for Hepatitis A Virus: Lyapunov Stability and Effects of Awareness and Vaccination Safi, Burhanuddin; Das, Agniva; Hasmani, A.H.
Communication in Biomathematical Sciences Vol. 8 No. 2 (2025)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2025.8.2.4

Abstract

Although Hepatitis A Virus (HAV) causes non-chronic infection, it poses serious health threats, particularly among children and older individuals due to poor sanitation and weak immunity. To better capture the memory-dependent progression of HAV, a novel SIR-type epidemic model is developed using Caputo fractional derivatives. The model incorporates awareness campaigns and a precautionary vaccination strategy represented by a Holling type-II functional response. We analytically established positivity, boundedness, and both local and global stability of equilibrium points using Jacobian matrices and Lyapunov functions are presented. Realworld data from the United States are used to estimate possible parameters through mean absolute error (MAE) minimization. Additionally, numerical simulations were perforemd to support the qualitative results revealing that fractional-order dynamics offer more accurate and realistic forecasts compared to classical integer-order models. Moreover, sensitivity analysis further identified the infection rate and recruitment rate as dominant drivers of HAV spread. Overall, the findings confirm that combining awareness and vaccination substantially reduces the infection levels and that fractional modelling provides critical advantages in disease forecasting and control planning.
Erratum: Assessing the Impact of Medical Treatment and Fumigation on the Superinfection of Malaria: A Study of Sensitivity Analysis Bevina D. Handari; Dipo Aldila; Evllyn Tamalia; Sarbaz H.A. Khoshnaw; Muhammad Shahzad
Communication in Biomathematical Sciences Vol. 8 No. 2 (2025)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2025.8.2.8

Abstract

This erratum has been issued to correct an error in the Acknowledgement section of our previously published article (COMMUN. BIOMATH. SCI., VOL. 6, NO. 1, PP. 51-73, 2023). The research grant number was incorrectly stated due to a typographical mistake during manuscript preparation. The correct research grant number should read as indicated in this erratum. The authors apologize for this oversight and confirm that the correction does not affect the scientific content, results, or conclusions of the original article.
Persistence and Extinction Dynamics in a Stochastic Predator-Prey Model with Emergent Allee Effects Carlos Granados; Leon A. Valencia
Communication in Biomathematical Sciences Vol. 9 No. 1 (2026)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2026.9.1.3

Abstract

The Allee effect describes a decline in population fitness at low densities, potentially leading to extinction. In predator-prey systems, an emergent Allee effect can arise due to interactions such as density-dependent maturation rates and predation constraints. This work studies a stochastic predator-prey model where the prey population is structured into juvenile and adult stages, with maturation following a nonlinear function. We introduce It.-type stochastic perturbations in mortality rates to account for environmental variability. We first establish the positivity of solutions and derive sufficient conditions for the stability of the trivial equilibrium, prey extinction, and conditional predator extinction. We then analyze prey persistence under specific maturation rate functions. Finally, numerical simulations illustrate the theoretical results and their ecological implications.
Dynamical Analysis of Mpox Transmission Model Incorporating Asymptomatic Individuals Tuhfatul Janan; Fatmawati; Agus Hasan
Communication in Biomathematical Sciences Vol. 9 No. 1 (2026)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2026.9.1.4

Abstract

In this paper, we develop a mathematical model for the transmission dynamics of monkeypox (Mpox) involving both human and rodent populations, with the human population including asymptomatic individuals. The analysis begins by establishing the well-posedness of the model using the contraction mapping principle, ensuring the existence, uniqueness, and stability of the solution. The model is further examined for the boundedness and non-negativity of the solutions. Three equilibrium points are identified: the disease-free equilibrium, the human-endemic equilibrium, and the endemic equilibrium. The disease-free equilibrium is shown to be both locally and globally asymptotically stable when the basic reproduction number is less than one. If they exist, the human-endemic equilibrium is proven to be globally asymptotically stable when the basic reproduction number of the rodent population is less than one, and the endemic equilibrium is always globally asymptotically stable. The sensitivity analysis indicates that vaccination and contact dynamics are the most influential factors in human transmission, while rodent transmission is primarily shaped by contact rates and mortality-related factors. Numerical simulations are provided to illustrate and validate the analytical results.
A Mathematical Model for Competition Between Local and Invasive Fish in Lake Poso, Indonesia Tokonyai Tawanda Jonathan Rabvemhiri; Hajar; Juni Wijayanti Puspita; Dipo Aldila
Communication in Biomathematical Sciences Vol. 9 No. 1 (2026)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2026.9.1.6

Abstract

The introduction of Nile Tilapia into Lake Poso has created both ecological and economic challenges, particularly in its interaction with the endemic species Oryzias nigrimas. To understand the potential longterm impacts of this competition and the community’s economic use of Nile Tilapia, we introduced a novel mathematical model describing their population dynamics. The model is formulated as a four-dimension ordinary differential equations and analyzed for the positivity of solutions, existence and local stability of equilibrium points, and the influence of harvesting strategies. Numerical simulations, including bifurcation and time-series analyses, are conducted to assess the effects of constant and periodic harvesting of Nile Tilapia. The findings suggest that periodic harvesting can play a significant role in maintaining population balance and mitigating the ecological pressure on Oryzias nigrimas, offering insights for sustainable management of invasive fish in Lake Poso.
Dynamic Behavior of Caputo Fractional-Order Model of Forest Biomass, Human Population, and Atmospheric Carbon Dioxide Moh. Nurul Huda; Agus Suryanto; Isnani Darti; Muhammad Fakhruddin
Communication in Biomathematical Sciences Vol. 9 No. 1 (2026)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2026.9.1.2

Abstract

This study aims to analyze the dynamical model of CO2 concentration, human population, and forest biomass. Human activities and land-use changes in forested areas play an important role as the primary contributors to the increase in CO2 emissions, which drive global warming. The inclusion of fractionalorder derivatives is considered to examine the long-term memory effects on the interactions within the CO2 concentration model. Theoretical results such as the existence, uniqueness, positivity, and boundedness of solutions, the local and global stability behavior of equilibrium points, and the existence of a Hopf bifurcation are explored. Furthermore, key parameters, including the deforestation rate and memory order, are investigated to determine their influence on the solution behavior of the CO2 concentration model. A fractionalorder numerical scheme is employed to illustrate various scenarios, validating the theoretical findings. The results show that fractional-order changes affect the dynamic behavior of the model. In addition, increased deforestation rates can increase CO2 concentrations and reduce human population in the long term.
Optimizing Weekly-Period Cyclical Lockdown Policies: A Simulation Study Using the A-SIR Model Arief Anbiya; Benny Yong
Communication in Biomathematical Sciences Vol. 9 No. 1 (2026)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2026.9.1.7

Abstract

This paper presents numerical simulations of COVID-19 cyclical lockdown scenario in which there is an alternating short phase between working days and lockdown days with weekly period. We use an adaptive SIR model with daily varying infection and recovery rates. The model is fitted with United States COVID-19 data. The rates for the model-fitting are obtained using the Method of Variational Imbedding (MVI) and fixed-point iteration that depend on actual COVID-19 data. Subsequently, we use the adaptive model to simulate cyclical lockdown of W working days (normal state) and L lockdown days with weekly cycle W +L = 7. To model the cyclical lockdown scenario, we multiply the infection rate by a piecewise continuous damping function that has value either 1 (when no lockdown is implemented) or 0.175 (when short lockdown is implemented). The numerical simulation shows that allowing up to 5 working days per week can flatten the curve of active cases. We also compare the model for cyclical lockdown scenario against the model for prolonged and continuous lockdown scenario: the simulation of prolonged continuous lockdown without allowing a short period of normal state result in smaller final epidemic size. However, as the number of lockdown L gets higher, the cyclical lockdown seems to converge to the prolonged continuous lockdown. Our result shows that using cyclical lockdown with L = 4 lockdown days per week for 177 weeks, which means 708 days of lockdown, gives total incidence (final epidemic size) of 4.311% (as a percentage of initial susceptible population S(0)), while using prolonged continuous lockdown for 708 consecutive days results in total incidence of 3.111%. Although the latter has smaller total incidence, the difference is not significant, which suggests that we can trade it for social and economic advantages that cyclical lockdown offers.

Page 13 of 14 | Total Record : 131

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