https://bulletinbiomath.org/index.php/bulletinbiomath/issue/feed Bulletin of Biomathematics 2024-04-30T00:00:00+03:00 Mehmet Yavuz editor@bulletinbiomath.org Open Journal Systems <table style="font-size: 0.875rem;" cellspacing="10" cellpadding="10"> <tbody> <tr> <td valign="top" width="250"> <h3><img src="https://bulletinbiomath.org/index.php/bulletinbiomath/management/settings/undefined" alt="" /><img style="font-size: 0.875rem;" 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" alt="" /></h3> <h3><img style="font-size: 0.875rem;" src="blob:https://bulletinbiomath.org/a2714d2a-5dbf-49c2-baba-6d540d574337" alt="" /><img style="font-size: 0.875rem;" src="blob:https://bulletinbiomath.org/76c04345-fcfe-4502-b5db-52bc6e081112" alt="" /><img style="font-size: 0.875rem;" src="blob:https://bulletinbiomath.org/d337e7f0-2fb6-4e76-b927-13c244fe3ed9" alt="" />ISSN Online: 2980-1869</h3> <p> </p> <div> <div> <div> <h2>Editor-in-Chief<span style="font-size: 0.875rem;"> </span></h2> </div> </div> <p><a title="Editor in Chief" href="https://scholar.google.com.tr/citations?user=ILxNgXgAAAAJ&amp;hl=en" target="_blank" rel="noopener">Mehmet Yavuz</a>, PhD, Necmettin Erbakan University, Türkiye</p> <div> <h3><br />Publisher</h3> </div> <p><a title="Publisher" href="http://fevirgen.baun.edu.tr/" target="_blank" rel="noopener">Fırat Evirgen</a>, PhD, Balıkesir University, Türkiye</p> <p><strong><a href="https://bulletinbiomath.org/index.php/bulletinbiomath/about/editorialTeam" target="_blank" rel="noopener"><em>View the Full Editorial Board</em></a></strong></p> </div> </td> <td valign="top"> <h3>Aims and Scope</h3> <p style="text-align: justify;">The <strong><em>Bulletin of Biomathematics (BBM) </em></strong>is an international research journal, which publishes <strong>top-level original</strong> and review papers, short communications and proceedings for theoretical and application perspectives that give insight into mathematical biology and ecology processes. It covers a very wide range of topics and is of interest to mathematicians, biologists and ecologists in many areas of research.</p> <p style="text-align: justify;">The <strong>BBM</strong> mainly publishes original papers on the interface between applied mathematics, data analysis, and the application of system-oriented ideas to natural and biosciences, and on the analyses of data and mathematical models derived from real-world problems, and focuses on the innovation of theory and research methods, especially the original research results of differential equations, nonlinear dynamical systems and their intersections and applications in related fields.</p> <p style="text-align: justify;">The scope of the journal is devoted to mathematical modelling with sufficiently advanced models, and the works studying mainly the existence and stability of stationary points of ODE systems without applications are not considered. The journal is essentially functioning on the basis of topical issues representing active areas of research. The authors are invited to submit papers to the announced issues or to suggest new issues.<br /><br />The <strong>BBM</strong> publishes all research papers and reviews in the areas of mathematical modeling listed below and will continue to provide information on the latest trends and developments in this ever-expanding topic.</p> <p style="text-align: justify;">Biological topics include but are not limited to, cell and developmental biology, physiology, neurobiology, genetics and population genetics, genomics, ecology, behavioral biology, evolution, epidemiology, immunology, molecular and structural biology, biofluids, oncology, neurobiology, cell biology, biostatistics, bioinformatics, bioengineering, infectious diseases, renewable biological resource, biomechanics, cancer biology, and medicine. <br />Mathematical approaches cover a wide range of mathematical disciplines, such as dynamical systems, differential equations of integer and fractional order, nonlinear and stochastic programming, optimization theory, optimal control theory, adaptive and robust control theory with applications, operational research in life and human sciences, artificial intelligence, as well as computational approaches.</p> </td> </tr> </tbody> </table> <p> </p> https://bulletinbiomath.org/index.php/bulletinbiomath/article/view/13 Mathematical modeling for the transmission dynamics of cholera with an optimal control strategy 2023-08-22T00:27:17+03:00 Umar Tasiu Mustapha umar.tasiu@fud.edu.ng Yahaya Adamu Maigoro aymaigoro0006@gmail.com Abdullahi Yusuf yusufabdullahi@fud.edu.ng Sania Qureshi sania.qureshi@faculty.muet.edu.pk <p>Cholera is an acute diarrheal disease caused by Vibrio cholera, its prevalence occurs in almost all the continents of the world, annually there are about 1.3 to 4.0 million cases of cholera and 21,000 to 143,000 deaths worldwide. In this paper, we propose a deterministic model for the transmission dynamics of cholera to assess the impact of vaccines in decreasing the spread of cholera infection in Nigeria. Moreover, we develop an optimal control strategy, in which we consider personal hygiene a control strategy on infection class, with u(t) as the control function. The best values of the fitting parameters have been obtained using least square minimization to validate the model with the help of experimental data obtained from Nigeria. We perform sensitivity analysis to determine the key parameters that have impacts on the control of the spread of cholera infections in the population. In addition, the numerical simulation of the model reveals that the use of vaccines and personal hygiene will effectively control the spread of cholera infection.</p> 2024-04-30T00:00:00+03:00 Copyright (c) 2024 Umar Tasiu Mustapha, Yahaya Adamu Maigoro, Abdullahi Yusuf, Sania Qureshi https://bulletinbiomath.org/index.php/bulletinbiomath/article/view/14 Dynamical analysis of HIV-TB co-infection transmission model in the presence of treatment for TB 2023-09-08T14:17:13+03:00 Bolarinwa Bolaji bolarinwa.s.bolaji@gmail.com Thomas Onoja tuonoja@gmail.com Celestine Agbata abcinfotech08@gmail.com Benjamin Idoko Omede benjaminomede197@gmail.com Udoka Benedict Odionyenma oudoka@aust.edu.ng <p>The immense disease burden of tuberculosis (TB) infection is well-documented, particularly among those co-infected with HIV and TB. To better understand the transmission dynamics of HIV-TB co-infection in the absence of readily available HIV treatment, we develop a deterministic compartmental co-infection model. Our model helps to identify the effects of TB infection on the co-infection dynamics of the two diseases, especially when treatment for TB is readily available. We find that susceptibility to TB reinfection after a previous infection leads to backward bifurcation in the TB-only model when the associated reproduction number (R_0) is less than unity. However, when we make the susceptibility to TB re-infection insignificant in the model, the disease-free equilibrium of the TB-only model is locally asymptotically stable when the associated R_0 is less than unity. We conduct sensitivity and uncertainty analyses to identify the key parameters driving TB infection dynamics, using the R_0 as the response function. We discover that the transmission rate for TB, the modification parameters accounting for the infectiousness of infected individuals with TB-only, and the treatment rates for singly infected individuals with latently infected TB are the top drivers of TB infection in the given population. Our numerical simulations suggest that concentrating treatment on TB-infected individuals in the diagnosed latently infected stage (singly or dually infected with HIV) could effectively reduce the co-infection disease burden and HIV incidence in the population under study.</p> 2024-04-30T00:00:00+03:00 Copyright (c) 2024 Bolarinwa Bolaji, Thomas Onoja, Celestine Agbata, Benjamin Idoko Omede, Udoka Benedict Odionyenma https://bulletinbiomath.org/index.php/bulletinbiomath/article/view/20 The impact of the COVID-19 pandemic on education in Bangladesh and its mitigation 2023-12-16T13:11:14+03:00 Md. Kamrujjaman kamrujjaman@du.ac.bd Sadia Shihab Sinje sadiashihab41@gmail.com Tanni Rani Nandi tanni2250@gmail.com Fariha Islam farihaislam415@gmail.com Md. Atikur Rahman atik.splash@gmail.com Asma Akter Akhi akhiasma752@gmail.com Farah Tasnim ftasnim@uncc.edu Md. Shah Alam malam20@cougarnet.uh.edu <p>The global COVID-19 pandemic disrupted various facets of societal functioning, with the education sector facing unprecedented challenges. The sudden closure of schools and universities, coupled with the shift towards remote learning, created a dynamic educational environment. It significantly affected academic performance, psychological health, dropout rates, school closures, and even increased early marriage rates in Bangladesh. In 2021, the dropout rate stood at 14.15 percent. This study delves into the specific repercussions of the pandemic on the education landscape in Bangladesh. The research reveals the disparities in access to online education, shedding light on the socio-economic factors influencing digital learning engagement. Through a comprehensive analysis of quantitative and qualitative data, we explore the multifaceted effects on educational institutions, students, and educators. We present the impact of COVID-19 on education graphically using interpolation polynomials. Mitigating the impact of COVID-19 on the education sector in Bangladesh necessitates a multifaceted approach that addresses various interconnected challenges. Moreover, prioritizing mental health support for students, teachers, and parents is paramount in navigating the emotional toll of the pandemic. Collaboration and partnerships with international organizations, non-government organizations (NGOs), and private sector entities are indispensable for mobilizing resources and expertise. Bangladesh can effectively manage the pandemic's complications and ensure the continued viability of its educational system by implementing such an all-encompassing approach.</p> 2024-04-30T00:00:00+03:00 Copyright (c) 2024 Md. Kamrujjaman, Sadia Shihab Sinje, Tanni Rani Nandi, Fariha Islam, Md. Atikur Rahman, Asma Akter Akhi, Farah Tasnim, Md. Shah Alam https://bulletinbiomath.org/index.php/bulletinbiomath/article/view/22 Study of fractional order SIR model with M-H type treatment rate and its stability analysis 2024-01-26T20:37:45+03:00 Subrata Paul paulsubrata564@gmail.com Animesh Mahata animeshmahata8@gmail.com Supriya Mukherjee supriyaskbu2013@gmail.com Meghadri Das dasmeghadri@gmail.com Prakash Chandra Mali pcmali1959@gmail.com Banamali Roy banamaliroy@yahoo.co.in Poulami Mukherjee poulamimukherjee2023@gmail.com Pramodh Bharati pramodbharatinilu@gmail.com <p>In this manuscript, we analyze a fractional-order susceptible-infected-recovered (SIR) mathematical model with a nonlinear incidence rate and nonlinear treatment rate for the control of infectious illness. The incidence rate of infection is considered as Holling type II and the treatment rate is considered as Monod-Haldane (MH) type. The existence and uniqueness criteria for the new model, as well as the non-negativity and boundedness, have been established. We also provide an ideal control strategy for the SIR model using the treatment rate as a control parameter. The solution of the suggested model is approximated using the fractional-order Taylor's method. With the help of MATLAB (2018a), we perform numerical simulations and illustrate the results through graphical representations.</p> 2024-04-30T00:00:00+03:00 Copyright (c) 2024 Subrata Paul, Animesh Mahata, Supriya Mukherjee, Meghadri Das, Prakash Chandra Mali, Banamali Roy, Poulami Mukherjee, Pramodh Bharati https://bulletinbiomath.org/index.php/bulletinbiomath/article/view/23 Fractional-order brucellosis transmission model between interspecies with a saturated incidence rate 2024-03-27T14:25:55+03:00 Dilara Yapışkan dilarayapiskan@ua.pt Beyza Billur İskender Eroğlu biskender@balikesir.edu.tr <p>In this study, brucellosis dynamics between interspecies are discussed with the Atangana-Baleanu fractional derivative to examine the transmission of brucellosis by its behavior. The recovered compartment, recruitment, and natural death rate for humans are considered for the fractional order model to analyze the transmission dynamics in more detail from an epidemiological point of view. Additionally, the saturated incidence rate is suggested for brucellosis as indirectly transmitted to individuals from the environment. By fixed point theory, it is verified that developed fractional transmission dynamics have a unique solution. The model under consideration employs the Adams-type predictor-corrector method for numerical solution. All comparative results are plotted by MATLAB.</p> 2024-04-30T00:00:00+03:00 Copyright (c) 2024 Dilara Yapışkan, Beyza Billur İskender Eroğlu