Communication in Biomathematical Sciences

A fractional optimal control model of electoral behavior in a multi-party democracy

2025-04-08T16:32:43+07:00

Political participation is a cornerstone that enables citizens to shape their nation’s political
system in every democratic environment. Registering on electoral lists, joining the political party
of choice, and voting during the election collectively contribute to the selection of representatives
for political positions. In the current work, we propose a fractional optimal control strategy for
an awareness program aimed at increasing the number of registered voters who vote during the
election. To accurately capture a number of desirable qualities such as non-locality and nonsingularity in the kernel, we employ the Atangana-Baleanu derivative. In addition, the existence
and uniqueness of the solutions of the model are established. The political party reproduction
number is also achieved. The stability of the model is demonstrated through the Hyers-Ulam
stability criteria. The model is validated using empirical data from the 2020 Ghana presidential
elections. We considered controls: the awareness campaign effort– this control represents the
resources dedicated to motivate registered voters to join the political party P1 and cast their votes
during an election; the persuasion effort– this control measures the effort required to persuade
registered voters to change their allegiance to party P2 and participate in the election; and the
electoral campaign effort– this control focuses on convincing non-participating registered voters
to support a political party by joining and voting during an election. Our findings indicate that
implementing all three control measures is crucial to increasing voter participation in elections.
This multifaceted approach will not only increase the participation rate, but will also have a
significant political impact. Again, this will help reduce the number of registered voters who do
not cast their ballots, making the elections more representative and inclusive. By focusing on
these three control areas, we can address the underlying issues that lead to low voter turnout.

Modelling the Transmission Dynamics of Malaria in Human and Non-human Hosts

2025-04-01T15:17:15+07:00

Malaria has been a global health menace for long, affecting mainly countries in Asia and Africa, especially the Sub-Saharan Africa. Recent investigations indicate that malaria can also affect non-human primates, which poses a threat to the current efforts towards eradicating malaria. With this new development, a continuous resurgence of the disease is possible if not contained in non-human primates. This work therefore aims at modelling the transmission dynamics of malaria incorporating non-human population hitherto not adequately addressed. A compartmental model consisting of ten compartments is formulated. The basic reproduction number is determined using the next generation matrix approach. The local and global stability analysis of the malaria-free equilibrium as well as the numerical simulations of the model equations are carried out. The results show that the malaria-free equilibrium is conditionally locally asymptotically stable for $R_{0hav}<1$, indicating that the disease can be contained subject to fulfilling the stated conditions. The results of the theoretical analysis also shows that the malaria-free equilibrium state is also globally asymptotically stable when $R_{0hav}<1$. Numerical results indicate that even in the absence of malaria in the human population, the disease still persists in the vector and non-human animal populations. The implications of the results of this research are that managing malaria in human population alone cannot lead to the eradication of the disease, hence the scope of treatment and other control strategies must be extended to non-human primates. Eliminating the malaria causing vectors remains the best strategy towards eradicating malaria in endemic regions.

The Optimal Control Analysis of Insecticide Susceptibility Status on Anopheles-gambiae Mosquitoes and the Community Knowledge on Malaria in Nigeria

2025-03-23T12:36:58+07:00

This study investigates the insecticide susceptibility status of Anopheles gambiae mosquitoes in Nigeria, and assesses community knowledge on malaria prevention and control. Using optimal control analysis, which subdivides the model into seven (7) compartments, aims to understand the dynamics of mosquito resistance and its implications for malaria transmission. The findings show that combining three control strategies combats malaria more effectively than applying a single control. Furthermore, the study employed a mathematical model to examine the resistance patterns of Anopheles gambiae mosquitoes to commonly used insecticides and evaluated the community's awareness and practices related to malaria prevention. By incorporating control techniques into the model equations, the paper identifies malathion, propoxur, and permethrin as key interventions that could enhance the effectiveness of existing malaria control techniques. Finally, the findings suggest the need to modify insecticide tactics and improve educational initiatives in order to combat the spread of malaria in Nigeria

Exploring the Squared XLindley Distribution: Improved Statistical Modeling and Estimation Methods with Application to the Ebola Dataset

2025-03-04T18:50:51+07:00

This paper presents the Squared XLindley (SXL) distribution, which serves as an extension of the XLindley distribution. Several essential statistical characteristics of the proposed distribution were identified and rigorously analyzed through comprehensive analytical techniques. The fuzzy reliability of the SXL model was systematically assessed using statistical methods, confirming its robustness and precision.
Various estimation techniques were proposed to accurately ascertain the parameters of the model, demonstrating its adaptability. The dynamics of these parameters were extensively investigated using data sets generated randomly along with the employed estimation techniques, yielding profound insights into the performance of the model across diverse scenarios.
Moreover, the SXL model was utilized in the analysis of the Ebola data set. The findings revealed the model’s superior performance relative to the fundamental XLindley model and several others well-established related distributions, highlighting its practical relevance and effectiveness in analyzing real-world data. This
research emphasizes the SXL distribution’s potential utility as a significant instrument in statistical modeling and analysis