Communication in Biomathematical Sciences

The effect of fear on two predator-prey pairs linked by competition

2025-08-28T21:26:37+07:00

This paper presents a mathematical model examining the dynamics of a linked predator-prey system that incorporates fear. Here each predator consumes on one prey only and the preys are in competition. Nature of predation is of Holling type II. The principal results explore various aspects, including positivity, boundedness, local and global stability of the coexistence equilibrium point, uniform persistence and Hopf bifurcation. The numerical simulations support the theoretical findings, offering practical insights into the model's behaviour.

AN APPROACH FOR CONTROLLING THE COVID-19 PANDEMIC BASED ON THE SVIHR TYPE

2025-08-25T14:16:40+07:00

COVID-19 has killed millions of people around the world. Medical professionals recommend vaccination
as a preventive measure. After administering two full doses of vaccination, the population of individuals in the
asymptomatic infected phase and the susceptible phase shifts to the population of vaccinated individuals based
on the proposed covid-19 epidemiological model with six populations. In this study a control system is also
proposed, namely maintaining social separation, good hygiene, vaccination, health testing, contact tracing, and
treatment. Numerical techniques are then used to address these issues. The results show that the probability
of transmission can be significantly reduced and can have a significant impact on reducing the infection rate
by providing optimal control.

AN APPROACH FOR CONTROLLING THE COVID-19 PANDEMIC BASED ON THE SVIHR TYPE

2025-08-25T14:11:52+07:00

Viability control of time delayed SIR models by set-valued analysis

2025-08-05T02:59:39+07:00

This paper viability controls time delayed SIR models of Kermack and McKendrick, with discrete and distributed time delays, and continuous initial conditions; under the effective reproduction constraint: for all $t\ge0$, $\exp(t)\mathcal{R}_t\le \mathcal{R}_0$, where $\exp$ is the exponential function, $\mathcal{R}_t$ is the effective Reproduction number, and $\mathcal{R}_0$ is the basic Reproduction number; and uses Contingent derivative to the subsets of viable state solutions $(S,I,R)^\top$, as tool of set-valued analysis on the differential inclusions, to characterize and express the feedback control solutions $u(t,S,I,R)$. The method covers a wide class of delayed SIR models, and stabilizes $\mathcal{R}_t$ to $0$ and $(S,I,R)^\top$ to $(0,0,1)^\top$.