article · Healthcare Analytics
A fractional-order mathematical model using Caputo derivatives evaluates the influence of high-risk quarantine and vaccination interventions on the transmission of COVID-19. Tested against real-world data, the model demonstrates the feasibility of these numerical solutions for physical epidemic scenarios. Simulations indicate that while implementing either high-risk quarantine or vaccination alone effectively lowers virus prevalence, combining both approaches yields greater effectiveness in reducing disease spread. The performance of these interventions fluctuates according to the rate of change within the system distribution. Detailed qualitative and comparative analyses with error evaluations illustrate potent methods for curbing viral transmission, offering structured pathways toward eradicating the disease without placing excessive pressure on socio-economic conditions.
Managing epidemic outbreaks requires balancing disease control measures against broader socio-economic impacts. By using real-world data and mathematical simulations, this work shows that combining vaccination with targeted quarantine for high-risk individuals offers the strongest protection against viral spread. These insights assist public health planners in evaluating intervention strategies to curb disease transmission effectively while minimising disruptions to society.
The model provides an analytical framework that could inform healthcare policy planning software and public health decision-support systems. Potential users include epidemiological analysts and public health organisations designing disease containment programmes. As an early-stage theoretical and simulation-based model validated against real-world data, it requires translation into user-facing software tools before it can see operational deployment in public health environments.
AI-generated from the published abstract. Always read the original work before citing.
The recent global Coronavirus disease (COVID-19) threat to the human race requires research on preventing its reemergence without affecting socio-economic factors. This study proposes a fractional-order mathematical model to analyze the impact of high-risk quarantine and vaccination on COVID-19 transmission. The proposed model is used to analyze real-life COVID-19 data to develop and analyze the solutions and their feasibilities. Numerical simulations study the high-risk quarantine and vaccination strategies and show that both strategies effectively reduce the virus prevalence, but their combined application is more effective. We also demonstrate that their effectiveness varies with the volatile rate of change in the system’s distribution. The results are analyzed using Caputo fractional order and presented graphically and extensively analyzed to highlight potent ways of curbing the virus. • A Caputo fractional order epidemic model evaluates high-risk quarantine and vaccination. • Qualitative analysis shows its feasibility in studying physical problems. • Comparative analysis of numerical solutions with error analysis. • Numerical simulations analyzing the effectiveness of single and combined applications. • Descriptive analysis of the simulation results obtained paving ways of eradicating the disease.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1016/j.health.2023.100179
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
