Indexed metadata

Mathematical Modelling of the Impact of Screening, Treatment and Media Campaigns of Breast Cancer Cell Population Dynamics in Kenya

Robert Njue Muriithi, Kennedy Otieno Awuor, Jeremiah Savali Kilonzi

Source record

Source: Crossref

Published: Oct 14, 2026

DOI: 10.9734/arjom/2026/v22i101172

Open original source ↗

Source abstract

Aims/Objectives: To formulate a mathematical model and quantify the impacts of screening, treatment, and media campaigns on breast cancer cells. The basic reproduction number is derived, sensitivity analysis is performed, and the model is simulated using the Ministry of Health data. We suggested a classical mathematical model comprising six compartments: healthy cells, cancerous cells, awareness, screened individuals, treated population, and recovered population. Methodology: The study employed the Next Generation Matrix Method (NGM) to determine the basic reproduction number . The results obtained indicated that the Tumor-Free Equilibrium is locally asymptotically stable whenever and globally asymptotically stable if . On the other hand, the Endemic Equilibrium was globally asymptotically stable if The numerical solutions are obtained using ODE45 in MATLAB R2025b for the analysis. Results: The simulation results showed that increasing the rate of media awareness by 6.32% led to a 2.179% increase in the screened population, while a 52.31% increase in the rate of screening for the treated population resulted in a 1.866% increase in the treated population, and a 65% decrease in the treatment rate caused a 15.26% increase in the number of cancerous cells in the body. Conclusions: To effectively control breast cancer progression, screening and media campaigns should be enhanced to minimize the cancerous cell population and consequently reduce the mortality rate.

Evidence graph

No public relationships recorded yet.

Integrity note: This page is a factual metadata record created by deterministic ingestion. It is not a claim that the work moves a mathematical frontier or has been independently verified.

Mathematical Modelling of the Impact of Screening, Treatment and Media Campaigns of Breast Cancer Cell Population Dynamics in Kenya — Mathematical Frontier Network