Report on Mathematical Modelling of Epidemic Spread and Control Strategies

This investigative report applies mathematical modelling to study the spread of infectious diseases and evaluate the effectiveness of intervention strategies. Conducted as pre-university research, the work integrates principles from epidemiology, applied mathematics, and systems analysis to examine how changes in parameters influence epidemic dynamics.The report covers:Model development – Formulation of the SIR (Susceptible–Infected–Recovered) model with relevant assumptions and constraints.Parameter estimation – Derivation of transmission and recovery rates from example datasets.Simulation results – Numerical modelling of outbreak progression under different reproduction numbers (R₀).Intervention analysis – Comparative study of quarantine, vaccination, and social distancing impacts on infection curves.Sensitivity testing – Exploration of parameter variations and their effects on outbreak scale and duration.Visual data representation – Use of time-series plots and phase portraits to communicate model outcomes.The study demonstrates how mathematical tools can be used to inform public health decision-making, providing insights into both disease dynamics and policy design.