Comprehensive analysis of the COVID-19 pandemic through the SIR model

Abstract

In the study of infectious disease transmission, understanding the dynamics of disease spread and the impact of population-wide preventive measures is crucial. This study is conducted with the overarching goal of investigating how a comprehensive set of protective measures affects the spread of infectious diseases, while simultaneously creating a mathematical model that can accurately describe the dynamics of disease transmission within a population. By utilizing a mathematical modeling approach, this study aim to unravel the intricate relationship between key variables, including the overall protection coefficient, the daily contact rate of infected individuals, and the size of the total population. Furthermore, the model is subjected to a rigorous refinement process to explore the conditions under which disease transmission comes to a halt. The findings of this research shed light on the paramount importance of implementing broad-scale protective measures at the population level in order to effectively control and mitigate the spread of infectious diseases. These insights not only inform the development of robust disease prevention strategies but also provide a foundation for evidence-based policymaking to safeguard public health and well-being.