The SIR (Susceptible-Infected-Recovered) model is one of the most fundamental mathematical models in epidemiology, designed to understand the spread of infectious diseases. This model categorizes the population into three main groups—Susceptible, Infected, and Recovered. Despite its simplicity, the model plays a crucial role in predicting the patterns of disease spread, although it often faces challenges regarding the accuracy of its parameters, such as infection and recovery rates.
This research focuses on developing an empirical approach to estimate the SIR model parameters more accurately and explicitly. By utilizing observed data, this study successfully constructs confidence intervals for these parameters, providing additional tools to estimate the degree of uncertainty within the model. This method enables more accurate and reliable epidemiological predictions, particularly in the context of emerging disease outbreaks.
The contribution of this research is not only significant for the advancement of epidemiological science but also aligns with the achievement of the Sustainable Development Goal (SDG) 3, “Good Health and Well-being.” With more accurate modeling, policymakers can make better-informed decisions in addressing outbreaks, protecting public health, and minimizing the impact of diseases on communities. This model also serves as a reference for designing faster and more effective intervention strategies.
The empirical approach proposed in this study helps overcome the limitations of using fixed parameters that are not always accurate. With empirically established confidence intervals, researchers and stakeholders now have better tools to anticipate various scenarios in disease spread, strengthening the resilience of health systems.
Keywords: SIR Model, Empirical Estimation, Epidemiology
Reference:
Susyanto, N., & Arcede, J.P. “Unveiling SIR Model Parameters: Empirical Parameter Approach for Explicit Estimation and Confidence Interval Construction.” Jambura Journal of Biomathematics (JJBM) 5 (1), 54-62.
Author: Nanang Susyanto