Applying the SIR Model to COVID-19
COVID is obviously one of the most impactful epidemics/pandemics in our lifetime. The fact that it happened so recently and influenced our college career makes the epidemic topics in networks incredibly relevant and applicable to the entire class. In a 2020 paper from the National Center for Biotechnology Information titled “A SIR Model Assumption for the Spread of COVID-19 in Different Communities,” the SIR Model is directly applied to a very real life example.
The SIR model is a simple model that is commonly used to study the spread of infectious diseases. The model divides the population into three groups: susceptible individuals who have not yet contracted the disease, infected individuals who have the disease and can spread it to others, and recovered/removed individuals who have either recovered from the disease or have died. The model progresses based on probability of transmission, the number of susceptible individuals, and the rate of recovery to predict how a disease can spread. The SIR model can be used to study the spread of a wide range of infectious diseases, including COVID-19.
The paper summarizes that while the SIR model definitely did not predict the long-term growth internationally of COVID-19, it did a fairly accurate job in predicting the spread through individual communities. This makes sense, since the model is simple it does not take into account the other factors that it takes for a pandemic to progress. However, it was able to produce graphs with peak predictions that accurately matched the spread of two waves in Texas and Italy.
It was incredibly reflective to read this article at the end of this semester after learning about these different networks topics. The paper directly relates class content and problems to a mathematical model that likely aided in the prevention of the worst pandemic of our lifetime. Additionally, it is interesting to see the next steps and math beyond the SIR model, which take many more factors into account.
1. Cooper, Ian; Mondal, Argha; Antonopoulos, Chris; “A SIR model assumption for the spread of COVID-19 in different communities,” National Center for Biotechnology Information. October, 2020. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7321055/.