Predicating COVID19 epidemic in Nepal using the SIR model

The study by Thapa (2021) focuses on the propagation of infectious diseases, specifically COVID-19, using the SIR (Susceptible, Infected, Recovered) model to understand and predict the disease's spatial diffusion. The model simulates the spread of COVID-19 in a worst-case scenario, estimating parameters by minimizing the negative log-likelihood function with the Nelder-Mead method. The findings suggest that the pandemic would peak between mid-August and the end of October, with approximately 1 million people aged 10-29 infected, leading to around 552 severe cases, 175 needing intensive care, and up to 30 deaths per day. The study emphasizes the importance of strict containment strategies to control the spread of the disease (Thapa, P. 2021).

Reference:

Thapa, P. (2021). Predicating COVID19 epidemic in Nepal using the SIR model. Artificial Intelligence for COVID-19, 229-237.