Sensitivity analysis of SEIR epidemic model of Covid 19 spread in Indonesia

Abstract

Epidemiological models may provide public health practitioners with some fundamental guidelines, allowing for the examination of issues that may influence disease prevention and treatment techniques. On establish the relative impact of the model parameters to disease transmission, a sensitivity analysis of the epidemiological model is undertaken. A sensitivity analysis of the Susceptible, Exposed, Infectious, and Recovered (SEIR) model of corona virus 2019 (COVID 19) was undertaken to determine the parameters’ influence on the basic reproduction number and endemic equilibrium. The rate of contact between susceptible individual and exposed individuals and rate of exposed to infected individuals are the most impactful parameters on the basic reproduction number and the number of infectious individuals, according to our findings. Furthermore, the number of people who have been exposed is affected by the rate at which they proceed from exposed to infect. The findings show that if infectious people recover faster, the number of contagious people will decrease.

Global Sensitivity Analysis of A Rabies Epidemic Model involving Dog Vaccination and Dog Population Management

“…Sensitivity analysis is divided into two, namely local and global sensitivity analysis. Global sensitivity analysis is usually performed by calculating the partial rank correlation coefficient (PRCC) from the parameter space generated using the Latin hypercube sampling (LHS) technique as done in [15]- [22]. LHS permits an unbiased estimate of the average model output, with the advantage that it needs fewer samples than simple random sampling to achieve the same accuracy [23].…”