A stochastic process based modular tool-box for simulating COVID-19 infection spread.

ABSTRACT:

Background

The novel coronavirus disease (COVID-19) culminated in a pandemic with many countries affected in varying stages. We aimed to develop a simulation environment for COVID-19 spread, taking environmental and social factors into account.

Methods

The program was written in R language. A stochastic point process simulation model for simulating epidemics, a maximum-likelihood estimation model, an exponential growth rate model for calculating the basic reproduction number (R0), and functions for generating graphical representations of the simulations were utilized.Geographical area definition, population size, the number of initial infected individuals, period of simulation, parameters accounting for the radius of spread like masks usage, mobility level, intrinsic viral v

SUBMITTER: Manathunga SS 

PROVIDER: S-EPMC8897234 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature