Stochastic Modeling, Analysis, and Simulation of the COVID-19 Pandemic with Explicit Behavioral Changes in Bogotá: A Case Study

Overview

Journal Infect Dis Model

Specialty Infectious Diseases

Date 2022 Jan 10

PMID 35005324

Authors

David Nino-Torres

Andres Rios-Gutierrez

Viswanathan Arunachalam

Comfort Ohajunwa

Padmanabhan Seshaiyer

Affiliations

Soon will be listed here.

Abstract

In this paper, a stochastic epidemiological model is presented as an extension of a compartmental SEIR model with random perturbations to analyze the dynamics of the COVID-19 pandemic in the city of Bogotá D.C., Colombia. This model incorporates the spread of COVID-19 impacted by social behaviors in the population and allows for projecting the number of infected, recovered, and deceased individuals considering the mitigation measures, namely confinement and partial relaxed restrictions. Also, the role of randomness using the concept of Brownian motion is emphasized to explain the behavior of the population. Computational experiments for the stochastic model with random perturbations were performed, and the model is validated through numerical simulations for actual data from Bogotá D.C.

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