A simple Stochastic SIR model for COVID 19 Infection Dynamics for Karnataka: Learning from Europe

TL;DR

This paper develops a stochastic SIR model using Itô differential equations, derived from European COVID-19 data, to project future infection trends in Karnataka, India, aiding strategic planning for mitigation efforts.

Contribution

It introduces a stochastic SIR model based on European data to predict COVID-19 trends in Karnataka, India, incorporating stochastic dynamics for better accuracy.

Findings

Model parameters derived from European data

Projected infection trends for Karnataka

Guidelines for mitigation strategies

Abstract

In this short note we model the region-wise trends of the evolution to COVID-19 infections using a stochastic SIR model. The SIR dynamics are expressed using \textit{It\^o-stochastic differential equations}. We first derive the parameters of the model from the available daily data from European regions based on a 24-day history of infections, recoveries and deaths. The derived parameters have been aggregated to project future trends for the Indian subcontinent, which is currently at an early stage in the infection cycle. The projections are meant to serve as a guideline for strategizing the socio-political counter measures to mitigate COVID-19.