Temporal Analysis of COVID-19 Peak Outbreak

TL;DR

This paper investigates using the SIR mathematical model to forecast the peak outbreak timeline of COVID-19, aiding policymakers in resource planning and epidemic control.

Contribution

It applies the SIR model specifically to COVID-19 to predict peak infection times from initial cases, providing a practical tool for epidemic management.

Findings

SIR model can effectively estimate peak outbreak timing

Early predictions assist in resource allocation

Model supports strategic decision-making during epidemics

Abstract

Intent of this research is to explore how mathematical models, specifically Susceptible-Infected-Removed (SIR) model, can be utilized to forecast peak outbreak timeline of COVID-19 epidemic amongst a population of interest starting from the date of first reported case. Till the time of this research, there was no effective and universally accepted vaccine to control transmission and spread of this infection. COVID-19 primarily spreads in population through respiratory droplets from an infected person cough and sneeze which infects people who are in proximity. COVID-19 is spreading contagiously across the world. If health policy makers and medical experts could get early and timely insights into when peak infection rate would occur after first reported case, they could plan and optimize medical personnel, ventilators supply, and other medical resources without over-taxing the infrastructure. The predictions may also help policymakers devise strategies to control the epidemic, potentially saving many lives. Thus, it can aid in critical decision-making process by providing actionable insights into COVID-19 outbreak by leveraging available data.