Litcius/Paper detail

Mathematical Models for Predicting Covid-19 Pandemic: A Review

Vishnu Vytla, Sravanth Kumar Ramakuri, Anudeep Peddi, K. Srinivas, N. Nithish Ragav

2021Journal of Physics Conference Series76 citationsDOIOpen Access PDF

Abstract

Abstract The catastrophic outbreak of the Novel Corona virus (Covid-19) has brought to light, the significance of reliable predictive mathematical models. The results from such models greatly affect the use of non-pharmaceutical intervention measures, management of medical resources and understanding risk factors. This paper compares popular mathematical models based on their predictive capabilities, practical validity, presumptions and drawbacks. The paper focuses on popular techniques in use for the predictive modeling of the Covid-19 epidemic. The paper covers the Gaussian Model, SIRD, SEIRD and the latest θ-SEIHRD techniques used for predictive modeling of epidemics.

Topics & Concepts

Coronavirus disease 2019 (COVID-19)Computer sciencePandemicMathematical modelOutbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakRisk analysis (engineering)Operations researchEconometricsEngineeringMathematicsInfectious disease (medical specialty)VirologyStatisticsMedicineDiseasePathologyCOVID-19 epidemiological studiesData-Driven Disease SurveillanceAnomaly Detection Techniques and Applications