Modeling the time-dependent transmission rate using gaussian pulses for analyzing the COVID-19 outbreaks in the world
Setianto Setianto, Darmawan Hidayat
Abstract
Abstract In this work, an SEIR epidemic model with time-dependent transmission rate parameters for the multiple waves of COVID-19 infection was investigated. It is assumed that the transmission rate is determined by the superposition of the Gaussian pulses. The interaction of these dynamics is represented by recursive equations. Analysis of the overall dynamics of disease spread is determined by the effective reproduction number R e ( t ) produced throughout the infection period. The study managed to show the evolution of the epidemic over time and provided important information about the occurrence of multiple waves of COVID-19 infection in the world and Indonesia.
Topics & Concepts
Superposition principleTransmission (telecommunications)Coronavirus disease 2019 (COVID-19)OutbreakTransmission rateBasic reproduction numberGaussianInfection rateSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Statistical physics2019-20 coronavirus outbreakDisease transmissionBiologyVirologyComputer scienceStatisticsPhysicsMathematicsDiseaseDemographyMedicineTelecommunicationsMathematical analysisInfectious disease (medical specialty)Quantum mechanicsSurgeryPopulationPathologySociologyCOVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology ModelsEvolution and Genetic Dynamics