A simple model for fitting mild, severe, and known cases during an epidemic with an application to the current SARS-CoV-2 pandemic
Matthew Betti, Jane M. Heffernan
Abstract
One of the major difficulties with modelling an ongoing epidemic is that often data is limited or incomplete, making it hard to estimate key epidemic parameters and outcomes (e.g. attack rate, peak time, reporting rate, reproduction number). In the current study, we present a model for data-fitting limited infection case data which provides estimates for important epidemiological parameters and outcomes. The model can also provide reasonable short-term (one month) projections. We apply the model to the current and ongoing COVID-19 outbreak in Canada both at the national and provincial/territorial level.
Topics & Concepts
PandemicCoronavirus disease 2019 (COVID-19)Basic reproduction numberSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)OutbreakEpidemic model2019-20 coronavirus outbreakCurrent (fluid)GeographyTerm (time)StatisticsDemographyComputer scienceEconometricsMedicineVirologyMathematicsSociologyEngineeringPopulationInfectious disease (medical specialty)DiseaseElectrical engineeringPathologyPhysicsQuantum mechanicsCOVID-19 epidemiological studiesSARS-CoV-2 and COVID-19 ResearchViral Infections and Outbreaks Research