The SHIR Model: Realistic Fits to COVID-19 Case Numbers

2020/07/28 by Theresa Barnes, Barnes, T. · 1 citation
Economics, Econometrics and Finance · Mathematics · #COVID-19 Pandemic Impacts #COVID-19 epidemiological studies #Complex Systems and Time Series Analysis #FOS: Biological sciences #FOS: Physical sciences #Physics and Society (physics.soc-ph) #Populations and Evolution (q-bio.PE)

paper · pdf · doi:10.48550/arxiv.2007.14804

openalex publication_date 2020/07/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We consider a global (location independent) model of pandemic growth which generalizes the SIR model to accommodate important features of the COVID-19 pandemic, notably the implementation of pandemic reduction measures. This "SHIR" model is applied to COVID-19 data, and shows promise as a simple, tractable formalism with few parameters that can be used to model pandemic case numbers. As an example we show that the average time dependence of new COVID-19 cases per day from 15 Central and Western European countries is in good agreement with the analytic, parameter-free prediction of the model

Cited by

• A nucleation and growth model for COVID-19 epidemic in Japan

Related

• Prospects and limits of SIR-type Mathematical Models to Capture the COVID-19 Pandemic
• Mathematical Models for Describing and Predicting the COVID-19 Pandemic Crisis
• Analyzing COVID-19 pandemic with a new growth model for population ecology
• Accounting for Symptomatic and Asymptomatic in a SEIR-type model of\n COVID-19
• Data-Driven Models for studying the Dynamics of the COVID-19 Pandemics