Literature DB >> 35960670

An evaluation of mathematical models for the outbreak of COVID-19.

Ning Wang1, Yuting Fu1, Hu Zhang2, Huipeng Shi3.   

Abstract

Mathematical modelling performs a vital part in estimating and controlling the recent outbreak of coronavirus disease 2019 (COVID-19). In this epidemic, most countries impose severe intervention measures to contain the spread of COVID-19. The policymakers are forced to make difficult decisions to leverage between health and economic development. How and when to make clinical and public health decisions in an epidemic situation is a challenging question. The most appropriate solution is based on scientific evidence, which is mainly dependent on data and models. So one of the most critical problems during this crisis is whether we can develop reliable epidemiological models to forecast the evolution of the virus and estimate the effectiveness of various intervention measures and their impacts on the economy. There are numerous types of mathematical model for epidemiological diseases. In this paper, we present some critical reviews on mathematical models for the outbreak of COVID-19. Some elementary models are presented as an initial formulation for an epidemic. We give some basic concepts, notations, and foundation for epidemiological modelling. More related works are also introduced and evaluated by considering epidemiological features such as disease tendency, latent effects, susceptibility, basic reproduction numbers, asymptomatic infections, herd immunity, and impact of the interventions.
© The Author(s) 2020. Published by Oxford University Press on behalf of the West China School of Medicine & West China Hospital of Sichuan University.

Entities:  

Keywords:  2019-nCoV; COVID-19; SARS-CoV-2; SEIR model; SIR model; asymptomatic infections; basic reproduction numbers; case fatality ratio; epidemiological modelling; herd immunity; intervention measures; novel coronavirus

Year:  2020        PMID: 35960670      PMCID: PMC7376265          DOI: 10.1093/pcmedi/pbaa016

Source DB:  PubMed          Journal:  Precis Clin Med        ISSN: 2516-1571


  20 in total

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