An Evaluation of Mathematical Models for the Outbreak of COVID-19

Ning Wang, Yuting Fu, Hu Zhang, Huipeng Shi

Research output: Contribution to conferencePaperpeer-review


Mathematical modelling performs a vital part in estimating and controlling the recent outbreak of novel coronavirus (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 in order to leverage between health and economic development. How and when to make clinical and public health decisions in the epidemic situation is a challenging question. The most appropriate solution is based on scientific evidence, which is mainly depending upon 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 models 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 more epidemiological features such as disease tendency, latent effects, susceptibility, basic reproduction numbers, asymptomatic infections, herd immunity, and impact of the interventions.
Original languageAmerican English
StatePublished - 2020
Externally publishedYes

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