#4950. Modeling analytics in COVID-19: prediction, prevention, control, and evaluation

August 2026publication date
Proposal available till 16-06-2025
4 total number of authors per manuscript0 $

The title of the journal is available only for the authors who have already paid for
Journal’s subject area:
Statistics and Probability;
Statistics, Probability and Uncertainty;
Business, Management and Accounting (miscellaneous);
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Abstract:
The outbreak of COVID-19 has attracted attention from all around the world. Governments and institutions have adopted ways to fight COVID-19, but its prevalence is still strong. The SIR (susceptible-infected-removed) model has important reference value for the novel coronavirus epidemic, offering both preventive measures and the ability to predict future trends. Based on an analysis of the classical epidemiological SIR model along with key parameters, this paper aims to analyze the patterns of COVID-19, to discuss potential anti-COVID-19 measures, and to explain why we need to conduct appropriate measures against COVID-19. The use of the SIR model can play an important role in public health emergencies. Among the parameters of the SIR model, the contact ratio and the reproduction ratio are the factors that have the potential to mitigate the consequences of COVID-19. Anti-COVID-19 measures include wearing a mask, washing one’s hands, keeping social distance, and staying at home if possible.
Keywords:
COVID-19; epidemiological compartment model; SIR model; social distancing; the contact ratio; the reproduction ratio

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