A Novel Model to Predict The Epidemics Trends And Its Application in Covid-19 Volume 5 - Issue 4

Shu-Qing Yang*

• School of Civil, Mining and Environmental Engineering, University of Wollongong NSW 2522, Australia

Received: October 07, 2020;   Published: October 22, 2020

*Corresponding author: Shu-Qing Yang1School of Civil, Mining and Environmental Engineering, University of Wollongong NSW 2522, Australia

DOI: 10.32474/LOJMS.2020.05.000217

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Abstract

For every epidemic, the public and decision-makers worry that the number of infected people will be far more than the healthcare system can afford, thus it is important to predict the cases which need medical services. This is similar to cases of natural disasters such as floods when a devastating outcome occurs with incoming and outgoing water volume being higher than a river’s storage capacity. The similarities between floods and epidemics inspire a modified rainfall-runoff model, I&α. This novel model focuses on the prediction of active cases, i.e., y0, which measures the number of people who need medical services. This model is based on the past data for the prediction of future epidemic trends. This model can effectively predict the maximum y0 and its peak date when applied to model COVID-19, with an average error of 3.8% and 2.7 days, respectively. The average error for y0 on May 12, 2020 is 22.7%.

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