Forecast of COVID-19 Epidemic Trend Based on Multiple Linear Regression Model

Yixi Zou

doi:10.54097/fcis.v1i3.2134

Authors

Yixi Zou

DOI:

https://doi.org/10.54097/fcis.v1i3.2134

Keywords:

Multiple regression model, COVID-19, Epidemic trend, Forecast

Abstract

At present, COVID-19 is prevalent all over the world, and countries are facing severe epidemic prevention and control problems. Most countries in the world have taken corresponding measures, and how to predict the dynamics and trends of the epidemic quickly and accurately plays a key role in the global joint efforts to fight the epidemic. Therefore, according to the spread characteristics of COVID-19 epidemic, this paper first analyzes the multiple linear regression model, and then predicts the epidemic trend of COVID-19 based on the multiple linear regression model. The experimental results showed that when COVID-19 broke out, the multiple linear regression model had a high accuracy, and its forecast results were in good agreement with the cumulative confirmed cases. This shows that this algorithm is more effective than other existing algorithms. Using multiple linear regression model to predict the epidemic trend of COVID-19 has certain theoretical and practical significance. Through the realization of this model, we can grasp the development and changes of epidemic situation in various regions in time in the management of epidemic prevention and control, prepare for epidemic prevention in advance through trend forecast, control epidemic situation in time and improve epidemic prevention effect.

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