Effective Utilization of Data for Predicting COVID-19 Dynamics: An Exploration through Machine Learning Models

This study is centered around the COVID-19 pandemic which has posed a global health concern for over three years. It emphasizes the importance of effectively utilizing epidemic simulation models for informed decision-making concerning epidemic control. The challenge lies in appropriately choosing, a...

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Bibliographic Details
Published in:International journal of telemedicine and applications 2023-12, Vol.2023, p.1-24
Main Authors: Chumachenko, Dmytro, Dudkina, Tetiana, Yakovlev, Sergiy, Chumachenko, Tetyana
Format: Article
Language:English
Subjects:
Accuracy
Asymptomatic
Communicable diseases
Coronaviruses
COVID-19 vaccines
Decision making
Decision trees
Disease control
Disease prevention
Disease transmission
Epidemics
Forecasting
Germany
Health aspects
Infectious diseases
Inverse problems
Japan
Machine learning
Medical research
Medicine, Experimental
Morbidity
Mortality
Pandemics
Performance evaluation
Public health
Regression analysis
Simulation models
South Korea
Telemedicine
Ukraine
Viral diseases
World health
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Summary:This study is centered around the COVID-19 pandemic which has posed a global health concern for over three years. It emphasizes the importance of effectively utilizing epidemic simulation models for informed decision-making concerning epidemic control. The challenge lies in appropriately choosing, adapting, and interpreting these models. The research constructs three statistical machine learning models to predict the spread of COVID-19 in specific regions and evaluates their performance using real COVID-19 incidence data. The paper presents short-term (3, 7, 14, 21, and 30 days) forecasts of COVID-19 morbidity and mortality for Germany, Japan, South Korea, and Ukraine. The precision of each model was scrutinized based on the type of input data used. Recommendations are provided on how various data sources can enhance the interpretation quality of machine learning models predicting infectious disease dynamics. The initial findings suggest the need for the comprehensive utilization of all available data, favoring cumulative data during holiday-rich periods and daily data otherwise. To minimize the absolute error, databases should be compiled using daily morbidity and mortality rates.
ISSN:1687-6415
1687-6423
DOI:10.1155/2023/9962100