Comparing Short-Term Univariate and Multivariate Time-Series Forecasting Models in Infectious Disease Outbreak

Predicting infectious disease outbreak impacts on population, healthcare resources and economics and has received a special academic focus during coronavirus (COVID-19) pandemic. Focus on human disease outbreak prediction techniques in current literature, Marques et al. (Predictive models for decisi...

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Bibliographic Details
Published in:Bulletin of mathematical biology 2023-01, Vol.85 (1), p.9-9, Article 9
Main Authors: Assad, Daniel Bouzon Nagem, Cara, Javier, Ortega-Mier, Miguel
Format: Article
Language:English
Subjects:
Cell Biology
Coronaviruses
COVID-19
COVID-19 - epidemiology
Disease Outbreaks
Epidemics
Forecasting
Humans
Impact prediction
Infectious diseases
Life Sciences
Machine learning
Mathematical and Computational Biology
Mathematical Concepts
Mathematical models
Mathematics
Mathematics and Statistics
Models, Biological
Models, Statistical
Multivariate analysis
Original
Original Article
Outbreaks
Prediction models
Statistical analysis
Statistical models
Time series
Viral diseases
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Summary:Predicting infectious disease outbreak impacts on population, healthcare resources and economics and has received a special academic focus during coronavirus (COVID-19) pandemic. Focus on human disease outbreak prediction techniques in current literature, Marques et al. (Predictive models for decision support in the COVID-19 crisis. Springer, Switzerland, 2021) state that there are four main methods to address forecasting problem: compartmental models, classic statistical models, space-state models and machine learning models. We adopt their framework to compare our research with previous works. Besides being divided by methods, forecasting problems can also be divided by the number of variables that are considered to make predictions. Considering this number of variables, forecasting problems can be classified as univariate, causal and multivariate models. Multivariate approaches have been applied in less than 10% of research found. This research is the first attempt to evaluate, over real time-series data of 3 different countries with univariate and multivariate methods to provide a short-term prediction. In literature we found no research with that scope and aim. A comparison of univariate and multivariate methods has been conducted and we concluded that besides the strong potential of multivariate methods, in our research univariate models presented best results in almost all regions’ predictions.
ISSN:0092-8240
1522-9602
DOI:10.1007/s11538-022-01112-5