Estimation and demographic analysis of COVID-19 infections with respect to weather factors in Europe

ABSTRACT

The main objective of this study is to investigate the relationship between the COVID-19 and the weather factors of the most populated and industrialised countries in Europe and propose the best mathematical model to forecast the daily number of COVID-19 cases. To find the relationship between the COVID-19 and the weather factors of absolute humidity and temperature in Spain, France, Italy, Germany, and the United Kingdom, we conducted a Poisson analysis. We also used the General Linear Neural Network (GRNN) model to forecast the trend and number of daily COVID-19 cases in these European countries. The results reveal a statistically significant negative relationship between the number of COVID-19 infections and weather factors of temperature & absolute humidity. Furthermore, the results show a stronger negative relationship between COVID-19 and absolute humidity than temperature. In our proposed GRNN method, we find better compatibility for the COVID-19 cases in Italy relative to the other European countries in this study.

KEY WORDS:

• COVID-19
• weather
• poisson
• GRNN
• Europe

Acknowledgments

The authors are thankful to the respectful editors and three anonymous reviewers for their very constructive comments to improve the paper’s quality. Moreover, Mahdi Fathi would like to thank Leon A. Kappelman, Professor of Information Systems & Chair, ITDS Department, Ryan College of Business, University of North Texas for his encouragement, mentoring, and support during this research.

Highlights

• The trend of the daily number of new COVID-19 cases is almost decreasing in France, Italy, Germany, and the U.K. but this trend is increasing in Spain again.

• France has the advantage of controlling the COVID-19 mortality rate compared to other European countries in this study.

• There is a negative statistical relationship between the number of daily new COVID-19 cases and weather factors of absolute humidity and temperature in Western Europe.

• There is a statistically more reliable negative relationship between the number of daily new COVID-19 cases and absolute humidity than the temperature in Western Europe.

• GRNN shows a promising forecast model in the forecasting of the number of COVID-19 cases.

Disclosure statement

There is no conflict of interest by the authors.

Notes

1. Machine learning and ANNs methods have been used to forecast typhoid fever (X. Zhang et al., 2013), haemorrhagic fever (W. Wu et al., 2015), hepatitis (Wei et al., 2016), dengue fever (Polwiang, 2020), and COVID-19 (Fong et al., 2020).