INFLUENCE OF ATMOSPHERIC PRESSURE ON THE COVID-19 EPIDEMIC PROCESS
Authors: Halushko Nataliia , Kuprienko Iryna 
Published: April 2023

Introduction. Identification of the main determinants of temporal changes in the epidemic process of COVID-19 is important for the development of effective strategies for the prevention and control of this infection.
Attempts to determine the relationship between the cyclical changes in atmospheric pressure and the course of the epidemic process of COVID-19 were made by scientists repeatedly, but scientific data on the influence of atmospheric pressure on the epidemic process of COVID‑19 are still controversial.
The objective of the research is to investigate the influence of atmospheric pressure on the epidemic process of COVID-19 using the example of Sumy city (Ukraine).
Materials and methods. In this research, we used data on the daily number of new cases of COVID-19, which were obtained from the daily reports of the Sumy Regional Center for Disease Control and Prevention of the Ministry of Health of Ukraine, as well as the results of daily monitoring of atmospheric pressure indicators of the Sumy Regional Hydrometeorology Center. The period of observation was from 05/1/2020 to 12/1/2022.
The dynamics of changes in meteorological indicators and the daily number of new cases of COVID-19 (hereinafter, the incidence of COVID-19) in Sumy were studied using simple moving averages. The smoothing period for morbidity indicators was equal to 7 days, for atmospheric pressure indicators was 19 days, and the lag between a series of indicators was 7 days. The total number of paired observations of the variables is n = 945. To find out whether the incidence of COVID‑19 (the response variable) varies depending on the level of atmospheric pressure (the independent variable), a non-parametric Kruskal–Wallis’s analysis of variance was used. For this, the numerical series of atmospheric pressure values was converted into a categorical series, and the quartile of the series was used as a grouping feature. A posteriori analysis (post hoc test) was performed using the Mann–Whitney test. The quantitative assessment of the differences between groups in the Mann–Whitney test was evaluated by Cohen's test.
Results. Kruskal–Wallis’s analysis of variance. The statistically significant difference in the incidence of COVID-19 was established in the four comparison groups (χ2 = 119.462, 3 df, p-value = 0.0001). The median of incidence of COVID-19 and the interquartile range in the 1st comparison group was 25 (6.4; 85.3) cases, in the 2nd group – 10.6 (5.0; 40.6) cases, in the 3rd group – 60.4 (14.3; 149.9) cases, in the 4th group – 99.1 (13.6; 202.5) cases.
Mann–Whitney test. The incidence of COVID-19 is lowest within the 2nd quartile of atmospheric pressure (743.63–745.0 mm Hg); an increase in atmospheric pressure to the level of the 3rd (745.01–748.11 mm Hg) and 4th (748.12–755.1 mm Hg) quartiles, as well as its decrease to the level of the 1st quartile (738.6–743.62 mm Hg), is associated with a statistically significant increase in the number of COVID-19 cases (p-value = 0.0000–0.0012). We estimated the magnitude of the effect as small (r = 0.15) in the case of a decrease in atmospheric pressure and medium in the case of an increase in atmospheric pressure.
Conclusions. 1. The results of the Kruskal–Wallis’s test showed that the multilevel factor, which is atmospheric pressure (explanatory variable), affects the level of the incidence of COVID-19 (response variable) and, therefore, the activity of its mechanism of transmission (χ2 = 119.462, 3 df, p-value = 0.0001).
The dependence of the daily cases of COVID-19 on atmospheric pressure is a non-linear function. This confirms the expediency of using the Kruskal–Wallis’s test in this study, and also indicates the irrationality of using Spearman and Pearson correlation analyses to study the correlation between variables.
The incidence of COVID-19 was minimal at average atmospheric pressure values of 743.6–745.0 mm Hg. Any changes in atmospheric pressure that went beyond this interval in one direction or another led to a statistically significant increase in morbidity. We estimate the magnitude of the effect as small in the case of a decrease in atmospheric pressure and medium in the case of an increase in atmospheric pressure.