Impact of Meteorological Conditions on the Dynamics of the COVID-19 Pandemic in Poland

Abstract

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the novel coronavirus. The role of environmental factors in COVID-19 transmission is unclear. This study aimed to analyze the correlation between meteorological conditions (temperature, relative humidity, sunshine duration, wind speed) and dynamics of the COVID-19 pandemic in Poland. Data on a daily number of laboratory-confirmed COVID-19 cases and the number of COVID-19-related deaths were gatheredfrom the official governmental website. Meteorological observations from 55 synoptic stations in Poland were used. Moreover, reports on the movement of people across different categories of places were collected. A cross-correlation function, principal component analysis and random forest were applied. Maximum temperature, sunshine duration, relative humidity and variability of mean daily temperature affected the dynamics of the COVID-19 pandemic. An increase intemperature and sunshine hours decreased the number of confirmed COVID-19 cases. The occurrence of high humidity caused an increase in the number of COVID-19 cases 14 days later. Decreased sunshine duration and increased air humidity had a negative impact on the number of COVID-19-related deaths. Our study provides information that may be used by policymakers to support the decision-making process in nonpharmaceutical interventions against COVID-19.

Correlation between COVID-19 and weather variables: A meta-analysis

“…The association of COVID-19 with meteorological parameters such as humidity, temperature, precipitation, wind speed, air pressure, rainfall, and sunlight has been examined in previous studies 10 , 11 , 12 , 13 , 14 , 15 . However, a weak association between COVID-19 and weather variables was found in the available studies 16 , 17 .…”

Impact of key meteorological parameters on the spread of COVID-19 in Mumbai: Correlation and Regression Analysis

“…However, since this is a new virus with effects and consequences different from its family, more extensive research needs to be done to establish facts about the influence of weather on COVID-19 spread. Various studies on components affecting the spread of the pandemic in India were also conducted (Majumder and Ray 2021, Yuan et al 2021, Sarkodie and Owusu 2020, Shankar et al 2021, Kumar and Kumar 2020, Kolluru et al 2020, Hridoy et al 2021, Bochenek et al 2021, Pani et al 2020. Preliminary studies done in this matter indicate some level of influence in cities like Delhi and Indore where cases showed moderate associations with temperature levels (Roy 2021).…”

Temporal variation of spatial autocorrelation of COVID-19 cases identified in Poland during the year from the beginning of the pandemic

“…Jarynowski et al (2020aJarynowski et al ( , 2020b for the entire analyzed period and the two indicators taken into account, calculated the Moran 'I' index, indicating a highly statistically significant (p < 0.001) positive autocorrelation. An isolated, but very interesting study is the publication by Bochenek et al (2021), who identified relationships between the dynamics of a pandemic, determined by the number of identified COVID-19 cases and the number of deaths caused by this disease, and meteorological conditions. However, when reading it, doubts arise as to whether the authors took into account a relationship between meteorological conditions and the efficiency of the pandemic data collection and reporting system.…”