Epidemiological Characteristics of 101,471 Patients Hospitalized with Chronic Obstructive Pulmonary Disease (COPD) in Poland in 2019: Multimorbidity, Duration of Hospitalization, In-Hospital Mortality.

Chronic obstructive pulmonary disease (COPD) is a common lung disease. There is a limited amount of nationwide data on COPD patients in Poland. This study aimed to characterize patients hospitalized with COPD in Poland in 2019 as well as to identify factors associated with the risk of in-hospital death and prolonged hospitalization among patients with COPD. This study is a retrospective database analysis. Data on patients hospitalized with COPD in Poland were obtained from the Nationwide General Hospital Morbidity Dataset. Data on all adults aged ≥40 years with a diagnosis of COPD from a physician (J44 code) were included in the analysis. Data were analyzed separately for patients hospitalized due to COPD (primary diagnosis) and patients with COPD as a comorbidity (secondary diagnosis). Completed medical records were available for 101,471 patients hospitalized with COPD (36.9% were females). Of those, 32% were hospitalized due to COPD. The mean age was 71.4 ± 9.7 years. The mean duration of hospitalization was 9.4 ± 11.4 days (median 7 days). Most of the COPD patients (89.3%) had at least one comorbidity. The in-hospital mortality rate was 6.8%. Older age, presence of cardiovascular diseases, and diseases of the genitourinary system (p < 0.05) were the most important factors associated with the risk of in-hospital death among patients hospitalized due to COPD.

Weather as a potential cause of regional differences in the dynamics of COVID-19 transmission in Poland: implications for epidemic forecasting.

INTRODUCTION: COVID­19 is an infectious disease caused by SARS-CoV-2. Little is known on the impact of weather conditions on the transmission of COVID­19. OBJECTIVES: We aimed to assess correlations between 6 different meteorologic parameters and the transmission dynamics of the COVID­19 pandemic in 16 administrative regions (voivodeships) of Poland. PATIENTS AND METHODS: Data for analysis were obtained from epidemiologic reports of the Polish Ministry of Health. For each voivodeship, one synoptic station was selected to provide meteorologic data on daily maximum and minimum temperatures, variability of daily temperature, sunshine duration, relative humidity, and wind speed. The periods with significant weather impact were determined using multiple linear regression. Cross­correlation function (CCF) and random forest models were used to assess correlations between meteorologic parameters and the incidence of COVID­19 as well as the number of hospitalizations for COVID­19. RESULTS: In all voivodeships, the incidence of new COVID­19 cases correlated with relative humidity (CCF = 0.41), daily maximum temperature (CCF = -0.41), variability of daily temperature (CCF = -0.40), and sunshine duration (CCF = 0.35). For all parameters, a similar time lag of 10 to 14 days was noted. There were no significant correlations for wind speed in most voivodeships. The risk of hospitalization for COVID­19 correlated with daily maximum temperature (CCF = -0.48; time lag, 10 days) and sunshine duration (CCF = -0.45; time lag, 10 days). CONCLUSIONS: The delayed effects of the meteorologic factors on the incidence of COVID­19 and the risk of hospitalization for COVID­19 were observed. In each voivodeship, the dynamics of COVID­19 transmission was most strongly affected by relative humidity and daily maximum temperature.

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

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.

Efficient Usage of Dense GNSS Networks in Central Europe for the Visualization and Investigation of Ionospheric TEC Variations.

The technique of the orthogonal projection of ionosphere electronic content variations for mapping total electron content (TEC) allows us to visualize ionospheric irregularities. For the reconstruction of global ionospheric characteristics, numerous global navigation satellite system (GNSS) receivers located in different regions of the Earth are used as sensors. We used dense GNSS networks in central Europe to detect and investigate a special type of plasma inhomogeneities, called travelling ionospheric disturbances (TID). Such use of GNSS sensors allows us to reconstruct the main TID parameters, such as spatial dimensions, velocities, and directions of their movement. The paper gives examples of the restoration of dynamic characteristics of ionospheric irregularities for quiet and disturbed geophysical conditions. Special attention is paid to the dynamics of ionospheric disturbances stimulated by the magnetic storms of two St. Patrick's Days (17 March 2013 and 2015). Additional opportunities for the remote sensing of the ionosphere with the use of dense regional networks of GNSS receiving sensors have been noted too.