The Level of Fear in the Polish Police Population during the COVID-19 Pandemic with the Impact of Sociodemographic Variables.

This study has a twofold objective. First, we aim to measure the levels of fear among Polish police officers using the COVID-19 Fear Scale (FCV-19S) that has a stable unidimensional structure allowing for the provision of additional data by combining variables. This structure allows the second objective to be met to measure the correlation with sociodemographic variables. The utilitarian objective of the study is to provide information for updating support policies for stress management in the service. The questionnaire was completed by 1862 people with a mean age of 38.75 years with a good Cronbach's alpha (0.89). The perceived level of fear associated with COVID-19 should be considered relatively low. Caring for the elderly does not affect the level of fear. The factors of gender, age and having children statistically significantly differentiate the perceptions of fear. Therefore, there is a necessity to focus on building support for police officers who are over 50 years old, as well as for women, where higher levels of fear in both men and women can translate into the development of psychosomatic illnesses.

Relationship between Visibility, Air Pollution Index and Annual Mortality Rate in Association with the Occurrence of Rainfall—A Probabilistic Approach

An innovative method was proposed to facilitate the analyses of meteorological conditions and selected air pollution indices’ influence on visibility, air quality index and mortality. The constructed calculation algorithm is dedicated to simulating the visibility in a single episode, first of all. It was derived after applying logistic regression methodology. It should be stressed that eight visibility thresholds (Vis) were adopted in order to build proper classification models with a number of relevant advantages. At first, there exists the possibility to analyze the impact of independent variables on visibility with the consideration of its’ real variability. Secondly, through the application of the Monte Carlo method and the assumed classification algorithms, it was made possible to model the number of days during a precipitation and no-precipitation periods in a yearly cycle, on which the visibility ranged practically: Vis < 8;Vis = 8–12 km, Vis = 12–16 km, Vis = 16–20 km, Vis = 20–24 km, Vis = 24–28 km, Vis = 28–32 km, Vis > 32 km. The derived algorithm proved a particular role of precipitation and no-precipitation periods in shaping the air visibility phenomena. Higher visibility values and a lower number of days with increased visibility were found for the precipitation period contrary to no-precipitation one. The air quality index was lower for precipitation days, and moreover, strong, non-linear relationships were found between mortality and visibility, considering precipitation and seasonality effects.