Quality of place as the winner of the third wave of the COVID-19 pandemic in terms of quality of life. Will this knowledge strengthen the development of geographical psychology?

The paper is focused on the third wave of the pandemic and its comparison with the first wave in terms of the quality of life of university students in Czechia. In the first wave, the society came together, with solidarity being a prominent manifestation. The third wave differed from the first one in medical (vaccination was already available) as well as social terms. The paper has two objectives, the first is to measure the quality of life and related variables in the third wave of the pandemic and to compare the values found in the third wave with those in the first wave of the pandemic. The second objective is to identify which of the factors related to quality of life are predictors of that quality. The hypothesis assumes different measured values of quality of life for men and women. The measurement yielded knowledge of the high value of quality of place and environmental quality, which can enrich the quality of life epistemology on the one hand and geographical psychology on the other. Trust, health, happiness, quality of place, and safety were identified as factors. The measurement revealed the finding of different quality of life values in the third and first wave of the pandemic. While quality of life values increased in the first wave compared to the pre-pandemic period, both quality of life values and factors decreased in the third wave compared to the first wave. The only exception was one factor that we consider to be a winner of the third wave of the pandemic. The factor that declined in all measurements is considered to be the loser of the third wave of the pandemic. The paper concludes with implications derived from these findings.

Social Capital as a Predictor of Quality of Life: The Czech Experience.

In the paper, we understand social capital as a variable that affects the quality of life. A variable whose change affects another variable is called a predictor. The paper is based on Putnam's understanding of social capital with the dimensions of trust, norms and networks. Trust is considered the most important dimension, and for the purposes of the paper social capital is identified with trust. Quality of life is a holistic concept with two dimensions expressing an assessment of satisfaction with life. After society became richer-in the 1960's in the West and, after the collapse of the bipolar world, also in Central and Eastern Europe-the need for quantity was replaced by the need for quality. The paper is focused on Czechia, with social capital as a predictor of quality of life being investigated geographically at the level of districts. According to the research hypothesis, social capital will have a strong influence on the quality of life of residents in Czechia, i.e., it will be its predictor. To test the validity of the research hypothesis, research was conducted. The aim of the paper is to outline the epistemology of social capital from the aspect of quality of life, description of quality of life and then to test the validity of the research hypothesis by measurements. The result of the quantification of social capital and quality of life at the level of districts and their correlation is important from an epistemological point of view for two reasons. The first is to question the generally accepted premise of the position of social capital as a strong predictor of quality of life. The second is the recognition that the premise of the position of social capital as a strong predictor of quality of life applies in the districts with the highest quality of life.

Analysis of Hazard Rate of Municipalities in Slovakia in Terms of COVID-19.

The coronavirus became a phenomenon in 2020, which is making an unwanted but wide space for the study of various scientific disciplines. The COVID-19 pandemic situation which has reached almost the whole civilized world by its consequences thus offers a unique possibility to analyze the graphic space and the human activities inside it. The aim of this study is to predict and identify the potential rate of threat on the example of COVID-19 in Slovakia through an established model. This model consisted of an assessment of the partial phenomena of exposure, vulnerability, and overall risk. The statistical data used to evaluate these phenomena concerned individual cities in Slovakia. These represent the smallest administrative unit. Indirect methods based on the point method were applied in the paper. The spreading and transfer of the disease was influenced much more by the exposure presented by traffic availability, especially, but also the concentration of inhabitants in the selected locations (shops, cemeteries, and others). In the results, our modeling confirmed the regions with the highest intensity, especially in the districts (Bratislava, Kosice, Presov, and Nitra). The selection of the data and method used in this study together with the results reached and presented may serve as an appropriate tool for the support of decision-making of other measures for the future.