Bogdan-Constantin Ibanescu (p), Mioara Cristea, Alexandra Gheorghiu, Gabriela Carmen Pascariu

Dani Broitman

As the COVID-19 pandemic hit the European continent at the beginning of 2020, one of the most significant socio-economic effects that immediately become the central focus of media and governing bodies was the unemployment and the sudden transformations suffered by the job market. This effect created major concerns for citizens and governing structures, as the pandemic generated a new and unparalleled economic context, where the short and medium-term future of several sectors seemed unpredictable. The concern acted upon the job insecurity of individuals, a perceived threat to the continuity and stability of their employment.
Based on a self-reported survey covering the first pandemic wave, our study classifies the regions (NUTS2 level) from six EU countries according to their performance in terms of job insecurity, but also the shock intensity (death rates and case fatality ratio), and identifies the overall over and under performers. The results show that the regional evolution of the job insecurity could be linked to the pandemic evolution, especially in the stronger economies. However, the model does not follow a classic economic core-periphery pattern. The model is challenged especially by a stronger performance of several less performant regions from Italy, Romania, or France.

Dani Broitman (p), Yakov Ben-Haim, Natalia Rybnikova, Murielle Mary-Krause, Maria Melchior

Bogdan-Constantin Ibanescu

Questionnaires are among the most basic and widespread tools to assess the mental health of a population in epidemiological and public health studies. Their most obvious advantage (first-hand self-report) is also the source of its main problems: the raw data require interpretation and are a snapshot of the specific sample’s status at a given time. Efforts to deal with both issues created a bi-dimensional space defined by two orthogonal axes, in which most of the quantitative mental health research can be located. Methods aimed to assure that mental health diagnoses are solidly grounded on existing raw data are part of the individual validity axis. Tools allowing the generalization of the results across the entire population, compose the collective validity axis. This paper raises a different question. Since one goal of mental health assessments is to obtain results that can be generalized to some extent, an important question is how robust a questionnaire result is when applied to a different population or to the same population at a different time. In this case, there is a deep uncertainty, without any a priori probabilistic information. The main claim of this paper is that this task requires the development of a new robustness to deep uncertainty axis, defining a three-dimensional research space. We demonstrate the analysis of deep uncertainty using the concept of robustness in info-gap decision theory. Based on data from questionnaires collected before and during the Covid-19 pandemic, we first locate a mental health assessment in the space defined by the individual validity axis and the collective validity axis. Then we develop a model of info-gap robustness to mental health assessment, showing how the robustness to deep uncertainty axis interacts with the other two axes, highlighting the contributions and the limitations of this approach.

Emil Israel (p), Tal Feder

Dani Broitman

Cities’ planned and built environments are key to healthier communities. Cities are regarded as a sustainable form of settlement. The Covid-19 pandemic challenged this relationship, when the issue of communities' compliance with government restrictions to mitigate the spread of the pandemic became apparent. However, the pandemic provided a chance to further enhance cities’ resilience, since identifying community characteristics that motivate individuals to follow health-promoting regimens became a key topic for social research.
Despite the growing literature on such relationship, little attention has been paid to the drivers of compliance at the city and community levels. Our study addresses this lack through the Bourdieusian concept of communities' capital resources. The study investigates how economic, social, and cultural capital, as well as its spatial distribution, can be used to explain the factors influencing compliance with limitations and recommendations for the promotion of public health. According to this approach, the 'habitus of place' is a set of dispositions formed by the idiosyncrasies of local communities. By defining local capital forms, local habitus can be measured.
By using Israel as a test case, we employed a data reduction technique to assess these capital forms, utilizing several factors pertaining to population characteristics and municipal budgets. Israeli cities have emerged as the key players in determining morbidity and establishing differential limitations during the outbreak of the pandemic. The investigation specified measures of capital forms at the community level across the country. It allowed to build regression models that estimated the relationship between capital and adherence to the limits implemented to curb the pandemic.
The analysis revealed how the spatial dispersion of the components of these capitals explains the likelihood of communities’ level of compliance. The results indicated that each of the capital forms contributed significantly to a greater compliance with health regulations. Some of the disparities in responsiveness across various groups in Israel can be attributed to the spatial dispersion of capital forms.
Connecting sociology to geo-urban variations in compliance with Covid-19 laws during the pandemic might shed light on the social mechanisms that drive health behaviors, as well as human practices that may influence morbidity and mortality rates. The study's findings in this regard highlight the explanatory power of local resources in collective spatial behavior patterns and the potential for escalating existing injustices, as well as the significance of the social-community component in dealing with risk situations in general and the COVID-19 pandemic in particular.

Dani Broitman (p), Nataliya Rybnikova

Emil Israel

Increasing evidence suggests that characteristics of environments where individuals live, such as their residential neighbourhood, are associated with mental health patterns. The specific research questions are two: To what extent do neighbourhood characteristics influence individuals’ mental and psychological well-being in the context of the COVID-19 epidemic? In particular, are there locational and urban characteristics that may alleviate mental health distress? To this end we study spatial associations between mental health disorders and individual and region-specific socio-economic characteristics of respondents before and during the COVID-19 pandemic. The results suggest that the interaction between individual characteristics and mental health disorders are mediated, at least partially, by the characteristics of the local environments where individuals live. However, the strength of these correlations depends also on the period characteristics. In normal times, neighbourhood characteristics seem to be influential. In emergency times, like during the Covid-19 pandemic, the characteristics of the urban (or even the functional urban area) become more important.