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Abstract: The COVID-19 pandemic and related physical distancing measures have disproportionally affected older adults living alone due to their greater social isolation. Unlike previous studies on the subject, the current research recognizes the diversity amongst older adults living alone by considering the impact of marital history. Combining information from Wave 8 of the Survey of Health Ageing and Retirement (SHARE), with data of SHARELIFE and the SHARE Corona survey, we investigated the differential impact of the COVID-19 pandemic on loneliness in older men (N = 1504) and women (N = 4822) living alone. Logistic multilevel analyses were performed on data from 26 European countries and Israel. For men, we found that the short-term widowed were more likely to report increased loneliness than the medium- and long-term widowed and those living apart together (LAT). For women, the results indicated that the short- and medium-term widowed and the divorced were at greater risk for increased loneliness than those in a LAT relationship. Also, medium-term widowed women were more likely to report increased loneliness than their long-term widowed counterparts. The three hypothesized underlying mechanisms – i.e., (i) the opportunity mechanism, (ii) the expectation mechanism, and (iii) the vulnerability mechanism – only played a small role in explaining the observed differences. In sum, our study highlights the importance of recognizing the diversity within the group of older adults living alone when investigating the effects of the pandemic on loneliness, yet the mechanisms behind the stratifying role of marital history are not fully understood.

The Covid-19 pandemic has forced governments to halt public transport operations. A consequence of such disruption is the reduction in access to critical facilities by individuals who rely on public transport for their daily mobility. We investigate the impact disparities caused by the restriction of public transportation on the access of healthcare workers and patients to healthcare facilities during the Covid-19 pandemic. Metro Manila is an appropriate case study site because the duration of suspension of public transport in the mega-city is one of the longest in the world. The prolonged duration of the lockdown could have devastating impacts on the well-being of individuals who are reliant on public transport to access essential services. Guided by the Yin-Eisenhardt approach to qualitative research, we examined the data from 55 individuals using within-case and cross-case analyses iteratively for the purpose of building a model on the impact of change in access due to public transport disruption on well-being. We mobilized constructs and concepts known in the literature, such as well-being, access, disruption, resistance, resilience, and vulnerability, in developing our two-step conceptual model. Given the profound impact of the prolonged and system-wide suspension of public transport on the well-being of individuals, it is necessary to provide sufficient public transport and active transport infrastructure and services that can cover their mobility needs. The two-step conceptual model from this study can provide guidance on specific policy interventions.

This thesis focuses on improving the understanding of the effects of climate and pandemic-related shocks on financial sector variables. Specifically, it aims to contribute to the development of climate risk stress tests, which translate initial climate shock parameters into variables that are relevant to assess financial institutions, such as solvency and liquidity metrics. The main objective in this thesis is therefore to investigate what the relationship is between climate-related shock variables and financial variables, with a focus on financial asset value and financial institution solvency. In the second chapter we provide a conceptual review of climate risk stress testing. In almost all cases, Climate Risk Stress Testing (CRST) combines climate, economic, and financial modelling, but not always through the macro-financial approach traditionally employed by central banks and supervisory authorities. We identify six types of climate shocks and four approaches to CRST (i.e., macro-financial, micro-financial, non-structural, and disaster risk). Findings include that existing CRST exercises may underestimate potential system-wide financial losses, due to their limited scope (e.g., not including all asset classes), incomplete modelling (e.g., lack of feedback effects), and a strong reliance on historically established relationships. Based on the review chapter we identify a novel, micro-financial, approach to assess the effects of carbon tax scenarios on the market value of equity and debt. The third chapter develops this micro-financial approach, based on structural modelling of credit losses in different carbon tax scenarios. We develop a more tractable finance (valuation) approach at the industry-level and use a Merton contingent claims model to assess the impact of a carbon tax shock on the market value of equity and debt instruments. This model is calibrated using detailed firm level vulnerability data and apply the model to 2-digit sectoral exposures of Dutch banks. Findings include declines in the market value of banks’ assets of 3-14% of core capital for a €100 carbon tax shock, increasing to 9-32% for a €200 carbon tax shock. The fourth chapter in this thesis builds on the structural credit modelling developed in the third chapter, but instead of linking the model to climate-related scenarios we employ the modelling to assess the economic shock related to the Covid-19 pandemic. Using a Merton contingent claims framework, the chapter develops a real time market-based approach to assess expected loan losses and apply it to euro area banks’ during the Covid-19 crisis. Although market-based indicators have improved considerably after an initial sharp downturn, they still provide warning signals for a range of (sub)sectors. During the market low point, implied losses on corporate loans amounted to 16-26% of banks’ capital. The chapter also uncovers a substantial role for monetary policy (lower discount rates) in the subsequent stock market recovery. The fifth and last chapter develops an empirical model to assess of the impact of climate-related disasters on loan portfolios. We empirically investigate the local effects (direct and indirect effects in regions where the disaster took place) and non-local effects (indirect effects in other regions in the same country) of climate change-related disasters on non-performing loans (NPLs) in Latin America. In our baseline specification we find that NPLs as a fraction of total loans increase with 1.1-1.4 percentage points (local effect) and 0.9-1.0 percentage points (non-local effect). For national banking systems as a whole, findings suggest that NPLs on average increase between 17-46 percent after a severe disaster.

Background: People with blood cancers have increased risk of severe outcomes from COVID-19 and were prioritised for vaccination. Methods: Individuals in the QResearch database aged 12 years and above on 1st December 2020 were included in the analysis. Kaplan-Meier analysis described time to COVID-19 vaccine uptake in people with blood cancer and other high-risk disorders. Cox regression was used to identify factors associated with vaccine uptake in people with blood cancer. Results: The analysis included 12,274,948 individuals, of whom 97,707 had a blood cancer diagnosis. 92% of people with blood cancer received at least one dose of vaccine, compared to 80% of the general population, but there was lower uptake of each subsequent vaccine dose (31% for fourth dose). Vaccine uptake decreased with social deprivation (HR 0.72, 95%CI 0.70-0.74 for most deprived versus most affluent quintile for first vaccine). Compared with White groups, uptake of all vaccine doses was significantly lower in people of Pakistani and Black ethnicity, and more of these groups remain unvaccinated. Conclusions: COVID-19 vaccine uptake declines following second dose and there are ethnic and social disparities in uptake in blood cancer populations. Enhanced communication of benefits of vaccination to these groups is needed.

International audience

We examine how the experience of time and locus of control influence organizational change in disruptive contexts. Through the cycles of the COVID-19 pandemic restrictions and their relaxations in Turkey, we found that organizations approached change similarly in the short term but differently in the long term. To unpack the mechanism behind these observations, we analyzed in-depth qualitative data from five organizations from March 2020 to September 2021. We reveal that the change process creates time pressure in disruptive contexts, and a time paradox emerges to the extent that the change outcomes increase the available time under time pressure. Depending on their locus of control, individuals either complement organizational change or resist it even more after triggering events that signal the lastingness of the post-disruption situation. Our framework may enhance organizational resilience to future disruptions by highlighting the requirement for change recipients to make complementary moves to regain control.

Abstract With the emergence of high-throughput technologies, computational screening based on gene expression profiles has become one of the most effective methods for drug discovery. More importantly, profile-based approaches remarkably enhance novel drug–disease pair discovery without relying on drug- or disease-specific prior knowledge, which has been widely used in modern medicine. However, profile-based systematic screening of active ingredients of traditional Chinese medicine (TCM) has been scarcely performed due to inadequate pharmacotranscriptomic data. Here, we develop the largest-to-date online TCM active ingredients-based pharmacotranscriptomic platform integrated traditional Chinese medicine (ITCM) for the effective screening of active ingredients. First, we performed unified high-throughput experiments and constructed the largest data repository of 496 representative active ingredients, which was five times larger than the previous one built by our team. The transcriptome-based multi-scale analysis was also performed to elucidate their mechanism. Then, we developed six state-of-art signature search methods to screen active ingredients and determine the optimal signature size for all methods. Moreover, we integrated them into a screening strategy, TCM-Query, to identify the potential active ingredients for the special disease. In addition, we also comprehensively collected the TCM-related resource by literature mining. Finally, we applied ITCM to an active ingredient bavachinin, and two diseases, including prostate cancer and COVID-19, to demonstrate the power of drug discovery. ITCM was aimed to comprehensively explore the active ingredients of TCM and boost studies of pharmacological action and drug discovery. ITCM is available at http://itcm.biotcm.net.

Abstract Although the safety and efficacy of vaccinations have been evaluated through clinical trials, medical experts and authorities are very interested in the reporting and investigation of adverse events following SARS-CoV-2 immunization in the general public. This article reports a 41-year-old man without history of underlying diseases, complaining of continuous morning stiffness and acute discomfort in his left elbow joint, 20 days after taking the first dosage of Sputnik V. The case was extensively studied, and a possible diagnosis of reactive arthritis was made.

Highlight Following the COVID-19 pandemic, there has been a sharp increase in rabies cases and deaths. Rabies outbreaks are being reported worldwide. Multiple disruptions in Rabies control occurred during the pandemic, significantly affecting lower-income countries. Countries need to develop specific action plans to become ‘rabies free’ by 2030.