Research Luxembourg: Results FNR COVID-19 Call

Corona viruses are constantly roaming the human population and are one of the causes for the common cold. SARS, MERS and COVID19 present more severe flu-like symptoms extending these symptoms to respiratory distress. Secondary symptoms include kidney problems, cardiovascular problems, diabetes and neurological signs, like headache and nausea. In the case of the SARS infection, it has been shown that the virus can invade the central nervous system in patients and laboratory animals. For COVID19, hyper-inflammation (“cytokine storm”) has been shown to be associated with disease severity and an increased mortality risk. Importantly, therapeutic approaches with inhibitors of cytokines like Tocilizumab, an interleukin (IL)-6 receptor antibody, have yielded first promising results. The infection of epithelial cells by a coronavirus will lead to a change of the cellular protein composition in response to the virus’ ability to rewire the protein production and regulation. Virus-induced cell rupture leads to the release of proteins to the serum changing its composition. The released proteins in the serum are specific to certain cell types and will reveal proteins that indicate damage to specific tissues, in case of SARS: kidney, neurons and lung tissue. In this proposal, we aim at identifying proteins sets which indicate damage to secondary tissues. Moreover, we will investigate levels of cytokines and other inflammatory markers. We thereby expect to identify (sets of) diagnostic markers for the identification of high-risk patients which may further provide information about the best suitable treatment options.

The current COVID-19 pandemic caused by the SARS-CoV-2 virus is an extreme challenge to mankind’s health affecting currently more than 1.7 million people world-wide. Current approaches to manage this challenge rely on reliable testing as well as the development of vaccination which both depend on the stability of specific sequences of the viral genome. Sequencing of viral genomes from patient samples provides deep insights on pathogen dynamics in terms of phylogeny and evolution allowing for spreading analysis and adaptation of molecular diagnostic and prevention strategies. Hence, the real-time monitoring and automated dynamic analysis of phylogenomic data derived from virus genome sequencing together with available geographical and clinical data in an accessible and portable manner is key to support decisions in research, diagnostics and physiology, which strongly impacts individuals and societies within and outside Luxembourg and is also important as a health monitoring resource for possible similar future events. In the frame of the planned COVID+ study, the Co-PhyloDyn project will lay the foundation of the retrospective in-depth genomic characterization of COVID-19 positive cases over the COVID-19 pandemic in Luxembourg and its neighbouring countries by implementing an efficient fully automated and reproducible infrastructure for the phylodynamic analysis of COVID-10 in Luxembourg. The close collaboration between the Luxembourg Centre of Systems Biomedicine (LCSB) at the University of Luxembourg and the Department of Microbiology at the Laboratoire National de Santé (LNS) will bring together the needed expertise in genomics, bioinformatics, sequencing and virology to tackle the needed in-time phylogenetic analysis of COVID-19 in Luxembourg.

Since March 11 2020, the world is facing a large-scale pandemic with the COVID-19 outbreak affecting more than 1.7 million individuals globally. The SARS-CoV-2 fatality rate has been maintained at a low level thanks to countermeasures established in many countries, in particular, physical distancing to limit the infection rate and the enormous effort of nursing staff. Yet there is a major risk of overwhelming health care systems, which would lead to a dramatic increase in morbidity. Several risk factors for developing a severe pathology have been identified to date: sex, age, obesity, diabetes, hypertension and cardiovascular disease. Co-infections have been reported in several Chinese studies, but have not been examined systematically. In the frame of the PREDICOVID study, the CO-INFECTOMICS project aims to understand if apart from SARS-CoV-2, co-infections are a predictive marker of disease severity in COVID-19 positive patients in Luxembourg. To achieve this, our project will compare the taxonomic microbial composition as well as the functional potential and transcriptional activity of the respiratory and intestinal tract microbiota of 60 mild and 60 severe COVID-19 patients with a non-targeted approach. Nucleic acids will be extracted from sputum, nasal/oropharyngeal swabs, and stool samples using in-house established protocols, which will be optimised for bacteria, fungi and for virus detection at once. To examine co-infection or potential co-carriage, metagenomic and metatranscriptomic analyses will be performed using our multi-omic computational pipelines, i.e. the Integrated Meta-Omic Pipeline (IMP) and PathoFact, amongst others. Multi-omic microbial profiles, covering viruses, bacteria, and fungi, will be generated and compared between mild and severe patients. Furthermore, the taxonomic composition as well as the functional potential and transcriptional activity of the upper and lower respiratory tract will be compared, using sputum and nasal/oropharyngeal swabs derived from the same patients, at two time points. The respiratory and intestinal microbial profiles will be associated to the immune response and clinical data to detect links between co-infection and disease severity. CO-INFECTOMICS aims to determine microbial markers which could be used in clinics and, thus, to support the stratification of high-risk patients.

The world wide scientific response to the COVID-19 pandemic is reflected in the ever-growing scientific literature. Enriching our current knowledge base (https://biokb.lcsb.uni.lu) with these publications requires joint efforts at each stage of the chain of process involved in the text-mining pipeline. This pipeline comprises several challenging tasks such as part-of-speech tagging, entity recognition and normalisation, or event extraction, which are essential to discover relevant knowledge in the form of entities, relations and events. Such knowledge is then made available to the public via semantic web technologies and curated through collaborative curation interfaces. This literature growth calls for updated ontologies to cope with the new terms and biological entities, more robust event extraction and named entity recognition, as well as further development of our collaborative curation interface and search tools. In this project we are building a knowledge base with relevant cross-domain events and relationships from available COVID19 publications can help in-silico and in-vitro researchers navigate the growing COVID-19 literature corpus.

The Cardiovascular Research Unit of Luxembourg Institute of Health proposes to apply its know-how on RNA biomarkers to identify circulating microRNAs (miRNAs) able to predict COVID-19 severity. This project is included in COVID-19 Task force WP02 and aims to fulfil the medical need of identifying patients at high risk of developing complications after infection by SARS-CoV-2 virus. The discovery of novel prognostic biomarkers will help tailoring healthcare to each individual for patient’s benefit. Considering the importance of the inflammatory storm on disease severity and patient outcome, we will first focus on inflammation-associated miRNAs. Knowing that one fifth of infected patients die from cardiovascular cause and not respiratory issues, we will also study miRNAs known to be related to cardiovascular disease. We will measure circulating levels of inflammatory and cardiac miRNAs by quantitative RT-PCR in plasma samples collected at admission in patients of the Luxembourg Predi-COVID study, and we will determine their ability to predict disease severity based on symptoms at 3 weeks (mild versus severe). We will use plasma samples from the first 100 patients enrolled in Predi-COVID study to allow project completion within 6 months. This pilot study is in line with the National Research priorities, with the Research priorities defined by the WHO’s Coordinated Global Research Roadmap (“need to implement diagnostics to improve clinical processes”) and by the European Commission (“tackle the spread of coronavirus and preparedness for other outbreaks”). It is the initial phase towards a large multicenter international study with members of the EU-CardioRNA COST Action COVID-19 Task Force.

While COVID-19 is mainly considered an airway and lung disease, up to 79% of patients present with gastrointestinal symptoms and recent studies report on the presence of SARS-CoV-2 viral RNA and particles in stools of infected patients, suggesting that the gastrointestinal (GI) tract may have a more important involvement in disease pathology than previously thought. The GI tract is also the site of the dense and diverse microbiome, which has the ability to regulate intestinal and systemic immunity through the conversion of dietary nutrients into bioactive metabolites. Consequently, perturbations in the microbiome composition may drive susceptibility to or participate in worsening disease pathology. This project aims at functionally characterizing the COVID-19 patient gut microbiome at the genomic and metabolic level in order to highlight a disease susceptibility signature and consequences for immunity to SARS-CoV-2. To this aim, we propose to collect stools and blood from COVID-19 positive individuals in the framework of existing CON-VINCE and PREDI-COVID cohort studies. Through metagenomic and metatranscriptomic sequencing of the DNA and RNA extracted from stool samples, we will characterize the strain-level taxonomic composition and functional capacity with respect to the carbohydrate-active enzyme (CAZyme) repertoire of the gut microbiome. Due to their documented role in immunomodulation, especially in the context of viral infection, we will also quantify levels of short-chain fatty acids in stools and sera. We will investigate the association of these metabolic markers to key antiviral immune pathways in the peripheral blood. The results will be paralleled with dietary habits and medical information to define disease susceptibility profiles in the healthy population, as well as outcome prediction models in diagnosed patients.

There is currently is no vaccine and no specific antiviral agent against coronaviruses. Existing antiviral drugs against other viruses are being repurposed to treat COVID-19 patients as best we can. In many countries including Luxembourg, hospitals might face a shortage in medication on top of hospital saturation and economic lockdown. Therefore alternative treatment options are urgently needed and many efforts are being deployed to develop a vaccine against SARS-CoV-2, the new Coronavirus causing COVID-19. Nevertheless, little is known on immunity against SARS-CoV-2 and on the efficacy and persistance of the antibody response. Passive immunization of patients with severe or critical COVID-19 using the plasma from recovered patients (plasmapheresis) is one approach considered to test COVID-19 patients. It has been used in the past to treat other lethal viral infections such as SARS, Flu, Ebola. Clinical protocols of plasmapheresis to treat COVID-19 are being launched in the US, in France and at Centre Hospitalier de Luxembourg (CHL). This project aims to develop a high througput assay to measure the neutralizing activity of plasma and antibodies against SARS-CoV-2. It will be used in the short term to assist CHL by identifying plasma from recovered COVID-19 patients with high neutralizing activity for plasmapheresis. It will also be used to identify which antibodies have neutralizing activity, thereby providing a rationale to predict patient outcome. On the mid-long term, it will be used to follow the effectiveness, duration and waning of neutralizing antibodies in patients recovered from COVID-19 and in vaccinated individuals when a vaccine becomes available. Additionnally, it can be used to screan for entry inhibitors, such as Hydrodychlorquine, Lopinavir/ritonavir or novel compounds. It will thus be a useful tool for projects in the COVID-19 Task Force.

Almost all Coronaviruses (CoVs) affecting human, including human CoV-NL63, -229E, -OC43, SARS-CoV and MERS-CoV, have a zoonotic origin. Similarly, phylogenetic and recombination analyses strongly suggested a zoonotic origin for SARS-CoV-2. After adaptation to human, some zoonotic viruses retain the capacity of infecting animals, as regularly shown for influenza A virus. There is a raising concern that SARS-CoV-2 virus may have a host switching potential as well. Anecdotic cases already suggest that Canidae and Felidae are susceptible to SARS-CoV-2 infection. Experimental intranasal infections in ferrets and cats were successful and several other species also express ACE2 virus entry receptors. After reverse zoonosis events, selection pressure during circulation in animals that are not dead-end hosts may lead to new genetic and antigenic variants, constituting a potential threat for public health. Therefore investigating the role of domestic and livestock species in SARS-CoV-2 epidemiology is absolutely essential to inform current virus containment and elimination measures. This project thus aims to (i) assess the prevalence of symptomatic and asymptomatic SARS-CoV-2 infections in domestic animal species; (ii) identify the factors promoting inter-species transmission; (iii) investigate the role of domestic and livestock animals as dead-end hosts or virus hosts able to sustain virus circulation through viral strain characterization; (iv) provide recommendation to public health authorities to assist their effort in SARS-CoV-2 containment and elimination.

Currently no vaccine or sufficiently validated pharmacological treatment is available for COVID-19. Drug-based strategies to reduce the viral load in patients with severe forms of COVID-19 include the repurposing of existing small molecule compounds that inhibit the activity of key viral proteins, or human proteins involved in mediating viral entry or release from the host cell. However, so far, the identified small molecule inhibitors for SARS-CoV-2 target proteins studied in -vitro have limitations in terms of either their binding affinity for the target protein, their bioavailability in the lung, known adverse effects, and high manufacturing costs. We therefore propose a combined computational and experimental approach to rank alternative candidate known drugs, antivirals and natural compounds, which are commercially available, inexpensive, and known to be safe in humans. We will focus on assessing , in terms of their ability to selectively bind to and inhibit the SARS-CoV-2 3CL protease (target 1), which is essential for viral replication, or the human protein TMPRSS2 (target 2), which is essential for viral entry into the host cell. For this purpose, we will screen and filter in silico x M~10k compounds using molecular docking and machine learning based lung bioavailability estimations, and conduct molecular dynamics simulations for refined binding affinity estimation of the 100 top-ranked compounds. The top 20 compounds per drug target in terms of predicted binding affinity will be validated experimentally in -vitro and cellular assays. As part of our prior work, we have already identified natural compounds which are safe in humans, reported to inhibit the replication of SARS-CoV (the predecessor82% identical to SARS-CoV-2, from the 2002/2003 outbreak), and for which our molecular docking and binding affinity estimation analyses predict similar inhibitory effects for the ortholog protein from SARS-CoV-2. This will enable us to start quickly with the first validation experiments for assessing ligand-binding, while selecting further candidate compounds in parallel through the computational screening., while conducting computational predictions for further candidate compounds in parallel. In summary, this project will provide a fast experimental validation of drug repurposing candidates for COVID-19 from a computational pre-selection of antivirals, drugs and natural compounds that are inexpensive, have known safety properties and high predicted bioavailability in the lung. These studies would pave the way for a quick progression to follow-up efficacy testing against virus infectivity in collaboration with a BSL-3 certified laboratory.

Among people infected by SARS-CoV-2, significant disparities have been observed regarding the severity of the symptoms. Although some factors such as the presence of comorbidities have been pointed out, for another part of the patients the high severity of the symptoms remains unexplained. The HorCoVIS project aims at assessing how the hormonal status of the patients prior to infection could be linked to symptoms` severity and possibly used as a predictive tool that will ultimately enable the prompt implementation of specific therapeutic measures in newly infected patients.

Receptors for entry of SARS-CoV-2 into lung pneumocytes belong to the renin-angiotensin system (RAS) and diseases that are associated to a dysregulation of the same system (e.g.: diabetes, hypertension, and cardiovascular diseases) are thought to be associated with a bad Covid-19 prognosis. These receptors are also expressed on cells of the immune system, which is involved in diseases associated to RAS dysregulation. Our project plan to employ an integrated mass spectrometry / flow cytometry approach to build a quantitative map of the RAS, at the peptide and protein level together with a single cell analysis of the immune cells in individuals infected by the SARS-CoV-2. The aim of the project is to use this integrated map together with data and metadata generated by running clinical trials to find correlations to Covid-19 prognosis. We expect to build a mechanistic model on how viral infection modulates the RAS, the immune system, and the expression of the receptors. Finally, we wish to find a potential biomarker for Covid-19 prognosis by a simple flow cytometric assay transferable to the clinic.

The current situation of lock-down in many countries creates a strong need for large screening efforts in order to assess the immune status of the population and to advice decision makers on measures to relaunch social and economic activites. Due to the critical need for serological testing on high numbers of individuals over several months, shortages are predictable and a major threat to society. The present proposal aims at the setup of a high-performance and flexible diagnostic assay using an immunodetection technique and recombinant viral surface proteins expressed and purified in Luxembourg, which can be readily adapted to changing needs, such as the inclusion of newly emerging specific virus strains in routine testing or the targeted monitoring of immune response kinetics in clinical studies.

The gold standard for Covid-19 diagnosis is RT-PCR for SARS-CoV-2 from the upper airways. This method suffers from decreased accuracy in more severe disease stages affecting the lower airways. False negative PCR tests in severe cases impose a massive risk to the health system, promoting intra-hospital disease spread in the actual pandemic situation. Reports from China indicate false negative PCR from upper airway samples in severe Covid-19 pneumonia in more than 50% of the cases. Therefore, complementary tests for the detection of these dangerous cases are urgently needed. The value of chest CT and/or X-ray has been demonstrated as complementary diagnostics. Luxembourg has already reacted to these needs, and is urgently acquiring four additional CT scanners only for lung CTs. Based on our experience in deep learning for medical imaging our project aims to rapidly provide AI tools to speed-up diagnosis of high-risk cases from medical imaging. Our short-term objective is a an AI tool for fast and accurate discrimination between Covid-19, other pneumonia, or healthy. This information can be key for early treatment as well as for the safety of health workers, hospitals and other patients. A basic version of an AI tool is already in training and aims to be applied as soon as possible during the current pandemic. Additionally, long term research and preparation to future scenarios is planned and will be integrated with diagnostic approaches using other biomarkers for disease staging by aligning with other groups in Luxembourg.

We propose the development of an integrated web-based data exploration tool for genomics, proteomics, phylogeny, evolutionary and geographical data on SARS-CoV-2 samples from Luxembourg supporting researchers and physicians to gauge the potential impact of viral evolution on virulence and transmission dynamics but also the efficacy of molecular detection methods. We believe that integrating different data sources and visualisation modes through a graphical web-interface will offer a unique perspective on the pathogen and serve as crucial tools to assess potential imminent risks. Our tool will enable researchers, clinicians and the general public to visualize and study different aspects of the evolutionary dynamics of the virus from most recent datasets using a single interface, reducing the need of cross-referencing and comparing different resources.

Logistics is an essential activity in general and even more so during the COVID-19 pandemic. Lockdowns and other restrictive measures (e.g. border controls) have severely slowed down the flow of goods and forced the European Commission to call on EU Member States to keep transport flows moving to deliver critical goods. The project will deploy a “national control tower” to assess and monitor the status of the logistics networks and essential supply chains, so to try and take corrective measures aimed at preventing collapses in essential services and other economic activities. Driven by LCL and LIST, Research Luxembourg reacted by providing in a matter of days a first weekly survey for transporters and logistics operators and is currently working on a second survey to collect data on the functioning of supply chains. The public agency INCERT hosts the surveys and provides basic visual analytics through a pre-existing dashboard that has been adapted to the need. To support decision-makers in selecting the right approach, LIST, LCL and INCERT will take advantage of the Digital Twin technology that Gartner ranks among the top 10 Strategic Technology Trends of the last three years. In the six months covered by this project they plan to adapt the two surveys following feedback from the user communities and the potential evolution of the crisis; improve the data analytics and visualisation tools as much as possible; start collecting requirements for a more sophisticated platform that should be able to automatically import data from external systems (e.g. ERPs), offer enhanced analytics and visualization functionalities as well as rapid alerts to its users via a dedicated mobile app. Finally, they will design, test and validate a prototype of the dashboard and the mobile app.

The PandemicGR project will address of the challenge of understanding and analysing the information diffusion mechanism in online social media during the COVID-19 pandemic, based on a newly collected and properly anonymised Twitter dataset concentrating on Luxembourg and the greater region. In this project, we aim to (1) achieve in-depth analysis of user engagement and communication patterns during this public health crisis, (2) build a machine learning model to simulate and predict COVID-19 information cascades, and (3) develop an effective classifier to detect misinformation in order to improve information trustworthiness in online social media. The results from the PandemicGR project will have both immediate and medium-term impact for crisis management for bother Luxembourg and the greater region.

REBORN is a data science project that focuses on the challenge of ensuring sustainable economic recovery in the face of COVID-19. The project team will apply advanced Machine Learning, business ecosystem modelling (i.e., expert knowledge) and simulation techniques to yield recommendations of economic actions given different scenarios in which the lockdown is relaxed, partially or totally lifted. By interacting with other teams of the Luxembourg Task Force, this project targets high impact for the various sectors of the Luxembourg economy, by providing appropriate data-driven recommendations for political decision-makers. We expect that REBORN could answer important questions such as: What are the industrial sectors to help in priority? What are the sectors that should be restarted first? What are the possible changes in consumer habits and the impact of neighboring country decisions on commuters?, etc. Ultimately, REBORN contributes towards reflections on initiatives to limit the spread of the future economic crisis due to COVID-19 as well as avoid worsening future waves of coronaviruses.

The aim of this project is to provide a platform to run a comprehensive analysis on the Social Distancing measures decided by the government in the context of the COVID-19 pandemic. To do so we propose to analyse anonymised video data in the city of Luxembourg. The first step will be to anonymise the video feed by using well known Artificial Intelligence (AI) models (face blurring). In a next step will use other AI models to identify pedestrians and groups of individuals, calculate their relative distances and overall density. Those metrics can then be evaluated over time for different locations and provide valuable insights on the greater or lesser risks of infection spreading based on behaviour. The rules can be used either to inform where the police need to focus their efforts in enforcing rules, or to inform and influence the public’s actions (or both).

This project aims at facilitating exit strategies that incorporate access control to the public space, border crossings, and critical areas. The strategies are based on the individual COVID-19 immunity and/or infection status. Also, the project will investigate the implementation of contact-tracing apps in Luxembourg, which clearly is an essential component of a successful exit strategy in order to backtrack and contain the infection. The smart access control system can be based on passports, ID cards or smart cards. We will propose a mechanism, produce a prototype implementation, and present a preliminary formal analysis of access control solutions for exit strategies. While it might be necessary to waive users’ privacy in order to efficiently contain the epidemic, we will look for mechanisms that waive it to the least possible extent. In this sense, the focus of the project will be on preserving privacy, unlinkability and GDPR compliance for the access control system. Further, contact-tracing apps with minimal privacy disclosure will be investigated, especially the DP-3T proposal from PEPP-PT.

In the current COVID-19 crisis, older adults are at particular risk for severe health outcomes and increased mortality. Whereas it is of prime importance to raise public awareness regarding the special risk of older people, and reduced in-person contact is essential to protect vulnerable groups, we have to take into account what effects these measures have on subjective well-being, mental health and further development of older persons. The present research project will tackle the question of how current measures and their communication to the public are experienced by the target group (60+) and will focus on the psychological and behavioral correlates and outcomes. In particular, the following questions will be addressed: 1) How are claims of being a risk group and COVID 19 related ageing stereotypes incorporated in views of self and others and how are they related to psychological and behavioral consequences, e.g. regarding the experience of self-efficacy and agency? 2) How is subjective risk experienced and how do older people commit to protective measures and guidelines, also depending on their self-views? 3) How can the risk for social isolation and loneliness be reduced? This includes the availability of appropriate information and communication channels? 4) What are resilience factors that protect older adults from negative mental health outcomes and help to maintain subjective well-being? Results will inform policies related to controlling the virus and information strategies to ensure compliance with the measures, especially (but not only) in the at-risk population of older adults. Furthermore, the project will contribute knowledge to reduce negative side effects of the preventive measures for older adults’ long-term autonomy, health, and well-being.

Whereas young people have a low risk for severe illness due to COVID-19, they are an important link in the transmission chain and they might find it particularly hard to accept and comply with governmental guidelines and measures to prevent and control the disease. Some of the measures may further interfere disproportionally with their development and result in short- and long-term consequences for education, professional careers, economic situation, psychosocial development, and mental health. Our project will generate the knowledge required to address the current and post-pandemic challenges of the COVID-19 crisis, by (1) focusing on how young people residing in Luxembourg comply with and accept the governmental measures to prevent and control infection with COVID-19 and (2) by identifying the economic, psycho-social, and health consequences of these measures during and after the COVID-19 pandemic in relation to a pre-pandemic baseline we were able to collect in 2019. Inequalities between and within socio-demographic and socio-economic groups in relation to (1) and (2) are of particular interest. To evaluate the situation during and after the pandemic, two intermediate waves (2020 and 2021) are added to the 2019 and 2023/24 waves of the Youth Survey Luxembourg. The Youth Survey Luxembourg is a representative large-scale survey among 16- to 29-year-old residents in Luxembourg, covering all relevant areas outlined above (e.g., education and employment, social situation, health, etc.). COVID-19-specific modules, for example on compliance with measures, will be included to provide vital information for the control of the COVID-19 pandemic. Statistical comparisons of recent data with pre-pandemic baselines will enable a broad and thorough assessment of the short-term, mid-term, and long-term impacts of the COVID-19 crisis on the lives of young people. Results will be made available to the public and the research community on a rolling basis. Furthermore, the evidence generated will inform policy-making in Luxembourg and contribute to address various key research priorities identified by the WHO.

The COVID-19 pandemic is still ongoing in Luxembourg and neighbouring countries. It is hoped that due to confinement measures the number of infected persons and deaths will decline in the near future. Largely unknown are the short- and medium-term socio-economic impacts of the pandemic on work and employment, daily activities and mobility, and (not directly COVID-related) health and health behaviours. To understand these impacts, a data collection is necessary. This will allow thorough analyses, designing appropriate and tailor-made policy measures to avoid or mitigate detrimental wider impacts of the COVID-19 outbreak, and combating social inequalities. Starting the data collection is an urgent priority right now, to form the basis of any evidence-based research to inform policy in this area. Public authorities in Luxembourg are considering to relieve the confinement measures to ‘unlock’ parts of economic and social life in the country as soon as the pandemic is becoming less severe and more ‘manageable’. As Luxembourg is currently still in the stage of confinement and has not yet entered the EXIT stage, this is the right time to start collecting data on the social, economic and health impacts of the pandemic. Two methods for data collection will be applied: an online questionnaire and an activity-mobility App for smartphones. People living in Luxembourg as well as cross border commuters will be asked (on a voluntarily basis) to participate in three stages of the pandemic: peak phase, post-peak phase and post-pandemic phase.

The COVID-19 pandemic is a global crisis, but its local impact on Luxembourg will be determined in part by how people memorialise its effects in the moment, and how they will remember it later. Luxembourg declared a state of emergency on 18 March which dramatically reshaped public and private life. Schools, businesses and shops are closed. Students stay home and learn online. New rules govern home workers and cross-border commuters. With no end yet in sight, it is already clear that we are experiencing an extraordinary moment in the collective memory of Luxembourg. With the online platform #covidmemory, the Luxembourg Centre for Contemporary and Digital History (C2DH) at the University of Luxembourg will offer people living or working in Luxembourg the opportunity to share their personal experiences with one another and to archive them for future generations. Contributors can post their photos, videos or stories on an open web-based platform from their personal computers or mobile devices. A team of reviewers and curators will oversee the website in the coming weeks and months. The #covidmemory project is inspired by the “Rapid Response Collecting” approach that has been used in public history and museum circles as a way to collect the stories, material culture, digital creations and ephemera of historical events as Hurricane Katrina, 9/11 and the 2015 terrorist attacks in France.

During pandemics, hospital guidelines regulate admissions and treatment in case of congestion. These guidelines prescribe the allocation of beds and intensive care units (ICU) based on trade-offs between different moral principles. Despite being discussed extensively in the medicine and philosophy literature, these trade-offs are rarely discussed in the media, and little is known about the views that citizens have about it. We study how people view these moral trade-offs and whether the prevailing moral principles change with the escalation of the COVID-19 pandemic. To do this, we conduct a series of surveys in samples of the U.S. population exploiting the temporal and geographical variation in the outbreak of the COVID-19 pandemic.

The LEGAFIGHT project proposes a strategic assessment of the existing legal framework to be respected both at the EU and domestic level (compliance with the GDPR) to fight the spreading of the virus through tracking applications. It will also consider the already existing legal measures taken by foreign legislatures. It aims, as a first step, to provide the Luxembourg with a specifically socially and ethically tailored legal regime for tracking applications, leading to the drafting of a legislation, which could be proposed, as a second step, as a European and global model system in the frame of a longer-term project of epidemiological data management.

Luxembourg is one of the countries with the highest household leveraging on private debt and mortgage loans. For ensuring financial stability in Luxembourg after the income disruption due to the COVID-19 lockdowns, it is crucial to examine if the COVID-19 shock caused a critical increase in the number of households that have not been able to service their mortgages. An additional crucial aspect of the problem is to study the extent to which banks in Luxembourg and the EU face a risk of increased nonperforming loans. The ability to detect threats of nonperforming loans to banks in a timely manner allows for developing policies that can tackle the financial instability problem. The project will have two parts. The first part will focus on collecting and analyzing data before and after the COVID-19 crisis. The second part will develop simulated household-finance models that can investigate a number of out-of-sample questions and policy questions. The central evaluation question is to predict how income losses due to the COVID-19 lockdown can influence nonperforming loans and how nonperforming loans can cause pressure on the banking system. Because Luxembourg is a very open economy having its banking system exposed banking-sector risks in Europe, studying this question problem both in Luxembourg and in other EU countries, is necessary and insightful. The policy questions involve studying whether, (i) extraordinary aid to households for meeting their mortgage responsibilities and (ii) aid to banks for tackling their nonperforming-loans problems, can avoid bank/household insolvency and a possible collapse in the housing market. In order to ensure that up-to-date post-COVID-19 data can be collected, a team from the Dept. of Finance, U Luxembourg, will collaborate with researchers from STATEC and the Austrian Institute of Economic Research (Wifo), Vienna. Beyond data collection and analysis, computer simulations of household-finance models will guide predictions and out-of-sample policy analysis.

Analyzing, understanding and determining the influence of the current health crisis on teleworkers’ well-being, motivations and productivity and efficiency of online collaborations that keep firms performant is essential to support the workforce for the current and future economic challenges, and turn them into opportunities. Indeed, in parallel with the current COVID-19 health crisis, the labour market is undergoing profound changes linked to the digital transformation, which will increase in the future (i.e. job replacement, new tasks to require digital skills). An increased use of digital tools at the workplace is not yet real for all organizations. While, for many years, the obstacles to voluntary efforts to switch to a generalized use of digital tools where huge (e.g. lack resources, training, incentive in terms of bonuses) the current lockdown has the power to change the situation. Whereas the use of current communication tools such as emails induces drawbacks for workers (e.g. infobesity), the upskilling to use more efficient collaborative tools (e.g. Microsoft Teams or Slack) will be beneficial for both workers and firms. Finally, if the telework period appears beneficial for both workers and firms, after the lockdown, the challenge will be to create a common framework in the Greater-Region to favor it.

Since the recent outbreak of the COVID-19 pandemic, a growing body of scientific literature has reported on the pre-infection viability and stability of the SARS-CoV-2 virus, qualitatively indicating the role of physical surfaces in transmission of the virus. The nature of the surfaces (e.g., paper, plastics, glass, or metals) and their properties (smooth v/s rough), are believed to play a critical role in determining the viability during the pre-infection phase. Virus-surface interactions are inherently physical in nature wherein dynamics of the environmental parameters (variations in temperature or humidity over time) could underpin the viral viability. Here, using non-pathogenic mutant of SARS-CoV-2 virus as our model organism, we will uncover key physical parameters that underpin viability of SARS-CoV-2 species on a range of commonly used surfaces. Enzyme-linked immunosorbent assay (ELISA) for S proteins, the material forming ‘spikes’ of the coronavirus will be used to test the surface-specific viability, and complemented by flow virometry and high resolution visualization of the chosen material surfaces (using AFM, SEM and fluorescence imaging), providing quantitative estimation of viral viability. Crucially, time series analysis of viability and concomitant changes in the chemical signature of the material surfaces (FTIR method), will give us unprecedented insights into the mechanistic underpinnings of surface-specific viability of coronavirus, under steady state and dynamic changes in temperature and humidity parameters. The data obtained from this three-pronged approach will be used to biophysically model the system, with a long-term goal of incorporating machine learning methods to identify surface-specific viabilities of virus species. In summary, by revealing the fundamental biophysics of virus-surface interactions, V-SIDE will be in a robust position to develop an integrative mechanistic framework for SARS-Cov-2 viability on various material surfaces. V-SIDE benefits from an active follow up strategy, wherein the overarching goal will be to develop generic recipes for tailoring anti-viral surfaces in a scalable and facile manner, equipping us ultimately to better tackle the recurring incidence of novel viral pandemics.

Viranostic aims at delivering a label-free diagnostic platform to detect Viral RNA (SARS-CoV-2) in symptomatic and convalescent patients. We propose a chip-based platform for POC diagnostics with technology based on two well-established label-free techniques, namely, Nanowire Field-Effect Transistors (FET), and Local surface plasmonic resonance (LSPR) sensors to push the limit of detection to allow direct detection of viral genomic RNA without nuclei acid amplification reducing also the time to test results to minutes. The proposed developments would leverage on expertise drawn from recently concluded projects, PLASENS (FNR-CORE), NANO-PH (FNR-Attract), and ongoing project ELECTROMED (FET-Open, H2020, coordinated by LIST). The proposed LIST technologies for the label-free biosensing are uniquely positioned to deliver sensitivity together with scalability compatible with industrial production. The platform will be compatible for multiplexing (> 50-plex), providing a differential possibility to monitor viral genomic drift during an outbreak to provide an increased resolution of anti-COVID-19 immune response over current diagnostics, with anticipated benefit to prognostics and monitoring of epidemic outbreaks. The biomarkers will be synthetic DNA and so can be mass produced globally, minimizing the risks of availability of critical reagents that may occur in current technologies.

Based on superficial inspection and anecdotal evidence, there appears to be a close correlation between being a hotspot area for COVID-19 prevalence or severity on one hand and environmental factors (such as air pollution and meteorological variables) and human behaviour on the other hand. For instance, the highest COVID-19 prevalence region in Italy (Lombardy) is also one of the most polluted areas of the country. This apparent correlation has led some researchers to hypothesize that environmental factor (e.g., air pollution) may play a causal role in increasing COVID-19 transmission and severity. While such a link is plausible, as COVID-19 is a respiratory transmitted from person to person through inhalation or exhalation in respiratory droplets or touching contaminated surfaces and public policies have been established based on this, the mere correlation between environmental pollution and infections might not be enough to predict infections and deaths from COVID-19. Thus human behaviour, public policy as well as socio-economic factors should be considered to vary with COVID-19 infection and death rate. In this project, we start by exploring the interrelationship between the environment, human behavior, public policy, and socio-economic factors with COVID-19 infection and death rates rigorously. We will use novel real-time satellite data and available social media data (Facebook), combined with COVID-19 infection and mortality data, for a global sample of countries. We aim to contribute to make informed public policy decisions in the context of a potential exit strategy.