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This dump provides access to the metadata records of publications, research data, software and projects that may be relevant to the Corona Virus Disease (COVID-19) fight. The dump contains records of the OpenAIRE COVID-19 Gateway, identified via full-text mining and inference techniques applied to the OpenAIRE Research Graph. The Graph is one of the largest Open Access collections of metadata records and links between publications, datasets, software, projects, funders, and organizations, aggregating 12,000+ scientific data sources world-wide, among which the Covid-19 data sources Zenodo COVID-19 Community, WHO (World Health Organization), BIP! FInder for COVID-19, Protein Data Bank, Dimensions, scienceOpen, and RSNA. The dump consists of a tar archive containing gzip files with one json per line. Each json is compliant to the schema available at https://doi.org/10.5281/zenodo.4723499.

The paper analyses the interindustry spillover effects of bilateral trade conflicts using the example of the 2018-2019 China-USA bilateral trade war. Empirical results are produced using a new heuristic method based on hypothetical extraction and substitution in an International Input-Output model. This model tracts a series of direct and indirect sectoral effects and provides an intuitive and computationally tractable way of mapping the potential gains and losses affecting other trade partners. It sheds light on some intricate inter-industry implications that are not obvious when considering traditional trade models. A large share of the negative impacts may be felt by third countries through two separate trade channels. Firstly, because the production of a final product in one country relies on importing intermediate goods from other trade partners, who may be negatively impacted by the trade destruction effects of the trade embargo. Secondly, because trade embargoes lead to trade substitution in order to fill the gaps left by embargoed products, and to trade deflection. Deflection occurs when the trade belligerents redeploy their unsold exports towards third countries, increasing competition for market shares. This situation is an additional threat for the Multilateral Trade Governance as large-scale trade deflection may induce a cascade of Tit-for-Tat protectionist measures, in a situation where the COVID-19 pandemics has fanned the industrial nationalism, trade protectionism and geo-political tensions which were already perceptible since the global crisis of 2008-2009.

This study investigated the impact of COVID-19 pandemic uncertainty shock on the macroeconomic stability in Ethiopia in the short run period. The World Pandemic Uncertainty Index (WPUI) was used a proxy variable to measure COVID-19 Uncertainty shock effect. The pandemic effect on core macroeconomic variables like investment, employment, prices (both food & non-food prices), import, export and fiscal policy indicators was estimated and forecasted using Dynamic Stochastic General Equilibrium (DSGE) Model. The role of fiscal policy in mitigating the shock effect of coronavirus pandemic on macroeconomic stability is also investigated. The finding of the study reveals that the COVID-19 impact lasts at least three years to shake the economy of Ethiopia. Given that the Ethiopian economy heavily relies on import to supply the bulk of its consumption and investment goods, COVID-19 uncertainty effect starts as supply chain shock, whose effect transmitted into the domestic economy via international trade channel. The pandemic uncertainty shock effect is also expected to quickly transcend to destabilize the economy via aggregate demand, food & non-food prices, investment, employment and export shocks. The overall impact of COVID-19 pandemic uncertainty shock impact is interpreted into the economy by resulting under consumption at least in the next three years since 2020. Therefore, the government is expected to enact incentives/policy directions which can boost business confidence. A managed expansionary fiscal policy is found to be key to promote investment, employment and to stabilize food & non-food prices. A particular role of fiscal policy was identified to stabilizing food, transport and communication prices. More importantly, price stabilization policies of the government can have spillover effects in boosting aggregate demand by spurring investments (and widening employment opportunities) in transport/logistics, hotel & restaurant, culture & tourism and export sectors in particular.

The Covid-19 pandemic is going to provoke a huge global crisis in all fields (humanitarian, social, economic). To evaluate its impact is difficult until the pandemic crisis will be stopped or at least its peak will be reached. In order to contribute to such work, we propose in this study a new estimation-simulation model, as an alternative to those models coming from probabilistic, genetic algorithms or other approach. Inspired by classical mechanic dynamics of systems, our model tries to formalize the dynamics of affected population by Covid-19 pandemic. By using a logistic model, in order to find the main characteristics of the system’s dynamics we resort to the first two differentiate function by time for four basic indicators (variables). Essentially for obtaining a solution to estimate the system’s dynamics, we used a balance equation for the variable of active cases, as the difference between the total number of infected and the sum between the number of healed (recovered) and the number of deaths, on the one hand, and the hypothesis that at the end of pandemic this variable must be zero, on the other hand. Because for this key-variable doesn't exist an analytical solution we used a numerical method to obtain some key-values for it. Finally, based on such methodology we classified the Covid-19 pandemic evolution in four phases.

What determines how a national government reacts in a crisis? The COVID-19 pandemic provides an opportunity to explore leadership behavior and crisis management, and this paper examines what drove the extent of the lockdown in countries around the world during the first wave of coronavirus. In particular, this paper posits that many of the policies undertaken were “extraordinary,” that is unlike those ever implemented or complemented by the leaders in charge at the start of the pandemic. Utilizing new and high-frequency data on government responses to COVID-19 and novel statistical techniques, the results of this analysis are that institutions and leadership attributes both matter, but for different policies; where the response called for more ‘normal” policies, it appeared that institutional mechanisms were adequate and played the largest role in influencing the extent of the lockdown. On the other hand, where the policies contemplated were very far from the ordinary (including stay-at-home orders or prohibitions on internal travel), the attributes of the leader determined the stringency of the lockdown more than institutions.

We study the economic effects generated by the proliferation of the Covid-19 epidemic and the implementation of non-pharmaceutical interventions by developing a SEIRD-RBC model, where the outbreak and policy interventions shape the labor input dynamic. We microfoundan Epidemic-Macro model grounded on the RBC tradition, useful for epidemic and economic analysis at business cycle frequency, which is able to reproduce the highly debated health-output trade-off. Assuming a positive approach, we show the potential of our model by matching the epidemic and macroeconomic empirical evidence of the Italian case.

Dress code is standard in the Australian public sector, with smart business casual the norm. However, over the last two years, as many workers relocated to the home office, bedroom or kitchen table during the COVID-19 pandemic , work attire has taken on new meaning. A key but under-researched advantage of remote working has been the relaxing in many professions dress codes, with ‘COVID casual’ becoming the norm for many workers. This report highlights the role of dress codes, appearance, and aesthetics in the Australian public sector and the refashioning of professional attire in the age of remote work.

Abstract The issue of coronavirus outbreak in the world, though new, is equally pervasive. It has posed a new and ambiguous challenge to the economic growth of countries around the world. Undoubtedly, the efforts of countries to curb the spread of this virus and reduce the number of deaths are necessary for other strategies that will be taken in other areas, especially in the economic field. Comparing countries only based on the statistics on virus spread and mortality without considering the contextual variables, can be misleading. Thus using dynamic data envelopment analysis, this study calculated the performance of 19 selected countries in two dimensions: inefficiency of preventing coronavirus spread and inefficiency of preventing deaths caused by a coronavirus from February 2 to April 12. According to the study, the inefficiency trend of preventing coronavirus spread in Singapore, South Korea, China, and Australia are decreasing during the period under review and the inefficiency trend of other countries, which of course differ in terms of inefficiency, are increasing with different slopes. Also, Australia, Finland, Japan, Malaysia, Singapore, and Thailand have experienced less inefficiency in preventing deaths caused by coronavirus compared to other countries. Stringency index and global health security (GHS) index have been used as well, to analyze the findings and in the end some suggestions have been presented.