Corpus overview


MeSH Disease

Disease (2)

Shock (1)

Human Phenotype

Large face (4)

Shock (1)


There are no transmission terms in the subcorpus


There are no seroprevalence terms in the subcorpus

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    Scenarios for a post-COVID-19 world airline network

    Authors: Jiachen Ye; Peng Ji; Marc Barthelemy

    id:2007.02109v1 Date: 2020-07-04 Source: arXiv

    The airline industry was severely hit by the COVID-19 crisis with an average demand decrease of about $64\%$ (IATA, April 2020) which triggered already several bankruptcies of airline companies all over the world. While the robustness of the world airline network (WAN) was mostly studied as an homogeneous network, we introduce a new tool for analyzing the impact of a company failure: the `airline company network' where two airlines are connected if they share at least one route segment. Using this tool, we observe that the failure of companies well connected with others has the largest impact on the connectivity of the WAN. We then explore how the global demand reduction affects airlines differently, and provide an analysis of different scenarios if its stays low and does not come back to its pre-crisis level. Using traffic data from the Official Aviation Guide (OAG) and simple assumptions about customer's airline choice strategies, we find that the local effective demand can be much lower than the average one, especially for companies that are not monopolistic and share their segments with larger companies. Even if the average demand comes back to $60\%$ of the total capacity, we find that between $46\%$ and $59\%$ of the companies could experience a reduction of more than $50\%$ of their traffic, depending on the type of competitive advantage that drives customer's airline choice. These results highlight how the complex competitive structure of the WAN weakens its robustness when facing such a large HP crisis.

    A Big Data Based Framework for Executing Complex Query Over COVID-19 Datasets (COVID-QF)

    Authors: Eman A. Khashan; Ali I. Eldesouky; M. Fadel; Sally M. Elghamrawy

    id:2005.12271v1 Date: 2020-05-25 Source: arXiv

    COVID-19's rapid global spread has driven innovative tools for Big Data Analytics. These have guided organizations in all fields of the health industry to track and minimized the effects of virus. Researchers are required to detect coronaviruses through artificial intelligence, machine learning, and natural language processing, and to gain a complete understanding of the disease MESHD. COVID-19 takes place in different countries in the world, with which only big data application and the work of NOSQL databases are suitable. There is a great number of platforms used for processing NOSQL Databases model like: Spark, H2O and Hadoop HDFS/MapReduce, which are proper to control and manage the enormous amount of data. Many challenges faced by large HP applications programmers, especially those that work on the COVID-19 databases through hybrid data models through different APIs and query. In this context, this paper proposes a storage framework to handle both SQL and NOSQL databases named (COVID-QF) for COVID-19 datasets in order to treat and handle the problems caused by virus spreading worldwide by reducing treatment times. In case of NoSQL database, COVID-QF uses Hadoop HDFS/Map Reduce and Apache Spark. The COVID-QF consists of three Layers: data collection layer, storage layer, and query Processing layer. The data is collected in the data collection layer. The storage layer divides data into collection of data-saving and processing blocks, and it connects the Connector of the spark with different databases engine to reduce time of saving and retrieving. While the Processing layer executes the request query and sends results. The proposed framework used three datasets increased for time for COVID-19 data (COVID-19-Merging, COVID-19-inside-Hubei and COVID-19-ex-Hubei) to test experiments of this study. The results obtained insure the superiority of the COVID-QF framework.

    The Successes and Failures of the Initial COVID-19 Pandemic Response in Romania

    Authors: Stefan Dascalu

    id:10.20944/preprints202004.0373.v1 Date: 2020-04-21 Source:

    In the context of the COVID-19 pandemic, countries around the world varied in the strength and timeliness of their responses. In Romania, specific challenges were faced with regards to managing the spread and limiting the impact of the disease MESHD, ranging from healthcare infrastructure to demographic and sociocultural aspects. As the country has a sizeable diaspora, major difficulties were faced when large HP numbers of individuals from highly affected areas returned to Romania. However, the fast implementation of control measures successfully averted a surge in the number of COVID-19 cases. This delayed the overburdening of an already challenged healthcare system during the initial phases of the epidemic. Furthermore, early control was facilitated by the exploitation of communication channels that penetrated all layers of society, from ordinary citizens to governmental authorities and high-ranking religious figures. The management of the COVID-19 crisis in Romania illustrates the importance of a fast initial response which takes into account the role played by sociocultural aspects in the context of an epidemic. As the challenges faced by Romania are not unique, these results could inform future public health strategies worldwide.

    Supply and demand shocks MESHD shocks HP in the COVID-19 pandemic: An industry and occupation perspective

    Authors: R. Maria del Rio-Chanona; Penny Mealy; Anton Pichler; Francois Lafond; Doyne Farmer

    id:2004.06759v1 Date: 2020-04-14 Source: arXiv

    We provide quantitative predictions of first order supply and demand shocks MESHD shocks HP for the U.S. economy associated with the COVID-19 pandemic at the level of individual occupations and industries. To analyze the supply shock MESHD shock HP, we classify industries as essential or non-essential and construct a Remote Labor Index, which measures the ability of different occupations to work from home. Demand shocks MESHD shocks HP are based on a study of the likely effect of a severe influenza epidemic developed by the US Congressional Budget Office. Compared to the pre-COVID period, these shocks MESHD shocks HP would threaten around 22% of the US economy's GDP, jeopardise 24% of jobs and reduce total wage income by 17%. At the industry level, sectors such as transport are likely to have output constrained by demand shocks MESHD shocks HP, while sectors relating to manufacturing, mining and services are more likely to be constrained by supply shocks MESHD shocks HP. Entertainment, restaurants and tourism face large HP supply and demand shocks MESHD shocks HP. At the occupation level, we show that high-wage occupations are relatively immune from adverse supply and demand-side shocks MESHD shocks HP, while low-wage occupations are much more vulnerable. We should emphasize that our results are only first-order shocks MESHD shocks HP -- we expect them to be substantially amplified by feedback effects in the production network.

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MeSH Disease
Human Phenotype

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