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This dataset 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 dataset contains the OpenAIRE COVID-19 Gateway records, identified via full-text mining and inference techniques applied to the OpenAIRE Graph. The OpenAIRE 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 dataset 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.8238913.

Database COVID

Background: Acute diarrhea is one of the most serious problems in global public health that causes considerable morbidity and mortality worldwide. Human caliciviruses (HuCV) including norovirus (NoV, genogroup GI and GII) and sapovirus (SaV), is a leading cause of acute sporadic diarrhea in individuals across all age groups. However, few studies had been conducted clarifying the characteristics of HuCV in diarrhea cases across all age groups in China. Our study was aimed at assessing the HuCV-related diarrhea burden and NoV genotypes distribution in southwest China. Methods: The study was conducted in four hospitals in Kunming city, Yunnan province, from June 2014 to July 2015. Stool specimens were collected from 1,121 diarrhea cases and 319 healthy controls in outpatient departments. Reverse transcription polymerase chain reaction (RT-PCR) was used to detect NoV (GI, GII) and SaV. Sequencing was applied to confirm the three viral infections and phylogenetic analysis was performed to determine their genotypes. A structured questionnaire was used to record the demographic information and clinical symptoms of subjects. Results: HuCV was detected at an 11.0 % infection rate in 1,121 diarrhea cases and at 3.4 % rate in 319 non-diarrhea subjects (p < 0.0001, OR = 3.5, 95 % CI 1.8–6.5). The prevalence of the NoV genogroup GII and genotype GII.4 in diarrhea cases was significantly higher than that found in healthy controls (p < 0.0001, p = 0.018, respectively). NoV GII (n = 118, 10.5 %) was the most common HuCV subtype in diarrhea cases, followed by SaV (n = 3, 0.3 %) and NoV GI (n = 2, 0.2 %). Of 118 NoV GII strains isolated from diarrhea patients. GII.4 (n = 55, 46.6 %) was the predominant strain, followed by GII.3 (n = 28, 23.7 %), GII.12 (n = 25, 21.2 %), GII.17 (n = 8, 6.8 %), and GII.5 (n = 2, 1.7 %). Of the 55 GII.4 strains, the GII.4 Sydney 2012 variant had absolutely predominant prevalence (n = 52, 94.5 %), followed by the NoV GII.4-2006b variant (n = 3, 5.5 %). The GII.4 Orleans 2009 variant was not found in diarrhea cases of the study. Conclusions: NoV GII was the major genogroup and GII.4 was the most predominant strain detected in diarrhea patients. The GII.17 is an emergent variant in sporadic diarrhea and might become the predominant strain in diarrhea cases in the near future. Rapid, accurate detection kits need to be developed to help us find and treat NoV-associated diarrhea in clinical settings in a timely manner. Figure 1Phylogenetic trees of SaV and NoV(GI, GII) based on dependent RNA polymerase ●: diarrhea cases over five years; ○: controls over five years; ▲: diarrhea cases under five years; △: controls under five years; The contents in brackets is that the number of same genotype The molecular analysis of SaV and NoV (GI, GII) among diarrhea cases and healthy controls in this study, NoV GII was the major pathogen and GII.4 was the most predominant strain detected in diarrhea patients, novel GII.17 variant was emergence in diarrhea cases.Phylogenetic trees of SaV and NoV(GI, GII)The representative gene sequences

In the course of our PubMed searches and preprints from MedRxiv, we identified a number of protocols for RCTs on preventive measures and treatments for Covid-19. This file is updated regularly.

As of December 2020, COVID-19 has spread all over the world with more than 81 million cases and more than 1.8 million deaths. The rapidly increasing number of patients mandates the consideration of potential treatments for patients under severe and critical conditions. Convalescent plasma (CP) treatment refers to the approach of infusing patients with plasma from recently recovered patients. CP appears to be a possible therapeutic option to manage patients suffering from severe or even lethal infectious disorders, in which “traditional therapies” have failed to obtain any result. In the present study, we develop a mathematical model on the treatment-donation-stockpile dynamics for an optimal implementation of CP therapy to examine potential benefits and complications in the logistic realization of this therapy in a large-scale population. We parameterize the model with COVID-19 epidemics in Italy, and conduct scenario analyses to estimate outcomes of population-wide CP therapy and to examine the maximum number of CP donation processions per day. Under the assumption that the efficacy of CP is 90%, we show that by the end of year 2020, initiating the population-wide CP therapy from April 2020 can save as many as 19,215 lives (ranging from 5000 - 28,000 depending on donor availability), while the demand for apheresis use is manageable in all scenarios: the maximum daily demand is 156 (ranging from 27 - 519 depending on donor availability) for the first outbreak wave and 1,434 (ranging from 224 - 4,817 depending on donor availability) for the second wave. Given that Italy has 61 centers with apheresis this maximum demand level corresponds to a daily average of 2.5 and 23.5 processions of CP donation being performed by each center with respect to each outbreak wave. Our analyses show that population-wide CP therapy can contribute to curbing COVID-19 related deaths, and the logistic implementation is feasible for developed countries. The reduction of deaths can be very significant if the CP therapy is started earlier at the outbreak, and remains significant even if it is implemented during the outbreak peak time.

This contains a set of MATLAB scripts and data that were used to generate the figures and results in the manuscripts.

We conduct an online survey to explore how Chinese people living in Germany perceive and react to group criticism in the context of the debate on the

To analyze how governments, hospitals and information technology(IT) companies use Internet technology to provide online health services during the early stage of corona virus disease 2019 (COVID-19) epidemic in January 2020 in China, and then provide suggestions and coping strategies for the later stage and post-epidemic time.We searched for information on ehealth services related to the outbreak of COVID-19 in China. The sources of information were mainstream search engines such as Baidu and the popular interactive social platforms such as Webchat. The keywords were "Internet+pneumonia", "Internet clinic", "pneumonia online clinic" and so on. The time of information was from January 20 to February 3, 2020. The key information was extracted and encoded by two persons back-to-back. The coding information included: name of organization provider, launching time, location of provider, service items, user, health workers engaging in the service, and so on. The coded information was entered and analyzed with SPSS 24.0 and Excel.There were totally 57 projects launched by local governments, hospitals and IT companies. Most of them were launched from January 24th to 27th, the hospital and government projects services regionally, especially in eastern provinces. In this study, 90.48% of the enterprises and 100.00% of the hospitals had online fever clinic and consultation services for COVID-19, 66.67% of the enterprises and 37.04% of the hospitals serviced derivative health problems. Only a few projects provided tele-medical consultation. There were individual projects that provided online health management for home quarantine people. Physicians were the main force of various projects. In some hospital projects, there were also nurses, pharmacists and professional technicians to provide featured consultation.Ehealth is useful and helpful for the health care system to rapidly cope with health demand during instantaneous and post epidemic time. Regional distribution of ehealth is unbalanced. There are institutional and technical feasibilities for the emergency application of Internet technology. However, community health centers seldom provide ehealth or connect with tertiary hospitals with Internet. Therefore, all kinds of providers within healthcare system should promote emergence ehealth. Tele-medical diagnosis and referral should be developed by local governments during COVID-19. The application of "Internet+medical treatment" in community medical institutions and synergy among various institutions should be promoted.