Articles: sars-cov-2.
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JMIR Public Health Surveill · May 2020
Tracking Social Media Discourse About the COVID-19 Pandemic: Development of a Public Coronavirus Twitter Data Set.
At the time of this writing, the coronavirus disease (COVID-19) pandemic outbreak has already put tremendous strain on many countries' citizens, resources, and economies around the world. Social distancing measures, travel bans, self-quarantines, and business closures are changing the very fabric of societies worldwide. With people forced out of public spaces, much of the conversation about these phenomena now occurs online on social media platforms like Twitter. ⋯ It is our hope that our contribution will enable the study of online conversation dynamics in the context of a planetary-scale epidemic outbreak of unprecedented proportions and implications. This data set could also help track COVID-19-related misinformation and unverified rumors or enable the understanding of fear and panic-and undoubtedly more.
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The coronavirus disease, COVID-19, caused by the novel coronavirus SARS-CoV-2, which first emerged in Wuhan, China and was made known to the World in December 2019 turned into a pandemic causing more than 126,124 deaths worldwide up to April 16th, 2020. It has 79.5% sequence identity with SARS-CoV-1 and the same strategy for host cell invasion through the ACE-2 surface protein. Since the development of novel drugs is a long-lasting process, researchers look for effective substances among drugs already approved or developed for other purposes. ⋯ According to docking analysis the most promising results were found for HCV protease, DPP-4, α-thrombin and coagulation Factor Xa known inhibitors, with several of them exhibiting estimated free binding energy lower than -8.00 kcal/mol and better prediction results than reference compounds. Since some of the compounds are well-tolerated drugs, the promising in silico results may warrant further evaluation for viral anticipation. DPP-4 inhibitors with anti-viral action may be more useful for infected patients with diabetes, while anti-coagulant treatment is proposed in severe SARS-CoV-2 induced pneumonia.
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J. Med. Internet Res. · May 2020
Using Reports of Symptoms and Diagnoses on Social Media to Predict COVID-19 Case Counts in Mainland China: Observational Infoveillance Study.
Coronavirus disease (COVID-19) has affected more than 200 countries and territories worldwide. This disease poses an extraordinary challenge for public health systems because screening and surveillance capacity is often severely limited, especially during the beginning of the outbreak; this can fuel the outbreak, as many patients can unknowingly infect other people. ⋯ Public social media data can be usefully harnessed to predict infection cases and inform timely responses. Researchers and disease control agencies should pay close attention to the social media infosphere regarding COVID-19. In addition to monitoring overall search and posting activities, leveraging machine learning approaches and theoretical understanding of information sharing behaviors is a promising approach to identify true disease signals and improve the effectiveness of infoveillance.
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Meta Analysis
Association of hypertension with the severity and fatality of SARS-CoV-2 infection: A meta-analysis.
Hypertension is a common comorbidity in COVID-19 patients. However, the association of hypertension with the severity and fatality of COVID-19 remain unclear. In the present meta-analysis, relevant studies reported the impacts of hypertension on SARS-CoV-2 infection were identified by searching PubMed, Elsevier Science Direct, Web of Science, Wiley Online Library, Embase and CNKI up to 20 March 2020. ⋯ Meanwhile, the pooled ORs of COVID-19 fatality for hypertension vs. non-hypertension was 6.43 (95% CI: 3.40-12.17) and 2.66 (95% CI: 1.27-5.57) in age <50 years and ⩾50 years patients, respectively. Neither considerable heterogeneity nor publication bias was observed in the present analysis. Therefore, our present results provided further evidence that hypertension could significantly increase the risks of severity and fatality of SARS-CoV-2 infection.
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The novel coronavirus SARS-CoV-2 was first detected in the Pacific Northwest region of the United States in January 2020, with subsequent COVID-19 outbreaks detected in all 50 states by early March. To uncover the sources of SARS-CoV-2 introductions and patterns of spread within the United States, we sequenced nine viral genomes from early reported COVID-19 patients in Connecticut. ⋯ Moreover, the risk of domestic importation to Connecticut exceeded that of international importation by mid-March regardless of our estimated effects of federal travel restrictions. This study provides evidence of widespread sustained transmission of SARS-CoV-2 within the United States and highlights the critical need for local surveillance.