BACKGROUND The coronavirus disease (COVID-19) pandemic, which began in Wuhan, China in December 2019, is rapidly spreading worldwide with over 1.9 million cases as of mid-April 2020. Infoveillance approaches using social media can help characterize disease distribution and public knowledge, attitudes, and behaviors critical to the early stages of an outbreak. OBJECTIVE The aim of this study is to conduct a quantitative and qualitative assessment of Chinese social media posts originating in Wuhan City on the Chinese microblogging platform Weibo during the early stages of the COVID-19 outbreak. METHODS Chinese-language messages from Wuhan were collected for 39 days between December 23, 2019, and January 30, 2020, on Weibo. For quantitative analysis, the total daily cases of COVID-19 in Wuhan were obtained from the Chinese National Health Commission, and a linear regression model was used to determine if Weibo COVID-19 posts were predictive of the number of cases reported. Qualitative content analysis and an indction to outbreak control and response measures, and other topics.  https://www.selleckchem.com/products/ga-017.html  Generally, these themes also exhibited public uncertainty and changing knowledge and attitudes about COVID-19, including posts exhibiting both protective and higher-risk behaviors. CONCLUSIONS The results of this study provide initial insight into the origins of the COVID-19 outbreak based on quantitative and qualitative analysis of Chinese social media data at the initial epicenter in Wuhan City. Future studies should continue to explore the utility of social media data to predict COVID-19 disease severity, measure public reaction and behavior, and evaluate effectiveness of outbreak communication. ©Jiawei Ken Li, Qing Xu, Raphael Cuomo, Vidya Purushothaman, Tim Mackey. Originally published in JMIR Public Health and Surveillance (http//publichealth.jmir.org), 21.04.2020.BACKGROUND The development of electronic health (eHealth) has offered the opportunity for remote care provision. eHealth addresses issues for patients and professionals favoring autonomy and compliance, respectively, while fostering closer links both between patients and health care professionals and among health care professionals themselves. OBJECTIVE The aim of this study was to analyze the patterns of use, benefits, and perceived obstacles in eHealth among people living with HIV (PLHIV) and their caring physicians at hospitals. METHODS An online multicenter observational survey was conducted October 15-19, 2018 in 51 medical units across France by means of self-administered questionnaires to collect sociodemographic and medical data, and perceptions of eHealth. Multiple correspondence analysis followed by mixed unsupervised classification were performed to analyze data of the respondents. RESULTS A total of 279 PLHIV and 219 physicians responded to all parts of the questionnaire. Three groups of PLHIV wercialists, and were more likely to believe that medical apps are useful for patient education and information. No link was found between the groups of PLHIV and physicians. CONCLUSIONS The literature on eHealth mainly classifies people as enthusiasts and skeptics; however, we identified a third profile among both PLHIV and physicians, albeit without a direct link between them. For PLHIV, this third group is attentive to eHealth for improving their health condition, and for physicians, this group considers eHealth to offer benefits to patients and their own practice. ©Christine Jacomet, Roxana Ologeanu-Taddei, Justine Prouteau, Céline Lambert, Françoise Linard, Pascale Bastiani, Pierre Dellamonica. Originally published in JMIR mHealth and uHealth (http//mhealth.jmir.org), 15.04.2020.BACKGROUND At the onset of the coronavirus outbreak, the World Health Organization's (WHO) Health Emergencies Learning and Capacity Development Unit, together with the WHO's health technical lead on coronaviruses, developed a massive open online course within 3 weeks as part of the global response to the emergency. The introductory coronavirus disease (COVID‑19) course was launched on January 26, 2020, on the health emergencies learning platform OpenWHO.org. OBJECTIVE The aim of this paper is to investigate the geographic reach of different language courses accessed by a worldwide audience seeking information on COVID-19. Users' professional identities and backgrounds were explored to inform course owners on the use case. The course was developed and delivered via the open-access learning platform OpenWHO.org. The self-paced resources are available in a total of 13 languages and were produced between January 26 and March 25, 2020. METHODS Data were collected from the online courses' statistical data and metri Spanish, have reached new user groups, fulfilling the platform's aim of providing learning everywhere to anyone that is interested. User surveys will be carried out to measure the real impact. ©Heini Utunen, Ngouille Ndiaye, Corentin Piroux, Richelle George, Melissa Attias, Gaya Gamhewage. Originally published in the Journal of Medical Internet Research (http//www.jmir.org), 27.04.2020.BACKGROUND Acute respiratory failure is generally treated with invasive mechanical ventilation or noninvasive respiratory support strategies. The efficacies of the various strategies are not fully understood. There is a need for accurate therapy-based phenotyping for secondary analyses of electronic health record data to answer research questions regarding respiratory management and outcomes with each strategy. OBJECTIVE The objective of this study was to address knowledge gaps related to ventilation therapy strategies across diverse patient populations by developing an algorithm for accurate identification of patients with acute respiratory failure. To accomplish this objective, our goal was to develop rule-based computable phenotypes for patients with acute respiratory failure using remotely monitored intensive care unit (tele-ICU) data. This approach permits analyses by ventilation strategy across broad patient populations of interest with the ability to sub-phenotype as research questions require. METHODS, Jarrod Mosier, Vignesh Subbian. Originally published in JMIR Medical Informatics (http//medinform.jmir.org), 15.04.2020.