Introduction: The globalization of the pharmaceutical supply chain has introduced new challenges, chief among them, fighting the international criminal trade in fake medicines. As the manufacture, supply, and distribution of drugs becomes more complex, so does the need for innovative technology-based solutions to protect patients globally. Areas covered: We conducted a multidisciplinary review of the science/health, information technology, computer science, and general academic literature with the aim of identifying cutting-edge existing and emerging ‘digital’ solutions to combat fake medicines. Our review identified five distinct categories of technology including mobile, radio frequency identification, advanced computational methods, online verification, and blockchain technology. Expert opinion: Digital fake medicine solutions are unifying platforms that integrate different types of anti-counterfeiting technologies as complementary solutions, improve information sharing and data collection, and are designed to overcome existing barriers of adoption and implementation. Investment in this next generation technology is essential to ensure the future security and integrity of the global drug supply chain.

Blockchain is a shared distributed digital ledger technology that can better facilitate data management, provenance and security, and has the potential to transform healthcare. Importantly, blockchain represents a data architecture, whose application goes far beyond Bitcoin – the cryptocurrency that relies on blockchain and has popularized the technology. In the health sector, blockchain is being aggressively explored by various stakeholders to optimize business processes, lower costs, improve patient outcomes, enhance compliance, and enable better use of healthcare-related data. However, critical in assessing whether blockchain can fulfill the hype of a technology characterized as ‘revolutionary’ and ‘disruptive’, is the need to ensure that blockchain design elements consider actual healthcare needs from the diverse perspectives of consumers, patients, providers, and regulators. In addition, answering the real needs of healthcare stakeholders, blockchain approaches must also be responsive to the unique challenges faced in healthcare compared to other sectors of the economy. In this sense, ensuring that a health blockchain is ‘fit-for-purpose’ is pivotal. This concept forms the basis for this article, where we share views from a multidisciplinary group of practitioners at the forefront of blockchain conceptualization, development, and deployment.

Quiz Ref ID Financial relationships between physicians and the biomedical industry are common.¹ Concern for financial conflicts of interest and their effect on patient care, medical research, and education^2,3 prompted the creation of the Open Payments program,^4,5 a comprehensive, nationwide public data repository reporting industry payments to physicians and teaching hospitals. Prior to Open Payments, such data were gathered from physician self-report,¹ a limited number of state databases,⁶ and third-party data sources.⁷ Open Payments, implemented under section 6002 of the Affordable Care Act and managed by the Centers for Medicare & Medicaid Services’ (CMS), requires biomedical manufacturers and group purchasing organizations (GPOs) to report all payments and ownership interests made to physicians starting in 2013. The recent release of the most current, complete, nationally representative Open Payments data⁸ presents the opportunity to analyze the distribution and variability of these financial relationships among physicians.

SUMMARY The definition of the heterogeneous group of coagulase-negative staphylococci (CoNS) is still based on diagnostic procedures that fulfill the clinical need to differentiate between Staphylococcus aureus and those staphylococci classified historically as being less or nonpathogenic. Due to patient- and procedure-related changes, CoNS now represent one of the major nosocomial pathogens, with S. epidermidis and S. haemolyticus being the most significant species. They account substantially for foreign body-related infections and infections in preterm newborns. While S. saprophyticus has been associated with acute urethritis, S. lugdunensis has a unique status, in some aspects resembling S. aureus in causing infectious endocarditis. In addition to CoNS found as food-associated saprophytes, many other CoNS species colonize the skin and mucous membranes of humans and animals and are less frequently involved in clinically manifested infections. This blurred gradation in terms of pathogenicity is reflected by species- and strain-specific virulence factors and the development of different host-defending strategies. Clearly, CoNS possess fewer virulence properties than S. aureus, with a respectively different disease spectrum. In this regard, host susceptibility is much more important. Therapeutically, CoNS are challenging due to the large proportion of methicillin-resistant strains and increasing numbers of isolates with less susceptibility to glycopeptides.

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 inductive manual coding approach were used to identify parent classifications of news and user-generated COVID-19 topics. Results: A total of 115,299 Weibo posts were collected during the study time frame consisting of an average of 2956 posts per day (minimum 0, maximum 13,587). Quantitative analysis found a positive correlation between the number of Weibo posts and the number of reported cases from Wuhan, with approximately 10 more COVID-19 cases per 40 social media posts (P<.001). This effect size was also larger than what was observed for the rest of China excluding Hubei Province (where Wuhan is the capital city) and held when comparing the number of Weibo posts to the incidence proportion of cases in Hubei Province. Qualitative analysis of 11,893 posts during the first 21 days of the study period with COVID-19-related posts uncovered four parent classifications including Weibo discussions about the causative agent of the disease, changing epidemiological characteristics of the outbreak, public reaction to outbreak control and response measures, and other topics. 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.