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Background: Illicit substance sales facilitated by social media platforms are a growing public health issue given recent increases in overdose deaths, including an alarming rise in cases of fentanyl poisoning. However, little is known about how online users evaluate what features of social media posts convey safety, which can influence their intent to source illicit substances. Objectives: This study adapts conjoint analysis which assessed how attributes of social media posts (i.e., features) influence safety evaluations of mock posts selling illicit substances. 440 participants were recruited online for self-reporting use or purchase of controlled substances or prescription medicines recreationally. The following attributes were tested: drug packaging, drug offerings, profile photo of seller, payment info provided, and use of emojis. Results: Packaging was ranked the most important attribute (Average Importance =43.68, Offering=14.94, Profile=13.86, Payment=14.11, Emoji=13.41), with posts that displayed drugs in pill bottles assessed as the most safe. Attribute levels for advertising multiple drugs, having a blank profile photo, including payment information, and including emojis also ranked higher in perceived safety. Rankings were consistent across tested demographic factors (i.e., gender, age, and income). Survey results show that online pharmacies were most likely to be perceived as safe for purchasing drugs and medications. Additionally, those who were younger in age, had higher income, and identified as female were more likely to purchase from a greater number of platforms. Conclusions: These findings can assist in developing more precise content moderation for platforms seeking to address this ongoing threat to public safety.

BackgroundE-cigarettes have emerged as popular products, especially for younger populations. However, concerns regarding health effects exist and there is a notable gap in understanding the prevalence and nature of adverse events. This study aims to examine the rate of adverse events in individuals who use e-cigarettes in a large sample.MethodsA cross-sectional survey was conducted with a sample of 4695 current and former e-cigarette users with a median age of 34 years. The survey collected data on e-cigarette use, adverse events experienced, product characteristics, related behaviors, sociodemographic factors and presence of medical comorbidities. Statistical analyses were conducted using Pearson's chi-squared tests and logistic regression.ResultsA total of 78.9% of respondents reported experiencing an adverse event within 6 h of using a vaping device, with the most common events being headache, anxiety and coughing. Product characteristics and related behaviors significantly influenced the risk of adverse events. There were also sociodemographic disparities, with Hispanic respondents and those with at least college-level education reporting higher rates of adverse events.ConclusionsOur study found a high rate of adverse events among e-cigarette users. We identified that certain e-cigarette product characteristics, behaviors and medical comorbidities significantly increased the risk of these events.

BackgroundManually analyzing public health-related content from social media provides valuable insights into the beliefs, attitudes, and behaviors of individuals, shedding light on trends and patterns that can inform public understanding, policy decisions, targeted interventions, and communication strategies. Unfortunately, the time and effort needed from well-trained human subject matter experts makes extensive manual social media listening unfeasible. Generative large language models (LLMs) can potentially summarize and interpret large amounts of text, but it is unclear to what extent LLMs can glean subtle health-related meanings in large sets of social media posts and reasonably report health-related themes.ObjectiveWe aimed to assess the feasibility of using LLMs for topic model selection or inductive thematic analysis of large contents of social media posts by attempting to answer the following question: Can LLMs conduct topic model selection and inductive thematic analysis as effectively as humans did in a prior manual study, or at least reasonably, as judged by subject matter experts?MethodsWe asked the same research question and used the same set of social media content for both the LLM selection of relevant topics and the LLM analysis of themes as was conducted manually in a published study about vaccine rhetoric. We used the results from that study as background for this LLM experiment by comparing the results from the prior manual human analyses with the analyses from 3 LLMs: GPT4-32K, Claude-instant-100K, and Claude-2-100K. We also assessed if multiple LLMs had equivalent ability and assessed the consistency of repeated analysis from each LLM.ResultsThe LLMs generally gave high rankings to the topics chosen previously by humans as most relevant. We reject a null hypothesis (P

BackgroundCancer patients often face multiple comorbidities and are at risk for various mental health conditions and substance use disorders. Tobacco/nicotine dependence (TND) is a known risk factor for poor health outcomes and has been associated with psychiatric disorders including substance use disorder. However, the specific relationship between TND and the risk of substance use disorder and mental health conditions among cancer patients remains underexplored. This study aimed to assess the association between TND and the risk of comorbid conditions among cancer patients.MethodsData were obtained from a database of electronic health records for patients from the University of California health system. The odds for every condition among cancer patients with TND were calculated and compared with those for cancer patients without TND. ORs were adjusted for gender, ethnicity, and race.ResultsThree thousand seven hundred and ninety-one cancer patients with TND had 252,619 total conditions, and 51,711 cancer patients without TND had 2,310,880 conditions. After adjusting for confounders, the condition for which TND most exacerbated risk was psychoactive substance-induced organic anxiety disorder (OR = 16.3, p

BackgroundIncreased public health and regulatory scrutiny concerning the youth vaping epidemic has led to greater attention to promotion and sales of vaping products on social media platforms.ObjectivesWe used unsupervised machine learning to identify and characterise sale offers of electronic nicotine delivery systems (ENDS) and associated products on Instagram. We examined types of sellers, geographic ENDS location and use of age verification.MethodsOur methodology was composed of three phases: data collection, topic modelling and content analysis. We used data mining approaches to query hashtags related to ENDS product use among young adults to collect Instagram posts. For topic modelling, we applied an unsupervised machine learning approach to thematically categorise and identify topic clusters associated with selling activity. Content analysis was then used to characterise offers for sale of ENDS products.ResultsFrom 70 725 posts, we identified 3331 engaged in sale of ENDS products. Posts originated from 20 different countries and were roughly split between individual (46.3%) and retail sellers (43.4%), with linked online sellers (8.8%) representing a smaller volume. ENDS products most frequently offered for sale were flavoured e-liquids (53.0%) and vaping devices (20.5%). Online sellers offering flavoured e-liquids were less likely to use age verification at point of purchase (29% vs 64%) compared with other products.ConclusionsInstagram is a global venue for unregulated ENDS sales, including flavoured products, and access to websites lacking age verification. Such posts may violate Instagram's policies and US federal and state law, necessitating more robust review and enforcement to prevent ENDS uptake and access.

Public trust in medical institutions is essential for ensuring compliance with medical directives. However, the politicization of public health issues and the polarized nature of major news outlets suggest that partisanship and news consumption habits can influence medical trust. This study employed a survey with 858 participants and used regression analysis to assesses how news consumption habits and information assessment traits (IATs) influence trust in medical scientists. IATs included were conscientiousness, openness, need for cognitive closure (NFCC), and cognitive reflective thinking (CRT). News sources were classified on the basis of factuality and political bias. Initially, readership of liberally biased news was positively associated with medical trust (p < 0.05). However, this association disappeared when controlling for the news source's factuality (p = 0.28), while CRT (p < 0.05) was positively associated with medical trust. When controlling for conservatively biased news sources, factuality of the news source (p < 0.05) and NFCC (p < 0.05) were positively associated with medical trust. While partisan media bias may influence medical trust, these results suggest that those who have higher abilities to assess information and who prefer more credible news sources have a greater trust in medical scientists.

A case-control study was conducted between 1 December 2021 and 31 January 2022 to identify factors, which increase risk for coronavirus disease 2019 (COVID-19) among athletes in the National Basketball Association (NBA). Behavioral factors and stadium attendance significantly decreased time to COVID-19 infection, but local COVID-19 rates were not associated in a multivariable model.

IntroductionThe state of California has enacted progressive anti-tobacco policies, including Proposition 56 in 2016. In response, the alternative and emerging tobacco product (ATP) industry has increased its political activity. This study explores the association between the proportion of people voting against Proposition 56 and tobacco/ATP retail density.MethodsWe conducted a retrospective analysis using data on licensed California tobacco retailers, which were then cross-referenced for categorization using Yelp. Proportion voting against Proposition 56 was obtained from the Secretary of State's website. A series of linear regression tests were performed between population-normalized retailer density and voting proportion at the county level before and after adjusting for covariates such as age, gender, race/ethnicity and median household income.ResultsThe total number of licensed tobacco retailers increased by 29.31% from 2015 to 2019. Association between proportion voting against Proposition 56 and retail density was significant during voting and during periods of policy implementation and post-implementation (2016-2018) for non-specialized tobacco retailers. For specialized/ATP retailers, significance was only detected during the post-implementation period (2018-2019) after normalization. Proportion voting against Proposition 56 was also a significant predictor of increase in total number of non-specific (β=0.48, p=0.008) as well as specialized tobacco and/or ATP retail storefronts (β=0.21, p=0.001) from 2016 to 2018.ConclusionsThis study provides initial evidence of the association between tobacco retail density and voting patterns for anti-tobacco policy. Future research should examine the role of tobacco retail density on variation in local support for state tobacco control initiatives, including tailoring outreach to specific voting census blocks in communities with heavy retail presence.

BackgroundSocial media has emerged as a critical mass communication tool, with both health information and misinformation now spread widely on the web. Prior to the COVID-19 pandemic, some public figures promulgated anti-vaccine attitudes, which spread widely on social media platforms. Although anti-vaccine sentiment has pervaded social media throughout the COVID-19 pandemic, it is unclear to what extent interest in public figures is generating anti-vaccine discourse.ObjectiveWe examined Twitter messages that included anti-vaccination hashtags and mentions of public figures to assess the connection between interest in these individuals and the possible spread of anti-vaccine messages.MethodsWe used a data set of COVID-19-related Twitter posts collected from the public streaming application programming interface from March to October 2020 and filtered it for anti-vaccination hashtags "antivaxxing," "antivaxx," "antivaxxers," "antivax," "anti-vaxxer," "discredit," "undermine," "confidence," and "immune." Next, we applied the Biterm Topic model (BTM) to output topic clusters associated with the entire corpus. Topic clusters were manually screened by examining the top 10 posts most highly correlated in each of the 20 clusters, from which we identified 5 clusters most relevant to public figures and vaccination attitudes. We extracted all messages from these clusters and conducted inductive content analysis to characterize the discourse.ResultsOur keyword search yielded 118,971 Twitter posts after duplicates were removed, and subsequently, we applied BTM to parse these data into 20 clusters. After removing retweets, we manually screened the top 10 tweets associated with each cluster (200 messages) to identify clusters associated with public figures. Extraction of these clusters yielded 768 posts for inductive analysis. Most messages were either pro-vaccination (n=329, 43%) or neutral about vaccination (n=425, 55%), with only 2% (14/768) including anti-vaccination messages. Three main themes emerged: (1) anti-vaccination accusation, in which the message accused the public figure of holding anti-vaccination beliefs; (2) using "anti-vax" as an epithet; and (3) stating or implying the negative public health impact of anti-vaccination discourse.ConclusionsMost discussions surrounding public figures in common hashtags labelled as "anti-vax" did not reflect anti-vaccination beliefs. We observed that public figures with known anti-vaccination beliefs face scorn and ridicule on Twitter. Accusing public figures of anti-vaccination attitudes is a means of insulting and discrediting the public figure rather than discrediting vaccines. The majority of posts in our sample condemned public figures expressing anti-vax beliefs by undermining their influence, insulting them, or expressing concerns over public health ramifications. This points to a complex information ecosystem, where anti-vax sentiment may not reside in common anti-vax-related keywords or hashtags, necessitating further assessment of the influence that public figures have on this discourse.

BackgroundAccess to tobacco products, including vape products, from local brick-and-mortar stores influences the exposure, uptake, and use of these products in local communities.MethodsLicensed tobacco retailers in California were classified as specialized tobacco/vape stores or non-specialized stores by obtaining categories published on Yelp. California smoking and vaping prevalence data were obtained from the 500 cities project and ESRI community analyst tool respectively. A series of simple linear regression tests were performed, at the zip code level, between the retailer count in each store category and smoking/vaping population. The Getis-Ord Gi* and Anselin Local Moran's I statistics were used for characterization of tobacco retail density hotspots and cold spots.ResultsThe association between CA smoking/vaping population and number of tobacco retailers was statistically significant for all store categories. Variability in smoking population was best explained by variability in non-specialized storefronts(R2=0.84). Spatial variability in tobacco-only storefronts explained the least proportion of variability in the overall smoking population. Similar results were obtained specific to vaping population, although the proportion of population explained by variability in the number of non-specialized storefronts was comparatively lower(R2=0.80).ConclusionsLocalities with greater numbers of non-specialized tobacco retailers had higher rates of smoking/vaping populations, and this association was much stronger for localities with greater numbers of specialized retailers. Non-specialized storefronts may represent convenient access points for nicotine products, while specialized storefronts may represent critical access points for initiation. Hence, regulations that address the entirety of the tobacco/vaping retail environment by limiting widespread access from non-specialized stores and reducing appeal generated by specialized retailers should be incorporated in future tobacco regulatory science and policymaking.

IntroductionThe urgent need to acquire medical supplies amidst the COVID-19 pandemic has led to bypassing of controls that govern the global pharmaceutical supply chain, increasing the risk of corruption. Hence, promoting anti-corruption, transparency, and accountability (ACTA) in supply chain and procurement has never been more important. The adoption of digital tools, if designed and implemented appropriately, can reduce the risks of corruption.Areas coveredFollowing PRISMA guidelines, we conducted an interdisciplinary systematic review of health/medicine, humanities/social sciences, engineering, and computer science literature, with the aims of identifying technologies used for pharmaceutical supply chain and procurement optimization and reviewing whether they address ACTA mechanisms to strengthen pharmaceutical governance. Our review identified four distinct categories of digital solutions: e-procurement and open contracting; track-and-trace technology; anti-counterfeiting technology; and blockchain technology.Expert opinionFindings demonstrate an increase in research of technologies to improve pharmaceutical supply chain and procurement functions; however, most technologies are not being leveraged to directly address ACTA or global health outcomes. Some blockchain and RFID technologies incorporated ACTA mechanisms and mentioned specific policy/governance frameworks, but more purposeful linkage is needed. Findings point to the need for targeted policy development and governance to activate these innovative technologies to improve global health .

BackgroundThe opioid epidemic has had a devastating impact on youth from American Indian and Alaska Native (AI/AN) Tribes and Villages, which also experience disparate suicide rates. The use of publicly available social media data originating from AI/AN communities may enhance public health response time to substance use disorder (SUD)-related overdose and augment Tribal public health surveillance systems, but these concepts have yet to be adequately explored. The goal of this exploratory analysis was to identify primary and secondary accounts of overdose and characterize relevant contextual factors in the AI/AN population on social media.MethodsThe Twitter application programming interface was queried for all Tweets containing geocoded data between March 2014 and June 2020 and filtered for the keyword ['overdose']. This sample of Tweets (n = 146,236) was then restricted to those geolocated from US Tribal lands (n = 619). Tweets were manually annotated for primary or secondary accounts of overdose as well as suicidal ideation, substance(s) used, stigma of drug use, and community-wide incidents.ResultsWe collected a total of 146,235 tweets that were geocoded and contained the word 'overdose,' of which 9.5% were posted on Tribal lands (n = 619). 9.4% of these tweets (n = 58) met our study inclusion criteria and were mainly posted from Oklahoma (n = 26, 45%) and North Carolina (n = 13, 22.4%). Most Tweets (n = 41, 71%) described a primary account of an overdose and were mostly posted from 2014 to 2015. Less than half of the Tweets (n = 27, 46.5%) referenced a specific substance. Those substances mentioned included alcohol, marijuana, methamphetamine, heroin, laundry softener, cocaine, K2-Spice (synthetic cannabinoid), codeine, morphine, Nyquil, and Xanax.DiscussionThough exploratory, our study identified SUD-related content self-reported by AI/AN communities on Twitter, especially in Oklahoma and North Carolina. These results may assist in the future design and detection of infodemiology trends and early warning signs that can better facilitate intervention specific to the ongoing Tribal opioid epidemic. While all data were collected from the public domain, additional care should be given to individual and community privacy.

BackgroundTikTok is a microvideo social media platform currently experiencing rapid growth and with 60% of its monthly users between the ages of 16 and 24 years. Increased exposure to e-cigarette content on social media may influence patterns of use, including the risk of overconsumption and possible nicotine poisoning, when users engage in trending challenges online. However, there is limited research assessing the characteristics of nicotine poisoning-related content posted on social media.ObjectiveWe aimed to assess the characteristics of content on TikTok that is associated with a popular nicotine poisoning-related hashtag.MethodsWe collected TikTok posts associated with the hashtag #nicsick, using a Python programming package (Selenium) and used an inductive coding approach to analyze video content and characteristics of interest. Videos were manually annotated to generate a codebook of the nicotine sickness-related themes. Statistical analysis was used to compare user engagement characteristics and video length in content with and without active nicotine sickness TikTok topics.ResultsA total of 132 TikTok videos associated with the hashtag #nicsick were manually coded, with 52.3% (69/132) identified as discussing firsthand and secondhand reports of suspected nicotine poisoning symptoms and experiences. More than one-third of nicotine poisoning-related content (26/69, 37.68%) portrayed active vaping by users, which included content with vaping behavior such as vaping tricks and overconsumption, and 43% (30/69) of recorded users self-reported experiencing nicotine sickness, poisoning, or adverse events such as vomiting following nicotine consumption. The average follower count of users posting content related to nicotine sickness was significantly higher than that for users posting content unrelated to nicotine sickness (W=2350.5, P=.03).ConclusionsTikTok users openly discuss experiences, both firsthand and secondhand, with nicotine adverse events via the #nicsick hashtag including reports of overconsumption resulting in sickness. These study results suggest that there is a need to assess the utility of digital surveillance on emerging social media platforms for vaping adverse events, particularly on sites popular among youth and young adults. As vaping product use-patterns continue to evolve, digital adverse event detection likely represents an important tool to supplement traditional methods of public health surveillance (such as poison control center prevalence numbers).

BackgroundSynthetic cannabinoids are a significant public health concern, especially among incarcerated populations due to increased reports of abuse. Recent news reports have highlighted the severe consequences of K2/Spice, a synthetic cannabinoid, among the prison population in the United States. Despite regulations against cell phone use, inmates use TikTok to post K2/Spice-related content.ObjectiveThis study aimed to examine TikTok posts for use and illicit distribution of psychoactive substances (eg, K2/Spice) among incarcerated populations.MethodsThe study collected TikTok videos associated with the #k2spice hashtag and used a data collection approach similar to snowball sampling. Inductive coding was used to conduct content analysis of video characteristics. Videos were manually annotated to generate binary classifications related to the use of K2/Spice as well as selling and buying activities associated with it. Statistical analysis was used to determine associations between a video's user engagement and an intent to buy or sell K2/Spice.ResultsA total of 89 TikTok videos with the hashtag #k2spice were manually coded, with 40% (n=36) identified as displaying the use, solicitation, or adverse effects of K2/Spice among the prison population. Of them, 44.44% (n=16) were in a prison-based setting documenting adverse effects including possible overdose. Videos with higher user engagement were positively correlated with comments indicating an intent to buy or sell K2/Spice.ConclusionsK2/Spice is a drug subject to abuse among prison inmates in the United States, including depictions of its harmful effects being recorded and shared on TikTok. Lack of policy enforcement on TikTok and the need for better access to treatment services within the prison system may be exacerbating substance use among this highly vulnerable population. Minimizing the potential individual harm of this content on the incarcerated population should be a priority for social media platforms and the criminal justice system alike.

IntroductionTobacco retailer density may be associated with greater youth initiation and reduced success during quit attempts; however, the extent to which tobacco retailer density has changed overtime across multiple categories of retailers has not been reported.MethodsData on licensed tobacco retailers within California from 2015-2019 were obtained from the California Department of Tax and Fee Administration. Store type was categorized by automated cross-referencing with Yelp. Geolocations were aggregated at county level for analyzing longitudinal trends in changes in tobacco retail density including demographic characteristics.ResultsThe number of active CA tobacco retailer licenses increased from 19825 in 2015 to 25635 in 2019. The highest percent increase in tobacco retailer licenses (9.1%) was observed in 2017. The number of specialized tobacco stores was highest in Los Angeles, San Diego, and Riverside counties. We observed a significant increase in the number of active licenses for non-specialized and specialized tobacco stores, both overall and after controlling for the size of populations within each region. Time was a statistically significant predictor for the number of active licenses for only non-specialized stores, after adjusting for covariates. Regional volume of retailers was positively associated with higher proportion of women, lower median household income, and higher proportion of Hispanic residents.ConclusionsMonitoring the changes in tobacco retail density and associated sociodemographic factors over time can help to identify communities at higher risk for tobacco and nicotine product exposure and access, and its associated health disparities.

IntroductionExposure to pro-tobacco and electronic nicotine delivery system (ENDS) social media content can lead to overconsumption, increasing the likelihood of nicotine poisoning. This study aims to examine trends and characteristics of nicotine sickness content on Twitter between 2018-2020.MethodsTweets were collected retrospectively from the Twitter Academic Research Application Programming Interface (API) stream filtered for keywords: 'nic sick', 'nicsick', 'vape sick', 'vapesick' between 2018-2020. Collected tweets were manually annotated to identify suspected user-generated reports of nicotine sickness and related themes using an inductive coding approach. The Augmented Dickey-Fuller (ADF) test was used to assess stationarity in the monthly variation of the volume of tweets between 2018-2020.ResultsA total of 5651 tweets contained nicotine sickness-related keywords and 18.29% (n=1034) tweets reported one or more suspected nicotine sickness symptoms of varied severity. These tweets were also grouped into five related categories including firsthand and secondhand reports of symptoms, intentional overconsumption of nicotine products, users expressing intention to quit after 'nic sick' symptoms, mention of nicotine product type/brand name that they consumed while 'nic sick', and users discussing symptoms associated with nicotine withdrawal following cessation attempts. The volume of tweets reporting suspected nicotine sickness appeared to increase throughout the study period, except between February and April 2020. Stationarity in the volume of 'nicsick' tweets between 2018-2020 was not statistically significant (ADF= -0.32, p=0.98) indicating a change in the volume of tweets.ConclusionsResults point to the need for alternative forms of adverse event surveillance and reporting, to appropriately capture the growing health burden of vaping. Infoveillance approaches on social media platforms can help to assess the volume and characteristics of user-generated content discussing suspected nicotine poisoning, which may not be reported to poison control centers. Increasing volume of user-reported nicotine sickness and intentional overconsumption of nicotine in twitter posts represent a concerning trend associated with ENDS-related adverse events and poisoning.

BackgroundIn 2016, the "Act on Support for Overseas Expansion of Healthcare System and Attraction of International Patients" was enacted by the South Korean government in an attempt to accelerate growth of its medical tourism industry. However, only a few years after its implementation, the benefits are not well understood, nor have the positive or negative impacts of expanding Korea's medical tourism sector been properly evaluated.ObjectiveWe aimed to systematically review and summarize existing literature describing South Korea's medical tourism policy and legislative history, while also assessing the impact of this domestic policy approach on the country's public health systems.MethodsA bilingual systematic literature review was conducted per PRISMA guidelines for all South Korean medical tourism legislative and policy literature using MeSH terms and other related keywords in two academic databases, PubMed and JSTOR. Published studies were included if they directly addressed South Korean medical tourism policy. To supplement results from the peer-review, the grey literature was also searched using Google search engine for relevant policy documents, information from government websites, and national statistics on medical tourism-related data.ResultsThis review included 14 peer-reviewed journal articles and 9 websites. The majority of literature focused on the legislative history of South Korea's pro-medical tourism policy, economic considerations associated with industry growth, and the specific experiences of medical tourists. There was a lack of studies, analytical or commentary-based, conducting in-depth analysis of the healthcare impact of these policies or comparing benefits and costs compared to other medical tourism destinations. Proponents of medical tourism continue to advocate the government for increased deregulation and investment in the sector.ConclusionThis systematic review suggests that policy decisions may prioritize economic growth offered by medical tourism over negative effects on the healthcare workforce, access and equity, and its potential to undermine Universal Health Coverage. South Korea continues to examine ways to further amend the Act and grow this sector, but these actions should be taken with caution by critically examining how other countries have adapted their policymaking based on the real-world costs associated with medical tourism.

IntroductionThe potential of regenerative medicine to improve human health has led to the rapid expansion of stem cell clinics throughout the world with varying levels of regulation and oversight. This has led to a market ripe for stem cell tourism, with Tijuana, Mexico, as a major destination. In this study, we characterize the online marketing, intervention details, pricing of services, and assess potential safety risks through web surveillance of regenerative medicine clinics marketing services in Tijuana.MethodsWe conducted structured online search queries from March to April 2019 using 296 search terms in English and Spanish on two search engines (Google and Bing) to identify websites engaged in direct-to-consumer advertising of regenerative medicine services. We performed content analysis to characterize three categories of interest: online presence, tokens of scientific legitimacy, and intervention details.ResultsOur structured online searches resulted in 110 unique websites located in Tijuana corresponding to 76 confirmed locations. These clinics' online presence consisted of direct-to-consumer advertising mainly through a dedicated website (94.5%) or Facebook page (65.5%). The vast majority of these websites (99.1%) did not mention any affiliation to an academic institutions or other overt tokens of scientific legitimacy. Most clinics claimed autologous tissue was the source of treatments (67.3%) and generally did not specify route of administration. Additionally, of the Tijuana clinics identified, 13 claimed licensing, though only 1 matched with available licensing information.ConclusionsRegenerative medicine clinics in Tijuana have a significant online presence using direct-to-consumer advertising to attract stem-cell tourism clientele in a bustling border region between Mexico and the USA. This study adds to existing literature evidencing the unregulated nature of online stem cell offerings and provides further evidence of the need for regulatory harmonization, particularly to address stem cell services being offered online across borders.

IntroductionEarly reports of COVID-19 cases and deaths may not accurately convey community-level concern about the pandemic during early stages, particularly in the United States where testing capacity was initially limited. Social media interaction may elucidate public reaction and communication dynamics about COVID-19 in this critical period, during which communities may have formulated initial conceptions about the perceived severity of the pandemic.MethodsTweets were collected from the Twitter public API stream filtered for keywords related to COVID-19. Using a pre-existing training set, a support vector machine (SVM) classifier was used to obtain a larger set of geocoded tweets with characteristics of user self-reporting COVID-19 symptoms, concerns, and experiences. We then assessed the longitudinal relationship between identified tweets and the number of officially reported COVID-19 cases using linear and exponential regression at the U.S. county level. Changes in tweets that included geospatial clustering were also assessed for the top five most populous U.S. cities.ResultsFrom an initial dataset of 60 million tweets, we analyzed 459,937 tweets that contained COVID-19-related keywords that were also geolocated to U.S. counties. We observed an increasing number of tweets throughout the study period, although there was variation between city centers and residential areas. Tweets identified as COVID-19 symptoms or concerns appeared to be more predictive of active COVID-19 cases as temporal distance increased.ConclusionResults from this study suggest that social media communication dynamics during the early stages of a global pandemic may exhibit a number of geospatial-specific variations among different communities and that targeted pandemic communication is warranted. User engagement on COVID-19 topics may also be predictive of future confirmed case counts, though further studies to validate these findings are needed.

Introduction: College-aged youth are active on social media yet smoking-related social media engagement in these populations has not been thoroughly investigated. We sought to conduct an exploratory infoveillance study focused on geolocated data to characterize smoking-related tweets originating from California 4-year colleges on Twitter. Methods: Tweets from 2015 to 2019 with geospatial coordinates in CA college campuses containing smoking-related keywords were collected from the Twitter API stream and manually annotated for discussions about smoking product type, sentiment, and behavior. Results: Out of all tweets detected with smoking-related behavior, 46.7% related to tobacco use, 50.0% to marijuana, and 7.3% to vaping. Of these tweets, 46.1% reported first-person use or second-hand observation of smoking behavior. Out of 962 tweets with user sentiment, the majority (67.6%) were positive, ranging from 55.0% for California State University, Long Beach to 95.8% for California State University, Los Angeles. Discussion: We detected reporting of first- and second-hand smoking behavior on CA college campuses representing possible violation of campus smoking bans. The majority of tweets expressed positive sentiment about smoking behaviors, though there was appreciable variability between college campuses. This suggests that anti-smoking outreach should be tailored to the unique student populations of these college communities. Conclusion: Among tweets about smoking from California colleges, high levels of positive sentiment suggest that the campus climate may be less receptive to anti-smoking messages or adherence to campus smoking bans. Further research should investigate the degree to which this varies by campuses over time and following implementation of bans including validating using other sources of data.

The Open Payments database reports payments made to physicians by industry. Given the potential for financial conflicts of interest relating to patient outcomes, further scrutiny of these data is valuable. Therefore, the objective of this study was to analyze physician-industry relationships by specialty type, payment type, geospatial trend, and longitudinal trend between 2014-2018. We conducted an observational, retrospective data analysis of payments from the Open Payments database for licensed United States physicians listed in the National Plan & Provider Enumeration System (NPPES). Datasets from 2013-2018 were joined using the Python programming language. Aggregation and sub-setting by characteristics of interest was done in R to calculate means and frequencies of reported general physician payments from industry across different specialties, locations, timeframes, and payment types. Normalization was applied for numbers of physicians or payments. Geospatial statistical hot spot analysis was conducted in ArcGIS. 51.73 million payment records were analyzed. In total, 50,047,930 payments were issued to 771,113 allopathic or osteopathic physicians, representing $8,702,631,264 transferred from industry to physicians over the five-year period between 2014 and 2018. The mean payment amount was $179, with a standard deviation of $12,685. Variability in physicians' financial relationships with industry were apparent across specialties, regions, time, and payment type. A limited match rate between records in the NPPES and Open Payments databases may have resulted in selection bias of trends related to physician characteristics. Further research is necessary, particularly in the context of changing industry payment trends and public perceptions of the appropriateness of these relationships.

Introduction and aimsInfoveillance approaches (i.e. surveillance methods using online content) that leverage big data can provide new insights about infectious disease outbreaks and substance use disorder topics. We assessed social media messages about HIV, opioid use and injection drug use in order to understand how unstructured data can prepare public health practitioners for response to future outbreaks.Design and methodsWe conducted an retrospective analysis of Twitter messages during the 2015 HIV Indiana outbreak using machine learning, statistical and geospatial analysis to examine the transition between opioid prescription drug abuse to heroin injection use and finally HIV transmission risk, and to test possible associations with disease burden and demographic variables in Indiana and Marion County. Tweets from October 2014 to June 2015 were compared to disease burden at the county level for Indiana, and classification of census blocks by presence of relevant messages was done at the census block level for Marion County. Marion County was used as it exhibited the highest total count of Tweets.Results257 messages about substance abuse and HIV were significantly related to HIV rates (P

Background: Pharmaceutical corruption is a serious challenge in global health. Digital technologies that can detect and prevent fraud and corruption are particularly important to address barriers to access to medicines, such as medicines availability and affordability, stockouts, shortages, diversion, and infiltration of substandard and falsified medicines.Objectives: To better understand how digital technologies are used to combat corruption, increase transparency, and detect fraud in pharmaceutical procurement systems to improve population health outcomes.Methods: We conducted a multidisciplinary review of the health/medicine, engineering, and computer science literature. Our search queries included keywords associated with medicines procurement and digital technology in combination with terms associated with transparency and anti-corruption initiatives. Our definition of 'digital technology' focused on Internet-based communications, including online portals and management systems, supply chain tools, and electronic databases.Results: We extracted 37 articles for in-depth review based on our inclusion criteria focused on the utilization of digital technology to improve medicines procurement. The vast majority of articles focused on electronic data transfer and/or e-procurement systems with fewer articles discussing emerging technologies such as machine learning and blockchain distributed ledger solutions. In the context of e-procurement, slow adoption, justifying cost-savings, and need for technical standards setting were identified as key challenges for current and future utilization.Conclusions: Though there is a significant promise for digital technologies, particularly e-procurement, overall adoption of solutions that can enhance transparency, accountability and concomitantly combat corruption, is still underdeveloped. Future efforts should focus on tying cost-saving measurements with anti-corruption indicators, prioritizing centralization of e-procurement systems, establishing regulatory harmonization with standards setting, and incorporating additional anti-corruption technologies into procurement processes for improving access to medicines and to reach the overall goal of Universal Health Coverage.

IntroductionFrom late 2014 through 2015, Scott County, Indiana faced an HIV outbreak triggered by opioid abuse and transition to injection drug use. Investigating the origins, risk factors, and responses related to this outbreak is critical to inform future surveillance, interventions, and policymaking. In response, this retrospective infoveillance study identifies and characterizes user-generated messages related to opioid abuse, heroin injection drug use, and HIV status using natural language processing (NLP) among Twitter users in Indiana during the period of this HIV outbreak.Materials and methodsOur study consisted of two phases: data collection and processing, and data analysis. We collected Indiana geolocated tweets from the public Twitter API using Amazon Web Services EC2 instances filtered for geocoded messages in the immediate pre and post period of the outbreak. In the data analysis phase we applied an unsupervised machine learning approach using NLP called the Biterm Topic Model (BTM) to identify tweets related to opioid, heroin/injection, and HIV behavior and then examined these messages for HIV risk-related topics that could be associated with the outbreak.ResultsMore than 10 million geocoded tweets occurring in Indiana during the immediate pre and post period of the outbreak were collected for analysis. Using BTM, we identified 1350 tweets thought to be relevant to the outbreak and then confirmed 358 tweets using human annotation. The most prevalent themes identified were tweets related to self-reported abuse of illicit and prescription drugs, opioid use disorder, self-reported HIV status, and public sentiment regarding the outbreak. Geospatial analysis found that these messages clustered in population dense areas outside of the outbreak, including Indianapolis and neighboring Clark County.DiscussionThis infoveillance study characterized the social media conversations of communities in Indiana in the pre and post period of the 2015 HIV outbreak. Behavioral themes detected reflect discussion about risk factors related to HIV transmission stemming from opioid and heroin abuse for priority populations, and also help identify community attitudes that could have motivated or detracted the use of HIV prevention methods, along with helping identify factors that can impede access to prevention services.ConclusionsInfoveillance approaches, such as the analysis conducted in this study, represent a possibly strategy to detect "signal" of the emergence of risk factors associated with an outbreak though may be limited in their scope and generalizability. Our results, in conjunction with other forms of public health surveillance, can leverage the growing ubiquity of social media platforms to better detect opioid-related HIV risk knowledge, attitudes and behavior, as well as inform future prevention efforts.

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.

BACKGROUND:Global health diplomacy (GHD) is a burgeoning field bridging the priorities of global health and foreign affairs. Given the increasing need to mobilize disparate global health stakeholders coupled with the need to design complex public health partnerships to tackle issues of international concern, effective and timely cooperation among state actors is critical. Health Attachés represent this coordination focal point and are key diplomatic professionals at the forefront of GHD. Despite their unique mandate, little is published about this profession and the perspectives of those who work in the field. METHODS:Through purposive sampling, we performed in-depth qualitative interviews with seven Health Attachés: three foreign Health Attachés accredited to the United States and four U.S. Health Attachés accredited to foreign governments. Our interviews explored four key topics: the role and mission of Health Attachés, skills needed to perform GHD, examples of successes and challenges in accomplishing their respective missions, and suggestions for the future development of the diplomatic profession. RESULTS:We identified several lessons to apply to the growing field of GHD. First, GHD actors need to receive appropriate training to successfully negotiate the intersection of global health and foreign affairs. Participants suggested several areas of training that would benefit GHD actors: diplomacy and negotiation, applied science, and cross-cultural competency. Second, participants articulated the need for a career path for GHD practitioners, increased opportunities for on-the-job training and mentored experiences, and GHD competencies with defined levels of mastery that can be used in occupational evaluation and career development. CONCLUSIONS:Our findings indicate that skills in diplomacy and negotiation, applied science, and cross cultural competency are essential for the statecraft of Health Attachés. Additionally, establishing a clear career pathway for Health Attachés is critical for future maturation of the profession and for fostering effective global health action that aligns public health and foreign diplomacy outcomes. Achieving these goals would ensure that this special cadre of diplomats could effectively practice GHD and would also better position Health Attachés to take the lead in advancing shared global health goals among nation states in a new era of twenty-first century diplomacy.

BackgroundAccessibility to essential cancer medications in low- and middle-income countries is threatened by insufficient availability and affordability. The objective of this study is to characterize variation in transactional prices for essential cancer medications across geographies, medication type, and time.MethodsDrug purchase prices for 19 national and international buyers (representing 29 total countries) between 2010 and 2014 were obtained from Management Sciences for Health. Median values for drug pricing were computed, to address outliers in the data. For comparing purchase prices across geographic units, medications, and over time; Mann-Whitney U tests were used to compare two groups, Kruskal Wallis H tests were used to compare more than two groups, and linear regression was used to compare across continuous independent variables.ResultsDuring the five-year data period examined, the median price paid for a package of essential cancer medication was $12.63. No significant differences in prices were found based on country-level wealth, country-level disease burden, drug formulation, or year when medication was purchased. Statistical tests found significant differences in prices paid across countries, regions, individual medications, and medication categories. Specifically, countries in the Africa region appeared to pay more for a package of essential cancer medication than countries in the Latin America region, and cancer medications tended to be more expensive than anti-infective medications and cardiovascular medications.ConclusionsThough preliminary, our study found evidence of variation in prices paid by health systems to acquire essential cancer medications. Primarily, variations in pricing based on geographic location and cancer medication type (including when comparing to essential medicines that treat cardiovascular and infectious diseases) indicate that these factors may impact availability, affordability and access to essential cancer drugs. These factors should be taken into consideration when countries assess formulary decisions, negotiate drug procurement terms, and when formulating health and cancer policy.

Background: Explanations for why social media users propagate misinformation include failure of classical reasoning (over-reliance on intuitive heuristics), motivated reasoning (conforming to group opinion), and personality traits (e.g., narcissism). However, there is a lack of consensus on which explanation is most predictive of misinformation spread. Previous work is also limited by not distinguishing between passive (i.e., "liking") and active (i.e., "retweeting") propagation behaviors. Methods: To examine this issue, 858 Twitter users were recruited to engage in a Twitter simulation task in which they were shown real tweets on public health topics (e.g., COVID-19 vaccines) and given the option to "like", "reply", "retweet", "quote", or select "no engagement". Survey assessments were then given tomeasure variables corresponding to explanations for: classical reasoning [cognitive reflective thinking (CRT)], motivated reasoning (religiosity, political conservatism, and trust in medical science), and personality traits (openness to new experiences, conscientiousness, empathy, narcissism). Results: Cognitive reflective thinking, conscientiousness, openness, and emotional concern empathy were all negatively associated with liking misinformation, but not significantly associated with retweeting it. Trust in medical scientists was negatively associated with retweeting misinformation, while grandiose narcissism and religiosity were positively associated. An exploratory analysis on engagement with misinformation corrections shows that conscientiousness, openness, and CRT were negatively associated with liking corrections while political liberalism, trust in medical scientists, religiosity, and grandiose narcissism were positively associated. Grandiose narcissism was the only factor positively associated with retweeting corrections. Discussion: Findings support an inhibitory role for classical reasoning in the passive spread of misinformation (e.g., "liking"), and a major role for narcissistic tendencies and motivated reasoning in active propagating behaviors ("retweeting"). Results further suggest differences in passive and active propagation, as multiple factors influence liking behavior while retweeting is primarily influenced by two factors. Implications for ecologically valid study designs are also discussed to account for greater nuance in social media behaviors in experimental research. [ABSTRACT FROM AUTHOR]