Abstract:
Background:
The 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.

Methods:
The 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.

Results:
We 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.

Conclusions:
Though 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.

Abstract:
Background:
Healthcare costs, especially those associated with emergency department (ED) visits, are increasing at an unsustainable rate. Often, ED visits for certain conditions can be prevented through patients utilizing their primary care physician. We consider two of these conditions: diabetes for adults (n=342,286 patient quarters), and ear, nose, and throat (ENT) conditions for children (n=2,660,733 patient quarters). Being able to identify patients at risk of an avoidable admission to the ED could lead to dramatically reduced costs for both patients and healthcare systems. We develop models to predict avoidable admissions (defined as visits to the ED for either of these ambulatory care sensitive conditions) and reduce healthcare costs.

Methods:
Patients with the chosen conditions (adult diabetes and juvenile ENT) were drawn from a major hospital system. The training set includes 10 total quarters, spanning from the third quarter of 2016 to the last quarter of 2018. The test set, where all models were compared, includes the first quarter of 2019. Logistic regression has commonly been used to identify high-risk patients, but more recently other statistical and machine learning techniques have been employed. We use a variety of models, including the lasso, a mixed model, random forest, and XGBoost to determine which model best predicts avoidable ED visits. All available predictors were included in the full model and compared. We also include novel predictors, such as how far a patient lives from the ED and a patient’s family’s tendencies to visit the ED. The predictors are compared using multiple methods (including LASSO, P values, and boosting).

Results:
We find the XGBoost model generally outperforms the other models in the validation sample (C-index of 0.80 in both the diabetes and ENT cohorts). Among the best predictors of future ED visits are past ED visits; a patient’s age and weight; and, for patients with diabetes, the amount of time since their initial diabetes diagnosis.

Conclusions:
If implemented, this model can identify 50 patients who would have gone to the ED unnecessarily by only contacting 600 patients. Or, by contacting 5,500 patients, identify (and potentially prevent) 170 unnecessary ED visits.

Abstract:
This study seeks to identify and characterize key barriers associated with PrEP therapy as self-reported by users on social media platforms. We used data mining and unsupervised machine learning approaches to collect and analyze COVID-19 and PrEP-related posts from three social media platforms including Twitter, Reddit, and Instagram. Predominant themes detected by unsupervised machine learning and manual annotation included users expressing uncertainty about PrEP treatment adherence due to COVID-19, challenges related to accessibility of clinics, concerns about PrEP costs and insurance coverage, perceived lower HIV risk leading to lack of adherence, and misinformation about PrEP use for COVID-19 prevention.

Abstract:
Background:
Previous studies have identified numerous adverse events experienced with the use
of ENDS or E-cigarettes. However, much remains unknown about adverse event frequency, duration, and response experienced by users. The purpose of this study was to inductively characterize
ENDS-attributed adverse events among young adults.

Methods:
Sixteen focus groups were held with 114 young adults (aged 18−29 years) who have
reported lifetime ENDS use in April 2021. Discussion topics included current and previous tobacco,
nicotine, and cannabis use; specific symptoms and frequency and duration of and response to
symptoms of ENDS-attributed adverse events; and the impact of other conditions such as COVID19 on ENDS use. Data were inductively analyzed using a team-based approach.

Results:
More than 40 ENDS-attributed adverse events were reported in focus groups among
approximately three quarters of all study participants, with headache, coughing, lightheadedness,
nausea, dry or sore throat, and dizziness the most common. In general, adverse events were transient, with most resolving in a few hours, although some tended to last for longer. The frequency of
adverse events varied most between every time ENDS were used and when someone vaped excessively. Finally, behavioral responses varied by adverse events, with difficulty in breathing, chest
pain, and lung discomfort more likely to result in quitting permanently.

Conclusions:
Overall, the results of this study show that not only do adverse events vary greatly,
but they also vary across multiple dimensions of user experience.

Abstract:
A case-control study was conducted between 12/01/2021–01/31/2022 to identify factors which increase risk for 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.

Abstract:
Social media has been documented as widely used for initiating online sales of illicit drugs such as opioids. However, not much is known about how affordances of social networking sites (SNS) influence how dealers advertise their supplies. To explore this topic, social media posts across 5 online platforms (Google Groups, Instagram, Twitter, Reddit, and Tumblr) were collected during 2020–2021. Biterm topic modeling (BTM) was used to identify signal posts specifically associated with the illegal online sale of opioids from drug selling social media accounts. Posts were analyzed by conducting a word count for drug names or slang terms associated with 5 categories: Opioids, Non-Opioid Prescription Controlled Drugs (e.g., Xanax, Valium), Other Illicit Drugs (e.g., Meth, Cocaine), Synthetic Opioids (Fentanyl), and Synthetic Marijuana. Number of mentions per post were calculated for each drug category and compared across platforms. Identifiers (e.g., publicly available email address) associated with posts were used to track dealers across different user accounts. Platforms with affordances for longer messages (e.g., Tumblr) had higher concentrations of drug mentions per post and higher variety of drug type mentions compared to SNS platforms Instagram and Twitter. Google Groups had the most drug mentions per post across all 5 categories. Additionally, each identifier was associated with multiple user accounts on a given platform. These results indicate that affordances of anonymity and message length may influence how drug dealers advertise their services on different platforms. Public health implications and strategies to counteract drug dealers and illicit drug diversion via SNS are also discussed.

Abstract:
Background:
Tobacco 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.

Methods:
Data 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.

Results:
The 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.

Conclusions:
Monitoring 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.

Abstract:
Electronic nicotine delivery systems (ENDS) are the most used tobacco products among middle and high schoolers in the United States (U.S.). Familial relations and access play a major role in uptake among adolescents; yet the role of social media in this phenomenon in the context of communities impacted by tobacco-related health disparities is understudied. In Spring 2019, data were collected from adolescents in 8th and 9th grades in a school located in a rural distressed county in Tennessee to assess social media’s role in ENDS uptake. Descriptive and multivariable statistical analyses were performed to delineate factors associated with ENDS use. Of a total of 399 respondents, 12.5 % reported current ENDS use and 22.1 % indicated having ever discussed ENDS on social media. Closed messaging platforms (Snapchat) and video platforms (Facebook/Instagram/You Tube) were the most reported form of social media used (8.31 % and 8.31 % respectively). Social media use was positively associated with both ever ENDS use (odds ratio [OR] = 2.9) and current ENDS use (OR = 3.98). Parental advice against ENDS use was positively associated with ever ENDS use. In conclusion, social media use was positively associated with both ever and current ENDS use, and Snapchat was the most popular platform among this population of students. The results indicate that youth social media engagement may lead to exposure that can influence ENDS uptake. Future studies are needed to further examine these associations among distressed communities.

Abstract:
Background:
The 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 covered: Following 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 opinion: Findings 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 .

Abstract:
Background:
Among racial and ethnic minority groups, the risk of HIV infection is an ongoing public health challenge. Pre-exposure prophylaxis (PrEP) is highly effective for preventing HIV when taken as prescribed. However, there is a need to understand the experiences, attitudes, and barriers of PrEP for racial and ethnic minority populations and sexual minority groups.

Objective:
This infodemiology study aimed to leverage big data and unsupervised machine learning to identify, characterize, and elucidate experiences and attitudes regarding perceived barriers associated with the uptake and adherence to PrEP therapy. This study also specifically examined shared experiences from racial or ethnic populations and sexual minority groups.

Methods:
The study used data mining approaches to collect posts from popular social media platforms such as Twitter, YouTube, Tumblr, Instagram, and Reddit. Posts were selected by filtering for keywords associated with PrEP, HIV, and approved PrEP therapies. We analyzed data using unsupervised machine learning, followed by manual annotation using a deductive coding approach to characterize PrEP and other HIV prevention–related themes discussed by users.

Results:
We collected 522,430 posts over a 60-day period, including 408,637 (78.22%) tweets, 13,768 (2.63%) YouTube comments, 8728 (1.67%) Tumblr posts, 88,177 (16.88%) Instagram posts, and 3120 (0.6%) Reddit posts. After applying unsupervised machine learning and content analysis, 785 posts were identified that specifically related to barriers to PrEP, and they were grouped into three major thematic domains: provider level (13/785, 1.7%), patient level (570/785, 72.6%), and community level (166/785, 21.1%). The main barriers identified in these categories included those associated with knowledge (lack of knowledge about PrEP), access issues (lack of insurance coverage, no prescription, and impact of COVID-19 pandemic), and adherence (subjective reasons for why users terminated PrEP or decided not to start PrEP, such as side effects, alternative HIV prevention measures, and social stigma). Among the 785 PrEP posts, we identified 320 (40.8%) posts where users self-identified as racial or ethnic minority or as a sexual minority group with their specific PrEP barriers and concerns.

Conclusions:
Both objective and subjective reasons were identified as barriers reported by social media users when initiating, accessing, and adhering to PrEP. Though ample evidence supports PrEP as an effective HIV prevention strategy, user-generated posts nevertheless provide insights into what barriers are preventing people from broader adoption of PrEP, including topics that are specific to 2 different groups of sexual minority groups and racial and ethnic minority populations. Results have the potential to inform future health promotion and regulatory science approaches that can reach these HIV and AIDS communities that may benefit from PrEP.

Abstract:
Background:
Though university smoke-free and tobacco-free campus policies have been proliferating across the US, compliance and enforcement remain challenges. This study examined perceptions and behaviors of employees and students who used tobacco products on tobacco-free campuses, to better understand policy noncompliance.

Methods:
Students (n=56) and employees (n=20) from two tobacco-free 4-year public universities in Southern California who self-reported using tobacco products on campus participated in focus groups, stratified by university and student or employee (faculty and staff) status, to discuss attitudes toward campus tobacco policies and on-campus smoking. Focus group discussions were transcribed and analyzed after structured coding and subcoding.

Results:
Participants were generally aware that smoking and vaping were not allowed on campus, though few could correctly identify their campus as tobacco-free. Attitudes toward the policy varied by subgroup and by campus, with students and employees at different universities expressing varying levels of support. Non-compliance was a unique interaction of individual, institutional, and interpersonal factors including a desire to smoke or vape to reduce stress, lack of formal enforcement or penalty for violating the policy, and efforts to smoke or vape in ways that reduce harm to others as a way of rationalizing non-compliance.

Conclusions:
Attitudes toward university tobacco-free policies are campus- and constituency-specific, with similarities in individual, institutional, and interpersonal factors underlying non-compliance. Interventions to increase compliance should address individual, institutional, and interpersonal influences on non-compliance through efforts tailored to specific campus constituencies based on their particular knowledge and attitudes towards tobacco-free policies.

Abstract:
Background:
Antimicrobial resistance is a significant global public health threat. However, the impact of sourcing potentially substandard and falsified antibiotics via the internet remains understudied, particularly in the context of access to and quality of common antibiotics. In response, this study conducted a multifactor quality and safety analysis of antibiotics sold and purchased via online pharmacies that did not require a prescription.

Objective:
The aim of this paper is to identify and characterize “no prescription” online pharmacies selling 5 common antibiotics and to assess the quality characteristics of samples through controlled test buys.

Methods:
We first used structured search queries associated with the international nonproprietary names of amoxicillin, azithromycin, amoxicillin and clavulanic acid, cephalexin, and ciprofloxacin to detect and characterize online pharmacies offering the sale of antibiotics without a prescription. Next, we conducted controlled test buys of antibiotics and conducted a visual inspection of packaging and contents for risk evaluation. Antibiotics were then analyzed using untargeted mass spectrometry (MS). MS data were used to determine if the claimed active pharmaceutical ingredient was present, and molecular networking was used to analyze MS data to detect drug analogs as well as possible adulterants and contaminants.

Results:
A total of 109 unique websites were identified that actively advertised direct-to-consumer sale of antibiotics without a prescription. From these websites, we successfully placed 27 orders, received 11 packages, and collected 1373 antibiotic product samples. Visual inspection resulted in all product packaging consisting of pill packs or blister packs and some concerning indicators of potential poor quality, falsification, and improper dispensing. Though all samples had the presence of stated active pharmaceutical ingredient, molecular networking revealed a number of drug analogs of unknown identity, as well as known impurities and contaminants.

Conclusions:
Our study used a multifactor approach, including web surveillance, test purchasing, and analytical chemistry, to assess risk factors associated with purchasing antibiotics online. Results provide evidence of possible safety risks, including substandard packaging and shipment, falsification of product information and markings, detection of undeclared chemicals, high variability of quality across samples, and payment for orders being defrauded. Beyond immediate patient safety risks, these falsified and substandard products could exacerbate the ongoing public health threat of antimicrobial resistance by circulating substandard product to patients.

Abstract:
Background:
TikTok 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.
Objective:
We aimed to assess the characteristics of content on TikTok that is associated with a popular nicotine poisoning–related hashtag.

Methods:
We 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.

Results:
A 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).

Conclusions:
TikTok 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).

Abstract:
Background:
Exposure 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.

Methods:
Tweets 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.

Results:
A 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.

Conclusions:
Results 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.

Abstract:
Background:
Though university smoke-free and tobacco-free campus policies have been proliferating across the US, compliance and enforcement remain challenges. This study examined perceptions and behaviors of employees and students who used tobacco products on tobacco-free campuses, to better understand policy non-compliance.

Methods:
Students (n=56) and employees (n=20) from two tobacco-free 4-year public universities in Southern California who self-reported using tobacco products on campus participated in focus groups, stratified by university and student or employee (faculty and staff) status, to discuss attitudes toward campus tobacco policies and on-campus smoking. Focus group discussions were transcribed and analyzed after structured coding and subcoding.

Results:
Participants were generally aware that smoking and vaping were not allowed on campus, though few could correctly identify their campus as tobacco-free. Attitudes toward the policy varied by subgroup and by campus, with students and employees at different universities expressing varying levels of support. Non-compliance was a unique interaction of individual, institutional, and interpersonal factors including a desire to smoke or vape to reduce stress, lack of formal enforcement or penalty for violating the policy, and efforts to smoke or vape in ways that reduce harm to others as a way of rationalizing non-compliance.

Conclusions:
Attitudes toward university tobacco-free policies are campus- and constituency-specific, with similarities in individual, institutional, and interpersonal factors underlying non-compliance. Interventions to increase compliance should address individual, institutional, and interpersonal influences on non-compliance through efforts tailored to specific campus constituencies based on their particular knowledge and attitudes towards tobacco-free policies.

Abstract:
Background:
Access to tobacco products, including vape products, from local brick-and-mortar stores influences the exposure, uptake, and use of these products in local communities.

Methods:
Licensed 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.

Results:
The 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).

Conclusions:
Localities 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.

Abstract:
Simultaneous expansion of the Internet and increased globalisation of the pharmaceutical industry have meant medication can be accessed transnationally from both legal and illicit sources. This has coincided with the rise of substandard and falsified medicines (SFMs) online. These products fail to meet regulatory or quality standards and/or are constituted with substandard ingredients, causing undesired pharmacological effects, including possible injury and death. This review aimed to identify original research studies that examined characteristics of SFM online sales, attitudes towards purchasing medicines online and strategies to address this drug safety challenge. Keywords of ‘Substandard’ and ‘Falsified’/‘Counterfeit’ and ‘Medicines’/‘Drugs’ and ‘Online’/‘Internet’ were searched using Web of Knowledge and PubMed databases. Resulting literature, which satisfied the study’s inclusion criteria, was included in the review, and the findings from each paper were assessed. From an initial 185 literature articles, 7 were eligible according to the inclusion criteria to be reviewed. These articles identified studies testing SFMs purchased online, surveys of attitudes and knowledge about SFMs online, and website content analysis to detect illegal online sales. Challenges identified were lack of knowledge and awareness among consumers and physicians, in addition to the use of direct-to-consumer-advertising, via Internet platforms and social media, providing easy access to SFMs. Despite this, medicine authentication technology, website verification approaches and new detection methods were identified as potential solutions specific to online SFM sales. To address online sales of SFMs, more robust research, greater awareness/educational programmes, analytical detection methods and more stringent online global governance are required.

Abstract:
Background:
Synthetic 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.

Objective:
This study aimed to examine TikTok posts for use and illicit distribution of psychoactive substances (eg, K2/Spice) among incarcerated populations.

Methods:
The 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.

Results:
A 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.

Conclusions:
K2/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.

Abstract:
Objective: We sought to determine school and community characteristics associated with proximity to tobacco and ENDS storefronts within a 0.5-kilometer radius in California.


Methods: A list of licensed tobacco retailers was obtained from the California Department of Tax and Fee Administration; retailer names and addresses were used to scrape Yelp in order to determine sub-categorization of business as a vape or tobacco shop. US Census Bureau data was used to assess characteristics at the census tract level, and the California Department of Education provided school characteristics. Logistic regression with backward selection was used to assess for associations.


Results: The final regression model included six community variables which were all negatively associated with retailer proximity (percent male, percent age 5-10, percent age 15-20, percent age 25-30, percent age 55-60, and percent age 60-65) as well as four school characteristics which were all positively associated (percent female students, percent Hispanic students, percent White students, percent eligible for free and reduced priced meals [FRPM]).


Conclusions: Variation in demographics reflected most of the risk associated with school proximity to tobacco retailers. FRPM was associated with storefront proximity indicating that schools with lower socioeconomic status may be at higher exposure to tobacco retailing.

Abstract:
Background
Shortly after Pfizer and Moderna received emergency use authorizations from the FDA, there have been increased reports of COVID-19 vaccine-related deaths in the Vaccine Adverse Event Reporting System (VAERS). In January 2021, MLB legend and Hall of Famer Hank Aaron passed away at the age of 86 from natural causes, just two weeks after he received the COVID-19 vaccine. Anti-vaccination groups attempted to link his death to the Moderna vaccine, similar to other attempts to mispresent data from the VAERS to spread COVID-19 misinformation.

Objective
This study assessed the spread of misinformation linked to erroneous claims about Hank Aaron’s death on Twitter and then characterized different vaccine misinformation and hesitancy themes generated from users who interacted with this misinformation discourse.

Methods
An initial sample of tweets, from January 31 to February 6, 2021, was queried from the Twitter Search Application Programming Interface (API) using the keywords “Hank Aaron” and “vaccine”. The sample was manually annotated for misinformation, reporting or news media, and public reaction. Non-media user accounts were also classified if they were verified by Twitter. A second sample of tweets, representing direct comments or retweets to misinformation-labeled content was also collected. User sentiment toward misinformation, positive (agree) or negative (disagree), was recorded. The SAGE vaccine hesitancy matrix from the World Health Organization was used to code the second sample of tweets for factors influencing vaccine confidence.

Results
A total of 436 tweets were initially sampled from the Twitter Search API. Misinformation was the most prominent content type (56%, n = 244) detected, followed by public reaction (28%, n = 122) and media reporting (16%, n = 69). No misinformation-related content reviewed was labeled as misleading by Twitter at the time of the study. An additional 1,243 comments on misinformation-labeled Tweets from 973 unique users were also collected, with 779 comments deemed relevant to study aims. Most of these comments expressed positive sentiment (78.6%, n = 612) to misinformation and did not refute it. Based on the WHO SAGE framework, the most common vaccine hesitancy theme was individual or group influences (65%, n=508), followed by vaccine or vaccination-specific influences (14%, n=110) and contextual influences (12%, n=93). Common misinformation themes observed included linking the death of Hank Aaron to “suspicious” elderly deaths following vaccination, claims about vaccines being used for depopulation, death panels, federal officials targeting Black Americans, and misinterpretation of VAERS reports. Four users engaging with or posting misinformation were verified on Twitter at the time of data collection.

Conclusions
Our study found that the death of a high-profile ethnic minority celebrity led to the spread of misinformation on Twitter. This misinformation directly challenged the safety and effectiveness of COVID-19 vaccines at a time when ensuring vaccine coverage among minority populations was paramount. Misinformation targeted at minority groups and echoed by other verified Twitter users has the potential to generate unwarranted vaccine hesitancy at the expense of people like Hank Aaron who sought to promote public health and community immunity.

Abstract: Smoke- and tobacco-free university polices have been expanding throughout the United States. In spite of the benefits of such policies, policy compliance remains a challenge. A better understanding of campus community enforcement approaches is needed to inform future policy implementation to bring about greater adherence to university smoke- and tobacco-free policies. To this end, thirteen focus groups with 76 participants from two universities in Southern California with tobacco-free policies were held from October 2019 through October 2020 to discuss attitudes toward and experiences with the campus smoking policy, campus tobacco use behavior, and policy enforcement. Focus groups discussions were recorded, transcribed, and analyzed using a general inductive analysis approach. A wide array of campus stakeholders were involved in enforcement actions, including formal entities such as police and parking enforcement, as well as the general campus community such as students and employees. However, the majority of participants in the study had never had an enforcement experience and those who did only did so on rare occasion. Enforcement experiences were often perceived as aggressive, which elicited a desire for a similarly aggressive response on the part of the person smoking or vaping. The enforcement of e-cigarettes is particularly challenging because of the speed and discretion with which they can be used compared to combustible tobacco and perceived favorable norms toward e-cigarettes. Universities should consider using proactive, consistent, and tailored actions to reinforce changing social norms for greater policy compliance.

Abstract:
Various tobacco vendors, including alternative tobacco product sellers, are listed on the popular crowdsourced business listing platform Yelp. Yelp is used to rate and choose tobacco, electronic nicotine delivery systems (ENDS) goods/services and includes self-reporting of user experiences with shops and products. We cross-referenced California Department of Tax and Fee Administration (CDTFA) licensed tobacco, vape, and head shop retail stores with publicly available Yelp business listings to identify licensed and unlicensed stores in California. We extracted metadata associated with store accounts and analyzed user comments and ratings for discussion of tobacco-related complaints and adverse events. We detected a total of 3,717 shops that were categorized as tobacco/vape/head shops on Yelp and by cross-referencing with CDTFA data, licensed businesses accounted for 49.5% (n = 1,841), licensed individual retailers 31.6% (n = 1,174), and suspected unlicensed storefronts 18.9% (n = 702). Businesses and individuals with a state tobacco retail license received a higher average rating from Yelp users (3.86 out of 5) compared to unlicensed shops (3.57) (p < 0.001). Additionally, 4,682 unique comments about licensed businesses, 1,535 unique comments about individual retailers, and 560 unique comments about unlicensed vendors were reviewed, with themes including discussion about defective and counterfeit products and adverse events including coughing, difficulty breathing and reports of hospitalization detected. In contrast, comments about licensed stores predominantly discussed customer service issues. Close to one-fifth of tobacco, vape and/or head shops reviewed on Yelp were not in CDTFA’s licensure database. Overall self-reported tobacco user experiences appeared to differ in content and severity based on whether an establishment was licensed. These results have the potential to identify unauthorized stores and adverse events associated with their tobacco and vaping products or services.

Abstract:
Background
Health advice in the wake of the COVID-19 pandemic has called upon the public to re-evaluate risk associated with recently routine behavior. However, di!erences in demographics, situational circumstances, and psychological dispositions create inequities in how people are able to respond to risks presented by the virus.

Method
Within a sample of 482 Americans, we examined the frequency of behavior reconceptualized as ‘risky’ by CDC public health guidelines released on 30 March 2020. We applied a cluster analysis using a data-driven persona framework from the "eld of user- design research, using only situational and dispositional (i.e. psychological) variables to identify pro"les of individuals.

Results
This pro"le approach unpacked important variability in the evaluation of risk for COVID-19 contagion, as well as adherence to public health guidance. Pro"les engaged in high-risk behaviors were more likely required to work on-site and report higher "nancial impact related to the pandemic.

Conclusion
Applying the pro"le approach facilitates personalized communications tailored to the psychological and situational circumstances of each pro"le that can promote compliance with public health guidelines and guide policy decisions. These results also suggest that risk- taking behaviors within the context of COVID-19 may also be driven by factors related to economic inequity since those who are more likely to be essential workers do not have the ability to remain as compliant to social distancing compared to those with higher economic status. Recommendations for policies promoting federally mandated paid leave policy in the US and employing qualitative methods for future research is discussed.

Abstract:
Background
Increased 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.

Objectives
We 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.

Methods
Our 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.

Results
From 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.

Conclusions
Instagram 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.

Abstract:
Objective
The objective of this study was to develop an inductive coding approach specifc to characterizing user-generated social media conversations about transition of use of different tobacco and alternative and emerging tobacco products (ATPs).

Results
A total of 40,206 tweets were collected from the Twitter public API stream that were geocoded from 2018 to 2019. Using data mining approaches, these tweets were then fltered for keywords associated with tobacco and ATP use behavior. This resulted in a subset of 5718 tweets, with 657 manually annotated and identifed as associated with user-generated conversations about tobacco and ATP use behavior. The 657 tweets were coded into 9 parent codes: inquiry, interaction, observation, opinion, promote, reply, share knowledge, use characteristics, and transition of use behavior. The highest number of observations occurred under transition of use (43.38%, n=285), followed by current use (39.27%, n=258), opinions about use (0.07%, n=46), and product promotion (0.06%, n=37). Other codes had less than ten tweets that discussed these themes. Results provide early insights into how social media users discuss topics related to transition of use and their experiences with different and emerging tobacco product use behavior.

Abstract:
Growing popularity of electronic nicotine-delivery systems (ENDS) has coincided with a need to strengthen tobacco-control policy. In response, the ENDS industry has taken actions to mobilize against public health measures, including coordination on social media platforms. To explore this phenomenon, data mining was used to collect public posts on two Facebook public group pages: the California Consumer Advocates for Smoke Free Alternatives Association (CCASAA) and the community page of the Northern California Chapter of SFATA (NC-SFATA). Posts were manually annotated to characterize themes associated with industry political interference and user interaction. We collected 288 posts from the NC-SFATA and 411 posts from CCASAA. A total of 522 (74.7%) posts were categorized as a form of political interference, with 339 posts (64.9%) from CCASAA and 183 posts (35.1%) from NC-SFATA. We identified three different categories of policy interference- related posts: (1) providing updates on ENDS-related policy at the federal, state, and local levels; (2) sharing opinions about ENDS-related policies; (3) posts related to scientific information related to vaping; and (4) calls to action to mobilize against tobacco/ENDS policies. Our findings indicate that pro-tobacco social media communities on Facebook, driven by strategic activities of trade associations and their members, may act as focal points for anti policy information dissemination, grass-roots mobilization, and industry coordination that needs further research.

Abstract:
Growing popularity of electronic nicotine-delivery systems (ENDS) has coincided with a need to strengthen tobacco-control policy. In response, the ENDS industry has taken actions to mobilize against public health measures, including coordination on social media platforms. To explore this phenomenon, data mining was used to collect public posts on two Facebook public group pages: the California Consumer Advocates for Smoke Free Alternatives Association (CCASAA) and the community page of the Northern California Chapter of SFATA (NC-SFATA). Posts were manually annotated to characterize themes associated with industry political interference and user interaction. We collected 288 posts from the NC-SFATA and 411 posts from CCASAA. A total of 522 (74.7%) posts were categorized as a form of political interference, with 339 posts (64.9%) from CCASAA and 183 posts (35.1%) from NC-SFATA. We identified three different categories of policy interference-related posts: (1) providing updates on ENDS-related policy at the federal, state, and local levels; (2) sharing opinions about ENDS-related policies; (3) posts related to scientific information related to vaping; and (4) calls to action to mobilize against tobacco/ENDS policies. Our findings indicate that pro-tobacco social media communities on Facebook, driven by strategic activities of trade associations and their members, may act as focal points for anti-policy information dissemination, grass-roots mobilization, and industry coordination that needs further research. View Full-Text

Abstract:
Objective
The objective of this study was to develop an inductive coding approach specific to characterizing user-generated social media conversations about transition of use of different tobacco and alternative and emerging tobacco products (ATPs).

Results
A total of 40,206 tweets were collected from the Twitter public API stream that were geocoded from 2018 to 2019. Using data mining approaches, these tweets were then filtered for keywords associated with tobacco and ATP use behavior. This resulted in a subset of 5718 tweets, with 657 manually annotated and identified as associated with user-generated conversations about tobacco and ATP use behavior. The 657 tweets were coded into 9 parent codes: inquiry, interaction, observation, opinion, promote, reply, share knowledge, use characteristics, and transition of use behavior. The highest number of observations occurred under transition of use (43.38%, n=285), followed by current use (39.27%, n=258), opinions about use (0.07%, n=46), and product promotion (0.06%, n=37). Other codes had less than ten tweets that discussed these themes. Results provide early insights into how social media users discuss topics related to transition of use and their experiences with different and emerging tobacco product use behavior.

Abstract:
The 2019 outbreak of E-cigarette, or Vaping, Product Use-Associated Lung Injury (EVALI) increased awareness of potential health risks associated with vaping among the general public. Little is known, however, about how unfolding information regarding EVALI affected knowledge, attitudes, and behaviors among e-cigarette users, particularly among young adults. This study describes attitudinal and behavioral responses to EVALI among young adult e-cigarette users. In October and November 2019, seven focus groups were held with college-going young adult tobacco users from two four-year public universities in California. Focus groups included questions regarding knowledge of and reaction to EVALI news, and how the news affected product use. Text from current e-cigarette users was extracted to develop individual phenomenological textural-structural descriptions of e-cigarette use for 38 individuals which were used to create a composite experience of e-cigarette use in light of EVALI. Experiences indicated that e-cigarette users were aware of information regarding EVALI and received information from numerous sources. Information was filtered for legitimacy of EVALI claims and causes of EVALI. Risk rationalizations were developed to assess potential harm of continued e-cigarette use and provided reasoning for behavioral responses to EVALI. The emerging harm associated with EVALI prompted e-cigarette users to engage in a cognitive process resulting in employment of a range of rationalities to justify continued use. These results suggest how environmental, cognitive, and behavioral factors may interact as young adults negotiate e-cigarette-related harms.

Abstract:
The most recent global refugee figures are staggering, with over 82.4 million people forcibly displaced and 26.4 million registered refugees. The ongoing conflict in Syria is a major contributor. After a decade of violence and destabilization, over 13.4 million Syrians have been displaced, including 6.7 million internally displaced persons and 6.7 million refugees registered in other countries. Beyond the immediate political and economic challenges, an essential component of any response to this humanitarian crisis must be health-related, including policies and interventions specific to mental health. This policy and practice review addresses refugee mental health in the context of the Syrian crisis, providing an update and overview of the current situation while exploring new initiatives in mental health research and global health policy that can help strengthen and expand services. Relevant global health policy frameworks are first briefly introduced, followed by a short summary of recent research on refugee mental health. We then provide an update on the current status of research, service provision, and health policy in the leading destinations for Syrians who have been forcibly displaced. This starts within Syria and then turns to Turkey, Lebanon, Jordan, and Germany. Finally, several general recommendations are discussed, including the pressing need for more data at each phase of migration, the expansion of integrated mental health services, and the explicit inclusion and prioritization of refugee mental health in national and global health policy.

Abstract:
Background
Vitamin D has been identified as a potential protective factor in the development of colorectal cancer (CRC). We expect to see a stronger association of ultraviolet B (UVB) exposure and CRC crude rates with increasing age since chronic vitamin D deficiency leads to sustained molecular changes that increase cancer risk. The DINOMIT (disjunction, initiation, natural selection, overgrowth, metastasis, involution, and transition) model postulates various stages of cancer development due to vitamin D deficiency and the associated latency period. The purpose of this study is to examine this age-dependent inverse relationship globally.

Methods
In this ecological study, a series of linear and polynomial regression tests were performed between country-specific UVB estimates adjusted for cloud cover and crude incidence rates of CRC for different age groups. Multiple linear regression was used to investigate the association between crude incidence rates of colorectal cancer and UVB estimate adjusting for urbanization, skin pigmentation, smoking, animal consumption, per capita GDP, and life expectancy. Statistical analysis was followed by geospatial visualization by producing choropleth maps.

Results
The inverse relationship between UVB exposure and CRC crude rates was stronger in older age groups at the country level. Quadratic curve fitting was preferred, and these models were statistically significant for all age groups. The inverse association between crude incidence rates of CRC and UVB exposure was statistically significant for age groups above 45 years, after controlling for covariates.

Conclusion
The age-dependent inverse association between UVB exposure and incidence of colorectal cancer exhibits a greater effect size among older age groups in global analyses. Studying the effect of chronic vitamin D deficiency on colorectal cancer etiology will help in understanding the necessity for population-wide screening programs for vitamin D deficiency, especially in regions with inadequate UVB exposure. Further studies are required to assess the need for adequate public health programs such as selective supplementation and food fortification.

Abstract:
Background
Suicide and substance use disorder (SUD) pose serious public health challenges among young adults in the United States. Increasing social media use among these populations can be leveraged as an alternative method to detect characteristics of suicide-related topics and behavior among substance users.Objective: To detect and characterize suicide and self-harm related conversations co-occurring with SUD posts and comments on the popular social media platform Instagram.

Methods
This study used big data and machine learning approaches to collect and classify Instagram posts containing 632 controlled substance-related hashtags. Posts were first classified for online drug diversion topics and then filtered to detect suicide and mental health discussions. Posts and comments were then manually annotated for SUD and mental health co-occurring themes. Associations between these characteristics were tested using the Chi-square test.

Results
We detected 719 Instagram posts/comments that included user-generated discussions about suicide, substance use and/or mental health. Posts self-reporting SUD and mental health topics were also more likely to discuss suicide compared to those that did not discuss SUD and mental health topics, respectively (p < 0.001). Major themes observed included concurrent discussions of suicide ideation and attempts and low self-esteem.

Conclusion
Our study results provide preliminary evidence of social media discussions about suicide and mental health among those with SUD. This co-occurrence represents a key health risk factor on a platform heavily utilized by young adults. Further studies are required to analyze specific patterns of suicide and self-harm ideations for the purposes of designing future suicide prevention campaigns through digital channels.

Abstract:
Introduction
Early 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.

Methods
Tweets 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.

Results
From 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.

Conclusion
Results 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.

Abstract:
This study investigates the types of misinformation spread on Twitter that evokes scientific authority or evidence when making false claims about the antimalarial drug hydroxychloroquine as a treatment for COVID-19. Specifically, we examined tweets generated after former U.S. President Donald Trump retweeted misinformation about the drug using an unsupervised machine learning approach called the biterm topic model that is used to cluster tweets into misinformation topics based on textual similarity. The top 10 tweets from each topic cluster were content coded for three types of misinformation categories related to scientific authority: medical endorsements of hydroxychloroquine, scientific information used to support hydroxychloroquine’s use, and a comparison group that included scientific evidence opposing hydroxychloroquine’s use. Results show a much higher volume of tweets featuring medical endorsements and use of supportive scientific information compared to accurate and updated scientific evidence, that misinformation-related tweets propagated for a longer time frame, and the majority of hydroxychloroquine Twitter discourse expressed positive views about the drug. Metadata from Twitter accounts found that prominent users within misinformation discourse were more likely to have media or political affiliation and explicitly expressed support for President Trump. Conversely, prominent accounts within the scientific opposition discourse primarily consisted of medical doctors or scientists but had far less influence in the Twitter discourse. Implications of these findings and connections to related social media research are discussed, as well as cognitive mechanisms for understanding susceptibility to misinformation and strategies to combat misinformation spread via online platforms.

Abstract:
Background
Growing use of social media has led to the emergence of virtual controlled substance and illicit drug marketplaces, prompting calls for action by government and law enforcement. Previous studies have analyzed Instagram drug selling via posts. However, comments made by users involving potential drug selling have not been analyzed. In this study, we use unsupervised machine learning to detect and classify prescription and illicit drug-related buying and selling interactions on Instagram.

Methods
We used over 1,000 drug-related hashtags on Instagram to collect a total of 43,607 Instagram comments between February 1st, 2019 and May 31st, 2019 using data mining approaches in the Python programming language. We then used an unsupervised machine learning approach, the Biterm Topic Model (BTM), to thematically summarize Instagram comments into distinct topic groupings, which were then extracted and manually annotated to detect buying and selling comments.
Results
We detected 5,589 comments from sellers, prospective buyers, and online pharmacies from 531 unique posts. The vast majority (99.7%) of comments originated from drug sellers and online pharmacies. Key themes from comments included providing contact information through encrypted third-party messaging platforms, drug availability, and price inquiry. Commonly offered drugs for sale included scheduled controlled substances such as Adderall and Xanax, as well as illicit hallucinogens and stimulants. Comments from prospective buyers of drugs most commonly included inquiries about price and availability.

Conclusions
We detected prescription controlled substances and other illicit drug selling interactions via Instagram comments to posts. We observed that comments were primarily used by sellers offering drugs, and typically not by prospective buyers interacting with sellers. Further research is needed to characterize these “social” drug marketplace interactions on this and other popular social media platforms.

Abstract:
Background
In 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.

Objective
We 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.

Methods
A 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.

Results
This 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.

Conclusion
This 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.

Abstract:
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.

Abstract:
Introduction
Concomitant with the popularization of vaping, vape shops have dramatically proliferated over the past years. This study assesses whether vape storefronts in California are significantly associated with density of different age groups, and whether this differs between tobacco storefronts or non-specific tobacco retailers.

Methods
Addresses for licensed tobacco retailers were obtained from the California Department of Tax and Fee Administration. Business names and addresses were used to obtain store categories cross-referenced from Yelp. Using a cross-sectional ecological design, stores categorized as ‘Vape Shop’ or ‘Tobacco Shop’ were geolocated and compared with age-related variables from the American Community Survey. Regression was conducted in R to determine relationships between age group concentration, in ventiles, and proportion of tracts with tobacco-specific or vape-specific stores. Geospatial visualization was conducted using ArcGIS.

Results
We found 848 vape shops, 820 tobacco shops, 419 categorized as both, and 20320 retailers with neither category. Overall, 1800 tobacco and/or vape shops were categorized in 1557 of California’s 23194 census tracts. A positive linear association was found between ventiles of two age categories, 20–24 and 25–34 years, and proportion of tracts with vape-specific or tobacco-specific shops separately.

Conclusions
Positive associations were found for ages 20–34 years but not for other ages, suggesting vape shops are strategically located in areas populated by young adults. Location-based targeting increases access, thereby increasing proportion of tobacco users, and could be a critical factor in e-cigarette uptake and use. Further study to identify additional age-related demographic characteristics among clientele of tobacco storefronts is warranted.

Abstract:
Introduction
The 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.

Methods
We 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.

Results
Our 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.

Conclusions
Regenerative 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.

Abstract:
In the context of blockchain technology, “off-chain” refers to computation or data that is structurally external to the blockchain network. Off-Chain Blockchain Systems (OCBS) enable this information processing and management through distributed software architecture where the blockchain network interacts with off-chain resources. Hence, OCBS are a critical data governance component in the design of enterprise blockchain solutions, resulting in extensive research and development exploring the interplay between on-chain and off-chain storage and computation and efforts to evaluate their performance relative to other information management systems. Key features of OCBS’ are their ability to improve scalability, reduce data storage requirements, and enhance data privacy, all extremely critical issues to enable broader blockchain adoption. These OCBS features map well to the needs of the healthcare industry, particularly due to the need to manage various types of medical, consumer, and other health-related data. However, different types of health data are also subject to stringent regulatory, security and legal requirements, a key factor limiting blockchain adoption in the sector. In response, there is a critical need to better align OCBS design features to different types of healthcare data management and their respective governance and privacy regimes. This article first reviews the characteristics of different constructs of OCBS. It then proposes a modular hybrid privacy-preserving framework leveraging off-chain and on-chain blockchain system design applied to three different reference models that illustrate how blockchain can enhance healthcare information management. Through this privacy-preserving framework we hope to liberate healthcare data by enabling sharing, sovereignty and enhanced trust.

No abstract available.

No Abstract Available.

Abstract:
Introduction
Recent reports of lung injury associated with Electronic Nicotine Delivery System (ENDS) products precipitated by increasing vaping prevalence and interest in flavors among adolescents has led to policies that restrict the sale, distribution, and accessibility of ENDS products. This study assessed compliance of online ENDS vendors to the Massachusetts temporary sales ban.

Methods
The study involved structured web surveillance for online ENDS vendors using keyword searches on Google search engine (October to November 2019.) Once vendors were identified, we conducted simulated online purchases, defined as placing an order for an ENDS product by putting it in the website shopping cart without finalizing payment. Simulated purchases and content analysis of websites was conducted to determine compliance characteristics. Fisher’s exact test was used to identify associations between compliance and website characteristics such as location and age verification requirements.

Results
Simulated online purchases from 50 identified ENDS vendors yielded 72% (n=36) stores that were non-compliant and allowed placement of ENDS product orders, without restrictions, to a Massachusetts address. The remaining 14 websites had processes in place to prevent orders from buyers located in Massachusetts. Other characteristics of interest, including use of age verification, location data, and web registrar/registrant data were collected and reported.

Conclusions
The September 2019 Massachusetts executive order was a comprehensive ban on selling ENDS products both online and offline. However, our study found that close to three-fourths of the vendors appeared to be non-compliant, indicating that implementation and enforcement are ongoing challenges for future tobacco control efforts on the internet. Policymaking needs to be specifically tailored to address the unique challenges of online environments, particularly in the context of identifying non-compliant sites, ensuring age verification, and addressing non-US sellers.

Abstract:
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.

Abstract:
This paper analyzes online user conversation topics and discourse on Twitter related to the “Liberate” Protest movement in reaction to social distancing guidelines at the early stages of the COVID-19 pandemic. Interdisciplinary approaches in big data, machine learning, content analysis, and social network analysis (SNA) were used to characterize the communicative behavior, conversation themes, and network structures of Liberate protest supporters and non-supporters. Tweets were content coded and grouped within topic clusters produced from an unsupervised machine learning algorithm using natural language processing. An analysis of topic clusters found that tweets that support the protests are highly concentrated and have higher volumes of replicated tweets. Protest Supporters were also more likely to retweet other users while Non-Supporters were more likely to include a URL from an outside media source and produce a unique tweet. SNA was also used to assess the characteristics of retweet networks and found that the Protester Supporter network had a more centralized structure and was strongly influenced by a political organization, in contrast to the Non-Supporter network that had a larger number of smaller and more evenly-sized nodes and more driven by media personalities and commentators. Collectively, these characteristics indicate that protest supporters had more centralized, consistent and disseminated discourse protesting COVID-19 social distancing requirements compared to non-supporters who were more diverse in their criticism of the Liberate movement and generally more fragmented in their support of public health measures. Results from this study provide important insights into pandemic communication dynamics of opposing twitter communities, including in the context of those who oppose and support public health measures in a highly politicized social and online environment. Results are important in the context of assessing the messages, communication propagation and overall activities of social media communities in response to basic public health measures needed to contain this post-digital era global pandemic.

No abstract available

Abstract:
Background:
The COVID-19 pandemic has reached 40 million confirmed cases worldwide. Given its rapid progression, it is important to examine its origins to better understand how people’s knowledge, attitudes, and reactions have evolved over time. One method is to use data mining of social media conversations related to information exposure and self-reported user experiences.

Objective:
This study aims to characterize the knowledge, attitudes, and behaviors of social media users located at the initial epicenter of the outbreak by analyzing data from the Sina Weibo platform in Chinese.

Methods:
We used web scraping to collect public Weibo posts from December 31, 2019, to January 20, 2020, from users located in Wuhan City that contained COVID-19–related keywords. We then manually annotated all posts using an inductive content coding approach to identify specific information sources and key themes including news and knowledge about the outbreak, public sentiment, and public reaction to control and response measures.

Results:
We identified 10,159 COVID-19 posts from 8703 unique Weibo users. Among our three parent classification areas, 67.22% (n=6829) included news and knowledge posts, 69.72% (n=7083) included public sentiment, and 47.87% (n=4863) included public reaction and self-reported behavior. Many of these themes were expressed concurrently in the same Weibo post. Subtopics for news and knowledge posts followed four distinct timelines and evidenced an escalation of the outbreak’s seriousness as more information became available. Public sentiment primarily focused on expressions of anxiety, though some expressions of anger and even positive sentiment were also detected. Public reaction included both protective and elevated health risk behavior.

Conclusions:
Between the announcement of pneumonia and respiratory illness of unknown origin in late December 2019 and the discovery of human-to-human transmission on January 20, 2020, we observed a high volume of public anxiety and confusion about COVID-19, including different reactions to the news by users, negative sentiment after being exposed to information, and public reaction that translated to self-reported behavior. These findings provide early insight into changing knowledge, attitudes, and behaviors about COVID-19, and have the potential to inform future outbreak communication, response, and policy making in China and beyond.

Abstract:
Objectives
According to current reporting, the number of active coronavirus disease 2019 (COVID-19) infections is not evenly distributed, both spatially and temporally. Reported COVID-19 infections may not have properly conveyed the full extent of attention to the pandemic. Furthermore, infection metrics are unlikely to illustrate the full scope of negative consequences of the pandemic and its associated risk to communities.

Methods
In an effort to better understand the impacts of COVID-19, we concurrently assessed the geospatial and longitudinal distributions of Twitter messages about COVID-19 which were posted between March 3rd and April 13th and compared these results with the number of confirmed cases reported for sub-national levels of the United States. Geospatial hot spot analysis was also conducted to detect geographic areas that might be at elevated risk of spread based on both volume of tweets and number of reported cases.

Results
Statistically significant aberrations of high numbers of tweets were detected in approximately one-third of US states, most of which had relatively high proportions of rural inhabitants. Geospatial trends toward becoming hotspots for tweets related to COVID-19 were observed for specific rural states in the United States.

Discussion
Population-adjusted results indicate that rural areas in the U.S. may not have engaged with the COVID-19 topic until later stages of an outbreak. Future studies should explore how this dynamic can inform future outbreak communication and health promotion.

Abstract:
Background
Corruption is a significant challenge to the future of human development, economic progress, and population health in the post millennium. Corruption, in its different forms of bribery, fraud, waste, collusion, and illicit financial flows, not only leads to waste but can also erode trust in government and public systems. Corruption is also complex and globalized with different forms of corruption occurring across different countries and multiple industries. One critical tool to leverage in the fight against corruption is the use of innovative technologies such as machine learning.

Methods
In this study, we deployed an unsupervised machine learning methodology using natural language processing to collect and analyze data from the popular social media platform Twitter with the aims of detecting self-reported experiences with corruption, including in the health sector. We collected data from the Twitter public API for keywords associated with corruption and used the biterm topic model to extract themes from the entire corpus of Tweets in order to detect user-generated messages reporting or discussing experiences with corruption.

Results
We analyzed 22, 180, 425 tweets filtered for corruption-related keywords from January–May 2019. Using a combination of NLP and manual annotation, we detected 2383 tweets from 1556 users that included self-reporting of corruption for two dominant themes: police bribery and healthcare corruption. Overall, we found a small number of users actively reporting experiences with corruption, identified users located in countries that are perceived as having higher levels of corruption by their citizens, and found that the majority of messages included reports of users’ own experiences and/or documentation of corruption.

Conclusion
Though technology is not a “silver bullet” that can entirely address the multifaceted nature of global corruption, this study demonstrates its potential utility as a force for good to enable better detection, characterize forms of corruption in different sectors, and hopefully inform future anti-corruption efforts. Additionally, the UN Sustainable Development Goals, with shared goals of fighting corruption, improving population health, encouraging technology adoption, and fostering multistakeholder partnerships, may serve as a critical governance space to catalyze technology-driven anti-corruption approaches.

Abstract:
Background:
The coronavirus disease (COVID-19) pandemic is perhaps the greatest global health challenge of the last century. Accompanying this pandemic is a parallel “infodemic,” including the online marketing and sale of unapproved, illegal, and counterfeit COVID-19 health products including testing kits, treatments, and other questionable “cures.” Enabling the proliferation of this content is the growing ubiquity of internet-based technologies, including popular social media platforms that now have billions of global users.

Objective:
This study aims to collect, analyze, identify, and enable reporting of suspected fake, counterfeit, and unapproved COVID-19–related health care products from Twitter and Instagram.

Methods:
This study is conducted in two phases beginning with the collection of COVID-19–related Twitter and Instagram posts using a combination of web scraping on Instagram and filtering the public streaming Twitter application programming interface for keywords associated with suspect marketing and sale of COVID-19 products. The second phase involved data analysis using natural language processing (NLP) and deep learning to identify potential sellers that were then manually annotated for characteristics of interest. We also visualized illegal selling posts on a customized data dashboard to enable public health intelligence.

Results:
We collected a total of 6,029,323 tweets and 204,597 Instagram posts filtered for terms associated with suspect marketing and sale of COVID-19 health products from March to April for Twitter and February to May for Instagram. After applying our NLP and deep learning approaches, we identified 1271 tweets and 596 Instagram posts associated with questionable sales of COVID-19–related products. Generally, product introduction came in two waves, with the first consisting of questionable immunity-boosting treatments and a second involving suspect testing kits. We also detected a low volume of pharmaceuticals that have not been approved for COVID-19 treatment. Other major themes detected included products offered in different languages, various claims of product credibility, completely unsubstantiated products, unapproved testing modalities, and different payment and seller contact methods.

Conclusions:
Results from this study provide initial insight into one front of the “infodemic” fight against COVID-19 by characterizing what types of health products, selling claims, and types of sellers were active on two popular social media platforms at earlier stages of the pandemic. This cybercrime challenge is likely to continue as the pandemic progresses and more people seek access to COVID-19 testing and treatment. This data intelligence can help public health agencies, regulatory authorities, legitimate manufacturers, and technology platforms better remove and prevent this content from harming the public.

Abstract:
Background:
An estimated US $2.6 billion loss is attributed to health care fraud and abuse. With traditional health care claims verification and reimbursement, the health care provider submits a claim after rendering services to a patient, which is then verified and reimbursed by the payer. However, this process leaves out a critical stakeholder: the patient for whom the services are actually rendered. This lack of patient participation introduces a risk of fraud and abuse. Blockchain technology enables secure data management with transparency, which could mitigate this risk of health care fraud and abuse.

Objective:
The aim of this study is to develop a framework using blockchain to record claims data and transactions in an immutable format and to enable the patient to act as a validating node to help detect and prevent health care fraud and abuse.

Methods:
We developed a health care fraud and abuse blockchain technical framework and prototype using key blockchain tools and application layers including consensus algorithms, smart contracts, tokens, and governance based on digital identity on the Ethereum platform (Ethereum Foundation).

Results:
Our technical framework maps to the claims adjudication process and focuses on Medicare claims, with the US Centers for Medicare and Medicaid Services (CMS) as the central authority. A prototype of the framework system was developed using the blockchain platform Ethereum (Ethereum Foundation), with its design features, workflow, smart contract functions, system architecture, and software implementation outlined. The software stack used to build the system consisted of a front-end user interface framework, a back-end processing server, and a blockchain network. React was used for the user interface framework, and NodeJS and an Express server were used for the back-end processing server; Solidity was the smart contract language used to interact with a local Ethereum blockchain network.

Abstract
At an estimated US$19 billion, the illicit wildlife trade is a serious threat to global conservation efforts. This criminal enterprise is now digital, expanding its footprint to consumers internationally by using the Internet and social media platforms. Recent studies have detected illegal wildlife selling posts on the popular social networking site Facebook in several different languages, including Chinese. In order to further explore this challenge to conservation, this study used big data approaches to identify and characterize wildlife trading activity in Chinese language on Facebook using an automated web scraper. We focused on keywords associated with elephants, rhinos and hawksbill turtles. We collected 10 303 unique Facebook posts over a 45-day period and were able to identify 639 posts from 268 unique users, which we suspect of directly marketing the sale of wildlife products. We also identified other species including Tibetan antelope, bears and African spurred tortoises. Facebook community pages appeared to have the highest percentage (48.2%) of wildlife selling posts. We also identified 14 different countries and regions with suspected wildlife-selling users, most located in Taiwan. Furthermore, we observed that the language used by some sellers changed from descriptive text to emojis and other code words. Collective action is needed from governments, law enforcement, civil society and technology companies leveraging big data approaches to better detect and interdict online Chinese-language wildlife trafficking.

Abstract
In the last two decades, global action to address noncommunicable diseases (NCDs) has accelerated, but policy adoption and implementation at the national level has been inadequate. This analysis examines the role of rationalities of governing, or governmentality, in national-level adoption of global recommendations. Critical discourse analysis was conducted using 49 formal institutional and organizational documents obtained through snowball sampling methodology. Text were coded using a framework of five forms of governmentality and analyzed to describe the order of discourse which has emerged within the global NCD policy domain. The dominant political rationality used to frame NCDs is rooted in risk governmentality. Recommendations for tobacco control and prevention of harmful alcohol use rely on a governmentality of police mixed with discipline. The promotion of physical activity relies heavily on disciplinary governmentality, and the prevention of unhealthy diet mixed disciplinary measures, discipline, and neoliberal governmentalities. To translate global NCD prevention and control strategies to national action, acceptability for the political rationalities embodied in policy options must be nurtured as new norms, procedures, and institutions appropriate to the political rationalities of specific interventions are developed.

Abstract
We discuss how corruption affects access to antiretroviral therapies (ARVs) globally. Recent cases of theft of ARVs, collusion, and manipulation in procurement found in countries such as Central African Republic, Bangladesh, Malawi, and Guinea, show there is still much work to be done to reduce the risk of corruption. This includes addressing the structural weaknesses in procurement mechanisms and supply chain management systems of health commodities and medicines.

Abstract:
Background:
The coronavirus disease (COVID-19) pandemic is a global health emergency with over 6 million cases worldwide as of the beginning of June 2020. The pandemic is historic in scope and precedent given its emergence in an increasingly digital era. Importantly, there have been concerns about the accuracy of COVID-19 case counts due to issues such as lack of access to testing and difficulty in measuring recoveries.

Objective:
The aims of this study were to detect and characterize user-generated conversations that could be associated with COVID-19-related symptoms, experiences with access to testing, and mentions of disease recovery using an unsupervised machine learning approach.

Methods:
Tweets were collected from the Twitter public streaming application programming interface from March 3-20, 2020, filtered for general COVID-19-related keywords and then further filtered for terms that could be related to COVID-19 symptoms as self-reported by users. Tweets were analyzed using an unsupervised machine learning approach called the biterm topic model (BTM), where groups of tweets containing the same word-related themes were separated into topic clusters that included conversations about symptoms, testing, and recovery. Tweets in these clusters were then extracted and manually annotated for content analysis and assessed for their statistical and geographic characteristics.

Results:
A total of 4,492,954 tweets were collected that contained terms that could be related to COVID-19 symptoms. After using BTM to identify relevant topic clusters and removing duplicate tweets, we identified a total of 3465 (<1%) tweets that included user-generated conversations about experiences that users associated with possible COVID-19 symptoms and other disease experiences. These tweets were grouped into five main categories including first- and secondhand reports of symptoms, symptom reporting concurrent with lack of testing, discussion of recovery, confirmation of negative COVID-19 diagnosis after receiving testing, and users recalling symptoms and questioning whether they might have been previously infected with COVID-19. The co-occurrence of tweets for these themes was statistically significant for users reporting symptoms with a lack of testing and with a discussion of recovery. A total of 63% (n=1112) of the geotagged tweets were located in the United States.

Conclusions:
This study used unsupervised machine learning for the purposes of characterizing self-reporting of symptoms, experiences with testing, and mentions of recovery related to COVID-19. Many users reported symptoms they thought were related to COVID-19, but they were not able to get tested to confirm their concerns. In the absence of testing availability and confirmation, accurate case estimations for this period of the outbreak may never be known. Future studies should continue to explore the utility of infoveillance approaches to estimate COVID-19 disease severity.

Abstract:
Introduction and Aims
Infoveillance 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 Methods
We 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.

Results
257 messages about substance abuse and HIV were significantly related to HIV rates (P < 0.001) and opioid-related hospitalisations (P = 0.037). Using 157 characteristics from the American Community Survey, a linear classifier was computed with an appreciable correlation (r = 0.49) to risk-related social media messages from Marion County.

Discussion and Conclusions
Communities appear to communicate online in response to disease burden. Classification produced an accurate equation to model census block risk based on census data, allowing for high-dimensional estimation of risk for blocks with sparse populations.

Abstract:
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.

Abstract:
Due to corruption and limited oversight, philanthropy in China has come under increasing scrutiny by both the Chinese government and public. In particular, corruption has impacted charities, resulting in operational funding declines that have also impacted legitimate charities serving the vulnerable. Hence, an increase in the number of Chinese charities without adequate transparency and needed good governance threatens the health of these organizations and their service groups. In response, the Chinese government enacted the 2016 Charity Law, implemented on September 1, 2016. Yet the impact of this law, if any, is unknown. We therefore conducted a literature review of the academic and gray literature to assess characteristics of the law, its strengths and limitations, and to explore anti-corruption case studies. In addition, we reviewed publicly available secondary data on the transparency status—complete financial information and responsible staff—of Chinese charity organizations and a group of health-related specific charities before and after the Law’s enactment. This included the transparency scores of the top 100 charities and top 30 health-related charities in China. The academic literature we reviewed focused on general governmental corruption and little on charity-related corruption. However, the gray literature reflected a poor view of charities in China due to publicized claims of fund and abuse. Based on our secondary data analysis, we found charity organizations’ transparency shows some variation but as a total continues to score low overall across the top net asset holding charities. Importantly, based on a regression analysis, the transparency scores of Chinese charities did not experience a significant change despite the Charity Law’s enactment. In response, strengthening the Charity Law by enhancing enforcement of financial regulations and implementing systemic good governance measures is needed. Further, efficiency initiatives such as philanthropy de-administration, e-government, and outsourcing monitoring of Chinese charities to external agencies would promote trustworthiness and credibility of Chinese charity organizations now and in the future.

Abstract:
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.

Abstract
Corruption is diverse in its forms and embedded in health systems worldwide. Health-sector corruption directly impedes progress towards universal health coverage by inhibiting people’s access to quality health services and to safe and effective medicines, and undermining systems for financial risk protection. Corruption is also a cross-cutting theme in the United Nations’ sustainable development goals (SDGs) which aim to improve population health, promote justice and strong institutions and advance sustainable human development. To address health-sector corruption, we need to identify how it happens, collect evidence on its impact and develop frameworks to assess the potential risks and put in place protective measures. We propose that the SDGs can be leveraged to develop a new approach to anti-corruption governance in the health sector. The aim will be to address coordination across the jurisdictions of different countries and foster partnerships among stakeholders to adopt coherent policies and anti-corruption best practices at all levels. Combating corruption requires a focused and invigorated political will, better advocacy and stronger institutions. There is no single solution to the problem. Nevertheless, a commitment to controlling corruption via the SDGs will better ensure the integrity of global health and human development now and beyond 2030.

Abstract
Surgical data recording technology has great promise to generate patient safety and quality data that can be utilized to potentially reduce medical errors. Variations of these systems aim to improve surgical technique, develop better training simulation, and promote adverse event investigation similar to the aims of black box technology utilized in other industries. However, many unknowns remain for surgical data recording utilization in operating rooms and clinical settings in the United States. This includes the need to appropriately design systems so they collect meaningful and useful data that can be discussed by surgical team members in an open and safe environment to optimize clinical care processes. In order to better understand the clinical and regulatory environment for surgical data recording systems, we conducted an interdisciplinary review to identify key technology approaches, and assess legal and regulatory implications associated with this potentially disruptive technology. We found technology ranging from audio and visual data, to systems utilizing mobile applications, and kinematic data capture. The data collected present legal questions over ownership of information and privacy, along with regulatory issues at the federal and state levels. The benefits of these data should be balanced with the need to develop appropriate policies and regulations that protect the interests of both clinicians and patients in order to encourage further innovation and better realize the potential of surgical data recording technology to improve clinical decision making and patient safety outcomes.

Abstract
Objectives: Prior research has not adequately examined the relationship between international migration and colorectal cancer (CRC) by cultural regions in the US. The purpose of this exploratory study was to determine how annual CRC incidence varied with US annual international migrant inflow in ten different regions, corresponding to dominant ancestry group.

Design: County-level international migrant inflow and dominant ancestry type were obtained from the American Community Survey, and age-adjusted CRC incidence was obtained from the National Cancer Institute. A linear regression model was tested for each ancestry region to assess the relationship between migrant inflow and CRC incidence.

Results: Higher international migrant inflow was associated with lower CRC incidence among counties where the dominant ancestry group was African American (p = 0.0207), British (p = 0.0212), Hispanic (p = 0.0001), and Native American (p = 0.0056).

Conclusions: These findings suggest that US residents in certain ancestry groups are at higher risk for CRC.

Abstract
Japan is undergoing a major population health transition as its society ages, and it continues to experience low birth rates. An aging Japan will bring new challenges to its public health system, highlighted as a model for universal health coverage (UHC) around the world. Specific challenges Japan’s health care system will face include an increase in national public health expenditures, higher demand for health care services, acute need for elder and long-term care, shortage of health care workers, and disparities between health care access in rural versus urban areas. Blockchain technology has the potential to address some of these challenges, but only if a health blockchain is conceptualized, designed, localized, and deployed in a way that is compatible with Japan’s centralized UHC-centric public health system. Blockchain solutions must also be adaptive to opportunities and barriers unique to Japan’s national health and innovation policy, including its regulatory sandbox system, while also seeking to learn from blockchain adoption in the private sector and in other countries. This viewpoint outlines the major opportunities and potential challenges to blockchain adoption for the future of Japan’s health care.

Abstract:
In 2015, the World Health Organization (WHO) Expert Committee approved the addition of 16 cancer medicines to the WHO Model List of Essential Medicines (EML), bringing the total number of cancer medicines on the list to 46. This change represented the first major revision to the EML oncology section in recent history and reinforces international recognition of the need to ensure access and affordability for cancer treatments. Importantly, many low and middle-income countries rely on the EML, as well as the children’s EML, as a guide to establish national formularies, and moreover use these lists as tools to negotiate medicine pricing. However, EML inclusion is only one component that impacts cancer treatment access. More specifically, factors such as intellectual property rights and international trade agreements can interact with EML inclusion, drug pricing, and accessibility. To better understand this dynamic, we conducted an interdisciplinary review of the patent status of EML cancer medicines compared to other EML noncommunicable disease medicines using the 17th, 18th, 19th, 20th, and 21st editions of the list. We also explored the interaction of intellectual property rights with the international trade regime and how trade agreements can and do impact cancer treatment access and affordability. Based on this analysis, we conclude that patent status is simply one factor in the complex international environment of health systems, IPR policies, and trade regimes and that aligning these oftentimes disparate interests will require shared global governance across the cancer care continuum.

Abstract:
Social media is an important channel for communication, information dissemination, and social interaction, but also provides opportunities to illicitly sell goods online, including the trade of wildlife products. In this study, we use the Twitter public application programming interface (API) to access Twitter messages in order to detect and classify suspicious wildlife trafficking and sale using an unsupervised machine learning topic model combined with keyword filtering and manual annotation. We choose two prohibited wildlife animals and related products: elephant ivory and pangolin, and collected tweets containing keywords and known code words related to these species. In total, we collected 138,357 tweets filtered for these keywords over a 14-day period and were able to identify 53 tweets from 38 unique users that we suspect promoted the sale of Ivory products, though no pangolin related promoted post were detected in this study. Study results show that machine learning combined with supplement analysis approaches such as those utilized in this study have the potential to detect illegal content without the use of an existing training data set. If developed further, these approaches can help technology companies, conservation groups, and law enforcement officials to expedite the process of identifying illegal online sales and stem supply for the billion-dollar criminal industry of online wildlife trafficking.

Abstract:

Corruption in the health sector has been a "dirty secret" in the health policy and international development community, but recent global activities point to a day when it will no longer be neglected as a key determinant of health. To further explore next steps forward, this commentary applies the Kingdon’s multiple-streams framework (MSF) to assess what opportunities are available to mobilize the global agenda to combat health corruption. Based on this analysis, it appears that Kingdon’s problem, policy, and political streams are coalescing to create a policy window opportunity that can be leveraged based on recent developments in the global health and international development community around corruption. This includes the recent formation of the Global Network on Anti-Corruption, Transparency and Accountability (GNACTA) led by the World Health Organization (WHO), the Global Fund, and the United Nations Development Programme in 2019. It also includes bridging shared goals of addressing corruption in order to make progress towards health-specific goals in the United Nations (UN) Sustainable Development Goals (SDGs) and for achieving universal health coverage.

Abstract:
Reducing preventable medical errors remains a universal goal, yet implementing effective solutions remains a challenge. The development of surgical data recording technology shows promise to generate robust qualitative and quantitative data in the surgical theater. These data can allow physicians and their teams to capture specific sources of error and implement corrective interventions. Surgical data recording technology encompasses rudimentary data tabulation on notecards, to integrated audio-video systems containing cameras, microphones, and sensors, capturing and synthesizing intraoperative, environmental, and instrumentation information, along with devices tailored to robotic surgical systems. There is growing interest in the implementation of such technology in medical centers, particularly in the United States, Canada, and Europe, but existing medicolegal and regulatory challenges necessitate further research and clinical assessment in order for this technology to facilitate improved surgical patient safety.

Abstract:

The U.S. health care system is in transition. Politicians, interest groups, and constituents disagree about how to change coverage, reduce costs, regulate health care markets, and navigate the future of health care reform after the Patient Protection and Affordable Care Act (ACA). Meanwhile, the number of uninsured adults has increased by 7 million since late 2016, and this number does not include the millions of Americans who remain underinsured. States have the power to regulate health insurance, medical benefits, providers, and other aspects of health care delivery, and they have started exploring reform measures to fill coverage gaps. However, these efforts face several federal barriers, some of which can be waived by the federal government and some of which cannot.

Abstract:
Few scholars have studied the use of "Global Health Diplomacy" by the Japanese Government, a unique form of diplomacy that relies on the use of "soft power" and "smart power" but also one that is undergoing changes based on current geopolitical developments in Japan and the Asia-pacific region. This article will provide a review of the literature based on a multilingual document review on Japanese global health diplomacy by examining how health diplomacy has been used by the Japanese government in furtherance of broader foreign policy and diplomatic goals in the international fora. This article will also discuss the limitations of Japan's nascent health diplomacy strategy and possible challenges in the near-future; specifically, the possible revision of Article 9 of its Constitution.

Abstract:
Background:
Social media use is now ubiquitous, but the growth in social media communications has also made it a convenient digital platform for drug dealers selling controlled substances, opioids, and other illicit drugs. Previous studies and news investigations have reported the use of popular social media platforms as conduits for opioid sales. This study uses deep learning to detect illicit drug dealing on the image and video sharing platform Instagram.

Objective:
The aim of this study was to develop and evaluate a machine learning approach to detect Instagram posts related to illegal internet drug dealing.

Methods:
In this paper, we describe an approach to detect drug dealers by using a deep learning model on Instagram. We collected Instagram posts using a Web scraper between July 2018 and October 2018 and then compared our deep learning model against 3 different machine learning models (eg, random forest, decision tree, and support vector machine) to assess the performance and accuracy of the model. For our deep learning model, we used the long short-term memory unit in the recurrent neural network to learn the pattern of the text of drug dealing posts. We also manually annotated all posts collected to evaluate our model performance and to characterize drug selling conversations.

Results:
From the 12,857 posts we collected, we detected 1228 drug dealer posts comprising 267 unique users. We used cross-validation to evaluate the 4 models, with our deep learning model reaching 95% on F1 score and performing better than the other 3 models. We also found that by removing the hashtags in the text, the model had better performance. Detected posts contained hashtags related to several drugs, including the controlled substance Xanax (1078/1228, 87.78%), oxycodone/OxyContin (321/1228, 26.14%), and illicit drugs lysergic acid diethylamide (213/1228, 17.34%) and 3,4-methylenedioxy-methamphetamine (94/1228, 7.65%). We also observed the use of communication applications for suspected drug trading through user comments.

Conclusions:
Our approach using a combination of Web scraping and deep learning was able to detect illegal online drug sellers on Instagram, with high accuracy. Despite increased scrutiny by regulators and policymakers, the Instagram platform continues to host posts from drug dealers, in violation of federal law. Further action needs to be taken to ensure the safety of social media communities and help put an end to this illicit digital channel of sourcing."

Abstract:

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.

Abstract

Falsified and substandard medicines are associated with tens of thousands of deaths, mainly in young children in poor countries. Poor-quality drugs exact an annual economic toll of up to US$200 billion and contribute to the increasing peril of antimicrobial resistance. The WHO has emerged recently as the global leader in the battle against poor-quality drugs, and pharmaceutical companies have increased their roles in assuring the integrity of drug supply chains. Despite advances in drug quality surveillance and detection technology, more efforts are urgently required in research, policy, and field monitoring to halt the pandemic of bad drugs. In addition to strengthening international and national pharmaceutical governance, in part by national implementation of the Model Law on Medicines and Crime, a quantifiable Sustainable Development Goal target and an international convention to insure drug quality and safety are urgent priorities.

Abstract:

Background
Advances in science and technology coupled with globalization are changing access to and utilization of reproductive health services. This includes the transnational phenomenon of families who use surrogate mothers to reproduce, with forms of altruistic and commercial surrogacy becoming more commonplace. Simultaneously, changes in law, regulation, and policy are necessary to protect surrogates, intended parents, and resulting children. These developments have been slow to adapt to challenges inherent to surrogacy arrangements, most specifically in low-and middle-income countries, including in South American countries.

Methods
We conducted an interdisciplinary non-systematic literature review and legal analysis of existing and pending policy, laws, and regulations related to commercial surrogacy arrangements in Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Paraguay, Peru, Uruguay, and Venezuela. The review focused on articles that discussed topics of domestic and international law, policy, regulation, and governance related to commercial surrogacy. We queried PubMed, JSTOR, and Google Scholar for Spanish and English-language articles limited to those published between 2000 and 2016.

Results
Our literature and legal review found a wide variance in how different countries address the issue, including two (Brazil and Uruguay) that have issued guidance attempting to clarify the legality of commercial surrogacy, others who have introduced surrogacy-specific legislation, and a final group with no specific legal mechanisms in place. Our extracted legal case studies also indicate that courts have a hard time interpreting existing law and its applicability to surrogacy. The influence of Catholicism also played a role in the adoption of surrogacy and other advanced reproductive technology (ART)-related legislation.

Conclusions
Changes in global infertility rates, the emergence of new family structures, and advancement of ART are factors that will influence future development of legal frameworks addressing surrogacy in South America. Despite a growing transnational market for commercial surrogacy in many of the countries examined, the current patchwork of policy does little to clarify what forms of surrogacy are legally permissible, nor do they adequately protect surrogates, intended parents, or the children themselves. This points to an urgent need for regional legal and policy harmonization specifically designed to align with public health and human rights principles.

Abstract:
Background
On April 28, 2014, the World Health Organization (WHO) declared polio a “Public Health Emergency of International Concern” (PHIC) under the authority of the International Health Regulations. Although polio has been eradicated from nearly every nation on earth, Pakistan is one of three countries where wild polio and vaccine-derived polio strains remain, thwarting global eradication efforts.

Aims
Polio eradication progress is complicated by security and conflict issues at the border area between Pakistan and Afghanistan. In addition to security issues, other critical challenges, such as maintaining cold supply chain for vaccines, active and sentinel surveillance, false beliefs about vaccines, distrust of healthcare workers, and accessibility to conflict areas due to terrorist activities, all play a role in the continued persistence of Polio. In response to these challenges, we assess the local and international policy environment and its impact on polio eradication in Pakistan.

Findings
Based on our analysis of existing barriers and challenges associated with polio eradication in Pakistan, this study discusses why employing “vaccine diplomacy” represents a key policy and advocacy strategic approach to achieve the overall end game of polio eradication. Specifically, we identify a set of concrete public health, international development, and diplomatic and policy recommendations that can act synergistically under the umbrella of health and vaccine diplomacy to finally put an end to polio.

Abstract:
Corruption is diverse in its forms and embedded in health systems worldwide. Health-sector corruption directly impedes progress towards universal health coverage by inhibiting people’s access to quality health services and to safe and effective medicines, and undermining systems for financial risk protection. Corruption is also a cross-cutting theme in the United Nations’ sustainable development goals (SDGs) which aim to improve population health, promote justice and strong institutions and advance sustainable human development. To address health-sector corruption, we need to identify how it happens, collect evidence on its impact and develop frameworks to assess the potential risks and put in place protective measures. We propose that the SDGs can be leveraged to develop a new approach to anti-corruption governance in the health sector. The aim will be to address coordination across the jurisdictions of different countries and foster partnerships among stakeholders to adopt coherent policies and anti-corruption best practices at all levels. Combating corruption requires a focused and invigorated political will, better advocacy and stronger institutions. There is no single solution to the problem. Nevertheless, a commitment to controlling corruption via the SDGs will better ensure the integrity of global health and human development now and beyond 2030.

Abstract:
The United States is in the midst of an opioid public health emergency, one that is also influenced by a convergence of Internet-based technology, health policy, and the need for stakeholder collaboration and action around the need to combat the illicit online sales of opioids by illegal online pharmacies and digital drug dealers. This risk is not new, however, with calls to actively reduce online opioid availability as online pharmacies use a growing array of digital channels, including search engines, social media platforms, and the dark Web. In response, the US Food and Drug Administration convened a special June 2018 summit bringing together technology companies, government agencies, researchers, and advocacy groups with the goal of collaboratively developing and implementing solutions to tackle the problem. Yet after this meeting, stakeholders remain fragmented in approaches despite the availability of technology that can detect, classify, and report illicit sellers who are in direct violation of Federal law. Despite ongoing challenges, advances in data science and the resources and expertise technology companies can contribute will be a key factor in ensuring that the Internet helps end and not fuel the public health emergency of opioid abuse.

Abstract:
In a press release reporting updates from the recent 71st World Health Assembly of the World Health Organization (WHO), member state delegates called special attention to development of a 5-year roadmap aimed at improving access to safe, effective, and affordable medicines and vaccines, a health target contained in the United Nations’ Sustainable Development Goals.1 The WHO also highlighted one of the key impediments of progress toward this target, the increasing numbers of substandard and falsified medicines (SF medicines) that undermine global health, social and economic progress, and human development.

Abstract:
We discuss how corruption affects access to antiretroviral therapies (ARVs) globally. Recent cases of theft of ARVs, collusion, and manipulation in procurement found in countries such as Central African Republic, Bangladesh, Malawi, and Guinea, show there is still much work to be done to reduce the risk of corruption. This includes addressing the structural weaknesses in procurement mechanisms and supply chain management systems of health commodities and medicines.

Abstract not available

Abstract:
The United Nations has declared the Syrian conflict, with more than 50% of Syria’s population currently displaced, as the worst humanitarian crisis of the twenty-first century. The Syrian conflict has led to a collapse of infrastructure, including access to critical and lifesaving healthcare services. Women and children account for approximately 75% of internally displaced Syrians and refugees. This population is also particularly vulnerable to poor health outcomes, a condition worsened by lack of access to maternal and child health services. In response to this crisis, a partnership of Saudi and Syrian physicians established a non-profit healthcare facility named the Brotherhood Medical Center (BMC) to serve women and children within a safe area near the Syrian–Turkish border. The project began in September 2014 and was implemented in three phases of establishment, phased construction and formal launch and operation. Currently, the BMC is working at about 70% of its capacity and is run in partnership with the Syrian Expatriate Medical Association. Although there was strong initial support from donors, the BMC continues to face many financial and operational challenges, including difficulties in transferring money to Syria, shortage of medical supplies, and lack of qualified medical personnel. Despite these challenges, the BMC represents a critical model and an important case study of the challenges of delivering healthcare services to underserved populations during an ongoing conflict. However, more robust support from the international community is needed to ensure it continues its important health and humanitarian mission.

Abstract:
Background
On December 6 and 7, 2017, the US Department of Health and Human Services (HHS) hosted its first Code-a-Thon event aimed at leveraging technology and data-driven solutions to help combat the opioid epidemic. The authors—an interdisciplinary team from academia, the private sector, and the US Centers for Disease Control and Prevention—participated in the Code-a-Thon as part of the prevention track.

Objective
The aim of this study was to develop and deploy a methodology using machine learning to accurately detect the marketing and sale of opioids by illicit online sellers via Twitter as part of participation at the HHS Opioid Code-a-Thon event.

Methods
Tweets were collected from the Twitter public application programming interface stream filtered for common prescription opioid keywords in conjunction with participation in the Code-a-Thon from November 15, 2017 to December 5, 2017. An unsupervised machine learning–based approach was developed and used during the Code-a-Thon competition (24 hours) to obtain a summary of the content of the tweets to isolate those clusters associated with illegal online marketing and sale using a biterm topic model (BTM). After isolating relevant tweets, hyperlinks associated with these tweets were reviewed to assess the characteristics of illegal online sellers.

Results
We collected and analyzed 213,041 tweets over the course of the Code-a-Thon containing keywords codeine, percocet, vicodin, oxycontin, oxycodone, fentanyl, and hydrocodone. Using BTM, 0.32% (692/213,041) tweets were identified as being associated with illegal online marketing and sale of prescription opioids. After removing duplicates and dead links, we identified 34 unique “live” tweets, with 44% (15/34) directing consumers to illicit online pharmacies, 32% (11/34) linked to individual drug sellers, and 21% (7/34) used by marketing affiliates. In addition to offering the “no prescription” sale of opioids, many of these vendors also sold other controlled substances and illicit drugs.

Conclusions
The results of this study are in line with prior studies that have identified social media platforms, including Twitter, as a potential conduit for supply and sale of illicit opioids. To translate these results into action, authors also developed a prototype wireframe for the purposes of detecting, classifying, and reporting illicit online pharmacy tweets selling controlled substances illegally to the US Food and Drug Administration and the US Drug Enforcement Agency. Further development of solutions based on these methods has the potential to proactively alert regulators and law enforcement agencies of illegal opioid sales, while also making the online environment safer for the public.

Abstract:
Background
After 7 years of increasing conflict and violence, the Syrian civil war now constitutes the largest displacement crisis in the world, with more than 6 million people who have been internally displaced. Among this already-vulnerable population group, women and children face significant challenges associated with lack of adequate access to maternal and child health (MCH) services, threatening their lives along with their immediate and long-term health outcomes.

Discussion
While several health and humanitarian aid organizations are working to improve the health and welfare of internally displaced Syrian women and children, there is an immediate need for local medical humanitarian interventions. Responding to this need, we describe the case study of the Brotherhood Medical Center (the “Center”), a local clinic that was initially established by private donors and later partnered with the Syrian Expatriate Medical Association to provide free MCH services to internally displaced Syrian women and children in the small Syrian border town of Atimah.

Conclusions
The Center provides a unique contribution to the Syrian health and humanitarian crisis by focusing on providing MCH services to a targeted vulnerable population locally and through an established clinic. Hence, the Center complements efforts by larger international, regional, and local organizations that also are attempting to alleviate the suffering of Syrians victimized by this ongoing civil war. However, the long-term success of organizations like the Center relies on many factors including strategic partnership building, adjusting to logistical difficulties, and seeking sustainable sources of funding. Importantly, the lessons learned by the Center should serve as important principles in the design of future medical humanitarian interventions working directly in conflict zones, and should emphasize the need for better international cooperation and coordination to support local initiatives that serve victims where and when they need it the most.

Abstract:
Background
Effective supply chain management is a challenge in every sector, but in healthcare there is added complexity and risk as a compromised supply chain in healthcare can directly impact patient safety and health outcomes. One potential solution for improving security, integrity, data provenance, and functionality of the health supply chain is blockchain technology.

Objectives
Provide an overview of the opportunities and challenges associated with blockchain adoption and deployment for the health supply chain, with a focus on the pharmaceutical supply, medical device and supplies, Internet of Healthy Things (IoHT), and public health sectors.

Methods
A narrative review was conducted of the academic literature, grey literature, and industry publications, in addition to identifying and characterizing select stakeholders engaged in exploring blockchain solutions for the health supply chain.

Results
Critical challenges in protecting the integrity of the health supply chain appear well suited for adoption of blockchain technology. Use cases are emerging, including using blockchain to combat counterfeit medicines, securing medical devices, optimizing functionality of IoHT, and improving the public health supply chain. Despite these clear opportunities, most blockchain initiatives remain in proof-of-concept or pilot phase.

Conclusion
Blockchain technology has the unrealized promise to help improve the health supply chain, but further study, evaluation and alignment with policy mechanisms is needed.

Abstract:
The withdrawal of the UK from the European Union (EU) is a complicated event. Although implications vary by industry, the biotechnology sector is especially vulnerable to the consequences of Brexit. Accordingly, here we evaluate potential repercussions under four post-Brexit political pathways: European Economic Area (EEA) affiliation (Norwegian Model); negotiated bilateral access (Swiss Model); limited participation in EU Customs Union (Turkish Model); or independence under the World Trade Organization (WTO) designation. We conclude that all four pathways fail to protect the mutually beneficial UK–EU biotechnology relationship and that alternative pathways need to be explored. Accordingly, we outline a suite of policy mechanisms aimed at ensuring continued EU–UK regulatory synergy, with the central aim of ensuring access to biomedical innovations and ensuring patient safety.

Abstract:
Introduction
Increased awareness of the importance of mental health for global health has led to a number of new initiatives, including influential policy instruments issued by the World Health Organization (WHO) and the United Nations (UN).

Method
This policy brief describes two WHO instruments, the Mental Health Action Plan for 2013–2020 (World Health Organization, 2013) and the Mental Health Atlas (World Health Organization, 2015), and presents a comparative analysis with the Sustainable Development Goals (SDGs) of the UN’s 2030 Agenda for Sustainable Development (United Nations, 2015).

Results
The WHO’s Action Plan calls for several specific objectives and targets, with a focus on improving global mental health governance and service coverage. In contrast, the UN’s Sustainable Development Goals include only one goal specific to mental health, with a single indicator tracking suicide mortality rates.

Discussion
The discrepancy between the WHO and UN frameworks suggests a need for increased policy coherence. Improved global health governance can provide the basis for ensuring and accelerating progress in global mental health.

Abstract:
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.

Illicit online pharmacies allow the purchase of prescription drugs online without a prescription. Such pharmacies leverage social media platforms such as Twitter as a promotion and marketing tool with the intent of reaching out to a larger, potentially younger demographics of the population. Given the serious negative health effects that arise from abusing such drugs, it is important to identify the relevant content on social media and exterminate their presence as quickly as possible. In response, we collected all the tweets that contained the names of certain preselected controlled substances over a period of 5 months. We found that an unsupervised topic modeling based methodology is able to identify tweets that promote and market controlled substances with high precision. We also study the meta-data characteristics of such tweets and the users who post them and find that they have several distinguishing characteristics that sets them apart. We were able to train supervised methods and achieve high performance in detecting such content and the users who post them.

Abstract:
The rise of digital technologies has created a complex online environment that now includes illicit Internet pharmacies, online facilitators, advertising sites, and foreign entities. Collectively, these networks create significant patient safety risks, including acting as unregulated access points encouraging prescription drug abuse. Although law enforcement is active in combating this form of cybercrime, there are several difficulties in prosecuting individuals involved in online prescription drug distribution. We characterize these challenges by conducting a comprehensive legal review and analysis of USA civil and criminal cases associated with online pharmacies. This is accomplished by reviewing legal documents/filings available via the Public Access to Court Electronic Records (PACER) database, the Drug Enforcement Agency's website, and structured search queries using the Google search engine. We found more than 100 cases, including criminal indictments, sentencing documents, judgments, forfeiture orders, motions, civil complaints, and restitution documents. Our review indicates that current legal tools and regulatory policies do not effectively deter this highly profitable criminal activity. Hence, we issue a “Call to Action,” advocating the need for more robust legal remedies and criminal penalties, and greater legal and policy coherence at the domestic, regional, and global level aimed at improving patient safety and ensuring the integrity of the drug supply chain.

Abstract:
Objectives
To deploy a methodology accurately identifying tweets marketing the illegal online sale of controlled substances.

Methods
We first collected tweets from the Twitter public application program interface stream filtered for prescription opioid keywords. We then used unsupervised machine learning (specifically, topic modeling) to identify topics associated with illegal online marketing and sales. Finally, we conducted Web forensic analyses to characterize different types of online vendors. We analyzed 619 937 tweets containing the keywords codeine, Percocet, fentanyl, Vicodin, Oxycontin, oxycodone, and hydrocodone over a 5-month period from June to November 2015.

Results
A total of 1778 tweets (< 1%) were identified as marketing the sale of controlled substances online; 90% had imbedded hyperlinks, but only 46 were “live” at the time of the evaluation. Seven distinct URLs linked to Web sites marketing or illegally selling controlled substances online.

Conclusions
Our methodology can identify illegal online sale of prescription opioids from large volumes of tweets. Our results indicate that controlled substances are trafficked online via different strategies and vendors.

No abstract available.

Abstract:
Purpose of Review
The use of social media to conduct digital surveillance to address different health challenges is growing. This multidisciplinary review assesses the current state of methods and applied research used to conduct digital surveillance for prescription drug abuse.

Recent Findings
Fifteen studies met our inclusion criteria from the databases reviewed (PubMed, IEEE Xplore, and ACM Digital Library). The articles were characterized based on their overarching goals and aims, data collection and dataset attributes, and analysis approaches. Overall, reviewed studies grouped into two overarching categories as either being method-focused (advancing novel methodologies using social media data), applied-focused (generating new information on prescription drug abuse behavior), or having both elements. The social media platform most predominantly used was Twitter, with wide variation in sample size and duration of data collection. Several data analysis strategies were employed, including machine learning, temporal analysis, rule-based approaches, and statistical analysis.

Summary
Our review indicates that the field of prescription drug abuse digital surveillance is still maturing. Though many studies captured large volumes of data, the majority did not analyze data to characterize user behavior, a critical step needed in order to better explain the underlying risk environment for prescription drug abuse. Future studies need to better translate method-based approaches into applied research, use data generated from social media platforms other than Twitter, and take advantage of emerging data analysis strategies, including deep learning and multimodal approaches.

Abstract:
Background
Accessibility 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.

Methods
Drug 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.

Results
During 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.

Conclusions
Though 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.

Abstract not available.

Abstract not available.

Abstract:
Importance
Given scrutiny over financial conflicts of interest in health care, it is important to understand the types and distribution of industry-related payments to physicians.

Objective
To determine the types and distribution of industry-related payments to physicians in 2015 and the association of physician specialty and sex with receipt of payments from industry.

Design, Setting, and Participants
Observational, retrospective, population-based study of licensed US physicians (per National Plan & Provider Enumeration System) linked to 2015 Open Payments reports of industry payments. A total of 933 295 allopathic and osteopathic physicians. Outcomes were compared across specialties (surgery, primary care, specialists, interventionalists) and between 620 166 male (66.4%) and 313 129 female (33.6%) physicians using regression models adjusting for geographic Medicare-spending region and sole proprietorship.

Exposures
Physician specialty and sex.

Main Outcomes and Measures
Reported physician payment from industry (including nature, number, and value), categorized as general payments (including consulting fees and food and beverage), ownership interests (including stock options, partnership shares), royalty or license payments, and research payments. Associations between physician characteristics and reported receipt of payment.

Results
In 2015, 449 864 of 933 295 physicians (133 842 [29.8%] women), representing approximately 48% of all US physicians were reported to have received $2.4 billion in industry payments, including approximately $1.8 billion for general payments, $544 million for ownership interests, and $75 million for research payments. Compared with 47.7% of primary care physicians (205 830 of 431 819), 61.0% of surgeons (110 604 of 181 372) were reported as receiving general payments (absolute difference, 13.3%; 95% CI, 13.1-13.6; odds ratio [OR], 1.72; P < .001). Surgeons had a mean per-physician reported payment value of $6879 (95% CI, $5895-$7862) vs $2227 (95% CI, $2141-$2314) among primary care physicians (absolute difference, $4651; 95% CI, $4014-$5288). After adjusting for geographic spending region and sole proprietorship, men within each specialty had a higher odds of receiving general payments than did women: surgery, 62.5% vs 56.5% (OR, 1.28; 95% CI, 1.26-1.31); primary care, 50.9% vs 43.0% (OR, 1.38; 95% CI, 1.36-1.39); specialists, 36.3% vs 33.4% (OR, 1.15; 95% CI, 1.13-1.17); and interventionalists, 58.1% vs 40.7% (OR, 2.03; 95% CI, 1.97-2.10; P < .001 for all tests). Similarly, men reportedly received more royalty or license payments than did women: surgery, 1.2% vs 0.03% (OR, 43.20; 95% CI, 25.02-74.57); primary care, 0.02% vs 0.002% (OR, 9.34; 95% CI, 4.11-21.23); specialists, 0.08% vs 0.01% (OR, 3.67; 95% CI, 1.71-7.89); and for interventionalists, 0.13% vs 0.04% (OR, 7.98; 95% CI, 2.87-22.19; P < .001 for all tests).

Conclusions and Relevance
According to data from 2015 Open Payments reports, 48% of physicians were reported to have received a total of $2.4 billion in industry-related payments, primarily general payments, with a higher likelihood and higher value of payments to physicians in surgical vs primary care specialties and to male vs female physicians

Abstract:
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.

Abstract:
Objective
Compared to most other diseases, the total burden of common cancers is rapidly increasing in low- and middle-income countries (LMICs). The World Health Organization (WHO) publishes the Essential Medicines List, which provides guidance to countries in selecting which cancer medications should be prioritized for general public access. Countries commonly have formularies which are representative of the specific medications that the national government has prioritized for its populations.

Methods
National formularies were collected from 116 countries, and the quantification of essential cancer medication was computed using text-matching software. The proportion of essential cancer medications listed on national formularies (i.e. “concordance”) was compared to per capita gross domestic product, per capita healthcare expenditures, the human development index, smoking prevalence, and the combined prevalence of overweight and obesity.

Results
Median concordance with cancer drugs among low- and middle-income countries (LMICs) was 42.71%. In bivariate comparisons, concordance was significantly associated with per capita GDP at PPP (p = 0.005), per capita health expenditures (p = 0.050), the human development index (p < 0.001), and the combined prevalence of overweight and obesity (p = 0.006). However, concordance was not associated with smoking prevalence (p = 0.292).

Conclusion
With national formularies analyzed for over 80% of all LMICs, this study found that most LMICs listed under half of cancer medications considered by the WHO to be essential. LMIC decision-making for policies related to cancer drug access may be heavily influenced by economic development, as well as by the high prevalence of certain cancer risk factors. The results from this study suggest that LMICs are generally ill-prepared to adequately provide essential treatment for their rapidly rising numbers of cancer patients.

Abstract not available

Abstract:
Ongoing failure by the international community to resolve the Syrian conflict has led to destruction of critical infrastructure. This includes the collapse of the Syrian health system, leaving millions of internally displaced persons (IDPs) in urgent need of healthcare services. As the conflict intensifies, IDP populations are suffering from infectious and non-communicable disease risks, poor maternal and child health outcomes, trauma, and mental health issues, while healthcare workers continually exit the country. Healthcare workers who remain face significant challenges, including systematic attacks on healthcare facilities and conditions that severely inhibit healthcare delivery and assistance. Within this conflict-driven public health crisis, the most susceptible population is arguably the IDP. Though the fundamental ‘right to health’ is a recognised international legal principle, its application is inadequate due to limited recognition by the UN Security Council and stymied global governance by the broader international community. These factors have also negatively impacted other vulnerable groups other than IDPs, such as refugees and ethnic minorities, who may or may not be displaced. Hence, this article reviews the current Syrian conflict, assesses challenges with local and global governance for IDPs, and explores potential governance solutions needed to address this health and humanitarian crisis.

Abstract:
Since the end of the Cold War, health has gone from a peripheral concern in foreign policy negotiations to a prominent place on the global political agenda. While the rise of health onto the foreign policy agenda is by now old news, the driving forces behind its expansion into new political spheres remain understudied and undertheorized. This article builds on empirical findings from a four-country study of the integration of health into foreign policy, and proposes a conceptual approach to GHD to improve understanding of the conditions under which health is successfully positioned on the foreign policy agenda. Our approach consists of three dimensions: features of institutions and the interest various actors represent in GHD; the ideational environment in which GHD operates; and issue characteristics of the specific health concern entering foreign policy. Within each dimension, we identify specific variables that, in combination, make up the explanatory power of the proposed approach. The proposed approach does not relate to, or build upon, a single social sciences, public health, or international relations (IR) theory, but can be seen as a heuristic device to identify dimensions and variables that may shape why certain health issues rise onto the foreign policy agenda.