Objectives To collect, appraise, select, and report the best available national estimates of cigarette consumption since 1970. Design Systematic collection of comparable data. Setting and population 71 of 214 countries for which searches for national cigarette consumption data were conducted, representing over 95% of global cigarette consumption and 85% of the world’s population. Main outcome measures Validated cigarette consumption data covering 1970-2015 were identified for 71 countries. Data quality appraisal was conducted by two research team members in duplicate, with greatest weight given to official government sources. All data were standardised into units of cigarettes consumed per year in each country, a detailed accounting of data quality and sourcing was prepared, and all collected data and metadata were made freely available in an open access dataset. Results Cigarette consumption fell in most countries over the past three decades but trends in country specific consumption were highly variable. For example, China consumed 2.5 million metric tonnes (MMT) of cigarettes in 2013, more than Russia (0.36 MMT), the United States (0.28 MMT), Indonesia (0.28 MMT), Japan (0.20 MMT), and the next 35 highest consuming countries combined. The US and Japan achieved reductions of more than 0.1 MMT from a decade earlier, whereas Russian consumption plateaued, and Chinese and Indonesian consumption increased by 0.75 MMT and 0.1 MMT, respectively. These data generally concord with modelled country level data from the Institute for Health Metrics and Evaluation and have the additional advantage of not smoothing year-over-year discontinuities that are necessary for robust quasi-experimental impact evaluations. Conclusions Before this study, publicly available data on cigarette consumption have been limited; they have been inappropriate for quasi-experimental impact evaluations (modelled data), held privately by companies (proprietary data), or widely dispersed across many national statistical agencies and research organisations (disaggregated data). This new dataset confirms that cigarette consumption has decreased in most countries over the past three decades, but that secular country specific consumption trends are highly variable. The findings underscore the need for more robust processes in data reporting, ideally built into international legal instruments or other mandated processes. To monitor the impact of the WHO Framework Convention on Tobacco Control and other tobacco control interventions, data on national tobacco production, trade, and sales should be routinely collected and openly reported.

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Vaccine misinformation on social media poses significant drawbacks to the efforts of vaccine coverage rates. This research studies the interlinkages between pro-and anti-vaccine YouTube videos to help public health professionals explore new ways to reach anti-vaccine and vaccine-hesitant audiences. Using YouTube's API, we retrieved 9,489 recommended videos from 250 seeds using keywords such as "vaccines" and its derivatives. We then manually identified 1,984 videos directly related to vaccination and then categorized their vaccine sentiment into pro-, anti-, and neutral. Results show that 65.02% of the videos were anti-vaccine, and only 20.87% were provaccine, 14.11% were neutral. Anti-vaccine videos were significantly more prevalent in the "News & Politics" and "People & Blogs" video categories; while pro-vaccine videos were more prevalent in the "Education" and "Science & Technology" categories. Results also showed that anti-vaccine sentiment videos have higher values of closeness centrality (p<0.05), suggesting that watching an anti-vaccine video will likely lead to more anti-vaccine video recommendations. Moreover, videos that had more dislikes than likes (dislike/like ratio) are positively related to pro-vaccine videos (OR=3.912), suggesting that pro-vaccine videos are more ill-received on YouTube than anti-vaccine videos. This study is the first to examine the network of vaccine-related videos on YouTube and their centralities. The results highlight some possible limitations of YouTube-based vaccination awareness campaigns and also emphasize the need to diversify how YouTube makes its recommendations to help viewers break out of the anti-vaccine "bubble." CCS Concepts• Networks → Network types → Overlay and other logical network structures → Social media networks Information systems → Information retrieval → Retrieval tasks and goals → Recommender systems.

Vaccine misinformation on social media poses significant drawbacks to the efforts of vaccine coverage rates. This research studies the interlinkages between pro- and anti-vaccine YouTube videos to help public health professionals explore new ways to reach anti-vaccine and vaccine-hesitant audiences. Using YouTube’s API, we retrieved 9,489 recommended videos from 250 seeds using keywords such as “vaccines” and its derivatives. We then manually identified 1,984 videos directly related to vaccination and then categorized their vaccine sentiment into pro-, anti-, and neutral. Results show that 65.02% of the videos were anti-vaccine, and only 20.87% were pro-vaccine, 14.11% were neutral. Anti-vaccine videos were significantly more prevalent in the “News & Politics” and “People & Blogs” video categories; while pro-vaccine videos were more prevalent in the “Education” and “Science & Technology” categories. Results also showed that anti-vaccine sentiment videos have higher values of closeness centrality (p<0.05), suggesting that watching an anti-vaccine video will likely lead to more anti-vaccine video recommendations. Moreover, videos that had more dislikes than likes (dislike/like ratio) are positively related to pro-vaccine videos (OR=3.912), suggesting that pro-vaccine videos are more ill-received on YouTube than anti-vaccine videos. This study is the first to examine the network of vaccine-related videos on YouTube and their centralities. The results highlight some possible limitations of YouTube-based vaccination awareness campaigns and also emphasize the need to diversify how YouTube makes its recommendations to help viewers break out of the anti-vaccine “bubble.”