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Journal Description

JMIR Public Health & Surveillance (JPHS, Editor-in-chief: Travis Sanchez, Emory University/Rollins School of Public Health) is a PubMed-indexed, peer-reviewed sister journal of the Journal of Medical Internet Research (JMIR), the top cited journal in health informatics, ranked #1 by Clarivate's Journal Impact Factor. JPH is a multidisciplinary journal with a unique focus on the intersection of innovation and technology in public health, and includes topics like health communication, public health informatics, surveillance, participatory epidemiology, infodemiology and infoveillance, digital disease detection, digital public health interventions, mass media/social media campaigns, and emerging population health analysis systems and tools. 

We publish regular articles, reviews, protocols/system descriptions and viewpoint papers on all aspects of public health, with a focus on innovation and technology in public health.

Apart from publishing traditional public health research and viewpoint papers as well as reports from traditional surveillance systems, JPH was one of the first (if not the only) peer-reviewed journal which publishes papers with surveillance or pharmacovigilance data from non-traditional, unstructured big data and text sources such as social media and the Internet (infoveillance, digital disease detection), or reports on novel participatory epidemiology projects, where observations are solicited from the public.  

Among other innovations, JPH is also dedicated to support rapid open data sharing and rapid open access to surveillance and outbreak data. As one of the novel features we plan to publish rapid or even real-time surveillance reports and open data. The methods and description of the surveillance system may be peer-reviewed and published only once in detail, in a  "baseline report" (in a JMIR Res Protoc or a JMIR Public Health & Surveill paper), and authors then have the possibility to publish data and reports in frequent intervals rapidly and with only minimal additional peer-review (we call this article type "Rapid Surveillance Reports"). JMIR Publications may even work with authors/researchers and developers of selected surveillance systems on APIs for semi-automated reports (e.g. weekly reports to be automatically published in JPHS and indexed in PubMed, based on data-feeds from surveillance systems and minmal narratives and abstracts).

Furthermore, duing epidemics and public health emergencies, submissions with critical data will be processed with expedited peer-review to enable publication within days or even in real-time.

We also publish descriptions of open data resources and open source software. Where possible, we can and want to publish or even host the actual software or dataset on the journal website.


Recent Articles:

  • Source: Freepik; Copyright:; URL:; License: Licensed by JMIR.

    Social Media Surveillance for Outbreak Projection via Transmission Models: Longitudinal Observational Study


    Background: Although dynamic models are increasingly used by decision makers as a source of insight to guide interventions in order to control communicable disease outbreaks, such models have long suffered from a risk of rapid obsolescence due to failure to keep updated with emerging epidemiological evidence. The application of statistical filtering algorithms to high-velocity data streams has recently demonstrated effectiveness in allowing such models to be automatically regrounded by each new set of incoming observations. The attractiveness of such techniques has been enhanced by the emergence of a new generation of geospatially specific, high-velocity data sources, including daily counts of relevant searches and social media posts. The information available in such electronic data sources complements that of traditional epidemiological data sources. Objective: This study aims to evaluate the degree to which the predictive accuracy of pandemic projection models regrounded via machine learning in daily clinical data can be enhanced by extending such methods to leverage daily search counts. Methods: We combined a previously published influenza A (H1N1) pandemic projection model with the sequential Monte Carlo technique of particle filtering, to reground the model bu using confirmed incident case counts and search volumes. The effectiveness of particle filtering was evaluated using a norm discrepancy metric via predictive and dataset-specific cross-validation. Results: Our results suggested that despite the data quality limitations of daily search volume data, the predictive accuracy of dynamic models can be strongly elevated by inclusion of such data in filtering methods. Conclusions: The predictive accuracy of dynamic models can be notably enhanced by tapping a readily accessible, publicly available, high-velocity data source. This work highlights a low-cost, low-burden avenue for strengthening model-based outbreak intervention response planning using low-cost public electronic datasets.

  • Source: iStock by Getty Images; Copyright: Jikaboom; URL:; License: Licensed by the authors.

    “Where There’s Smoke, There’s Fire”: A Content Analysis of Print and Web-Based News Media Reporting of the Philip Morris–Funded Foundation for a...


    Background: In September 2017, the Foundation for a Smoke-Free World (FSFW), a not-for-profit organization with a core purpose “to accelerate global efforts to reduce deaths and harm from smoking” was launched. However, the legitimacy of the FSFW’s vision has been questioned by experts in tobacco control because of the organization’s only funding partner, Philip Morris International (PMI). Objective: This study aimed to examine the response to the FSFW in Web-based and print news media to understand how the FSFW and its funding partner, PMI, were framed. Methods: News articles published within a 6-month period after the FSFW was announced were downloaded via Google News and Factiva and coded for topic, framing argument, slant, mention of tobacco control policies, and direct quotes or position statements. Results: A total of 124 news articles were analyzed. The news coverage of the FSFW was framed by 6 key arguments. Over half of the news articles presented a framing argument in opposition to the FSFW (64/124, 51.6%). A further 20.2% (25/124) of articles framed the FSFW positively and 28.2% of articles (35/124) presented a neutral debate with no primary slant. The FSFW was presented as not credible because of the funding link to PMI in 29.0% (36/124) of articles and as a tactic to mislead and undermine effective tobacco control measures in 11.3% of articles (14/124). However, 12.9% of articles (16/124) argued that the FSFW or PMI is part of the solution to reducing the impact of tobacco use. Evidence-based tobacco control policies were mentioned positively in 66.9% (83/124) of news articles and 9.6% (12/124) of articles presented tobacco control policies negatively. Conclusions: The Web-based and print news media reporting of the formation of the FSFW and its mission and vision has primarily been framed by doubt, skepticism, and disapproval.

  • Source: Pexels; Copyright: Krisztina Papp; URL:; License: Licensed by JMIR.

    Programmatic Mapping: Providing Evidence for High Impact HIV Prevention Programs for Female Sex Workers


    Programmatic mapping (PM) is a rapid and efficient mechanism to develop size estimates of key populations including female sex workers (FSWs) and geolocate them at physical locations in a systematic and scientific manner. At the macro level, this information forms the basis for allocating program resources, setting performance targets, and assess coverage. At a micro level, PM data provide specific information on hot spots, estimates of FSWs at those spots, and hot spot typology and days and times of operation, all of which provides targeted service delivery strategies. This information can provide a reliable platform to plan HIV prevention and treatment services to considerable scale and intensity. Above all, the entire PM process requires deep involvement of FSWs, which increases community ownership of the data and can lead to an increased uptake of services. Despite a few limitations, the approach is versatile and can be used in varied country contexts to generate important information about sex work and its dynamics. In this paper, we describe experiences and lessons learned from using evidence generated from PM of FSWs in multiple countries to develop HIV prevention programs at scale.

  • Source: Flickr; Copyright: Alexander Northey; URL:; License: Creative Commons Attribution + Noncommercial (CC-BY-NC).

    Identifying Key Topics Bearing Negative Sentiment on Twitter: Insights Concerning the 2015-2016 Zika Epidemic


    Background: To understand the public sentiment regarding the Zika virus, social media can be leveraged to understand how positive, negative, and neutral sentiments are expressed in society. Specifically, understanding the characteristics of negative sentiment could help inform federal disease control agencies’ efforts to disseminate relevant information to the public about Zika-related issues. Objective: The purpose of this study was to analyze the public sentiment concerning Zika using posts on Twitter and determine the qualitative characteristics of positive, negative, and neutral sentiments expressed. Methods: Machine learning techniques and algorithms were used to analyze the sentiment of tweets concerning Zika. A supervised machine learning classifier was built to classify tweets into 3 sentiment categories: positive, neutral, and negative. Tweets in each category were then examined using a topic-modeling approach to determine the main topics for each category, with focus on the negative category. Results: A total of 5303 tweets were manually annotated and used to train multiple classifiers. These performed moderately well (F1 score=0.48-0.68) with text-based feature extraction. All 48,734 tweets were then categorized into the sentiment categories. Overall, 10 topics for each sentiment category were identified using topic modeling, with a focus on the negative sentiment category. Conclusions: Our study demonstrates how sentiment expressed within discussions of epidemics on Twitter can be discovered. This allows public health officials to understand public sentiment regarding an epidemic and enables them to address specific elements of negative sentiment in real time. Our negative sentiment classifier was able to identify tweets concerning Zika with 3 broad themes: neural defects,Zika abnormalities, and reports and findings. These broad themes were based on domain expertise and from topics discussed in journals such as Morbidity and Mortality Weekly Report and Vaccine. As the majority of topics in the negative sentiment category concerned symptoms, officials should focus on spreading information about prevention and treatment research.

  • Source: Freepik; Copyright: Freepik; URL:; License: Licensed by JMIR.

    Early Detection of Adverse Drug Reactions in Social Health Networks: A Natural Language Processing Pipeline for Signal Detection


    Background: Adverse drug reactions (ADRs) occur in nearly all patients on chemotherapy, causing morbidity and therapy disruptions. Detection of such ADRs is limited in clinical trials, which are underpowered to detect rare events. Early recognition of ADRs in the postmarketing phase could substantially reduce morbidity and decrease societal costs. Internet community health forums provide a mechanism for individuals to discuss real-time health concerns and can enable computational detection of ADRs. Objective: The goal of this study is to identify cutaneous ADR signals in social health networks and compare the frequency and timing of these ADRs to clinical reports in the literature. Methods: We present a natural language processing-based, ADR signal-generation pipeline based on patient posts on Internet social health networks. We identified user posts from the Inspire health forums related to two chemotherapy classes: erlotinib, an epidermal growth factor receptor inhibitor, and nivolumab and pembrolizumab, immune checkpoint inhibitors. We extracted mentions of ADRs from unstructured content of patient posts. We then performed population-level association analyses and time-to-detection analyses. Results: Our system detected cutaneous ADRs from patient reports with high precision (0.90) and at frequencies comparable to those documented in the literature but an average of 7 months ahead of their literature reporting. Known ADRs were associated with higher proportional reporting ratios compared to negative controls, demonstrating the robustness of our analyses. Our named entity recognition system achieved a 0.738 microaveraged F-measure in detecting ADR entities, not limited to cutaneous ADRs, in health forum posts. Additionally, we discovered the novel ADR of hypohidrosis reported by 23 patients in erlotinib-related posts; this ADR was absent from 15 years of literature on this medication and we recently reported the finding in a clinical oncology journal. Conclusions: Several hundred million patients report health concerns in social health networks, yet this information is markedly underutilized for pharmacosurveillance. We demonstrated the ability of a natural language processing-based signal-generation pipeline to accurately detect patient reports of ADRs months in advance of literature reporting and the robustness of statistical analyses to validate system detections. Our findings suggest the important contributions that social health network data can play in contributing to more comprehensive and timely pharmacovigilance.

  • Source: Pexels; Copyright: Negative Space; URL:; License: Licensed by JMIR.

    Google Trends in Infodemiology and Infoveillance: Methodology Framework


    Internet data are being increasingly integrated into health informatics research and are becoming a useful tool for exploring human behavior. The most popular tool for examining online behavior is Google Trends, an open tool that provides information on trends and the variations of online interest in selected keywords and topics over time. Online search traffic data from Google have been shown to be useful in analyzing human behavior toward health topics and in predicting disease occurrence and outbreaks. Despite the large number of Google Trends studies during the last decade, the literature on the subject lacks a specific methodology framework. This article aims at providing an overview of the tool and data and at presenting the first methodology framework in using Google Trends in infodemiology and infoveillance, including the main factors that need to be taken into account for a strong methodology base. We provide a step-by-step guide for the methodology that needs to be followed when using Google Trends and the essential aspects required for valid results in this line of research. At first, an overview of the tool and the data are presented, followed by an analysis of the key methodological points for ensuring the validity of the results, which include selecting the appropriate keyword(s), region(s), period, and category. Overall, this article presents and analyzes the key points that need to be considered to achieve a strong methodological basis for using Google Trends data, which is crucial for ensuring the value and validity of the results, as the analysis of online queries is extensively integrated in health research in the big data era.

  • Screenshot of Instagram #dexcom. Source:; Copyright: Instagram/JMIR Publications; URL:; License: Fair use/fair dealings.

    Continuous Glucose Monitoring in the Real World Using Photosurveillance of #Dexcom on Instagram: Exploratory Mixed Methods Study


    Background: Individuals with diabetes are using social media as a method to share and gather information about their health via the diabetes online community. Infoveillance is one methodological approach to examine health care trends. However, infoveillance, while very effective in identifying many real-world health trends, may miss opportunities that use photographs as primary sources for data. We propose a new methodology, photosurveillance, in which photographs are analyzed to examine real-world trends. Objective: The purpose of this research is to (1) assess the use of photosurveillance as a research method to examine real-world trends in diabetes and (2) report on real-world use of continuous glucose monitoring (CGM) on Instagram. Methods: This exploratory mixed methods study examined all photographs posted on Instagram that were identified with the hashtag #dexcom over a 3-month period—December 2016 to February 2017. Photographs were coded by CGM location on the body. Original posts and corresponding comments were textually coded for length of CGM device wear and CGM failure and were analyzed for emerging themes. Results: A total of 2923 photographs were manually screened; 12.08% (353/2923) depicted a photograph with a CGM site location. The majority (225/353, 63.7%) of the photographs showed a CGM site in an off-label location, while 26.2% (92/353) were in an FDA-approved location (ie, abdomen) and 10.2% (36/353) were in an unidentifiable location. There were no significant differences in the number of likes or comments based on US Food and Drug Administration (FDA) approval. Five themes emerged from the analysis of original posts (N=353) and corresponding comments (N=2364): (1) endorsement of CGM as providing a sense of well-being; (2) reciprocating information, encouragement, and support; (3) reciprocating CGM-related frustrations; (4) life hacks to optimize CGM use; and (5) sharing and learning about off-label CGM activity. Conclusions: Our results indicate that individuals successfully used CGM in off-label locations, posting photos of these areas with greater frequency than of the abdomen, with no indication of sensor failure. While these photographs only capture a snapshot in time, these posts can be used to inform providers and industry leaders of real-world trends in CGM use. Additionally, there were instances in which sensors were worn beyond the FDA-approved 7-day period; however, they represented the minority in this study.

  • Source: Image created by the Authors; Copyright: Amani S Alqahtani; URL:; License: Creative Commons Attribution (CC-BY).

    Exploring Australian Hajj Tour Operators’ Knowledge and Practices Regarding Pilgrims’ Health Risks: A Qualitative Study


    Background: Travel agents are known to be one of the main sources of health information for pilgrims, and their advice is associated with positive health behaviors. Objective: This study aimed to investigate travel agents’ health knowledge, what health advice they provide to the pilgrims, and their sources of health information. Methods: In-depth interviews were conducted among specialist Hajj travel agents in Sydney, Australia. Thematic analysis was undertaken. Results: Of the 13 accredited Hajj travel agents, 9 (69%) were interviewed. A high level of awareness regarding gastrointestinal infections, standard hygiene methods, and the risk of injury was noted among the participants and was included in advice provided to pilgrims. However, very limited knowledge and provision of advice about the risk of respiratory infections was identified. Knowledge of the compulsory meningococcal vaccine was high, and all participated travel agents reported influenza vaccine (a recommended vaccine) as a second “compulsory” vaccine for Hajj visas. Conversely, participants reported very limited knowledge about other recommended vaccines for Hajj. The Ministry of Hajj website and personal Hajj experience were the main sources of information. Conclusions: This study identifies a potential path for novel health promotion strategies to improve health knowledge among Hajj travel agents and subsequently among Hajj pilgrims.

  • Source: Pixabay; Copyright: Belova59; URL:; License: Licensed by JMIR.

    Tools for the Diagnosis of Herpes Simplex Virus 1/2: Systematic Review of Studies Published Between 2012 and 2018


    Background: Herpes simplex virus (HSV)-1 and HSV-2 are common infections affecting the global population, with HSV-1 estimated to affect 67% of the global population. HSV can have rare but severe manifestations, such as encephalitis and neonatal herpes, necessitating the use of reliable and accurate diagnostic tools for the detection of the viruses. Currently used HSV diagnostic tools require highly specialized skills and availability of a laboratory setting but may lack sensitivity. The numerous recently developed HSV diagnostic tools need to be identified and compared in a systematic way to make the best decision about which diagnostic tool to use. The diagnosis of HSV is essential for prompt treatment with antivirals. To select the best test for a patient, knowledge of the performance and limitations of each test is critical. Objective: This systematic review has summarized recent studies evaluating HSV-1 and HSV-2 diagnostic tools. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, selection criteria, data extraction, and data analysis were determined before the commencement of the study. Studies assessing the specificity/sensitivity of HSV-1 or HSV-2 diagnostic tools published between 2012 and 2018 were included. Quality assessment of included studies was performed using the quality assessment of diagnostic accuracy studies (QUADAS-2) tool. Results: Searches of the PubMed database yielded 264 studies; 11 studies included 11 molecular assays, and 8 studies included 19 different serological assays for the detection of HSV-1, HSV-2, or both. A greater proportion of molecular assay–based tools are being developed by commercial entities. Studies that tested molecular assays mostly focused on cutaneous and mucosal HSV infections (n=13); 2 studies focused on ocular disease, whereas only 1 study focused on the central nervous system manifestations. The Simplexa HSV 1 & 2 Direct is currently the only Food and Drug Administration–approved device for use on cerebrospinal fluid. No tools focused on prenatal screening. We also present performance metrics of tests for benchmarking of future technology. Most of the included studies had a high risk of bias rating in half of the QUADAS-2 tool risk of bias domains. Conclusions: The use of serologic tests to diagnose genital lesions is inappropriate because positive results may be due to chronic infection, whereas negative results may overlook recent infection. The incidence of acute infections is rising. As these infections present the greatest risk to fetuses, work needs to be done to prevent vertical transfer. Prenatal screening for primary infection and subsequent medical intervention will assist in lowering the rate of neonatal herpes. In conclusion, HSV diagnosis is moving away from culture-based methods to serology-based or polymerase chain reaction–based methods. Sensitive, rapid, and efficient HSV diagnostic tools should be adopted for the prevention of acute infections and neonatal herpes.

  • Source: picjumbo; Copyright: Viktor Hanacek; URL:; License: Licensed by the authors.

    Google for Sexual Relationships: Mixed-Methods Study on Digital Flirting and Online Dating Among Adolescent Youth and Young Adults


    Background: According to a 2015 report from the Pew Research Center, nearly 24% of teens go online almost constantly and 92% of teens are accessing the internet daily; consequently, a large part of adolescent romantic exploration has moved online, where young people are turning to the Web for romantic relationship-building and sexual experience. This digital change in romantic behaviors among youth has implications for public health and sexual health programs, but little is known about the ways in which young people use online spaces for sexual exploration. An examination of youth sexual health and relationships online and the implications for adolescent health programs has yet to be fully explored. Objective: Although studies have documented increasing rates of sexually transmitted infections and HIV among young people, many programs continue to neglect online spaces as avenues for understanding sexual exploration. Little is known about the online sexual health practices of young people, including digital flirting and online dating. This study explores the current behaviors and opinions of youth throughout online sexual exploration, relationship-building, and online dating, further providing insights into youth behavior for intervention opportunities. Methods: From January through December 2016, an exploratory study titled TECHsex used a mixed-methods approach to document information-seeking behaviors and sexual health building behaviors of youth online in the United States. Data from a national quantitative survey of 1500 youth and 12 qualitative focus groups (66 youth) were triangulated to understand the experiences and desires of young people as they navigate their sexual relationships through social media, online chatting, and online dating. Results: Young people are using the internet to begin sexual relationships with others, including dating, online flirting, and hooking up. Despite the fact that dating sites have explicit rules against minor use, under 18 youth are using these products regardless in order to make friends and begin romantic relationships, albeit at a lower rate than their older peers (19.0% [64/336] vs 37.8% [440/1163], respectively). Nearly 70% of youth who have used online dating sites met up with someone in person (44.78% [30/67] under 18 vs 74.0% [324/438] over 18). Focus group respondents provided further context into online sexual exploration; many learned of sex through pornography, online dating profiles, or through flirting on social media. Social media played an important role in vetting potential partners and beginning romantic relationships. Youth also reported using online dating and flirting despite fears of violence or catfishing, in which online profiles are used to deceive others. Conclusions: Youth are turning to online spaces to build sexual relationships, particularly in areas where access to peers is limited. Although online dating site use is somewhat high, more youth turn to social media for online dating. Sexual relationship-building included online flirting and online dating websites and/or apps. These findings have implications for future sexual health programs interested in improving the sexual health outcomes of young people. Researchers may be neglecting to include social media as potential sources of youth hookup culture and dating. We implore researchers and organizations to consider the relationships young people have with technology in order to more strategically use these platforms to create successful and youth-centered programs to improve sexual health outcomes.

  • Source: Flickr; Copyright: NIAID; URL:; License: Creative Commons Attribution (CC-BY).

    Pneumococcal Vaccination Utilization Among Hispanic Long-Term Colorectal Cancer Survivors: Cross-Sectional Assessment of Claims


    Background: Colorectal cancer (CRC) is the second leading cancer-related cause of death in the United States. However, survivorship has been increasing. Both cancer survivors and underserved populations experience unique health-related challenges and disparities that may exist among long-term CRC survivors as it relates to routine preventive care, specifically pneumococcal (PNM) vaccination. Objective: The aim of this study was to explore the relationship between long-term CRC survival and the receipt of PNM vaccine among Hispanic Medicare recipients compared with non-Hispanic populations. Methods: This study is a cross-sectional analysis of the Surveillance, Epidemiology, and End Results (SEER)-Medicare claims data examining ethnic differences in the receipt of PNM vaccination among long-term CRC survivors. Multivariable logistic regression models considered Hispanic ethnicity while controlling for sociodemographic characteristics, comorbidity score, age, tumor stage, and SEER registry. Results: Our sample revealed 32,501 long-term CRC survivors, and 1509 identified as Hispanic (4.64%) based on an established SEER algorithm. In total, 16,252 CRC survivors, or 50.00% of our sample, received a PNM vaccination. We found that Hispanic CRC survivors had 10% decreased odds of having received a PNM vaccine compared with non-Hispanic survivors (P=.03). Conclusions: Disparities likely exist in the utilization of PNM vaccination among long-term CRC survivors. Among Medicare beneficiaries, the use of claims data regarding PNM vaccination highlights the relatively poor utilization of guideline-directed preventive care.

  • Image by Dean Moriarty from Pixabay. Source: Image by Dean Moriarty from Pixabay; Copyright: Dean Moriarty; URL:; License: Public Domain (CC0).

    A Software Tool Aimed at Automating the Generation, Distribution, and Assessment of Social Media Messages for Health Promotion and Education Research


    Background: Social media offers promise for communicating the risks and health effects of harmful products and behaviors to larger and hard-to-reach segments of the population. Nearly 70% of US adults use some social media. However, rigorous research across different social media is vital to establish successful evidence-based health communication strategies that meet the requirements of the evolving digital landscape and the needs of diverse populations. Objective: The aim of this study was to expand and test a software tool (Trial Promoter) to support health promotion and education research by automating aspects of the generation, distribution, and assessment of large numbers of social media health messages and user comments. Methods: The tool supports 6 functions (1) data import, (2) message generation deploying randomization techniques, (3) message distribution, (4) import and analysis of message comments, (5) collection and display of message performance data, and (6) reporting based on a predetermined data dictionary. The tool was built using 3 open-source software products: PostgreSQL, Ruby on Rails, and Semantic UI. To test the tool’s utility and reliability, we developed parameterized message templates (N=102) based upon 2 government-sponsored health education campaigns, extracted images from these campaigns and a free stock photo platform (N=315), and topic-related hashtags (N=4) from Twitter. We conducted a functional correctness analysis of the generated social media messages to assess the algorithm’s ability to produce the expected output for each input. We defined 100% correctness as use of the message template text and substitution of 3 message parameters (ie, image, hashtag, and destination URL) without any error. The percent correct was calculated to determine the probability with which the tool generates accurate messages. Results: The tool generated, distributed, and assessed 1275 social media health messages over 85 days (April 19 to July 12, 2017). It correctly used the message template text and substituted the message parameters 100% (1275/1275) of the time as verified by human reviewers and a custom algorithm using text search and attribute-matching techniques. Conclusions: A software tool can effectively support the generation, distribution, and assessment of hundreds of health promotion messages and user comments across different social media with the highest degree of functional correctness and minimal human interaction. The tool has the potential to support social media–enabled health promotion research and practice: first, by enabling the assessment of large numbers of messages to develop evidence-based health communication, and second, by providing public health organizations with a tool to increase their output of health education messages and manage user comments. We call on readers to use and develop the tool and to contribute to evidence-based communication methods in the digital age.

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