JMIR Publications

JMIR Public Health and Surveillance

A multidisciplinary journal that focuses on the intersection of public health and technology, public health informatics, mass media campaigns, surveillance, participatory epidemiology, and innovation in public health practice and research.

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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 (Impact Factor 2015: 4.532). 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: Getty Images; License: Licensed by JMIR.

    Social Media and Sexual Behavior Among Adolescents: Is there a link?

    Abstract:

    Background: Adolescent sexual risk taking and its consequences remain a global public health concern. Empirical evidence on the impact that social media has on sexual health behaviors among youth is sparse. Objective: The study aimed to examine the relationship between social media and the change in sexual risk over time and whether parental monitoring moderates this relationship. Methods: This study comprised a sample of 555 Latino youth aged 13-19 years from Maryland, United States completing baseline and follow-up surveys. Mixed-effects linear regression was used to examine the relationship between social media and the change in sexual risk over time and whether parental monitoring moderated the relationship. Results: Sexual risk behaviors significantly increased between baseline (T1) and follow up (T2) (mean=0.432 vs mean=0.734, P<.001). Youth sending more than 100 text messages per day had significantly higher sexual risk scores (beta=1.008, P<.001) but significantly larger declines in sexual risk scores for higher levels of parental monitoring (beta=−.237, P=.009). Conclusions: Although adolescents exchange SMS at high rates, parental monitoring remains vital to parent-child relationships and can moderate SMS frequency and sexual risk behaviors, despite parental influence diminishing and peer pressure and social influences increasing during adolescence.

  • Tablet showing screenshot of GapMap (montage). Source: Placeit / JMIR Publications; Copyright: JMIR Publications; URL: http://publichealth.jmir.org/2017/2/e27/; License: Creative Commons Attribution (CC-BY).

    GapMap: Enabling Comprehensive Autism Resource Epidemiology

    Abstract:

    Background: For individuals with autism spectrum disorder (ASD), finding resources can be a lengthy and difficult process. The difficulty in obtaining global, fine-grained autism epidemiological data hinders researchers from quickly and efficiently studying large-scale correlations among ASD, environmental factors, and geographical and cultural factors. Objective: The objective of this study was to define resource load and resource availability for families affected by autism and subsequently create a platform to enable a more accurate representation of prevalence rates and resource epidemiology. Methods: We created a mobile application, GapMap, to collect locational, diagnostic, and resource use information from individuals with autism to compute accurate prevalence rates and better understand autism resource epidemiology. GapMap is hosted on AWS S3, running on a React and Redux front-end framework. The backend framework is comprised of an AWS API Gateway and Lambda Function setup, with secure and scalable end points for retrieving prevalence and resource data, and for submitting participant data. Measures of autism resource scarcity, including resource load, resource availability, and resource gaps were defined and preliminarily computed using simulated or scraped data. Results: The average distance from an individual in the United States to the nearest diagnostic center is approximately 182 km (50 miles), with a standard deviation of 235 km (146 miles). The average distance from an individual with ASD to the nearest diagnostic center, however, is only 32 km (20 miles), suggesting that individuals who live closer to diagnostic services are more likely to be diagnosed. Conclusions: This study confirmed that individuals closer to diagnostic services are more likely to be diagnosed and proposes GapMap, a means to measure and enable the alleviation of increasingly overburdened diagnostic centers and resource-poor areas where parents are unable to diagnose their children as quickly and easily as needed. GapMap will collect information that will provide more accurate data for computing resource loads and availability, uncovering the impact of resource epidemiology on age and likelihood of diagnosis, and gathering localized autism prevalence rates.

  • San Francisco Carnaval 2011 King & Queen Competition. Copyright: Carnaval.com Studios; URL: https://goo.gl/0FcHqJ; License: Creative Commons Attribution (CC-BY).

    The RSVP Project: Factors Related to Disengagement From Human Immunodeficiency Virus Care Among Persons in San Francisco

    Abstract:

    Background: In the United States, an estimated two-thirds of persons with human immunodeficiency virus (HIV) infection do not achieve viral suppression, including those who have never engaged in HIV care and others who do not stay engaged in care. Persons with an unsuppressed HIV viral load might experience poor clinical outcomes and transmit HIV. Objective: The goal of the Re-engaging Surveillance-identified Viremic Persons (RSVP) project in San Francisco, CA, was to use routine HIV surveillance databases to identify, contact, interview, and reengage in HIV care persons who appeared to be out of care because their last HIV viral load was unsuppressed. We aimed to interview participants about their HIV care and barriers to reengagement. Methods: Using routinely collected HIV surveillance data, we identified persons with HIV who were out of care (no HIV viral load and CD4 laboratory reports during the previous 9-15 months) and with their last plasma HIV RNA viral load >200 copies/mL. We interviewed the located persons, at baseline and 3 months later, about whether and why they disengaged from HIV care and the barriers they faced to care reengagement. We offered them assistance with reengaging in HIV care from the San Francisco Department of Public Health linkage and navigation program (LINCS). Results: Of 282 persons selected, we interviewed 75 (26.6%). Of these, 67 (89%) reported current health insurance coverage, 59 (79%) had ever been prescribed and 45 (60%) were currently taking HIV medications, 59 (79%) had seen an HIV provider in the past year, and 34 (45%) had missed an HIV appointment in the past year. Reasons for not seeing a provider included feeling healthy, using alcohol or drugs, not having enough money or health insurance, and not wanting to take HIV medicines. Services needed to get to an HIV medical care appointment included transportation assistance, stable living situation or housing, sound mental health, and organizational help and reminders about appointments. A total of 52 (69%) accepted a referral to LINCS. Additionally, 64 (85%) of the persons interviewed completed a follow-up interview 3 months later and, of these, 62 (97%) had health insurance coverage and 47 (73%) reported having had an HIV-related care appointment since the baseline interview. Conclusions: Rather than being truly out of care, most participants reported intermittent HIV care, including recent HIV provider visits and health insurance coverage. Participants also frequently reported barriers to care and unmet needs. Health department assistance with HIV care reengagement was generally acceptable. Understanding why people previously in HIV care disengage from care and what might help them reengage is essential for optimizing HIV clinical and public health outcomes.

  • Italia 2 - 1 Mexico. Confederations Cup. Source: FlickR; Copyright: Leandro Neumann Ciuffo; URL: https://www.flickr.com/photos/18115835@N00/9062785804; License: Creative Commons Attribution (CC-BY).

    Saúde na Copa: The World’s First Application of Participatory Surveillance for a Mass Gathering at FIFA World Cup 2014, Brazil

    Abstract:

    Background: The 2005 International Health Regulations (IHRs) established parameters for event assessments and notifications that may constitute public health emergencies of international concern. These requirements and parameters opened up space for the use of nonofficial mechanisms (such as websites, blogs, and social networks) and technological improvements of communication that can streamline the detection, monitoring, and response to health problems, and thus reduce damage caused by these problems. Specifically, the revised IHR created space for participatory surveillance to function, in addition to the traditional surveillance mechanisms of detection, monitoring, and response. Participatory surveillance is based on crowdsourcing methods that collect information from society and then return the collective knowledge gained from that information back to society. The spread of digital social networks and wiki-style knowledge platforms has created a very favorable environment for this model of production and social control of information. Objective: The aim of this study was to describe the use of a participatory surveillance app, Healthy Cup, for the early detection of acute disease outbreaks during the Fédération Internationale de Football Association (FIFA) World Cup 2014. Our focus was on three specific syndromes (respiratory, diarrheal, and rash) related to six diseases that were considered important in a mass gathering context (influenza, measles, rubella, cholera, acute diarrhea, and dengue fever). Methods: From May 12 to July 13, 2014, users from anywhere in the world were able to download the Healthy Cup app and record their health condition, reporting whether they were good, very good, ill, or very ill. For users that reported being ill or very ill, a screen with a list of 10 symptoms was displayed. Participatory surveillance allows for the real-time identification of aggregates of symptoms that indicate possible cases of infectious diseases. Results: From May 12 through July 13, 2014, there were 9434 downloads of the Healthy Cup app and 7155 (75.84%) registered users. Among the registered users, 4706 (4706/7155, 65.77%) were active users who posted a total of 47,879 times during the study period. The maximum number of users that signed up in one day occurred on May 30, 2014, the day that the app was officially launched by the Minister of Health during a press conference. During this event, the Minister of Health announced the special government program Health in the World Cup on national television media. On that date, 3633 logins were recorded, which accounted for more than half of all sign-ups across the entire duration of the study (50.78%, 3633/7155). Conclusions: Participatory surveillance through community engagement is an innovative way to conduct epidemiological surveillance. Compared to traditional epidemiological surveillance, advantages include lower costs of data acquisition, timeliness of information collected and shared, platform scalability, and capacity for integration between the population being served and public health services.

  • Source: Flickr/Foter; Copyright: Gatis Gribusts; URL: https://www.flickr.com/photos/gatiuss/5223834995/; License: Creative Commons Attribution + Noncommercial (CC-BY-NC).

    TwiMed: Twitter and PubMed Comparable Corpus of Drugs, Diseases, Symptoms, and Their Relations

    Abstract:

    Background: Work on pharmacovigilance systems using texts from PubMed and Twitter typically target at different elements and use different annotation guidelines resulting in a scenario where there is no comparable set of documents from both Twitter and PubMed annotated in the same manner. Objective: This study aimed to provide a comparable corpus of texts from PubMed and Twitter that can be used to study drug reports from these two sources of information, allowing researchers in the area of pharmacovigilance using natural language processing (NLP) to perform experiments to better understand the similarities and differences between drug reports in Twitter and PubMed. Methods: We produced a corpus comprising 1000 tweets and 1000 PubMed sentences selected using the same strategy and annotated at entity level by the same experts (pharmacists) using the same set of guidelines. Results: The resulting corpus, annotated by two pharmacists, comprises semantically correct annotations for a set of drugs, diseases, and symptoms. This corpus contains the annotations for 3144 entities, 2749 relations, and 5003 attributes. Conclusions: We present a corpus that is unique in its characteristics as this is the first corpus for pharmacovigilance curated from Twitter messages and PubMed sentences using the same data selection and annotation strategies. We believe this corpus will be of particular interest for researchers willing to compare results from pharmacovigilance systems (eg, classifiers and named entity recognition systems) when using data from Twitter and from PubMed. We hope that given the comprehensive set of drug names and the annotated entities and relations, this corpus becomes a standard resource to compare results from different pharmacovigilance studies in the area of NLP.

  • Source: unsplash.com via pexels.com; URL: https://www.pexels.com/photo/adult-blur-boy-child-286421/; License: Public Domain (CC0).

    Measuring Sexual Behavior Stigma to Inform Effective HIV Prevention and Treatment Programs for Key Populations

    Abstract:

    Background: The levels of coverage of human immunodeficiency virus (HIV) treatment and prevention services needed to change the trajectory of the HIV epidemic among key populations, including gay men and other men who have sex with men (MSM) and sex workers, have consistently been shown to be limited by stigma. Objective: The aim of this study was to propose an agenda for the goals and approaches of a sexual behavior stigma surveillance effort for key populations, with a focus on collecting surveillance data from 4 groups: (1) members of key population groups themselves (regardless of HIV status), (2) people living with HIV (PLHIV) who are also members of key populations, (3) members of nonkey populations, and (4) health workers. Methods: We discuss strengths and weaknesses of measuring multiple different types of stigma including perceived, anticipated, experienced, perpetrated, internalized, and intersecting stigma as measured among key populations themselves, as well as attitudes or beliefs about key populations as measured among other groups. Results: With the increasing recognition of the importance of stigma, consistent and validated stigma metrics for key populations are needed to monitor trends and guide immediate action. Evidence-based stigma interventions may ultimately be the key to overcoming the barriers to coverage and retention in life-saving antiretroviral-based HIV prevention and treatment programs for key populations. Conclusions: Moving forward necessitates the integration of validated stigma scales in routine HIV surveillance efforts, as well as HIV epidemiologic and intervention studies focused on key populations, as a means of tracking progress toward a more efficient and impactful HIV response.

  • Source: The authors; URL: http://www.jmir.org/2017/4/e126/; License: Created by the authors.

    Zika in Twitter: Temporal Variations of Locations, Actors, and Concepts

    Abstract:

    Background: The recent Zika outbreak witnessed the disease evolving from a regional health concern to a global epidemic. During this process, different communities across the globe became involved in Twitter, discussing the disease and key issues associated with it. This paper presents a study of this discussion in Twitter, at the nexus of location, actors, and concepts. Objective: Our objective in this study was to demonstrate the significance of 3 types of events: location related, actor related, and concept related, for understanding how a public health emergency of international concern plays out in social media, and Twitter in particular. Accordingly, the study contributes to research efforts toward gaining insights on the mechanisms that drive participation, contributions, and interaction in this social media platform during a disease outbreak. Methods: We collected 6,249,626 tweets referring to the Zika outbreak over a period of 12 weeks early in the outbreak (December 2015 through March 2016). We analyzed this data corpus in terms of its geographical footprint, the actors participating in the discourse, and emerging concepts associated with the issue. Data were visualized and evaluated with spatiotemporal and network analysis tools to capture the evolution of interest on the topic and to reveal connections between locations, actors, and concepts in the form of interaction networks. Results: The spatiotemporal analysis of Twitter contributions reflects the spread of interest in Zika from its original hotspot in South America to North America and then across the globe. The Centers for Disease Control and World Health Organization had a prominent presence in social media discussions. Tweets about pregnancy and abortion increased as more information about this emerging infectious disease was presented to the public and public figures became involved in this. Conclusions: The results of this study show the utility of analyzing temporal variations in the analytic triad of locations, actors, and concepts. This contributes to advancing our understanding of social media discourse during a public health emergency of international concern.

  • Public Response to Scientific Misconduct: Assessing Changes in Public Sentiment Toward the Stimulus-Triggered Acquisition of Pluripotency (STAP) Cell Case...

    Abstract:

    Background: In this age of social media, any news—good or bad—has the potential to spread in unpredictable ways. Changes in public sentiment have the potential to either drive or limit investment in publicly funded activities, such as scientific research. As a result, understanding the ways in which reported cases of scientific misconduct shape public sentiment is becoming increasingly essential—for researchers and institutions, as well as for policy makers and funders. In this study, we thus set out to assess and define the patterns according to which public sentiment may change in response to reported cases of scientific misconduct. This study focuses on the public response to the events involved in a recent case of major scientific misconduct that occurred in 2014 in Japan—stimulus-triggered acquisition of pluripotency (STAP) cell case. Objectives: The aims of this study were to determine (1) the patterns according to which public sentiment changes in response to scientific misconduct; (2) whether such measures vary significantly, coincident with major timeline events; and (3) whether the changes observed mirror the response patterns reported in the literature with respect to other classes of events, such as entertainment news and disaster reports. Methods: The recent STAP cell scandal is used as a test case. Changes in the volume and polarity of discussion were assessed using a sampling of case-related Twitter data, published between January 28, 2014 and March 15, 2015. Rapidminer was used for text processing and the popular bag-of-words algorithm, SentiWordNet, was used in Rapidminer to calculate sentiment for each sample Tweet. Relative volume and sentiment was then assessed overall, month-to-month, and with respect to individual entities. Results: Despite the ostensibly negative subject, average sentiment over the observed period tended to be neutral (−0.04); however, a notable downward trend (y=−0.01 x +0.09; R ²=.45) was observed month-to-month. Notably polarized tweets accounted for less than one-third of sampled discussion: 17.49% (1656/9467) negative and 12.59% positive (1192/9467). Significant polarization was found in only 4 out of the 15 months covered, with significant variation month-to-month (P<.001). Significant increases in polarization tended to coincide with increased discussion volume surrounding major events (P<.001). Conclusions: These results suggest that public opinion toward scientific research may be subject to the same sensationalist dynamics driving public opinion in other, consumer-oriented topics. The patterns in public response observed here, with respect to the STAP cell case, were found to be consistent with those observed in the literature with respect to other classes of news-worthy events on Twitter. Discussion was found to become strongly polarized only during times of increased public attention, and such increases tended to be driven primarily by negative reporting and reactionary commentary.

  • Web-based intervention: Peer-to-peer tailored video message of a peer’s experiences with consistent condom use represents the method of using role models. Source: Figure 2 from JMIR Public Health Surveill 2017;3(2):e20; Copyright: The authors; URL: http://publichealth.jmir.org/2017/2/e20/; License: Creative Commons Attribution (CC-BY).

    The Use of Intervention Mapping to Develop a Tailored Web-Based Intervention, Condom-HIM

    Abstract:

    Background: Many HIV (human immunodeficiency virus) prevention interventions are currently being implemented and evaluated, with little information published on their development. A framework highlighting the method of development of an intervention can be used by others wanting to replicate interventions or develop similar interventions to suit other contexts and settings. It provides researchers with a comprehensive development process of the intervention. Objective: The objective of this paper was to describe how a systematic approach, intervention mapping, was used to develop a tailored Web-based intervention to increase condom use among HIV-positive men who have sex with men. Methods: The intervention was developed in consultation with a multidisciplinary team composed of academic researchers, community members, Web designers, and the target population. Intervention mapping involved a systematic process of 6 steps: (1) needs assessment; (2) identification of proximal intervention objectives; (3) selection of theory-based intervention methods and practical strategies; (4) development of intervention components and materials; (5) adoption, implementation, and maintenance; and (6) evaluation planning. Results: The application of intervention mapping resulted in the development of a tailored Web-based intervention for HIV-positive men who have sex with men, called Condom-HIM. Conclusions: Using intervention mapping as a systematic process to develop interventions is a feasible approach that specifically integrates the use of theory and empirical findings. Outlining the process used to develop a particular intervention provides clarification on the conceptual use of experimental interventions in addition to potentially identifying reasons for intervention failures.

  • Traffic on the highway next to Boston Chinatown. Source: Photo taken by Doug Brugge, one of the co-authors; Copyright: Doug Brugge, one of the co-authors; URL: https://sites.tufts.edu/cafeh/files/2017/03/image4.jpg; License: Permission granted by Doug Brugge..

    Making Air Pollution Visible: A Tool for Promoting Environmental Health Literacy

    Abstract:

    Background: Digital maps are instrumental in conveying information about environmental hazards geographically. For laypersons, computer-based maps can serve as tools to promote environmental health literacy about invisible traffic-related air pollution and ultrafine particles. Concentrations of these pollutants are higher near major roadways and increasingly linked to adverse health effects. Interactive computer maps provide visualizations that can allow users to build mental models of the spatial distribution of ultrafine particles in a community and learn about the risk of exposure in a geographic context. Objective: The objective of this work was to develop a new software tool appropriate for educating members of the Boston Chinatown community (Boston, MA, USA) about the nature and potential health risks of traffic-related air pollution. The tool, the Interactive Map of Chinatown Traffic Pollution (“Air Pollution Map” hereafter), is a prototype that can be adapted for the purpose of educating community members across a range of socioeconomic contexts. Methods: We built the educational visualization tool on the open source Weave software platform. We designed the tool as the centerpiece of a multimodal and intergenerational educational intervention about the health risk of traffic-related air pollution. We used a previously published fine resolution (20 m) hourly land-use regression model of ultrafine particles as the algorithm for predicting pollution levels and applied it to one neighborhood, Boston Chinatown. In designing the map, we consulted community experts to help customize the user interface to communication styles prevalent in the target community. Results: The product is a map that displays ultrafine particulate concentrations averaged across census blocks using a color gradation from white to dark red. The interactive features allow users to explore and learn how changing meteorological conditions and traffic volume influence ultrafine particle concentrations. Users can also select from multiple map layers, such as a street map or satellite view. The map legends and labels are available in both Chinese and English, and are thus accessible to immigrants and residents with proficiency in either language. The map can be either Web or desktop based. Conclusions: The Air Pollution Map incorporates relevant language and landmarks to make complex scientific information about ultrafine particles accessible to members of the Boston Chinatown community. In future work, we will test the map in an educational intervention that features intergenerational colearning and the use of supplementary multimedia presentations.

  • Ticks displayed on finger. Copyright: California Department of Public Health; URL: https://www.flickr.com/photos/fairfaxcounty/7209178448; License: Creative Commons Attribution (CC-BY).

    Health Care Professionals’ Evidence-Based Medicine Internet Searches Closely Mimic the Known Seasonal Variation of Lyme Borreliosis: A Register-Based Study

    Abstract:

    Background: Both health care professionals and nonprofessionals seek medical information on the Internet. Using Web-based search engine searches to detect epidemic diseases has, however, been problematic. Physician’s databases (PD) is a chargeable evidence-based medicine (EBM) portal on the Internet for health care professionals and is available throughout the entire health care system in Finland. Lyme borreliosis (LB), a well-defined disease model, shows temporal and regional variation in Finland. Little data exist on health care professionals’ searches from Internet-based EBM databases in public health surveillance. Objective: The aim of this study was to assess whether health care professionals’ use of Internet EBM databases could describe seasonal increases of the disease and supplement routine public health surveillance. Methods: Two registers, PD and the register of primary health care diagnoses (Avohilmo), were used to compare health care professionals’ Internet searches on LB from EBM databases and national register-based LB diagnoses in order to evaluate annual and regional variations of LB in the whole country and in three selected high-incidence LB regions in Finland during 2011-2015. Results: Both registers, PD and Avohilmo, show visually similar patterns in annual and regional variation of LB in Finland and in the three high-incidence LB regions during 2011-2015. Conclusions: Health care professionals’ Internet searches from EBM databases coincide with national register diagnoses of LB. PD searches showed a clear seasonal variation. In addition, notable regional differences were present in both registers. However, physicians’ Internet medical searches should be considered as a supplementary source of information for disease surveillance.

  • Source: Flickr; Copyright: William Brawley; URL: https://www.flickr.com/photos/williambrawley/4195919691; License: Creative Commons Attribution (CC-BY).

    Determinants of Participants’ Follow-Up and Characterization of Representativeness in Flu Near You, A Participatory Disease Surveillance System

    Abstract:

    Background: Flu Near You (FNY) is an Internet-based participatory surveillance system in the United States and Canada that allows volunteers to report influenza-like symptoms using a brief weekly symptom report. Objective: Our objective was to evaluate the representativeness of the FNY population compared with the general population of the United States, explore the demographic and behavioral characteristics associated with FNY’s high-participation users, and summarize results from a user survey of a cohort of FNY participants. Methods: We compared (1) the representativeness of sex and age groups of FNY participants during the 2014-2015 flu season versus the general US population and (2) the distribution of Human Development Index (HDI) scores of FNY participants versus that of the general US population. We analyzed associations between demographic and behavioral factors and the level of participant follow-up (ie, high vs low). Finally, descriptive statistics of responses from FNY’s 2015 and 2016 end-of-season user surveys were calculated. Results: During the 2014-2015 influenza season, 47,234 unique participants had at least one FNY symptom report that was either self-reported (users) or submitted on their behalf (household members). The proportion of female FNY participants was significantly higher than that of the general US population (n=28,906, 61.2% vs 51.1%, P<.001). Although each age group was represented in the FNY population, the age distribution was significantly different from that of the US population (P<.001). Compared with the US population, FNY had a greater proportion of individuals with HDI >5.0, signaling that the FNY user distribution was more affluent and educated than the US population baseline. We found that high-participation use (ie, higher participation in follow-up symptom reports) was associated with sex (females were 25% less likely than men to be high-participation users), higher HDI, not reporting an influenza-like illness at the first symptom report, older age, and reporting for household members (all differences between high- and low-participation users P<.001). Approximately 10% of FNY users completed an additional survey at the end of the flu season that assessed detailed user characteristics (3217/33,324 in 2015; 4850/44,313 in 2016). Of these users, most identified as being either retired or employed in the health, education, and social services sectors and indicated that they achieved a bachelor’s degree or higher. Conclusions: The representativeness of the FNY population and characteristics of its high-participation users are consistent with what has been observed in other Internet-based influenza surveillance systems. With targeted recruitment of underrepresented populations, FNY may improve as a complementary system to timely tracking of flu activity, especially in populations that do not seek medical attention and in areas with poor official surveillance data.

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  • Classification of Twitter users who tweet about e-cigarettes

    Date Submitted: May 17, 2017

    Open Peer Review Period: May 17, 2017 - May 31, 2017

    Background: Despite concerns about their health risks, e cigarettes have gained in popularity in recent years. Concurrent with recent increases in e-cigarette use, social media sites like Twitter have...

    Background: Despite concerns about their health risks, e cigarettes have gained in popularity in recent years. Concurrent with recent increases in e-cigarette use, social media sites like Twitter have become a common platform for sharing information about and marketing of e-cigarettes. Monitoring trends in e-cigarette–related social media activity requires timely assessment of the content of posts and the types of users generating the content. However, little is known about the diversity of user types responsible for e-cigarette–related content on Twitter. Objective: The aim of this study was to demonstrate a novel methodology for automatically classifying Twitter users who tweet about e-cigarette–related topics into distinct categories of users. Methods: We collected approximately 11.5 million e-cigarette–related tweets posted between November 2014 and October 2016, and obtained a random sample of Twitter handles that have tweeted about e-cigarettes. Trained human coders examined the handles’ profiles and manually categorized each as one of the following user types: (1) individual (N = 2,168), (2) vaper enthusiast (N = 334), (3) informed agency (N = 622), (4) marketer (N = 752), and (5) spammer (N =1,021). Next, we gathered Twitter metadata and a sample of tweets for each labeled user and created features that reflect users’ metadata and tweeting behavior. Finally, we tested multiple machine learning algorithms to identify a model with the best performance in classifying user types. Results: Using a classification model that included metadata and tweeting behavior features, we were able to predict with relatively high accuracy five different types of Twitter users that tweet about e cigarettes (average F1 score = 83.5%). Accuracy varied by user type, with F1 scores ranging among individuals (91.7%), informed agencies (84.3%), marketers (80.9%), spammers (80.5%), and vaper enthusiasts (44.1%). Including additional tweet-derived features that capture tweeting behavior significantly improves the model performance—an overall F1 score gain of 11.2%—beyond metadata features alone. Conclusions: This study provides a method for classifying five different types of users who tweet about e-cigarettes. Our model achieved high levels of classification performance for most groups, and examining tweeting behavior was critical in improving the model performance. Results can help identify groups engaged in conversations about e-cigarettes online to help inform public health surveillance, education, and regulatory efforts.

  • HIV Surveillance of Key Populations: Opportunities for Enhanced Strategic Use of Surveys, Health Records, and Program Data

    Date Submitted: May 14, 2017

    Open Peer Review Period: May 15, 2017 - May 29, 2017

    Background: The UNAIDS 90-90-90 targets pose a new challenge for HIV surveillance among key populations and offer new opportunities for better alignment of surveillance, program monitoring and evaluat...

    Background: The UNAIDS 90-90-90 targets pose a new challenge for HIV surveillance among key populations and offer new opportunities for better alignment of surveillance, program monitoring and evaluation. Objective: To describe current objectives and challenges of the enhanced strategic information mandate as applied to key populations, provide an historical perspective, and identify future opportunities to better align and enhance the use of survey, health sector and program data to describe the epidemic among key populations and measure programmatic response Methods: Literature review and expert consultation. Results: Currently surveillance indicators rely primarily on data from independent special surveys of key populations that often are not well aligned with local programming needs, however, improvements in the quality and completeness of routinely collected health and program data could reduce dependence on independent and costly surveys. Conclusions: Current reliance on standard national and key-population specific surveys is still necessary until the quality and completeness of program and health record data for key populations is better established.

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