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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.


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 2016: 5.175). 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:

  • The SIEMA Workflow Diagram with "Brass Head Bug" by Kenny Hays. Source: Image created by the Authors; Copyright: Arash Shaban-Nejad; URL:; License: Creative Commons Attribution (CC-BY).

    A Surveillance Infrastructure for Malaria Analytics: Provisioning Data Access and Preservation of Interoperability


    Background: According to the World Health Organization, malaria surveillance is weakest in countries and regions with the highest malaria burden. A core obstacle is that the data required to perform malaria surveillance are fragmented in multiple data silos distributed across geographic regions. Furthermore, consistent integrated malaria data sources are few, and a low degree of interoperability exists between them. As a result, it is difficult to identify disease trends and to plan for effective interventions. Objective: We propose the Semantics, Interoperability, and Evolution for Malaria Analytics (SIEMA) platform for use in malaria surveillance based on semantic data federation. Using this approach, it is possible to access distributed data, extend and preserve interoperability between multiple dynamic distributed malaria sources, and facilitate detection of system changes that can interrupt mission-critical global surveillance activities. Methods: We used Semantic Automated Discovery and Integration (SADI) Semantic Web Services to enable data access and improve interoperability, and the graphical user interface-enabled semantic query engine HYDRA to implement the target queries typical of malaria programs. We implemented a custom algorithm to detect changes to community-developed terminologies, data sources, and services that are core to SIEMA. This algorithm reports to a dashboard. Valet SADI is used to mitigate the impact of changes by rebuilding affected services. Results: We developed a prototype surveillance and change management platform from a combination of third-party tools, community-developed terminologies, and custom algorithms. We illustrated a methodology and core infrastructure to facilitate interoperable access to distributed data sources using SADI Semantic Web services. This degree of access makes it possible to implement complex queries needed by our user community with minimal technical skill. We implemented a dashboard that reports on terminology changes that can render the services inactive, jeopardizing system interoperability. Using this information, end users can control and reactively rebuild services to preserve interoperability and minimize service downtime. Conclusions: We introduce a framework suitable for use in malaria surveillance that supports the creation of flexible surveillance queries across distributed data resources. The platform provides interoperable access to target data sources, is domain agnostic, and with updates to core terminological resources is readily transferable to other surveillance activities. A dashboard enables users to review changes to the infrastructure and invoke system updates. The platform significantly extends the range of functionalities offered by malaria information systems, beyond the state-of-the-art.

  • Source: Pixnio; Copyright: Pixnio; URL:; License: Public Domain (CC0).

    Identifying Methods for Monitoring Foodborne Illness: Review of Existing Public Health Surveillance Techniques


    Background: Traditional methods of monitoring foodborne illness are associated with problems of untimeliness and underreporting. In recent years, alternative data sources such as social media data have been used to monitor the incidence of disease in the population (infodemiology and infoveillance). These data sources prove timelier than traditional general practitioner data, they can help to fill the gaps in the reporting process, and they often include additional metadata that is useful for supplementary research. Objective: The aim of the study was to identify and formally analyze research papers using consumer-generated data, such as social media data or restaurant reviews, to quantify a disease or public health ailment. Studies of this nature are scarce within the food safety domain, therefore identification and understanding of transferrable methods in other health-related fields are of particular interest. Methods: Structured scoping methods were used to identify and analyze primary research papers using consumer-generated data for disease or public health surveillance. The title, abstract, and keyword fields of 5 databases were searched using predetermined search terms. A total of 5239 papers matched the search criteria, of which 145 were taken to full-text review—62 papers were deemed relevant and were subjected to data characterization and thematic analysis. Results: The majority of studies (40/62, 65%) focused on the surveillance of influenza-like illness. Only 10 studies (16%) used consumer-generated data to monitor outbreaks of foodborne illness. Twitter data (58/62, 94%) and Yelp reviews (3/62, 5%) were the most commonly used data sources. Studies reporting high correlations against baseline statistics used advanced statistical and computational approaches to calculate the incidence of disease. These include classification and regression approaches, clustering approaches, and lexicon-based approaches. Although they are computationally intensive due to the requirement of training data, studies using classification approaches reported the best performance. Conclusions: By analyzing studies in digital epidemiology, computer science, and public health, this paper has identified and analyzed methods of disease monitoring that can be transferred to foodborne disease surveillance. These methods fall into 4 main categories: basic approach, classification and regression, clustering approaches, and lexicon-based approaches. Although studies using a basic approach to calculate disease incidence generally report good performance against baseline measures, they are sensitive to chatter generated by media reports. More computationally advanced approaches are required to filter spurious messages and protect predictive systems against false alarms. Research using consumer-generated data for monitoring influenza-like illness is expansive; however, research regarding the use of restaurant reviews and social media data in the context of food safety is limited. Considering the advantages reported in this review, methods using consumer-generated data for foodborne disease surveillance warrant further investment.

  • Source: Pixabay; Copyright: StockSnap; URL:; License: Public Domain (CC0).

    Junk Food Marketing on Instagram: Content Analysis


    Background: Omnipresent marketing of processed foods is a key driver of dietary choices and brand loyalty. Market data indicate a shift in food marketing expenditures to digital media, including social media. These platforms have greater potential to influence young people, given their unique peer-to-peer transmission and youths’ susceptibility to social pressures. Objective: The aim of this study was to investigate the frequency of images and videos posted by the most popular, energy-dense, nutrient-poor food and beverage brands on Instagram and the marketing strategies used in these images, including any healthy choice claims. Methods: A content analysis of 15 accounts was conducted, using 12 months of Instagram posts from March 15, 2015, to March 15, 2016. A pre-established hierarchical coding guide was used to identify the primary marketing strategy of each post. Results: Each brand used 6 to 11 different marketing strategies in their Instagram accounts; however, they often adhered to an overall theme such as athleticism or relatable consumers. There was a high level of branding, although not necessarily product information on all accounts, and there were very few health claims. Conclusions: Brands are using social media platforms such as Instagram to market their products to a growing number of consumers, using a high frequency of targeted and curated posts that manipulate consumer emotions rather than present information about their products. Policy action is needed that better reflects the current media environment. Public health bodies also need to engage with emerging media platforms and develop compelling social counter-marketing campaigns.

  • Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution + ShareAlike (CC-BY-SA).

    Accurately Inferring Compliance to Five Major Food Guidelines Through Simplified Surveys: Applying Data Mining to the UK National Diet and Nutrition Survey


    Background: National surveys in public health nutrition commonly record the weight of every food consumed by an individual. However, if the goal is to identify whether individuals are in compliance with the 5 main national nutritional guidelines (sodium, saturated fats, sugars, fruit and vegetables, and fats), much less information may be needed. A previous study showed that tracking only 2.89% of all foods (113/3911) was sufficient to accurately identify compliance. Further reducing the data needs could lower participation burden, thus decreasing the costs for monitoring national compliance with key guidelines. Objective: This study aimed to assess whether national public health nutrition surveys can be further simplified by only recording whether a food was consumed, rather than having to weigh it. Methods: Our dataset came from a generalized sample of inhabitants in the United Kingdom, more specifically from the National Diet and Nutrition Survey 2008-2012. After simplifying food consumptions to a binary value (1 if an individual consumed a food and 0 otherwise), we built and optimized decision trees to find whether the foods could accurately predict compliance with the major 5 nutritional guidelines. Results: When using decision trees of a similar size to previous studies (ie, involving as many foods), we were able to correctly infer compliance for the 5 guidelines with an average accuracy of 80.1%. This is an average increase of 2.5 percentage points over a previous study, showing that further simplifying the surveys can actually yield more robust estimates. When we allowed the new decision trees to use slightly more foods than in previous studies, we were able to optimize the performance with an average increase of 3.1 percentage points. Conclusions: Although one may expect a further simplification of surveys to decrease accuracy, our study found that public health dietary surveys can be simplified (from accurately weighing items to simply checking whether they were consumed) while improving accuracy. One possibility is that the simplification reduced noise and made it easier for patterns to emerge. Using simplified surveys will allow to monitor public health nutrition in a more cost-effective manner and possibly decrease the number of errors as participation burden is reduced.

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

    New Tobacco and Tobacco-Related Products: Early Detection of Product Development, Marketing Strategies, and Consumer Interest


    Background: A wide variety of new tobacco and tobacco-related products have emerged on the market in recent years. Objective: To understand their potential implications for public health and to guide tobacco control efforts, we have used an infoveillance approach to identify new tobacco and tobacco-related products. Methods: Our search for tobacco(-related) products consists of several tailored search profiles using combinations of keywords such as “e-cigarette” and “new” to extract information from almost 9000 preselected sources such as websites of online shops, tobacco manufacturers, and news sites. Results: Developments in e-cigarette design characteristics show a trend toward customization by possibilities to adjust temperature and airflow, and by the large variety of flavors of e-liquids. Additionally, more e-cigarettes are equipped with personalized accessories, such as mobile phones, applications, and Bluetooth. Waterpipe products follow the trend toward electronic vaping. Various heat-not-burn products were reintroduced to the market. Conclusions: Our search for tobacco(-related) products was specific and timely, though advances in product development require ongoing optimization of the search strategy. Our results show a trend toward products resembling tobacco cigarettes vaporizers that can be adapted to the consumers’ needs. Our search for tobacco(-related) products could aid in the assessment of the likelihood of new products to gain market share, as a possible health risk or as an indicator for the need on independent and reliable information of the product to the general public.

  • Source:; Copyright: US Navy (Marie Montez); URL:; License: Public Domain (CC0).

    Opportunities for Enhanced Strategic Use of Surveys, Medical Records, and Program Data for HIV Surveillance of Key Populations: Scoping Review


    Background: Normative guidelines from the World Health Organization recommend tracking strategic information indicators among key populations. Monitoring progress in the global response to the HIV epidemic uses indicators put forward by the Joint United Nations Programme on HIV/AIDS. These include the 90-90-90 targets that require a realignment of surveillance data, routinely collected program data, and medical record data, which historically have developed separately. Objective: The aim of this study was to describe current challenges for monitoring HIV-related strategic information indicators among key populations ((men who have sex with men [MSM], people in prisons and other closed settings, people who inject drugs, sex workers, and transgender people) and identify future opportunities to enhance the use of surveillance data, programmatic data, and medical record data to describe the HIV epidemic among key populations and measure the coverage of HIV prevention, care, and treatment programs. Methods: To provide a historical perspective, we completed a scoping review of the expansion of HIV surveillance among key populations over the past three decades. To describe current efforts, we conducted a review of the literature to identify published examples of SI indicator estimates among key populations. To describe anticipated challenges and future opportunities to improve measurement of strategic information indicators, particularly from routine program and health data, we consulted participants of the Third Global HIV Surveillance Meeting in Bangkok, where the 2015 World Health Organization strategic information guidelines were launched. Results: There remains suboptimal alignment of surveillance and programmatic data, as well as routinely collected medical records to facilitate the reporting of the 90-90-90 indicators for HIV among key populations. Studies (n=3) with estimates of all three 90-90-90 indicators rely on cross-sectional survey data. Programmatic data and medical record data continue to be insufficiently robust to provide estimates of the 90-90-90 targets for key populations. Conclusions: Current reliance on more active data collection processes, including key population-specific surveys, remains warranted until the quality and validity of passively collected routine program and medical record data for key populations is optimized.

  • HIV-prevention seminar with Sub Saharan African migrants in Spain (2007). Source: Image created by the authors; Copyright: The authors; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).

    Overcoming Barriers to HIV Prevention and Healthcare Among Sub-Saharan African Migrants in Spain


  • Source: Nellis Air Force Base (Jake Carter); Copyright: US Air Force; URL:; License: Public Domain (CC0).

    Causality Patterns for Detecting Adverse Drug Reactions From Social Media: Text Mining Approach


    Background: Detecting adverse drug reactions (ADRs) is an important task that has direct implications for the use of that drug. If we can detect previously unknown ADRs as quickly as possible, then this information can be provided to the regulators, pharmaceutical companies, and health care organizations, thereby potentially reducing drug-related morbidity and saving lives of many patients. A promising approach for detecting ADRs is to use social media platforms such as Twitter and Facebook. A high level of correlation between a drug name and an event may be an indication of a potential adverse reaction associated with that drug. Although numerous association measures have been proposed by the signal detection community for identifying ADRs, these measures are limited in that they detect correlations but often ignore causality. Objective: This study aimed to propose a causality measure that can detect an adverse reaction that is caused by a drug rather than merely being a correlated signal. Methods: To the best of our knowledge, this was the first causality-sensitive approach for detecting ADRs from social media. Specifically, the relationship between a drug and an event was represented using a set of automatically extracted lexical patterns. We then learned the weights for the extracted lexical patterns that indicate their reliability for expressing an adverse reaction of a given drug. Results: Our proposed method obtains an ADR detection accuracy of 74% on a large-scale manually annotated dataset of tweets, covering a standard set of drugs and adverse reactions. Conclusions: By using lexical patterns, we can accurately detect the causality between drugs and adverse reaction–related events.

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

    The Acceptability and Feasibility of Implementing a Bio-Behavioral Enhanced Surveillance Tool for Sexually Transmitted Infections in England: Mixed-Methods...


    Background: Sexually transmitted infection (STI) surveillance is vital for tracking the scale and pattern of epidemics; however, it often lacks data on the underlying drivers of STIs. Objective: This study aimed to assess the acceptability and feasibility of implementing a bio-behavioral enhanced surveillance tool, comprising a self-administered Web-based survey among sexual health clinic attendees, as well as linking this to their electronic health records (EHR) held in England’s national STI surveillance system. Methods: Staff from 19 purposively selected sexual health clinics across England and men who have sex with men and black Caribbeans, because of high STI burden among these groups, were interviewed to assess the acceptability of the proposed bio-behavioral enhanced surveillance tool. Subsequently, sexual health clinic staff invited all attendees to complete a Web-based survey on drivers of STI risk using a study tablet or participants’ own digital device. They recorded the number of attendees invited and participants’ clinic numbers, which were used to link survey data to the EHR. Participants’ online consent was obtained, separately for survey participation and linkage. In postimplementation phase, sexual health clinic staff were reinterviewed to assess the feasibility of implementing the bio-behavioral enhanced surveillance tool. Acceptability and feasibility of implementing the bio-behavioral enhanced surveillance tool were assessed by analyzing these qualitative and quantitative data. Results: Prior to implementation of the bio-behavioral enhanced surveillance tool, sexual health clinic staff and attendees emphasized the importance of free internet/Wi-Fi access, confidentiality, and anonymity for increasing the acceptability of the bio-behavioral enhanced surveillance tool among attendees. Implementation of the bio-behavioral enhanced surveillance tool across sexual health clinics varied considerably and was influenced by sexual health clinics’ culture of prioritization of research and innovation and availability of resources for implementing the surveys. Of the 7367 attendees invited, 85.28% (6283) agreed to participate. Of these, 72.97% (4585/6283) consented to participate in the survey, and 70.62% (4437/6283) were eligible and completed it. Of these, 91.19% (4046/4437) consented to EHR linkage, which did not differ by age or gender but was higher among gay/bisexual men than heterosexual men (95.50%, 722/756 vs 88.31%, 1073/1215; P<.003) and lower among black Caribbeans than white participants (87.25%, 568/651 vs 93.89%, 2181/2323; P<.002). Linkage was achieved for 88.88% (3596/4046) of consenting participants. Conclusions: Implementing a bio-behavioral enhanced surveillance tool in sexual health clinics was feasible and acceptable to staff and groups at STI risk; however, ensuring participants’ confidentiality and anonymity and availability of resources is vital. Bio-behavioral enhanced surveillance tools could enable timely collection of detailed behavioral data for effective commissioning of sexual health services.

  • Source: Wikimedia Commons; Copyright: Holland Kati; URL:; License: Creative Commons Attribution + ShareAlike (CC-BY-SA).

    Trends in HIV Terminology: Text Mining and Data Visualization Assessment of International AIDS Conference Abstracts Over 25 Years


    Background: The language encompassing health conditions can also influence behaviors that affect health outcomes. Few published quantitative studies have been conducted that evaluate HIV-related terminology changes over time. To expand this research, this study included an analysis of a dataset of abstracts presented at the International AIDS Conference (IAC) from 1989 to 2014. These abstracts reflect the global response to HIV over 25 years. Two powerful methodologies were used to evaluate the dataset: text mining to convert the unstructured information into structured data for analysis and data visualization to represent the data visually to assess trends. Objective: The purpose of this project was to evaluate the evolving use of HIV-related language in abstracts presented at the IAC from 1989 to 2014. Methods: Over 80,000 abstracts were obtained from the International AIDS Society and imported into a Microsoft SQL Server database for data processing and text mining analyses. A text mining module within the KNIME Analytics Platform, an open source software, was then used to mine the partially processed data to create a terminology corpus of key HIV terms. Subject matter experts grouped the terms into categories. Tableau, a data visualization software, was used to visualize the frequency metrics associated with the terms as line graphs and word clouds. The visualized dashboards were reviewed to discern changes in terminology use across IAC years. Results: The major findings identify trends in HIV-related terminology over 25 years. The term “AIDS epidemic” was dominantly used from 1989 to 1991 and then declined in use. In contrast, use of the term “HIV epidemic” increased through 2014. Beginning in the mid-1990s, the term “treatment experienced” appeared with increasing frequency in the abstracts. Use of terms identifying individuals as “carriers or victims” of HIV rarely appeared after 2008. Use of the terms “HIV positive” and “HIV infected” peaked in the early-1990s and then declined in use. The terms “men who have sex with men” and “MSM” were rarely used until 1994; subsequently, use of these terms increased through 2014. The term “sex worker” steadily increased in frequency throughout conference years, whereas the term “prostitute” decreased over time. Conclusions: The results of this study highlight changes in HIV terminology use over 25 years, including the addition, disappearance, and changing use of terms that reflect advances in HIV research and medical practice and destigmatization of the disease. Coupled with findings from related quantitative research, HIV-related terminology recommendations based on results of this study are included. Adoption of these recommendations will further efforts to use less stigmatizing language and facilitate effective communication between health professionals and people affected by HIV.

  • Untitled. Source: Wikicommons; Copyright: Victor Grigas; URL:; License: Creative Commons Attribution + ShareAlike (CC-BY-SA).

    Recommendations for the Development of a Mobile HIV Prevention Intervention for Men Who Have Sex With Men and Hijras in Mumbai: Qualitative Study


    Background: As Internet and mobile phone use expands in India, there is an opportunity to develop mobile health (mHealth) interventions for marginalized populations, including men who have sex with men (MSM) and hijras (transgender women), hesitant to access traditional health care systems. Objective: The purpose of this study was to determine if an mHealth intervention was acceptable to MSM and hijras living in Mumbai, and if so, what features would be useful in targeting the prevention of HIV acquisition and to increase the quality of life among persons living with HIV/AIDS. Methods: Data from 4 focus groups with MSM and interviews with 4 hijras, 10 health service providers, and 8 mHealth developers were thematically analyzed. Results: Once the need for an mHealth intervention was confirmed, comments about features were organized into 3 themes: content, interface, and retention. Content subthemes included providing sex education for younger community members, providing information about STIs, and providing information and social support for persons living with HIV. Interface subthemes included presenting content using pictures; using videos to present stories of role models; using push notifications for testing, appointment, and medication reminders; using geolocation to link to just-in-time services; and using telemedicine to increase access to health service providers and community services. The 5 retention subthemes included keeping it fun, using gaming mechanics, developing content in regional languages, protecting confidentiality, and linking to social networking apps. Conclusions: These findings may help inform mHealth development in India.

  • The visualized female breast cancer survival proportions by senatorial district in Missouri. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Licensed by JMIR.

    Improving Visualization of Female Breast Cancer Survival Estimates: Analysis Using Interactive Mapping Reports


    Background: The Missouri Cancer Registry collects population-based cancer incidence data on Missouri residents diagnosed with reportable malignant neoplasms. The Missouri Cancer Registry wanted to produce data that would be of interest to lawmakers as well as public health officials at the legislative district level on breast cancer, the most common non-skin cancer among females. Objective: The aim was to measure and interactively visualize survival data of female breast cancer cases in the Missouri Cancer Registry. Methods: Female breast cancer data were linked to Missouri death records and the Social Security Death Index. Unlinked female breast cancer cases were crossmatched to the National Death Index. Female breast cancer cases in subcounty senate districts were geocoded using TIGER/Line shapefiles to identify their district. A database was created and analyzed in SEER*Stat. Senatorial district maps were created using US Census Bureau’s cartographic boundary files. The results were loaded with the cartographic data into InstantAtlas software to produce interactive mapping reports. Results: Female breast cancer survival profiles of 5-year cause-specific survival percentages and 95% confidence intervals, displayed in tables and interactive maps, were created for all 34 senatorial districts. The maps visualized survival data by age, race, stage, and grade at diagnosis for the period from 2004 through 2010. Conclusions: Linking cancer registry data to the National Death Index database improved accuracy of female breast cancer survival data in Missouri and this could positively impact cancer research and policy. The created survival mapping report could be very informative and usable by public health professionals, policy makers, at-risk women, and the public.

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  • Developing a Data Dashboard for Population Health Surveillance: Widening Access to Clinical Trial Findings

    Date Submitted: Jun 19, 2018

    Open Peer Review Period: Jun 20, 2018 - Jul 4, 2018

    Background: Demographic surveillance platforms play a vital role in assessing the effects that disease has on a population, and the resulting impact of subsequent healthcare interventions. Population...

    Background: Demographic surveillance platforms play a vital role in assessing the effects that disease has on a population, and the resulting impact of subsequent healthcare interventions. Population surveillance sites generate many datasets relevant to disease surveillance, however there is a risk that this data is under-utilised, misunderstood or not acted on in a timely manner due to the volume of data captured. Data visualisation offers stakeholders a means to quickly understand and interpret collected data. Objective: This paper describes the development and evaluation of dashboard to visualise trial to staff and researchers at a demographic surveillance site and investigate the role that visualisation could play increasing the visibility and understanding of datasets produced therein. Methods: This paper presents the development of a dashboard for visualising data generated within, a demographic surveillance platform at the Africa Health Research Institute (AHRI), in KwaZulu-Natal., South Africa. An evaluation study was undertaken to assess the effectiveness of the dashboards as a data dissemination tool. A mixed-methods approach combined benchmark task evaluation to assess usability with a questionnaire to study attitudes to the use of dashboards. The evaluation was recruited 20 participants drawn from scientific, operational nursing and community advisory staff working at AHRI. Results: The results of the questionnaire showed that the majority of respondents felt that the dashboards provided a clear understanding of the results of the trial presented and would like to see the use of dashboards within the research centre to disseminate results. The evaluation demonstrated high usability for the dashboard across the study groups with scientific and operational staff having minimal issues in completing the tasks outlined. There were notable differences in the efficiency of task completion among different groups of respondents, indicating varying familiarity with data visualisation interfaces. Conclusions: The paper has demonstrated the viability of data visualisation dashboards as a means of increasing the visibility and access to datasets at a population surveillance site. The usability differences between the different groups demonstrates the need for user-led design of dashboards in future, addressing varying computer and visualisation literacy’s present among user groups.

  • The Annual American Men's Internet Survey of Behaviors of Men Who have Sex with Men in the United States: 2016 Key Indicators Report

    Date Submitted: Jun 16, 2018

    Open Peer Review Period: Jun 19, 2018 - Jul 3, 2018

    The American Men’s Internet Survey (AMIS) is an annual Web-based behavioral survey of men who have sex with men (MSM) living in the United States. This Rapid Surveillance Report describes the fourth...

    The American Men’s Internet Survey (AMIS) is an annual Web-based behavioral survey of men who have sex with men (MSM) living in the United States. This Rapid Surveillance Report describes the fourth cycle of data collection (September 2016 through February 2017; AMIS-2016). The key indicators are the same as previously reported for AMIS (December 2013 through May 2014, AMIS-2013; November 2014 through April 2015, AMIS-2014; September 2015 through April 2016; AMIS-2015). The AMIS survey methodology has not substantively changed since AMIS-2015. MSM were recruited from a variety of websites using banner advertisements and email blasts. Additionally, participants from AMIS-2015 who agreed to be recontacted for future research were emailed a link to the AMIS-2016 survey. Men were eligible to participate if they were 15 years old and over, resided in the United States, provided a valid US ZIP code and reported ever having sex with a man or identified as gay or bisexual. We examined demographic and recruitment characteristics using multivariable regression modeling (P<.05) stratified by participants’ self-reported human immunodeficiency virus (HIV) status. The AMIS-2016 round of data collection resulted in 10,166 completed surveys from MSM representing every US state, Puerto Rico, Guam and the US Virgin Islands. Participants were mainly non-Hispanic white, over the age of 40, living in the US South, living in urban areas and recruited from general social networking websites. Self-reported HIV prevalence was 10.80% (1098/10,166). Compared to HIV-negative/unknown status participants, HIV-positive participants were more likely to have had anal sex without a condom with any male partner in the past 12 months (75.77% vs 65.88%, P<.001) and more likely to have had anal sex without a condom with a serodiscordant or unknown status partner (33.24% vs 16.06%, P<.001). The reported use of marijuana and other illicit substances in the past 12 months was higher among HIV-positive participants than HIV-negative/unknown status participants (28.05% vs 24.99% and 28.14% vs 18.46%, respectively; both P<.001). Most (79.93%, 7248/9068) HIV-negative/unknown status participants reported ever having a previous HIV test, and 56.45% (5119/9068) reported HIV testing in the past 12 months. HIV-positive participants were more likely to report sexually transmitted infection (STI) testing and diagnosis compared to HIV-negative/unknown status participants (70.86% vs 40.13% and 24.04% vs 8.97%, respectively; both P<.001).

  • A Matter of Both Quality and Quantity: A Technical Framework for Health Promotion and Intervention Research in the Social Media Era

    Date Submitted: Jun 15, 2018

    Open Peer Review Period: Jun 16, 2018 - Jun 25, 2018

    Background: Social media (SM) offers promise for communicating the risks and health effects of harmful products and behaviors, and thus for modifying health knowledge, attitudes and behavior. Nearly...

    Background: Social media (SM) offers promise for communicating the risks and health effects of harmful products and behaviors, and thus for modifying health knowledge, attitudes and behavior. Nearly 70% of U.S. adults use some type of SM, which varies by factors such as age, gender, and race/ethnicity. Rigorous research across different SM types is vital to establish successful, evidence-based health communication strategies that meet the requirements of the evolving SM landscape and the needs of diverse populations. Objective: To develop and test the functional correctness of a software tool that automates aspects of production, distribution and assessment of SM messages to assess their influence on user engagement. Methods: The software tool enables six functions: (1) data import; (2) message generation deploying randomization techniques; (3) message distribution across SM; (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 application was built using three 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 two government-sponsored online tobacco 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 automatically generated SM messages: 100% correctness was defined as use of the message template text and substitution of three message parameters (i.e., image, hashtag, destination URL) without any error. Percent correct was calculated to determine the probability with which the tool generates accurate messages. Results: The tool generated, distributed and assessed 1,275 SM messages over the course of 85 days (April 19 to July 12, 2017). It correctly used the message template text and substituted the message parameters 100% 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 production, distribution, and assessment of hundreds of health promotion messages across different SM types with the highest degree of functional correctness and minimal human interaction. The tool has the potential to influence SM-driven health promotion research and practice: first, by enabling the assessment of large numbers of messages to develop evidence-based health communication approaches; and second, by providing public health groups with a technical framework to increase the output of health education messages to potentially counteract the growing prevalence of online marketing featuring products and behaviors harmful to health, e.g., tobacco products. We call on readers to use and further develop the software code and to contribute to evidence-based communication methods in the digital age.

  • Kuantim mi tu (‘Count me too’): using multiple methods to estimate the number of female sex workers, men who have sex with men and transgender women in Papua New Guinea in 2016 and 2017.

    Date Submitted: Jun 13, 2018

    Open Peer Review Period: Jun 15, 2018 - Jun 29, 2018

    Background: Female sex workers (FSW), men who have sex with men (MSM), and transgender women (TGW) are at high risk of acquiring HIV in many settings, such as Papua New Guinea (PNG). An understanding...

    Background: Female sex workers (FSW), men who have sex with men (MSM), and transgender women (TGW) are at high risk of acquiring HIV in many settings, such as Papua New Guinea (PNG). An understanding of the approximate size of these populations can inform resource allocation for HIV services for FSW, MSM, and TGW. Objective: An objective of this multi-site survey was to conduct updated population size estimations (PSE) of FSW and MSM/TGW. Methods: Respondent-driven sampling (RDS) biobehavioral surveys of FSW and MSM/TGW were conducted in three major cities: 1) Port Moresby, 2) Lae, and 3) Mt. Hagen between June 2016 and December 2017. Eligibility criteria for FSW included: age >=12 years, born female, could speak English or Tok Pisin (PNG Pidgin), and had sold or exchanged sex with a man in the past six months. Eligibility for MSM/TGW included: age >=12 years, born male, could speak English or Tok Pisin, and had engaged in oral or anal sex with another person born male in the past six months. PSE methods included unique object multiplier, service multiplier, and successive sampling using imputed visibility. Weighted data analyses were conducted using RDS-Analyst (v. 0.62) and Microsoft Excel (2016). Results: Sample sizes for FSW and MSM/TGW in Port Moresby, Lae, and Mt. Hagen included: 1) 673 and 400; 2) 709 and 352; and 3) 709 and 111 respectively. Keychains were used for the unique object multiplier method and were distributed one week prior to the start of each RDS survey. HIV service testing data were only available in Port Moresby and Mt. Hagen and successive sampling estimates were calculated for all cities. Due to limited service provider data and uncertain prior size estimation knowledge, unique object multiplier weighted estimations were chosen for estimates. In Port Moresby, we estimate that there are 16,053 (95% CI: 8,232-23,874) FSW and 7,487 (95% CI: 3,975-11,000) MSM/TGW. In Lae, we estimate that there are 6,105 (95% CI: 4,459-7,752) FSW and 4,669 (95% CI: 3,068-6,271) MSM/TGW. In Mt. Hagen, we estimate that there are 2,646 (95% CI: 1,655-3,638) FSW and 1,095 (95% CI: 913-1151) MSM/TGW using service multiplier and successive sampling, respectively. Conclusions: As the HIV epidemic in PNG rapidly evolves among KP, PSE should be repeated in order to produce up-to-date estimates for timely comparison and eventual trend analysis.

  • Programmatic mapping of key populations to estimate size, distribution and dynamics to inform HIV prevention programs in Kosovo

    Date Submitted: May 31, 2018

    Open Peer Review Period: Jun 13, 2018 - Jun 27, 2018

    Background: The burden of HIV epidemic in Kosovo lies among the key populations (KPs) of FSWs, MSM and PWIDs. The available interventions for KPs are fragmented, lack sufficient and appropriate granul...

    Background: The burden of HIV epidemic in Kosovo lies among the key populations (KPs) of FSWs, MSM and PWIDs. The available interventions for KPs are fragmented, lack sufficient and appropriate granularity of information needed to develop large scale outreach programs. Objective: We conducted this study to estimate the size and distribution of these populations to create evidence for developing action plans for HIV prevention. Methods: Programmatic mapping approach was used to collect systematic information from key informants including geographic and virtual locations in 26 municipalities of Kosovo. In Level 1, information was gathered about KPs numbers and locations through 1,537 key informant interviews within each municipality. Level 2 involved validating these spots by conducting another 976 interviews with KPs congregating at those spots. Population size estimates were calculated for each spot, and finally a National estimate was developed which was corrected for duplication and overlaps. Results: Of the estimated 6,814 MSM (6,445 to 7,117), nearly 4,940 operate through the internet owing to the large stigma and discrimination against same sex relationships. Geo-based MSM congregate at a few spots having large spot sizes (13.3 MSM/spot). Three-fourth of the MSM are distributed in five major municipalities. Fridays and Saturdays are the peak days of operation, however the number only increase by 5%. A significant number are involved in sex work i.e., provide sex to other men for money. PWID are largely geo-based; 4,973 (range; 3,932 to 6,015) PWID of the total number of 5,819 (range; 4,777 to 6,860) visit geographical spots with an average spot size of 7.1. In smaller municipalities, they mostly inject in residential locations. The numbers stay stable during the entire week and there are no peak days. Of the 5,037 (range; 4,213 to 5,860) FSW, 20% use cell phones while 10% use websites to connect with clients. The number increase by 25% on weekends, especially in larger municipalities where sex work is mostly concentrated. Other than a few street based spots, most spots are establishments run by pimps, which is reflective of the highly institutionalized, structured and organized FSW network. Conclusions: This study provides valuable information about the population size estimates as well as dynamics of each KP, which is the key to developing effective HIV prevention strategies. The information needs to be used to micro-plan and design plans to contact and provide effective outreach using information on how each KP operates within each typology.

  • Adapting methods of key population programmatic mapping and enumeration to inform HIV prevention programs for adolescent girls and young women

    Date Submitted: May 31, 2018

    Open Peer Review Period: Jun 13, 2018 - Jun 27, 2018

    Background: Standard programmatic mapping involves identifying locations where key populations meet, profiling of these locations (hotspots) and estimating the key population size. Information gained...

    Background: Standard programmatic mapping involves identifying locations where key populations meet, profiling of these locations (hotspots) and estimating the key population size. Information gained from this method has been used for HIV programming – resource allocation, program planning, service delivery, and monitoring and evaluation – for people who inject drugs, men who has sex with men, and female sex workers (FSW). With an increasing focus on adolescent girls and young women (AGYW) as a priority population for HIV prevention, programs need to know where and how to effectively reach individuals that are at increased risk for HIV but were conventionally considered part of the general population. We hypothesize that AGYW who engage in transactional and casual sex also congregate at sex work hotspots to meet sex partners. Therefore, we adapted the standard programmatic mapping approach to understand the geographic distribution and population size of AGYW in Mombasa County, Kenya. Objective: The objectives are several-fold: (1) to detail and compare the modified programmatic mapping approach used in this study to the standard approach; (2) to estimate the number of young FSW; (3) to estimate the number of AGYW who congregate in sex work hotspots to meet sex partners other than clients; (4) to estimate the overlap in sexual network in hotspots; (5) to describe the distribution of sex work hotspots across Mombasa and its four sub-counties; and (6) to compare the distribution of hotspots that were known to the local HIV prevention program prior to this study and those newly identified. Methods: The standard programmatic mapping approach was modified to estimate the population of young women aged 14-24 years who visit sex work hotspots in Mombasa to meet partners for commercial, transactional and casual sex. Results: We estimated that there were 11,777 FSW (range 9,265-14,290) in Mombasa in 2014; among whom, 6,127 (52.0%) were 14-24 years old. The population estimate for women aged 14-24 years who engaged in transactional and casual sex and congregated at the hotspots were 5,348 (range 4,185-6,510) and 4,160 (range 3,194-5,125), respectively. Of the 1,025 validated sex work hotspots, 856 (83.5%) were locations also visited by women engaged in both transactional and casual sex. Only 48 (4.7%) hotspots were exclusive sex work locations. The geographic and typological distribution of hotspots were significantly different between the four sub-counties (P < .001). Of the 1,025 hotspots, 419 (40.9%) were already known to the local HIV prevention program and 606 (59.1%) were newly identified. Conclusions: Using the adapted programmatic mapping approach detailed in this study, our results show that HIV prevention programs tailored to AGYW can focus delivery of their interventions to traditional sex work hotspots to reach subgroups that may be at increased risk for HIV.