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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:

  • People at Denver Civic Center Park. Source: FlickR; Copyright: Xuilla; URL:; License: Creative Commons Attribution + ShareAlike (CC-BY-SA).

    Applying National Estimates of Adults With Indications for Pre-Exposure Prophylaxis to Populations of Men Who Have Sex With Men and People Who Inject Drugs...


    Background: Oral pre-exposure prophylaxis (PrEP) is a highly effective option for HIV prevention. To realize the full benefit of PrEP at the population level, uptake must reach those at the greatest risk of HIV acquisition. Guidance published by Centers for Disease Control and Prevention (CDC) suggests that the number of individuals with indications for PrEP is 1.1-1.2 million nationally based on survey data of key populations and local transmission patterns. We applied these estimates at state and county levels to determine the number of individuals who might benefit from PrEP locally and compared our estimates to CDC-published estimates for Colorado. Objective: This analysis aimed to produce estimates of key populations with indications for PrEP in Colorado as a whole and by county type. These estimates will be used for public health strategic planning for HIV prevention goals at the state and county jurisdictional levels. Methods: Colorado population estimates were obtained from the state demography office, which utilizes US decennial census data and input from county and local agencies to forecast the population. We limited our analysis to adults aged 18-59 years to be consistent with CDC methodology for PrEP estimates. We performed a literature review to define the best population-level percentages to determine numbers of HIV-negative men who have sex with men (MSM) and people who inject drugs (PWID) in Colorado. These percentages were applied to the state and to each county by its rural-urban designation. Finally, CDC-derived percentages of MSM and PWID with indications for PrEP were applied to these estimates to determine numbers of MSM and PWID who may benefit from PrEP use. Results: In 2017, 3,252,648 adults aged 18-59 years were living in Colorado. By applying published estimates of percentages of men who had sex with other men in the past 12 months, we determined that 41,353-49,624 adult males could be considered sexually active MSM. We estimated that 9758-13,011 adults aged 18-59 years were likely to have injected drugs in the past 12 months. By accounting for numbers of people living with HIV in those categories and applying the CDC PrEP percentages of MSM and PWID with indications for PrEP nationally, we estimated that 8792-12,528 MSM and PWID in Colorado had indications for PrEP; this number is smaller than that estimated by CDC, although within the lower CI limit. Conclusions: By employing a simple framework consisting of census data, literature review, population estimates, and national estimates for PrEP indicators, we derived estimates for potential PrEP use in our state. Statewide estimates of key populations by state and county type will enable health officials to set informed goals and track progress toward optimizing PrEP uptake. This formula may be applicable to other states with similar epidemics and resources. 

  • A method to identify the shortest period of measurement without significantly decreasing the prediction performance for a time-series analysis of disease counts (montage). Source: The Authors / Smartmockups; Copyright: JMIR Publications; URL:; License: Creative Commons Attribution (CC-BY).

    Period of Measurement in Time-Series Predictions of Disease Counts from 2007 to 2017 in Northern Nevada: Analytics Experiment


    Background: The literature in statistics presents methods by which autocorrelation can identify the best period of measurement to improve the performance of a time-series prediction. The period of measurement plays an important role in improving the performance of disease-count predictions. However, from the operational perspective in public health surveillance, there is a limitation to the length of the measurement period that can offer meaningful and valuable predictions. Objective: This study aimed to establish a method that identifies the shortest period of measurement without significantly decreasing the prediction performance for time-series analysis of disease counts. Methods: The data used in this evaluation include disease counts from 2007 to 2017 in northern Nevada. The disease counts for chlamydia, salmonella, respiratory syncytial virus, gonorrhea, viral meningitis, and influenza A were predicted. Results: Our results showed that autocorrelation could not guarantee the best performance for prediction of disease counts. However, the proposed method with the change-point analysis suggests a period of measurement that is operationally acceptable and performance that is not significantly different from the best prediction. Conclusions: The use of change-point analysis with autocorrelation provides the best and most practical period of measurement.

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

    Generating Engagement on the Make Healthy Normal Campaign Facebook Page: Analysis of Facebook Analytics


    Background: Facebook is increasingly being used as part of mass media campaigns in public health, including the Make Healthy Normal (MHN) campaign in New South Wales, Australia. Therefore, it is important to understand what role Facebook can play in mass media campaigns and how best to use it to augment or amplify campaign effects. However, few studies have explored this. Objective: This study aimed to investigate usage of and engagement with the MHN Facebook page and to identify influential factors in driving engagement with the page. Methods: We examined both post-level and page-level analytic data from Facebook from the campaign’s launch in June 2015 to September 2017. For post-level data, we conducted a series of negative binomial regressions with four different outcome measures (likes, shares, comments, post consumers), including some characteristics of Facebook posts as predictors. We also conducted time series analyses to examine associations between page-level outcomes (new page likes or “fans” and number of engaged users) and different measures of exposure to the page (number of unique users reached and total count of impressions) and to television advertising. Results: Of the 392 posts reviewed, 20.7% (n=81) received a paid boost and 58.9% (n=231) were photo posts. We found that posts that received a paid boost reached significantly more users and subsequently received significantly more engagement than organic (unpaid) posts (P<.001). After adjusting for reach, we found the effect of being paid was incremental for all outcome measures for photos and links, but not videos. There were also associations between day of the week and time of post and engagement, with Mondays generally receiving less engagement and posts on a Friday and those made between 8 AM and 5 PM receiving more. At the page level, our time series analyses found that organic impressions predicted a higher number of new fans and engaged users, compared to paid impressions, especially for women. We also found no association between television advertising and engagement with the Facebook page. Conclusions: Our study shows that paying for posts is important for increasing their reach, but that page administrators should look to maximize organic reach because it is associated with significantly higher engagement. Once reach is accounted for, video posts do not benefit from being paid, unlike the other post types. This suggests that page administrators should carefully consider how they use videos as part of a Facebook campaign. Additionally, the lack of association between television advertising and engagement suggests that future campaigns consider how best to link different channels to amplify effects. These results highlight the need for ongoing evaluation of Facebook pages if administrators are to maximize engagement.

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

    Real Time Influenza Monitoring Using Hospital Big Data in Combination with Machine Learning Methods: Comparison Study


    Background: Traditional surveillance systems produce estimates of influenza-like illness (ILI) incidence rates, but with 1- to 3-week delay. Accurate real-time monitoring systems for influenza outbreaks could be useful for making public health decisions. Several studies have investigated the possibility of using internet users’ activity data and different statistical models to predict influenza epidemics in near real time. However, very few studies have investigated hospital big data. Objective: Here, we compared internet and electronic health records (EHRs) data and different statistical models to identify the best approach (data type and statistical model) for ILI estimates in real time. Methods: We used Google data for internet data and the clinical data warehouse eHOP, which included all EHRs from Rennes University Hospital (France), for hospital data. We compared 3 statistical models—random forest, elastic net, and support vector machine (SVM). Results: For national ILI incidence rate, the best correlation was 0.98 and the mean squared error (MSE) was 866 obtained with hospital data and the SVM model. For the Brittany region, the best correlation was 0.923 and MSE was 2364 obtained with hospital data and the SVM model. Conclusions: We found that EHR data together with historical epidemiological information (French Sentinelles network) allowed for accurately predicting ILI incidence rates for the entire France as well as for the Brittany region and outperformed the internet data whatever was the statistical model used. Moreover, the performance of the two statistical models, elastic net and SVM, was comparable.

  • HIV/AIDS support group in rural Kenya. Source: Flickr; Copyright: khym54; URL:; License: Creative Commons Attribution (CC-BY).

    Approaches to Improve the Surveillance, Monitoring, and Management of Noncommunicable Diseases in HIV-Infected Persons: Viewpoint


    Low-income and middle-income countries (LMICs) are undergoing an epidemiological transition, in which the burden of noncommunicable diseases (NCDs) is rising and mortality will shift from infectious diseases to NCDs. Specifically, cardiovascular disease, diabetes, renal diseases, chronic respiratory diseases, and cancer are becoming more prevalent. In some regions, particularly sub-Saharan Africa, the dual HIV and NCD epidemics will pose challenges because their joint burden will have adverse effects on the quality of life and will likely increase global inequities. Given the austere clinical infrastructure in many LMICs, innovative models of care delivery are needed to provide comprehensive care in resource-limited settings. Improved data collection and surveillance of NCDs among HIV-infected persons in LMICs are necessary to inform integrated NCD-HIV prevention, care, and treatment models that are effective across a range of geographic settings. These efforts will preserve the considerable investments that have been made to prevent the number of lives lost to HIV, promote healthy aging of persons living with HIV, and contribute to meeting United Nations Sustainable Development Goals.

  • Adelante program participants. Source: Image created by the Authors; Copyright: George Washington University; URL:; License: Licensed by JMIR.

    Strategies to Increase Latino Immigrant Youth Engagement in Health Promotion Using Social Media: Mixed-Methods Study


    Background: Generating participant engagement in social media applications for health promotion and disease prevention efforts is vital for their effectiveness and increases the likelihood of effecting sustainable behavior change. However, there is limited evidence regarding effective strategies for engaging Latino immigrant youth using social media. As part of the Avance Center for the Advancement of Immigrant/Refugee Health in Washington, DC, USA, we implemented Adelante, a branded primary prevention program, to address risk factors for co-occurring substance use, sexual risk, and interpersonal violence among Latino immigrant adolescents aged 12 to 19 years in a Washington, DC suburb. Objective: The objectives of this study were to (1) characterize Adelante participant Facebook reach and engagement and (2) identify post content and features that resulted in greater user engagement. Methods: We established the Adelante Facebook fan page in October of 2013, and the Adelante social marketing campaign used this platform for campaign activities from September 2015 to September 2016. We used Facebook Insights metrics to examine reach and post engagement of Adelante Facebook page fans (n=743). Data consisted of Facebook fan page posts between October 1, 2013 and September 30, 2016 (n=871). We developed a 2-phased mixed-methods analytical plan and coding scheme, and explored the association between post content categories and features and a composite measure of post engagement using 1-way analysis of variance tests. P<.05 determined statistical significance. Results: Posts on the Adelante Facebook page had a total of 34,318 clicks, 473 comments, 9080 likes or reactions, and 617 shares. Post content categories that were statistically significantly associated with post engagement were Adelante program updates (P<.001); youth achievement showcases (P=.001); news links (P<.001); social marketing campaign posts (P<.001); and prevention topics, including substance abuse (P<.001), safe sex (P=.02), sexually transmitted disease prevention (P<.001), and violence or fighting (P=.047). Post features that were significantly associated with post engagement comprised the inclusion of photos (P<.001); Spanish (P<.001) or bilingual (P=.001) posts; and portrayal of youth of both sexes (P<.001) portrayed in groups (P<.001) that were facilitated by adults (P<.001). Conclusions: Social media outreach is a promising strategy that youth programs can use to complement in-person programming for augmented engagement. The Latino immigrant youth audience in this study had a tendency toward more passive social media consumption, having implications for outreach strategies and engagement measurement in future studies. While study findings confirmed the utility of social marketing campaigns for increasing user engagement, findings also highlighted a high level of engagement among youth with posts that covered casual, day-to-day program activity participation. This finding identifies an underexplored area that should be considered for health messaging, and also supports interventions that use peer-to-peer and user-generated health promotion approaches.

  • Earthquake and Tsunami damage-Dai Ichi Power Plant, Japan. Source: Wikipedia; Copyright: Digital Globe; URL:; License: Creative Commons Attribution + Noncommercial + ShareAlike (CC-BY-NC-SA).

    Analysis of the Regionality of the Number of Tweets Related to the 2011 Fukushima Nuclear Power Station Disaster: Content Analysis


    Background: The Great East Japan Earthquake on March 11, 2011, triggered a huge tsunami, causing the Fukushima Daiichi nuclear disaster. Radioactive substances were carried in all directions, along with the risks of radioactive contamination. Mass media companies, such as television stations and news websites, extensively reported on radiological information related to the disaster. Upon digesting the available radiological information, many citizens turned to social media, such as Twitter and Facebook, to express their opinions and feelings. Thus, the Fukushima Daiichi nuclear disaster also changed the social media landscape in Japan. However, few studies have explored how the people in Japan who received information on radiation propagated the information. Objective: This study aimed to reveal how the number of tweets by citizens containing radiological information changed regionally on Twitter. Methods: The research used about 19 million tweets that included the terms “radiation,” “radioactivity,” and “radioactive substance” posted for 1 year after the Fukushima Daiichi nuclear disaster. Nearly 45,000 tweets were extracted based on their inclusion of geographic information (latitude and longitude). The number of monthly tweets in 4 districts (Fukushima Prefecture, prefectures around Fukushima Prefecture, within the Tokyo Electric Power Company area, and others) were analyzed. Results: The number of tweets containing the keywords per 100,000 people at the time of the casualty outbreak was 7.05 per month in Fukushima Prefecture, 2.07 per month in prefectures around Fukushima Prefecture, 5.23 per month in the area within Tokyo Electric Power Company, and 1.35 per month in others. The number of tweets per 100,000 people more than doubled in Fukushima Prefecture 2 months after the Fukushima Daiichi nuclear disaster, whereas the number decreased to around 0.7~0.8 tweets in other districts. Conclusions: The number of tweets per 100,000 people became half of that on March 2011 3 or 4 months after the Fukushima Daiichi Nuclear Plant disaster in 3 districts except district 1 (Fukushima Prefecture); the number became a half in Fukushima Prefecture half a year later.

  • Steps used in the demographic data matching process (montage). Source: The Authors / Smartmockups; Copyright: JMIR Publications; URL:; License: Creative Commons Attribution (CC-BY).

    Where No Universal Health Care Identifier Exists: Comparison and Determination of the Utility of Score-Based Persons Matching Algorithms Using Demographic Data


    Background: A universal health care identifier (UHID) facilitates the development of longitudinal medical records in health care settings where follow up and tracking of persons across health care sectors are needed. HIV case-based surveillance (CBS) entails longitudinal follow up of HIV cases from diagnosis, linkage to care and treatment, and is recommended for second generation HIV surveillance. In the absence of a UHID, records matching, linking, and deduplication may be done using score-based persons matching algorithms. We present a stepwise process of score-based persons matching algorithms based on demographic data to improve HIV CBS and other longitudinal data systems. Objective: The aim of this study is to compare deterministic and score-based persons matching algorithms in records linkage and matching using demographic data in settings without a UHID. Methods: We used HIV CBS pilot data from 124 facilities in 2 high HIV-burden counties (Siaya and Kisumu) in western Kenya. For efficient processing, data were grouped into 3 scenarios within (1) HIV testing services (HTS), (2) HTS-care, and (3) within care. In deterministic matching, we directly compared identifiers and pseudo-identifiers from medical records to determine matches. We used R stringdist package for Jaro, Jaro-Winkler score-based matching and Levenshtein, and Damerau-Levenshtein string edit distance calculation methods. For the Jaro-Winkler method, we used a penalty (р)=0.1 and applied 4 weights (ω) to Levenshtein and Damerau-Levenshtein: deletion ω=0.8, insertion ω=0.8, substitutions ω=1, and transposition ω=0.5. Results: We abstracted 12,157 cases of which 4073/12,157 (33.5%) were from HTS, 1091/12,157 (9.0%) from HTS-care, and 6993/12,157 (57.5%) within care. Using the deterministic process 435/12,157 (3.6%) duplicate records were identified, yielding 96.4% (11,722/12,157) unique cases. Overall, of the score-based methods, Jaro-Winkler yielded the most duplicate records (686/12,157, 5.6%) while Jaro yielded the least duplicates (546/12,157, 4.5%), and Levenshtein and Damerau-Levenshtein yielded 4.6% (563/12,157) duplicates. Specifically, duplicate records yielded by method were: (1) Jaro 5.7% (234/4073) within HTS, 0.4% (4/1091) in HTS-care, and 4.4% (308/6993) within care, (2) Jaro-Winkler 7.4% (302/4073) within HTS, 0.5% (6/1091) in HTS-care, and 5.4% (378/6993) within care, (3) Levenshtein 6.4% (262/4073) within HTS, 0.4% (4/1091) in HTS-care, and 4.2% (297/6993) within care, and (4) Damerau-Levenshtein 6.4% (262/4073) within HTS, 0.4% (4/1091) in HTS-care, and 4.2% (297/6993) within care. Conclusions: Without deduplication, over reporting occurs across the care and treatment cascade. Jaro-Winkler score-based matching performed the best in identifying matches. A pragmatic estimate of duplicates in health care settings can provide a corrective factor for modeled estimates, for targeting and program planning. We propose that even without a UHID, standard national deduplication and persons-matching algorithm that utilizes demographic data would improve accuracy in monitoring HIV care clinical cascades.

  • A comforting hand. Source: Pexels; Copyright: Matthias Zomer; URL:; License: Licensed by the authors.

    Issues in Building a Nursing Home Syndromic Surveillance System with Textmining: Longitudinal Observational Study


    Background: New nursing homes (NH) data warehouses fed from residents’ medical records allow monitoring the health of elderly population on a daily basis. Elsewhere, syndromic surveillance has already shown that professional data can be used for public health (PH) surveillance but not during a long-term follow-up of the same cohort. Objective: This study aimed to build and assess a national ecological NH PH surveillance system (SS). Methods: Using a national network of 126 NH, we built a residents’ cohort, extracted medical and personal data from their electronic health records, and transmitted them through the internet to a national server almost in real time. After recording sociodemographic, autonomic and syndromic information, a set of 26 syndromes was defined using pattern matching with the standard query language-LIKE operator and a Delphi-like technique, between November 2010 and June 2016. We used early aberration reporting system (EARS) and Bayes surveillance algorithms of the R surveillance package (Höhle) to assess our influenza and acute gastroenteritis (AGE) syndromic data against the Sentinelles network data, French epidemics gold standard, following Centers for Disease Control and Prevention surveillance system assessment guidelines. Results: By extracting all sociodemographic residents’ data, a cohort of 41,061 senior citizens was built. EARS_C3 algorithm on NH influenza and AGE syndromic data gave sensitivities of 0.482 and 0.539 and specificities of 0.844 and 0.952, respectively, over a 6-year period, forecasting the last influenza outbreak by catching early flu signals. In addition, assessment of influenza and AGE syndromic data quality showed precisions of 0.98 and 0.96 during last season epidemic weeks’ peaks (weeks 03-2017 and 01-2017) and precisions of 0.95 and 0.92 during last summer epidemic weeks’ low (week 33-2016). Conclusions: This study confirmed that using syndromic information gives a good opportunity to develop a genuine French national PH SS dedicated to senior citizens. Access to senior citizens’ free-text validated health data on influenza and AGE responds to a PH issue for the surveillance of this fragile population. This database will also make possible new ecological research on other subjects that will improve prevention, care, and rapid response when facing health threats.

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

    Characterizing Tweet Volume and Content About Common Health Conditions Across Pennsylvania: Retrospective Analysis


    Background: Tweets can provide broad, real-time perspectives about health and medical diagnoses that can inform disease surveillance in geographic regions. Less is known, however, about how much individuals post about common health conditions or what they post about. Objective: We sought to collect and analyze tweets from 1 state about high prevalence health conditions and characterize the tweet volume and content. Methods: We collected 408,296,620 tweets originating in Pennsylvania from 2012-2015 and compared the prevalence of 14 common diseases to the frequency of disease mentions on Twitter. We identified and corrected bias induced due to variance in disease term specificity and used the machine learning approach of differential language analysis to determine the content (words and themes) most highly correlated with each disease. Results: Common disease terms were included in 226,802 tweets (174,381 tweets after disease term correction). Posts about breast cancer (39,156/174,381 messages, 22.45%; 306,127/12,702,379 prevalence, 2.41%) and diabetes (40,217/174,381 messages, 23.06%; 2,189,890/12,702,379 prevalence, 17.24%) were overrepresented on Twitter relative to disease prevalence, whereas hypertension (17,245/174,381 messages, 9.89%; 4,614,776/12,702,379 prevalence, 36.33%), chronic obstructive pulmonary disease (1648/174,381 messages, 0.95%; 1,083,627/12,702,379 prevalence, 8.53%), and heart disease (13,669/174,381 messages, 7.84%; 2,461,721/12,702,379 prevalence, 19.38%) were underrepresented. The content of messages also varied by disease. Personal experience messages accounted for 12.88% (578/4487) of prostate cancer tweets and 24.17% (4046/16,742) of asthma tweets. Awareness-themed tweets were more often about breast cancer (9139/39,156 messages, 23.34%) than asthma (1040/16,742 messages, 6.21%). Tweets about risk factors were more often about heart disease (1375/13,669 messages, 10.06%) than lymphoma (105/4927 messages, 2.13%). Conclusions: Twitter provides a window into the Web-based visibility of diseases and how the volume of Web-based content about diseases varies by condition. Further, the potential value in tweets is in the rich content they provide about individuals’ perspectives about diseases (eg, personal experiences, awareness, and risk factors) that are not otherwise easily captured through traditional surveys or administrative data.

  • Source: Unsplash; Copyright: David Marcu; URL:; License: Licensed by JMIR.

    Increasing Active Transportation Through E-Bike Use: Pilot Study Comparing the Health Benefits, Attitudes, and Beliefs Surrounding E-Bikes and Conventional...


    Background: The emergence of electric pedal-assist bicycles (e-bikes) presents an opportunity to increase active transportation by minimizing personal barriers of engaging in physical activity. Objectives: The aim of this study was to assess the beliefs of individuals using e-bikes for active transport and report preliminary biometric measurements while using e-bikes for physical activity compared with conventional bikes. Methods: Participants used both conventional bicycles and e-bikes to compare energy expenditure while riding on the study route. Apple smart watches were used to track each participant’s heart rate, distance, speed, and time while riding both bicycles. A total of 3 survey instruments were used to estimate beliefs: one administered before riding the bicycles, a second administered after riding a conventional bike, and the final survey completed after riding an e-bike. Survey instruments were constructed using constructs from the theory of planned behavior. Results: The study sample (N=33) included adults aged between 19 and 28 years. Paired t test analysis revealed that participants believed a conventional bike was more likely than an e-bike to benefit their physical health (P=.002) and save them money (P=.005), while an e-bike was perceived to be more likely than a conventional bike to save them time (P<.001). Paired t test analysis revealed participants significantly agreed more with the statement that they could ride an e-bike most days (P=.006) compared with a conventional bike. After participants traveled approximately 10 miles on each type of bicycle, participants’ mean average heart rate while riding the e-bike was 6.21 beats per minute lower than when riding the conventional bike (P=.04), but both were significantly higher than resting heart rate (P<.001). Conclusions: This pilot study suggests that e-bikes are an active form of transportation capable of providing much of the cardiovascular health benefits obtained during conventional bike use. E-bikes may help reduce some of the obstacles to conventional bike use, such as increased transportation time, decreased convenience, and physical fatigue.

  • SMARTConnections facilitator posting an intervention message to her group. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).

    An Online Support Group Intervention for Adolescents Living with HIV in Nigeria: A Pre-Post Test Study


    Background: Adolescents living with HIV (ALHIVs) enrolled in HIV treatment services experience greater loss to follow-up and suboptimal adherence than other age groups. HIV-related stigma, disclosure-related issues, lack of social support, and limited HIV knowledge impede adherence to antiretroviral therapy (ART) and retention in HIV services. The 90-90-90 goals for ALHIVs will only be met through strategies targeted to meet their specific needs. Objectives: We aimed to evaluate the feasibility of implementing a social media-based intervention to improve HIV knowledge, social support, ART adherence, and retention among ALHIV aged 15-19 years on ART in Nigeria. Methods: We conducted a single-group pre-post test study from June 2017 to January 2018. We adapted an existing support group curriculum and delivered it through trained facilitators in 5 support groups by using Facebook groups. This pilot intervention included five 1-week sessions. We conducted structured interviews with participants before and after the intervention, extracted clinical data, and documented intervention implementation and participation. In-depth interviews were conducted with a subset of participants at study completion. Quantitative data from structured interviews and group participation data were summarized descriptively, and qualitative data were coded and summarized. Results: A total of 41 ALHIV enrolled in the study. At baseline, 93% of participants reported existing phone access; 65% used the internet, and 64% were Facebook users. In addition, 37 participants completed the 5-session intervention, 32 actively posted comments in at least one session online, and at least half commented in each of the 5 sessions. Facilitators delivered most sessions as intended and on-time. Participants were enthusiastic about the intervention. Aspects of the intervention liked most by participants included interacting with other ALHIVs; learning about HIV; and sharing questions, experiences, and fears. The key recommendations were to include larger support groups and encourage more group interaction. Specific recommendations on various intervention components were made to improve the intervention. Conclusions: This novel intervention was feasible to implement in a predominantly suburban and rural Nigerian setting. Social media may be leveraged to provide much-needed information and social support on platforms accessible and familiar to many people, even in resource-constrained communities. Our findings have been incorporated into the intervention, and an outcome study is underway. Trial Registration: NCT03076996; (Archived by WebCite at

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  • Infodemiological patterns in searching medication errors: relationship with risk management and shift work

    Date Submitted: Jan 14, 2019

    Open Peer Review Period: Jan 15, 2019 - Jan 29, 2019

    Background: Western world health care systems have been trying to improve their efficiency and effectiveness in order to respond properly to the aging of the population and the epidemic of noncommunic...

    Background: Western world health care systems have been trying to improve their efficiency and effectiveness in order to respond properly to the aging of the population and the epidemic of noncommunicable diseases. Errors in drugs administration is an actual important issue due to different causes. Objective: Aim of this study is to measure interest in online seeking medical errors information online related to interest in risk management and shift work. Methods: We investigated Google Trends® for popular search relating to medical errors, risk management and shift work. Relative search volumes (RSVs) were evaluated for the period November 2008-November 2018 all around the world. A comparison between RSV curves related to medical errors, risk management and shift work was carried out. Then we compared world to Italian search. Results: RSVs were persistently higher for risk management than for medication errors during the study period (mean RSVs 74 vs. 51%) and RSVs were stably higher for medical errors than shift work during the study period (mean RSVs 51 vs 23%). In Italy, RSVs were much lower than the rest of the world, and RSVs for medication errors during the study period were negligible. Mean RSVs for risk management and shift work were 3 and 25%, respectively. RSVs related to medication errors and clinical risk management were correlated (r=0.520, p<0.0001). Conclusions: Google search query volumes related to medication errors, risk management and shift work are different. RSVs for risk management are higher, are correlated with medication errors, and the relationship with shift work appears to be even worse, by analyzing the entire world. In Italy such a relationship completely disappears, suggesting that it needs to be emphasized by health care authorities.