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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:

  • Steps used in the demographic data matching process (montage). Source: The Authors / Smartmockups; Copyright: JMIR Publications; URL: http://publichealth.jmir.org/2018/4/e10436/; License: Creative Commons Attribution (CC-BY).
    Innovative Methods in Public Health...

    Dec 13, 2018

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

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    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: https://www.pexels.com/photo/action-adult-affection-eldery-339620/; License: Licensed by the authors.
    Surveillance Systems

    Dec 13, 2018

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

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    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: https://www.istockphoto.com/photo/sick-woman-in-bed-at-home-talking-on-phone-gm501040158-81126673; License: Licensed by the authors.
    Infoveillance, Infodemiology and...

    Dec 6, 2018

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

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    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: https://unsplash.com/photos/Op5JMbkOqi0; License: Licensed by JMIR.
    Prevention and Health Promotion

    Nov 29, 2018

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

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    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: http://publichealth.jmir.org/2018/4/e12397/; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).
    HIV/AIDS/STI Prevention and Care

    Nov 28, 2018

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

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    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: ClinicalTrials.gov NCT03076996; https://clinicaltrials.gov/ct2/show/NCT03076996 (Archived by WebCite at http://www.webcitation.org/73oCCEBBC).

  • London, a conurbation. Source: Wikimedia Commons; Copyright: Daniel Chapman; URL: https://commons.wikimedia.org/wiki/File:London_from_a_hot_air_balloon.jpg; License: Creative Commons Attribution (CC-BY).
    Surveillance Reports

    Nov 26, 2018

    Conurbation, Urban, and Rural Living as Determinants of Allergies and Infectious Diseases: Royal College of General Practitioners Research and Surveillance...

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    Background: Living in a conurbation, urban, or rural environment is an important determinant of health. For example, conurbation and rural living is associated with increased respiratory and allergic conditions, whereas a farm or rural upbringing has been shown to be a protective factor against this. Objective: The objective of the study was to assess differences in general practice presentations of allergic and infectious disease in those exposed to conurbation or urban living compared with rural environments. Methods: The population was a nationally representative sample of 175 English general practices covering a population of over 1.6 million patients registered with sentinel network general practices. General practice presentation rates per 100,000 population were reported for allergic rhinitis, asthma, and infectious conditions grouped into upper and lower respiratory tract infections, urinary tract infection, and acute gastroenteritis by the UK Office for National Statistics urban-rural category. We used multivariate logistic regression adjusting for age, sex, ethnicity, deprivation, comorbidities, and smoking status, reporting odds ratios (ORs) with 95% CIs. Results: For allergic rhinitis, the OR was 1.13 (95% CI 1.04-1.23; P=.003) for urban and 1.29 (95% CI 1.19-1.41; P<.001) for conurbation compared with rural dwellers. Conurbation living was associated with a lower OR for both asthma (OR 0.70, 95% CI 0.67-0.73; P<.001) and lower respiratory tract infections (OR 0.94, 95% CI 0.90-0.98; P=.005). Compared with rural dwellers, the OR for upper respiratory tract infection was greater in urban (OR 1.06, 95% CI 1.03-1.08; P<.001) but no different in conurbation dwellers (OR 1.00, 95% CI 0.97-1.03; P=.93). Acute gastroenteritis followed the same pattern: the OR was 1.13 (95% CI 1.01-1.25; P=.03) for urban dwellers and 1.04 (95% CI 0.93-1.17; P=.46) for conurbation dwellers. The OR for urinary tract infection was lower for urban dwellers (OR 0.94, 95% CI 0.89-0.99; P=.02) but higher in conurbation dwellers (OR 1.06, 95% CI 1.00-1.13; P=.04). Conclusions: Those living in conurbations or urban areas were more likely to consult a general practice for allergic rhinitis and upper respiratory tract infection. Both conurbation and rural living were associated with an increased risk of urinary tract infection. Living in rural areas was associated with an increased risk of asthma and lower respiratory tract infections. The data suggest that living environment may affect rates of consultations for certain conditions. Longitudinal analyses of these data would be useful in providing insights into important determinants.

  • Mosquitos are a carrier of Zika virus. Source: Flickr; Copyright: confierconifer; URL: https://www.flickr.com/photos/conifer/14951771097/; License: Creative Commons Attribution (CC-BY).
    Infoveillance, Infodemiology and...

    Nov 22, 2018

    Dynamics of Health Agency Response and Public Engagement in Public Health Emergency: A Case Study of CDC Tweeting Patterns During the 2016 Zika Epidemic

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    Background: Social media have been increasingly adopted by health agencies to disseminate information, interact with the public, and understand public opinion. Among them, the Centers for Disease Control and Prevention (CDC) is one of the first US government health agencies to adopt social media during health emergencies and crisis. It had been active on Twitter during the 2016 Zika epidemic that caused 5168 domestic noncongenital cases in the United States. Objective: The aim of this study was to quantify the temporal variabilities in CDC’s tweeting activities throughout the Zika epidemic, public engagement defined as retweeting and replying, and Zika case counts. It then compares the patterns of these 3 datasets to identify possible discrepancy among domestic Zika case counts, CDC’s response on Twitter, and public engagement in this topic. Methods: All of the CDC-initiated tweets published in 2016 with corresponding retweets and replies were collected from 67 CDC–associated Twitter accounts. Both univariate and multivariate time series analyses were performed in each quarter of 2016 for domestic Zika case counts, CDC tweeting activities, and public engagement in the CDC-initiated tweets. Results: CDC sent out >84.0% (5130/6104) of its Zika tweets in the first quarter of 2016 when Zika case counts were low in the 50 US states and territories (only 560/5168, 10.8% cases and 662/38,885, 1.70% cases, respectively). While Zika case counts increased dramatically in the second and third quarters, CDC efforts on Twitter substantially decreased. The time series of public engagement in the CDC-initiated tweets generally differed among quarters and from that of original CDC tweets based on autoregressive integrated moving average model results. Both original CDC tweets and public engagement had the highest mutual information with Zika case counts in the second quarter. Furthermore, public engagement in the original CDC tweets was substantially correlated with and preceded actual Zika case counts. Conclusions: Considerable discrepancies existed among CDC’s original tweets regarding Zika, public engagement in these tweets, and actual Zika epidemic. The patterns of these discrepancies also varied between different quarters in 2016. CDC was much more active in the early warning of Zika, especially in the first quarter of 2016. Public engagement in CDC’s original tweets served as a more prominent predictor of actual Zika epidemic than the number of CDC’s original tweets later in the year.

  • Source: JMIR Publications/Placeit; Copyright: JMIR Publications; URL: http://publichealth.jmir.org/2018/4/e10262/; License: Creative Commons Attribution (CC-BY).
    Infoveillance, Infodemiology and...

    Nov 22, 2018

    How Twitter Can Support the HIV/AIDS Response to Achieve the 2030 Eradication Goal: In-Depth Thematic Analysis of World AIDS Day Tweets

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    Background: HIV/AIDS is a tremendous public health crisis, with a call for its eradication by 2030. A human rights response through civil society engagement is critical to support and sustain HIV eradication efforts. However, ongoing civil engagement is a challenge. Objective: This study aimed to demonstrate the use of Twitter data to assess public sentiment in support of civil society engagement. Methods: Tweets were collected during World AIDS Days 2014 and 2015. A total of 39,940 unique tweets (>10 billion users) in 2014 and 78,215 unique tweets (>33 billion users) in 2015 were analyzed. Response frequencies were aggregated using natural language processing. Hierarchical rank-2 nonnegative matrix factorization algorithm generated a hierarchy of tweets into binary trees. Tweet hierarchy clusters were thematically organized by the Joint United Nations Programme on HIV/AIDS core action principles and categorized under HIV/AIDS Prevention, Treatment or Care, or Support. Results: Topics tweeted 35 times or more were visualized. Results show a decrease in 2015 in the frequency of tweets associated with the fight to end HIV/AIDS, the recognition of women, and to achieve an AIDS-free generation. Moreover, an increase in tweets was associated with an integrative approach to the HIV/AIDS response. Hierarchical thematic differences in 2015 included no prevention discussion and the recognition of the pandemic’s impact and discrimination. In addition, a decrease was observed in motivation to fast track the pandemic’s end and combat HIV/AIDS. Conclusions: The human rights–based response to HIV/AIDS eradication is critical. Findings demonstrate the usefulness of Twitter as a low-cost method to assess public sentiment for enhanced knowledge, increased hope, and revitalized expectations for HIV/AIDS eradication.

  • Source: Flickr; Copyright: GbergT; URL: https://www.flickr.com/photos/habesha/875265756; License: Creative Commons Attribution (CC-BY).
    HIV/AIDS/STI Prevention and Care

    Nov 5, 2018

    Viral Loads Within 6 Weeks After Diagnosis of HIV Infection in Early and Later Stages: Observational Study Using National Surveillance Data

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    Background: Early (including acute) HIV infection is associated with viral loads higher than those in later stages. Objective: This study aimed to examine the association between acute infection and viral loads near the time of diagnosis using data reported to the US National HIV Surveillance System. Methods: We analyzed data on infections diagnosed in 2012-2016 and reported through December 2017. Diagnosis and staging were based on the 2014 US surveillance case definition for HIV infection. We divided early HIV-1 infection (stage 0) into two subcategories. Subcategory 0α: a negative or indeterminate HIV-1 antibody test was ≤60 days after the first confirmed positive HIV-1 test or a negative or indeterminate antibody test or qualitative HIV-1 nucleic acid test (NAT) was ≤180 days before the first positive test, the latter being a NAT or detectable viral load. Subcategory 0β: a negative or indeterminate antibody or qualitative NAT was ≤180 days before the first positive test, the latter being an HIV antibody or antigen/antibody test. We compared median earliest viral loads for each stage and subcategory in each of the first 6 weeks after diagnosis using only the earliest viral load for each individual. Results: Of 203,392 infections, 56.69% (115,297/203,392) were reported with a quantified earliest viral load within 6 weeks after diagnosis and criteria sufficient to determine the stage at diagnosis. Among 5081 infections at stage 0, the median earliest viral load fell from 694,000 copies/mL in week 1 to 125,022 in week 2 and 43,473 by week 6. Among 30,910 infections in stage 1, the median earliest viral load ranged 15,412-17,495. Among 42,784 infections in stage 2, the median viral load declined from 44,973 in week 1 to 38,497 in week 6. Among 36,522 infections in stage 3 (AIDS), the median viral load dropped from 205,862 in week 1 to 119,000 in week 6. The median earliest viral load in stage 0 subcategory 0α fell from 1,344,590 copies/mL in week 1 to 362,467 in week 2 and 47,320 in week 6, while that in subcategory 0β was 70,114 copies/mL in week 1 and then 32,033 to 44,067 in weeks 2-6. The median viral load in subcategory 0α was higher than that in subcategory 0β in each of the first 6 weeks after diagnosis (P<.001). Conclusions: In the 1st week after diagnosis, viral loads in early infections are generally several times higher than those in later stages at diagnosis. By the 3rd week, however, most are lower than those in stage 3. High viral loads in early infection are much more common in subcategory 0α than in subcategory 0β, consistent with 0α comprising mostly acute infections and 0β comprising mostly postacute early infections. These findings may inform the prioritization of interventions for prevention.

  • M-Spot dried blood spot collection. Source: The Authors; Copyright: The Authors; URL: http://publichealth.jmir.org/2018/4/e10847; License: Licensed by JMIR.
    HIV/AIDS/STI Prevention and Care

    Nov 1, 2018

    Quantification of HIV-1 RNA Among Men Who Have Sex With Men Using an At-Home Self-Collected Dried Blood Spot Specimen: Feasibility Study

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    Background: Suboptimal antiretroviral therapy (ART) adherence and disengagement in care present significant public health challenges because of the increased probability of HIV transmission. In the United States, men who have sex with men (MSM) continue to be disproportionately affected by HIV, highlighting a critical need to engage high-risk MSM living with HIV who are not engaged or retained in care. Objective: The aim of the study was to assess the feasibility of at-home blood self-collection and laboratory quantification of HIV-1 RNA viral load (VL) to report laboratory-based VL outcomes and compare self-reported and laboratory-reported VL Methods: Between 2016 and 2017, 766 US HIV-positive MSM enrolled in a Web-based behavioral intervention were invited to participate in an at-home dried blood spot (DBS) collection study using HemaSpot-HF kits (Spot On Sciences, Inc, Austin, TX) for laboratory-quantified VL. Results: Of those invited to participate, 72.3% (554/766) enrolled in the DBS study. Most (79.2%, 439/554) men enrolled reported attempting to collect their blood, 75.5% (418/554) of participants mailed a DBS specimen to the research laboratory, and 60.8% (337/554) had an adequate blood sample for VL testing. Of the 337 specimens tested for VL by the laboratory, 52.5% (177/337) had detectable VL (median: 3508 copies/mL; range: 851-1,202,265 copies/mL). Most men (83.9%, 135/161) who returned a DBS specimen with laboratory-quantified detectable VL self-reported an undetectable VL during their last clinical visit. Conclusions: Home collection of DBS samples from HIV-positive MSM is feasible and has the potential to support clinical VL monitoring. Discrepant laboratory HIV-1 RNA values and self-reported VL indicate a need to address perceived VL status, especially in the era of treatment as prevention. Most participants were willing to use an at-home DBS kit in the future, signaling an opportunity to engage high-risk MSM in long-term HIV care activities.

  • A surveillance officer using a mobile health tool FOR OUTBREAK RESPONSE. Source: Image created by the Authors; Copyright: SORMAS / Helmholtz Centre for Infection Research (HZI); URL: http://publichealth.jmir.org/2018/4/e68/; License: Creative Commons Attribution (CC-BY).
    Infectious Diseases (non-STD/STI)

    Oct 29, 2018

    Assessing the Concepts and Designs of 58 Mobile Apps for the Management of the 2014-2015 West Africa Ebola Outbreak: Systematic Review

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    Background: The use of mobile phone information technology (IT) in the health sector has received much attention especially during the 2014-2015 Ebola virus disease (EVD) outbreak. mHealth can be attributed to a major improvement in EVD control, but there lacks an overview of what kinds of tools were available and used based on the functionalities they offer. Objective: We aimed to conduct a systematic review of mHealth tools in the context of the recent EVD outbreak to identify the most promising approaches and guide further mHealth developments for infectious disease control. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we searched for all reports on mHealth tools developed in the context of the 2014-2015 EVD outbreak published between January 1, 2014 and December 31, 2015 on Google Scholar, MEDLINE, CAB Abstracts (Global Health), POPLINE, and Web of Science in any language using the search strategy: (“outbreak” OR “epidemic”) AND (“mobile phone” OR “smartphone” OR “smart phone” OR “mobile phone” OR “tablet” OR “mHealth”) AND (“Ebola” OR ”EVD” OR “VHF” OR “Ebola virus disease” OR “viral hemorrhagic fever”) AND (“2014” OR “2015”). The relevant publications were selected by 2 independent reviewers who applied a standardized data extraction form on the tools’ functionalities. Results: We identified 1220 publications through the search strategy, of which 6.31% (77/1220) were original publications reporting on 58 specific mHealth tools in the context of the EVD outbreak. Of these, 62% (34/55) offered functionalities for surveillance, 22% (10/45) for case management, 18% (7/38) for contact tracing, and 6% (3/51) for laboratory data management. Only 3 tools, namely Community Care, Sense Ebola Followup, and Surveillance and Outbreak Response Management and Analysis System supported all four of these functionalities. Conclusions: Among the 58 identified tools related to EVD management in 2014 and 2015, only 3 appeared to contain all 4 key functionalities relevant for the response to EVD outbreaks and may be most promising for further development.

  • Source: Health.mil (Jacob Sippel); Copyright: US Navy; URL: https://health.mil/News/Gallery/Photos/2018/09/28/Prostate-Cancer-Screening-2018; License: Public Domain (CC0).
    Longitudinal and Cohort Studies in...

    Oct 23, 2018

    Factors Related to Prostate-Specific Antigen–Based Prostate Cancer Screening in Primary Care: Retrospective Cohort Study of 120,587 French Men Over the Age...

    Authors List:

    Abstract:

    Background: International guidelines recommend avoiding prostate-specific antigen (PSA)-based prostate cancer screening in the elderly when life expectancy is less than 10 years. For younger men, most recommendations encourage a shared decision-making process taking into account patient comorbidities. Objective: The objective was to assess the performance of PSA-based prostate cancer screening in men older than 74 years and assess whether the presence (vs absence) of comorbidities was related to the performance of PSA testing in younger men aged 50 to 74 years who were eligible for screening. Methods: We analyzed data from the French national health care database (Loire-Atlantique geographic area). We reported the follow-up of two cohorts of men from April 1, 2014, to March 31, 2016: 22,480 men aged over 74 years and 98,107 men aged 50 to 74 years. We analyzed whether these patients underwent PSA testing after 2 years of follow-up and whether PSA testing performance was related to the following patient-related variables: age, low income, proxy measures indicative of major comorbidities (repeated ambulance transportation, having one of 30 chronic diseases, taking 5 or more drugs per day), or proxy measures indicative of specific comorbidities (cancer diseases, cardiovascular diseases, or psychiatric disorders). Statistical analysis was based on a multivariate mixed-effects logistic regression. Results: The proportion of patients who underwent a PSA-based screening test was 41.35% (9296/22,480) among men older than 74 years versus 41.05% (40,275/98,107) among men aged 50 to 74 years. The following factors were associated with less frequent PSA testing in men older than 74 years—age (odds ratio [OR] 0.89, 95% CI 0.88-0.89), low income (OR 0.18, 95% CI 0.05-0.69), suffering from a chronic disease (OR 0.82, 95% CI 0.76-0.88), repeated ambulance transportation (OR 0.37, 95% CI 0.31-0.44), diabetes requiring insulin (OR 0.51, 95% CI 0.43-0.60), dementia (OR 0.68, 95% CI 0.55-0.84), and antipsychotic treatment (OR 0.62, 95% CI 0.51-0.75)—whereas cardiovascular drug treatment was associated with more frequent PSA testing (OR 1.6, 95% CI 1.53-1.84). The following factors were associated with less frequent PSA testing in men aged 50 to 74 years—low income (OR 0.61, 95% CI 0.55-0.68); nonspecific conditions related to frailty: suffering from a chronic disease (OR 0.80, 95% CI 0.76-0.83), repeated ambulance transportation (OR 0.29, 95% CI 0.23-0.38), or chronic treatment with 5 or more drugs (OR 0.89, 95% CI 0.83-0.96); and various specific comorbidities: anticancer drug treatment (OR 0.67, 95% CI 0.55-0.83), diabetes requiring insulin (OR 0.55, 95% CI 0.49-0.61), and antiaggregant treatment (OR 0.91, 95% CI 0.86-0.96)—whereas older age (OR 1.07, 95% CI 1.07-1.08) and treatment with other cardiovascular drugs (OR 2.23, 95% CI 2.15-2.32) were associated with more frequent PSA testing. Conclusions: In this study, 41.35% (9296/22,480) of French men older than 74 years had a PSA-based screening test. Although it depends on patient comorbidities, PSA testing remains inappropriate in certain populations.

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  • Modelling HIV incidence using case surveillance data with the ECDC HIV Modelling Tool.”

    Date Submitted: Nov 29, 2018

    Open Peer Review Period: Dec 4, 2018 - Dec 18, 2018

    Background: Accurately estimating HIV incidence and the number of people living with HIV informs programme evaluation and planning. Objective: This study documents the manner in which a selection of E...

    Background: Accurately estimating HIV incidence and the number of people living with HIV informs programme evaluation and planning. Objective: This study documents the manner in which a selection of EU/EEA Member States (MS) used the ECDC HIV Modelling Tool to model HIV incidence estimates, including the number of undiagnosed, using surveillance data. Methods: Belgium, Greece, Ireland, Luxembourg and Portugal were selected based on their HIV epidemics, surveillance system characteristics and data availability. Each country calculated its national HIV estimates with the tool and provided feedback on data validation (e.g. CD4 count completeness), selection of diagnosis probabilities, assessment of goodness of fit and interpretation of outputs through a questionnaire developed by ECDC. Results: MS relied on tool assumptions regarding the CD4 count completeness, which varied among participants between 46 and 80%. Each country modelled several HIV diagnosis probabilities based on their surveillance system characteristics and HIV epidemic such as outbreaks or an increasing HIV migrant population. The final model was chosen based on goodness of fit statistics and the perceived reliability of the estimates when compared to other estimates or data sources. Over the period 2014-16, the undiagnosed proportion of people living with HIV ranged from 9.7% to 20.4% and the estimated mean time from HIV infection to diagnosis was four years. Conclusions: Our study shows that the modelling outcomes provide a more realistic picture of the true HIV burden which are based on transparent assumptions and quantitative surveillance data and the outputs may be considered suitable for national policy making.

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