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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.
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.
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Background: Key populations, including female sex workers (FSW), are at disproportionately high risk for HIV infection. Estimates of the size of these populations serve as denominator data to inform H...
Background: Key populations, including female sex workers (FSW), are at disproportionately high risk for HIV infection. Estimates of the size of these populations serve as denominator data to inform HIV prevention and treatment programming and are necessary for the equitable allocation of limited public health resources. Objective: To present the Respondent Driven Sampling (RDS) adjusted Reverse Tracking Method (RTM) (RadR), a novel population size estimation (PSE) approach that combines venue mapping data with RDS data to estimate the population size, adjusted for double counting and non-attendance biases. Methods: We used data from a 2014 respondent-driven sampling surveys of FSW in Windhoek and Katima Mulilo, Namibia to demonstrate the RadR method. Information from venue mapping and enumeration from the survey formative assessment phase were combined with survey-based “venue-inquiry” questions to estimate population size, adjusting for double counting and FSW who do not attend venues. RadR estimates were compared to the official population size estimates, published by the Namibian Ministry of Health and Social Services (MoHSS), and the unadjusted Reverse Tracking Method. Results: Using the RadR method, we estimated 1,739 (95% Simulation Intervals: 1,278-2,616) FSW in Windhoek and 583 (95% Simulation Intervals: 387-758) FSW in Katima Mulilo. These estimates were slightly more conservative than the MoHSS estimates (Windhoek: 3,000 [1,800 – 3,400]; Katima Mulilo: 800 [380 – 2,000]), though not statistically different. We also found 75 extra venues in Windhoek and 59 extra venues in Katima Mulilo identified by RDS participants’ responses that were not detected during the initial mapping exercise. Conclusions: The RadR estimates were comparable to official estimates from the MoHSS. The RadR method is easily integrated into RDS studies, producing plausible population size estimates, and also validates and updates the venue-based sampling frame.
The use of social networking sites has exponentially increased in the recent years and the increment was most noticeable among the youth. However, suicide is the second leading cause of death among th...
The use of social networking sites has exponentially increased in the recent years and the increment was most noticeable among the youth. However, suicide is the second leading cause of death among this group and they are the most active group in the different social networking sites. They share their thoughts, photos, opinions and news including the news of suicide. Whenever, they came to know the death of a friend or follower they share the news express their grief. In addition they also show their condolence to the death of the relative or friends of Facebook friends Moreover, all the television channels and newspapers share their information and news in Facebook, Tweeter and other social media from where we can collect information. Bangladesh is a Muslim developing country in South East Asia that lacks any national suicide database due a number of sociocultural, religious and political factors. As a result, the existing the data on suicide in the country shows about 20 fold variation in different reports. However, the country can develop national suicide database by extracting the information shared in the Facebook and verifying each incidents from different Facebook users. This idea can solve a long lasting problem in many developing low and middle income countries.