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.
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.
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Latest Submissions Open for Peer-Review:View All Open Peer Review Articles
The acceptability and feasibility of implementing a bio-behavioural enhanced surveillance tool for sexually transmitted infections in England: a mixed methods study
Date Submitted: Sep 21, 2017
Open Peer Review Period: Oct 17, 2017 - Oct 31, 2017
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: We as...
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: We assessed the acceptability and feasibility of implementing a bio-behavioural enhanced surveillance tool (BBEST), comprising of a self-administered online survey among sexual health clinic (SHC) attendees, and linking this to their electronic patient records (EPR) held in England’s national STI surveillance system. Methods: Staff from 16 purposively selected SHCs across England, and men who have sex with men (MSM) and black Caribbeans, due to high STI burden among these groups, were interviewed to assess the acceptability of the proposed BBEST model. Subsequently, SHC staff invited all attendees to complete an online survey on drivers of STI risk using a study tablet or participants’ own digital device. They recorded the numbers of attendees invited and participants’ clinic numbers, which were used to link survey data to the EPR. Participants’ online consent was obtained, separately for survey participation and linkage. In post-implementation phase, SHC staff was re-interviewed to assess the feasibility of implementing BBEST. Acceptability and feasibility of implementing BBEST were assessed by analysing these qualitative and quantitative data. Results: Pre-BBEST implementation, SHC staff and attendees emphasised the importance of free internet/wifi access, confidentiality and anonymity for increasing the acceptability of BBEST among attendees. Implementation of BBEST across SHCs varied considerably and was influenced by SHCs’ culture of prioritisation of research and innovation, and available resources. Of 7367 attendees invited, 85.3% agreed to participate. Of these 6283, 73.0% logged into the survey; 70.6% (n=4437) were eligible and completed it. Of these, 91.2% (n=4,046) consented to EPR linkage, which did not differ by age or gender but was higher among MSM than heterosexual men (95.5% vs. 88.4%; P<0.01), and lower among Black Caribbean than white participants (87.1% vs 93.8%; P <0.01). Linkage was achieved for 88.9% of consenting participants. Conclusions: Implementing the BBEST in SHCs was feasible and acceptable to staff and groups at STI risk; however ensuring participants’ confidentiality and anonymity, and availability of resources is vital. BBEST could enable timely collection of detailed behavioural data for effective commissioning of sexual health services.
Date Submitted: Oct 13, 2017
Open Peer Review Period: Oct 13, 2017 - Oct 21, 2017
Background: West-Nile virus (WNV) is an arbovirus responsible of an infection, which tends to peak during the late summer and early fall period. Recently, tools monitoring web searches are emerging as...
Background: West-Nile virus (WNV) is an arbovirus responsible of an infection, which tends to peak during the late summer and early fall period. Recently, tools monitoring web searches are emerging as powerful sources of data concerning especially infectious diseases. Objective: This study aimed at exploring the potentially predictive power of WNV-related web searches. Methods: Google Trends (GT) was used to extract search trends. Data regarding WNV were obtained from Centers for Disease Control and prevention (CDC). Data were analyzed using times series analysis. Results: We found that there was a good correlation between web searches and real-world epidemiological figures (Spearman's coefficient 0.73, p<0.0001). The best seasonal autoregressive integrated moving average (SARIMA) model was (0,1,1)X(0,1,1)4. Using data from 2004 to 2015 we were able to predict data for 2016. Conclusions: Our study demonstrated correlation between epidemiological data and search pattern related to WNV. Based on this correlation, further studies are needed to examine the practicality of these findings, making our model more accurate and reliable.
Date Submitted: Sep 22, 2017
Open Peer Review Period: Oct 6, 2017 - Oct 20, 2017
Background: New Nursing Homes (NH) data warehouses fed from residents’ medical records open the way for monitoring health elderly population on a daily basis. Elsewhere syndromic surveillance has al...
Background: New Nursing Homes (NH) data warehouses fed from residents’ medical records open the way for monitoring health 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 through a long term follow-up of the same cohort. Objective: The goal of this study was to build and assess a national ecological NH PH surveillance system (SS). Methods: Using a national network of 126 NH, an elderly cohort was built. Medical and personal data were extracted from residents’ electronic health records (EHR) and transmitted through internet to a national server in almost real time. Socio-demographic, autonomy and syndromic information were recorded. A set of twenty-six syndromes was defined using pattern matching with the standard query language LIKE operator and a Delphi-like method, through [November 2010 - June 2016]. Early aberration reporting system EARS and Bayes surveillance algorithms of the R surveillance® package were then used to assess this syndromic data against the Sentinelles network data, French epidemics gold-standard, following Centers for Disease and Control (CDC) surveillance system assessment guidelines. Results: By extracting all socio-demographic residents’ data, a cohort of 41 061 elderly was built. EARS_C3 algorithm on NH influenza and acute gastro enteritis AGE syndromic data gave respectively sensitivities of 0.482 and 0.539 and specificities of 0.844 and 0.952 over a 6 year-period, allowing to forecast the last influenza outbreak by more than 2 weeks. Also, assessing influenza and AGE syndromic data quality, precisions through last season epidemic weeks’ peaks (weeks 03-2017 and 01-2017) were of 0.98 and 0.96, whereas through last summer epidemic weeks’ low of 0.95 and 0.92 (week 33-2016). Conclusions: This study confirmed that using the NH medical care transmissions gives a good opportunity to develop a genuine French national PH SS dedicated to the elderly. Access to seniors’ free-text validated health data responds to a PH issue for the surveillance of this fragile population. This database will also make possible new ecological research that will improve prevention, care and rapid response when facing health threats. Clinical Trial: Not applicable