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.

Editor-in-Chief:

Travis Sanchez, DVM, MPH, Emory University Rollins School of Public Health, USA


Impact Factor 3.5 CiteScore 13.7

JMIR Public Health & Surveillance (JPHS, Editor-in-chief: Travis Sanchez, Emory University/Rollins School of Public Health) is a top-ranked (Q1) Clarivate (SCIE, SSCI etc), ScopusPMC/PubMedMEDLINE, CABI, and EBSCO/EBSCO essentials indexed, peer-reviewed international multidisciplinary journal with a unique focus on the intersection of innovation and technology in public health, and includes topics like public health informatics, surveillance (surveillance systems and rapid reports), participatory epidemiology, infodemiology and infoveillance, digital disease detection, digital epidemiology, electronic public health interventions, mass media/social media campaigns, health communication, and emerging population health analysis systems and tools. 

In 2024, JMIR Public Health and Surveillance received a Journal Impact Factor™ of 3.5 (5-Year Journal Impact Factor™: 4.7), ranked Q1 #84/403 journals in the category Public, Environmental & Occupational Health) (Clarivate Journal Citation Reports™, 2024) and a Scopus CiteScore of 13.7, placing it in the 97th percentile (#18/665) as a Q1 journal in the field of Public Health, Environmental and Occupational Health.

JPHS has an international author- and readership and welcomes submissions from around the world.

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. The main themes/topics covered by this journal can be found here.

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 journals to publish 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, JPHS 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 minimal narratives and abstracts).

Furthermore, during 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

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Mass Media/Social Media Communication and Campaigns

Well-designed public health messages can help people make informed choices, while poorly designed messages or persuasive messages can confuse, lead to poorly informed decisions, and diminish trust in health authorities and research. Communicating uncertainties to the public about the results of health research is challenging, necessitating research on effective ways to disseminate this important aspect of randomized trials.

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Cross-Sectional Studies in Public Health

Increased ageing and accelerated urbanization have led to the migration of older adults in China. The migration older adults (MOA) suffered physical and psychological discomfort in influx cities, and they are a vulnerable group that has emerged in the course of fast urbanization. Previous studies have confirmed the association between oral health and loneliness as well as the relationship between social support and loneliness; however, no research has been done to clarify the underlying mechanisms and the migrant-local difference between oral health, social support and loneliness.

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General Articles on Innovation and Technology in Public Health

COVID-19 has caused over 46,000 deaths in New York City, with a disproportional impact on certain communities. As part of the COVID-19 response, the city has directly administered over six million COVID-19 tests (not including millions of indirectly administered tests not covered in this analysis), at no cost to the individual, resulting in nearly half a million positive results. Given that testing throughout the pandemic has tended to be higher in more affluent areas, these tests were targeted to areas with fewer resources.

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Surveillance Systems

Syndromic surveillance systems are crucial for the monitoring of population health and early detection of emerging health problems. Internationally, there are numerous established systems reporting on different types of data. In the Netherlands, the Nivel syndromic surveillance system provides real-time monitoring on all diseases and symptoms presented in general practice.

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Cross-Sectional Studies in Public Health

Although understanding long-term trends in adolescent screen time and the influence of family structure is essential, there is a lack of research addressing these issues comprehensively.

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Open Source and Data for Public Health

The COVID-19 pandemic exposed challenges in pandemic management, particularly in real-time data sharing and effective decision-making. Data protection concerns and the lack of data interoperability and standardization hindered the collection, analysis, and interpretation of critical information. Effective data visualization and customization are essential to facilitate decision-making.

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Cross-Sectional Studies in Public Health

Self-efficacy in monkeypox (mpox) prevention plays a pivotal role in promoting preventive behaviors by fostering a sense of control and motivation, especially among men who have sex with men (MSM), the population most affected by mpox in many countries.

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Viewpoint and Opinions on Technology and Innovation in Public Health

Foodborne illness is a continuous public health risk. The recognition of signals indicating a cluster of foodborne illness is key to the detection, mitigation, and prevention of foodborne adverse event incidents and outbreaks. With increased internet availability and access, novel data streams (NDS) for foodborne illness reports initiated by users outside of the traditional public health framework have emerged. These include, but are not limited to, social media websites, online product reviews posted to retailer websites, and private companies that host public-generated notices of foodborne illnesses. Information gathered by these platforms can help identify early signals of foodborne illness clusters or help inform ongoing public health investigations. Here we present an overview of NDS and three investigations of foodborne illness incidents by the U.S. Food and Drug Administration that included the use of NDS at various stages. Each example demonstrates how these data were collected, integrated into traditional data sources, and used to inform the investigation. NDS present a unique opportunity for public health agencies to identify clusters that may not have been identified otherwise, due to new or unique etiologies as shown in the three examples. Clusters may also be identified earlier than they would have through traditional sources. NDS can further provide investigators supplemental information that may help confirm or rule out a source of illness. However, data collected from NDS are often incomplete and lack critical details for investigators, such as product information (e.g., lot numbers), clinical/medical details (e.g., laboratory results of affected individuals), and contact information for report follow-up. In the future, public health agencies may wish to standardize an approach to maximize the potential of NDS to catalyze and supplement adverse event investigations. Additionally, the collection of essential data elements by NDS platforms and data sharing processes with public health agencies may aid in the investigation of foodborne illness clusters and inform subsequent public health and regulatory actions.

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Reviews on Public Health Technology and Innovation

Adolescents, particularly those in Sub-Saharan Africa, experience major challenges in getting accurate and comprehensive sexual and reproductive health (SRH) information because of sociocultural norms, stigma, and limited SRH educational resources. Digital educational tools, leveraging the widespread use of mobile phones and internet connectivity, present a promising avenue to overcome these barriers and enhance SRH education among adolescents in Sub-Saharan Africa.

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Surveillance Systems

Emergency department (ED) routine data offer a unique opportunity for syndromic surveillance of communicable and non-communicable diseases (NCDs). In 2020 the Robert Koch Institute (RKI) established a syndromic surveillance system, using ED data from the AKTIN registry. The system provides daily insights into ED utilization for infectious diseases. Adding NCD indicators to the surveillance is of great public health importance, especially during acute events, where timely monitoring enables targeted public health responses and communication.

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COVID-19 Vaccination

Vaccination against COVID-19 is a critical measure for managing the pandemic and achieving herd immunity. In 2021, Slovenia had a significantly lower COVID-19 vaccination rate compared to the average rate in the European Union, with individuals aged younger than 37 years showing the highest hesitancy. Previous studies primarily explored vaccination willingness before vaccines were available to young people, leaving a gap in understanding the factors influencing vaccination behavior and differences within the population of young people.

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Cross-Sectional Studies in Public Health

Non-suicidal self-injury (NSSI), second only to disorders such as depression and anxiety, is a major public health problem leading to psychological problems in adolescents and young adults.

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