Special Issue "Public Health Informatics"

Guest Editor
Dr. Maged N. Kamel Boulos
Faculty of Health and Social Work, University of Plymouth, Drake Circus, Plymouth, Devon, PL4 8AA, UK
Website: http://www.plymouth.ac.uk/staff/mnkamelboulos
E-Mail:
Interests: medical and health informatics; including telehealthcare/eHealth; geographic informatics; 3D virtual worlds and virtual globes (mirror worlds); web 2.0; e-learning

Public Health Informatics (PHI) is the science of applying information-age technology to serve the specialized needs of public health. PHI is ¡°the systematic application of information and computer science and technology to public health practice, research and learning.¡± As a discipline, PHI focuses on the information science and technology applications that are relevant to public health, while always keeping in mind that:

- The primary focus of public health is to promote the health of populations and not the health of specific individuals.
- The primary strategy of public health is prevention of disease and injury by altering the conditions or the environment that put populations at risk.
- Public health professionals explore the potential for prevention at all vulnerable points in the causal chains leading to disease, injury, or disability; public health activities are not restricted to particular social, behavioural, or environmental contexts.
- Public health interventions must reflect the governmental context in which public health is practiced.

We are using the broadest definition of Public Health Informatics, which also covers applications, systems, services and solutions with noticeable impacts on communities (including patient communities, older populations, etc.) and/or on health and social care systems and services. Prospective authors are invited to submit manuscripts on related topics, including, but not limited to, Internet-based public education and outreach; telehealthcare and domotic services for populations with special needs; real-time outbreak and disease surveillance; Internet-based engagement and empowerment of citizens and communities, including Social Web applications; e-epidemiology; privacy-preserving solutions for public health studies that involve person-identifiable data (e.g., home addresses), etc.

• - free for readers, with low publishing fees paid by authors or their institutions
• Rapid publication: accepted papers are immediately published online (we started to publish papers quickly since September 2008). The printed edition will only be continued for the Proceedings of the yearly International Symposiums on Recent Advances in Environmental Health Research starting 2009.

Submission

The Int. J. Environ. Res. Public Health (ISSN 1660-4601) was launched in 2004 and is an Open Access journal, with the main Editorial Office located in Basel, Switzerland. It has been accepted for coverage in Science Citation Index Expanded, available as the Web of Science and in Current Contents/Agriculture, Biology, and Environmental Sciences. Coverage will begin with the 2009 issues. This journal is also abstracted and indexed very rapidly by Chemical Abstracts, MedLine/PubMed and EMBASE. The IJERPH maintains a rapid editorial procedure and a rigorous peer-review system. Well written papers have been peer-reviewed and published in less than 4 weeks from manuscript submission. All papers published in IJERPH have DOI numbers.

All papers should be submitted to ijerph@mdpi.org with copy to the guest editor. To be published continuously until the deadline and papers will be listed together at this special issue website.

Please visit the Instructions for Authors page before submitting a paper. Open Access publication fees are 300 CHF per paper. English correction fees (250 CHF) will be added in certain cases (550 CHF per paper for those papers that require extensive additional formatting and/or English corrections).

• real-time outbreak and disease surveillance
• disease surveillance
• Internet-based engagement and empowerment of citizens and communities
• Internet-based public health education and outreach
• e-epidemiology
• privacy-preserving solutions for public health studies that involve person-identifiable data

Type of Paper: Article
Title: Knowledge Mapping for the Early Detection of Outbreaks: Decision Support for Frontlines Surveillance
Author: Jay A. Brown; E-Mail: brownjay@haz-map.com
Abstract: Mapping knowledge into a relational database became possible with the availability of personal computers and user-friendly database software in the early 1990s. To design such a database the domain expert works like a mapmaker to first outline the domain and then add the details, starting with most prominent features. The resulting "intelligent database" can support the decisions of healthcare professionals. The author developed an intelligent database of outbreaks based on case definitions of all diseases known to cause acute syndromes in clusters of patients. Diseases were categorized into 15 syndromes, e.g., respiratory symptoms with fever. Users can query the database for all diseases matching one or more specific criteria (syndrome, symptom, endemic region of the world, occupation, or epidemiological factor). Epidemiological factors include source (patients, water, soil, or animals), route of entry, and insect vectors and animal reservoirs. The database content includes all diseases that could present as outbreaks, mainly communicable diseases such as childhood infections, foodborne illnesses, and zoonoses, but also noninfectious diseases such as those caused by chemical accidents and bioterrorist attacks. Medical and public health professionals could use such a map to help them participate in the surveillance cycle for the early detection of outbreaks.

Type of Paper: Article
Title: Text and Structural Data Mining of Influenza Mentions in Web and Social Media
Authors: Courtney D. Corley ¹, Diane J. Cook ², Armin R. Mikler ³ and Karan P. Singh ⁴
Affiliations: ¹ Pacific Northwest National Laboratory / 902 Battelle Blvd., Richland, WA 99352, USA; E-Mail: court@pnl.gov (C.D.C.)
² School of Electrical Engineering and Computer Science, Washington State University / PO Box 642752 Pullman, Washington 99164, USA; E-Mail: cook@eecs.wsu.edu (D.J.C.)
³ Department of Computer Science and Engineering, University of North Texas / 1155 Union Circle #311366 Denton, TX 76203, USA; E-Mail: mikler@unt.edu (A.R.M.)
⁴ Department of Biostatistics, University of North Texas Health Science Center / 3500 Camp Bowie Blvd. Fort Worth, TX 76107, USA; E-Mail: ksingh@hsc.unt.edu (K.P.S.)
Abstract: Text and structural data mining of Web and social media (WSM) provides a novel disease surveillance resource and can identify online communities for targeted public health communications (PHC) to assure wide dissemination of pertinent information. WSM that mention influenza are harvested over a 24-week period, 5-October-2008 to 21-March-2009. Link analysis reveals communities for targeted PHC. Text mining is shown to identify trends in flu posts that correlate to real-world influenza-like illness patient report data. We also bring to bear a graph-based data mining technique to detect anomalies among flu blogs connected by publisher type, links, and user-tags.
Keywords: disease surveillance; public health epidemiology; health informatics; graph-based data mining; web and social media; social network analysis

Title: Spatial and Semantic Query of Respiratory Disease Information
Authors: Sheng Gao ¹, Harold Boley ², Darka Mioc ^1,3, Francois Anton ⁴ and Xiaolun Yi ⁵
Affiliations: ¹ Department of Geodesy and Geomatics Engineering, University of New Brunswick, Fredericton, NB, Canada; E-Mail: sheng.gao@unb.ca
² Institute for Information Technology, NRC, Fredericton, NB, Canada; E-Mail: Harold.Boley@nrc.gc.ca
³ National Space Institute, Technical University of Denmark, Denmark; dmioc@unb.ca
⁴ Department of Informatics and Mathematical Modelling, Technical University of Denmark; E-Mail: fa@imm.dtu.dk
⁵ Service New Brunswick, Fredericton, NB, Canada; E-Mail: Xiaolun.Yi@snb.ca
Abstract: With the increasing growth of health data, the semantic query of the health information is important in data retrieval. Adding the spatial component for health data can assist in the understanding of health phenomena.
The spatial component in health data is useful in health data integration, query and visualization, with the use of spatial operations and spatial relation operators. Therefore, the utilization of explicit spatial information on the Semantic Web environment will enhance the querying and visualization of health data. The major advantage of supporting an explicit representation of spatial information is that it allows spatial analysis and visualization. In this paper, a semantic health data query and visualization framework is proposed through the incorporation and processing of spatial information. Furthermore, we built a fully integrated system that allows the geospatial-semantic query and reasoning.
With the extension of RuleML (that we used in this research), we added geometry types, and enabled spatial operation and spatial relation rules for health information query. We include the geometric representation into RuleML, and apply ontologies and rules for the querying, reasoning, and visualization of health information. The geospatial built-ins were implemented as an extension to OO jDREW. Case studies were carried out on using this Geospatial RuleML for respiratory disease information. The paper thus demonstrates an approach to enhance RuleML for geospatial-semantic querying of health information.
In the case scenarios, the use of semantic in semantic, geometric and graphic dimensions, useful disease information is discovered and deducted through the integration of various kinds of data sources. Ontologies are defined to represent the data that we collected, and rules are generated to support reasoning and visualization of health information.
The use of geometric and cartographic representation in our study allows the health information to be mapped, which can improve health practitioners in understanding health phenomena. This research fosters the use of ontologies and rules in representing semantics, geometrics, and graphics in the public health field. It can improve the deduction of heterogeneous information collected by different health organizations. Our further work will be devoted to the development of geometric and cartographic domain ontologies, and the spatio-temporal reasoning and cartographic generalization rules for perfecting the functionalities in semantic integration, query, and visualization of health information.
Keywords: public health; Ontologies; respiratory diseases; RuleML; geospatial data