Towards cross-lingual alerting for bursty epidemic events

Background: Online news reports are increasingly becoming a source for event based early warning systems that detect natural disasters. Harnessing the massive volume of information available from multilingual newswire presents as many challenges as opportunities due to the patterns of reporting complex spatiotemporal events. Results: In this article we study the problem of utilising correlated event reports across languages. We track the evolution of 16 disease outbreaks using 5 temporal aberration detection algorithms on text-mined events classified according to disease and outbreak country. Using ProMED reports as a silver standard, comparative analysis of news data for 13 languages over a 129 day trial period showed improved sensitivity, F1 and timeliness across most models using cross-lingual events. We report a detailed case study analysis for Cholera in Angola 2010 which highlights the challenges faced in correlating news events with the silver standard. Conclusions: The results show that automated health surveillance using multilingual text mining has the potential to turn low value news into high value alerts if informed choices are used to govern the selection of models and data sources. An implementation of the C2 alerting algorithm using multilingual news is available at the BioCaster portal http://born.nii.ac.jp/?page=globalroundup

Ontological representation of CDC Active Bacterial Core Surveillance Case Reports

The Center for Disease Control and Prevention’s Active Bacterial Core Surveillance (CDC ABCs) Program is a collaborative effort betweeen the CDC, state health departments, laboratories, and universities to track invasive bacterial pathogens of particular importance to public health [1]. The year-end surveillance reports produced by this program help to shape public policy and coordinate responses to emerging infectious diseases over time. The ABCs case report form (CRF) data represents an excellent opportunity for data reuse beyond the original surveillance purposes

Decision Support System for the Response to Infectious Disease Emergencies Based on WebGIS and Mobile Services in China

Background: For years, emerging infectious diseases have appeared worldwide and threatened the health of people. The emergence and spread of an infectious-disease outbreak are usually unforeseen, and have the features of suddenness and uncertainty. Timely understanding of basic information in the field, and the collection and analysis of epidemiological information, is helpful in making rapid decisions and responding to an infectious-disease emergency. Therefore, it is necessary to have an unobstructed channel and convenient tool for the collection and analysis of epidemiologic information in the field. Methodology/Principal Findings: Baseline information for each county in mainland China was collected and a database was established by geo-coding information on a digital map of county boundaries throughout the country. Google Maps was used to display geographic information and to conduct calculations related to maps, and the 3G wireless network was used to transmit information collected in the field to the server. This study established a decision support system for the response to infectious-disease emergencies based on WebGIS and mobile services (DSSRIDE). The DSSRIDE provides functions including data collection, communication and analyses in real time, epidemiological detection, the provision of customized epidemiological questionnaires and guides for handling infectious disease emergencies, and the querying of professional knowledge in the field. These functions of the DSSRIDE could be helpful for epidemiological investigations in the field and the handling of infectious-disease emergencies. Conclusions/Significance: The DSSRIDE provides a geographic information platform based on the Google Maps application programming interface to display information of infectious disease emergencies, and transfers information between workers in the field and decision makers through wireless transmission based on personal computers, mobile phones and personal digital assistants. After a 2-year practice and application in infectious disease emergencies, the DSSRIDE is becoming a useful platform and is a useful tool for investigations in the field carried out by response sections and individuals. The system is suitable for use in developing countries and low-income districts

Doctor of Philosophy

dissertationPublic health reporting is an important source of information for public health investigation and surveillance, which are necessary for the prevention and control of disease. There are two important problems with the current public health reporting process in the United States: (a) the reporting specifications are unstructured and are communicated with reporting facilities using nonstandard public health department Web sites and (b) most reporting facilities transmit reports to public health entities using manual and paper-based processes. Our research focuses on the development and evaluation of new strategies to improve the public health reporting process by addressing these problems. To improve the communication of public health reporting specifications by public health authorities, we: (a) examined the business process of a laboratory complying with the reporting requirements, (b) evaluated public health department Websites to understand the problems faced by reporting facilities while accessing the reporting specifications, (c) identified the content requirements of a knowledge management system for public health reporting specifications, (d) designed the representation of the public health reporting specifications, and (e) evaluated the content and design using a prototype web-based query system for public health reporting specifications. To improve the transmission of case reports from healthcare facilities to public health entities, we: (a) described public health workflow associated with the management of case reports, (b) identified the content of a case report to meet the needs of public health authorities, (c) modeled the case report using Health Level Seven (HL7) v2.5.1, and (d) evaluated the electronic case reports by comparing the timeliness, completeness of information content, and the completeness of the electronic reporting process with the paper-based reporting processes. We demonstrated a model for public health reporting specifications using a prototype web-based query system. The evaluation conducted with users from laboratories, healthcare facilities, and public health entities showed that the proposed model met most of the users' needs and requirements. We also identified variation in the reporting specifications, some of which could be standardized to improve reporting compliance. We implemented HL7 v2.5.1 case reports from Intermountain Healthcare hospitals to the Utah Department of Health. The electronic reports transmitted from the Intermountain hospitals were more timely (median delay: 2 days) than the paper reports sent from other clinical facilities (median delay: 3.5 days) but less timely than the paper reports from Intermountain laboratories (median: 1 day). However, the evaluation of the completeness of data elements needed for public health triage prior to investigation showed that electronic case reports from Intermountain hospitals included more complete information than paper reports from Intermountain laboratories. Even though the paper reports from Intermountain laboratories were more timely, the incomplete reports may delay investigation. There are informatics opportunities and public health needs to improve both electronic laboratory reporting and electronic case reporting

Adventures in Semantic Publishing: Exemplar Semantic Enhancements of a Research Article

Scientific innovation depends on finding, integrating, and re-using the products of previous research. Here we explore how recent developments in Web technology, particularly those related to the publication of data and metadata, might assist that process by providing semantic enhancements to journal articles within the mainstream process of scholarly journal publishing. We exemplify this by describing semantic enhancements we have made to a recent biomedical research article taken from PLoS Neglected Tropical Diseases, providing enrichment to its content and increased access to datasets within it. These semantic enhancements include provision of live DOIs and hyperlinks; semantic markup of textual terms, with links to relevant third-party information resources; interactive figures; a re-orderable reference list; a document summary containing a study summary, a tag cloud, and a citation analysis; and two novel types of semantic enrichment: the first, a Supporting Claims Tooltip to permit “Citations in Context”, and the second, Tag Trees that bring together semantically related terms. In addition, we have published downloadable spreadsheets containing data from within tables and figures, have enriched these with provenance information, and have demonstrated various types of data fusion (mashups) with results from other research articles and with Google Maps. We have also published machine-readable RDF metadata both about the article and about the references it cites, for which we developed a Citation Typing Ontology, CiTO (http://purl.org/net/cito/). The enhanced article, which is available at http://dx.doi.org/10.1371/journal.pntd.0000228.x001, presents a compelling existence proof of the possibilities of semantic publication. We hope the showcase of examples and ideas it contains, described in this paper, will excite the imaginations of researchers and publishers, stimulating them to explore the possibilities of semantic publishing for their own research articles, and thereby break down present barriers to the discovery and re-use of information within traditional modes of scholarly communication

VetCompass Australia: A National Big Data Collection System for Veterinary Science

VetCompass Australia is veterinary medical records-based research coordinated with the global VetCompass endeavor to maximize its quality and effectiveness for Australian companion animals (cats, dogs, and horses). Bringing together all seven Australian veterinary schools, it is the first nationwide surveillance system collating clinical records on companion-animal diseases and treatments. VetCompass data service collects and aggregates real-time, clinical records for researchers to interrogate, delivering sustainable and cost-effective access to data from hundreds of veterinary practitioners nationwide. Analysis of these clinical records will reveal geographical and temporal trends in the prevalence of inherited and acquired diseases, identify frequently prescribed treatments, revolutionize clinical auditing, help the veterinary profession to rank research priorities, and assure evidence-based companion-animal curricula in veterinary schools. VetCompass Australia will progress in three phases: (1) roll-out of the VetCompass platform to harvest Australian veterinary clinical record data; (2) development and enrichment of the coding (data-presentation) platform; and (3) creation of a world-first, real-time surveillance interface with natural language processing (NLP) technology. The first of these three phases is described in the current article. Advances in the collection and sharing of records from numerous practices will enable veterinary professionals to deliver a vastly improved level of care for companion animals that will improve their quality of life

Open source software – a key component of E-health in Developing nations

The global burden of disease falls most heavily on people in developing countries. Few resources for healthcare, geographical and infrastructure issues, lack of trained staff, language and cultural diversity and political instability all affect the ability of health providers to support effective and efficient healthcare. Health information systems are a key aspect of improving healthcare, but existing systems are often expensive and unsuitable. Open source software appears to be a promising avenue for quickly and cheaply introducing health information systems that are appropriate for developing nations. This article describes some aspects of open source e-health software that are particularly relevant to developing nations, issues and problems that may arise and suggests some future areas for research and action. Suggestions for critical success factors are included. Much of the discussion will be related to a case study of a training and e-health project, currently running in the Himalayan kingdom of Bhutan

Distributed data processing for public health surveillance

BACKGROUND: Many systems for routine public health surveillance rely on centralized collection of potentially identifiable, individual, identifiable personal health information (PHI) records. Although individual, identifiable patient records are essential for conditions for which there is mandated reporting, such as tuberculosis or sexually transmitted diseases, they are not routinely required for effective syndromic surveillance. Public concern about the routine collection of large quantities of PHI to support non-traditional public health functions may make alternative surveillance methods that do not rely on centralized identifiable PHI databases increasingly desirable. METHODS: The National Bioterrorism Syndromic Surveillance Demonstration Program (NDP) is an example of one alternative model. All PHI in this system is initially processed within the secured infrastructure of the health care provider that collects and holds the data, using uniform software distributed and supported by the NDP. Only highly aggregated count data is transferred to the datacenter for statistical processing and display. RESULTS: Detailed, patient level information is readily available to the health care provider to elucidate signals observed in the aggregated data, or for ad hoc queries. We briefly describe the benefits and disadvantages associated with this distributed processing model for routine automated syndromic surveillance. CONCLUSION: For well-defined surveillance requirements, the model can be successfully deployed with very low risk of inadvertent disclosure of PHI – a feature that may make participation in surveillance systems more feasible for organizations and more appealing to the individuals whose PHI they hold. It is possible to design and implement distributed systems to support non-routine public health needs if required

Integrating open-source technologies to build low-cost information systems for improved access to public health data

Effective public health practice relies on the availability of public health data sources and assessment tools to convey information to investigators, practitioners, policy makers, and the general public. Emerging communication technologies on the Internet can deliver all components of the "who, what, when, and where" quartet more quickly than ever with a potentially higher level of quality and assurance, using new analysis and visualization tools. Open-source software provides the opportunity to build low-cost information systems allowing health departments with modest resources access to modern data analysis and visualization tools. In this paper, we integrate open-source technologies and public health data to create a web information system which is accessible to a wide audience through the Internet. Our web application, "EpiVue," was tested using two public health datasets from the Washington State Cancer Registry and Washington State Center for Health Statistics. A third dataset shows the extensibility and scalability of EpiVue in displaying gender-based longevity statistics over a twenty-year interval for 3,143 United States counties. In addition to providing an integrated visualization framework, EpiVue's highly interactive web environment empowers users by allowing them to upload their own geospatial public health data in either comma-separated text files or MS Excel™ spreadsheet files and visualize the geospatial datasets with Google Maps™