Removing a barrier to computer-based outbreak and disease surveillance--the RODS Open Source Project.

INTRODUCTION Computer-based outbreak and disease surveillance requires high-quality software that is well-supported and affordable. Developing software in an open-source framework, which entails free distribution and use of software and continuous, community-based software development, can produce software with such characteristics, and can do so rapidly. OBJECTIVES The objective of the Real-Time Outbreak and Disease Surveillance (RODS) Open Source Project is to accelerate the deployment of computer-based outbreak and disease surveillance systems by writing software and catalyzing the formation of a community of users, developers, consultants, and scientists who support its use. METHODS The University of Pittsburgh seeded the Open Source Project by releasing the RODS software under the GNU General Public License. An infrastructure was created, consisting of a website, mailing lists for developers and users, designated software developers, and shared code-development tools. These resources are intended to encourage growth of the Open Source Project community. Progress is measured by assessing website usage, number of software downloads, number of inquiries, number of system deployments, and number of new features or modules added to the code base. RESULTS During September--November 2003, users generated 5,370 page views of the project website, 59 software downloads, 20 inquiries, one new deployment, and addition of four features. CONCLUSIONS Thus far, health departments and companies have been more interested in using the software as is than in customizing or developing new features. The RODS laboratory anticipates that after initial installation has been completed, health departments and companies will begin to customize the software and contribute their enhancements to the public code base.

[1]  Andrew W. Moore,et al.  Application of Information Technology: Automated Syndromic Surveillance for the 2002 Winter Olympics , 2003, J. Am. Medical Informatics Assoc..

[2]  Gregory F Cooper,et al.  Research Paper: Creating a Text Classifier to Detect Radiology Reports Describing Mediastinal Findings Associated with Inhalational Anthrax and Other Disorders , 2003, J. Am. Medical Informatics Assoc..

[3]  William B. Lober,et al.  Roundtable on bioterrorism detection: information system-based surveillance. , 2002, Journal of the American Medical Informatics Association : JAMIA.

[4]  Monson H. Hayes,et al.  Statistical Digital Signal Processing and Modeling , 1996 .

[5]  Michael M. Wagner,et al.  Value of ICD-9-Coded Chief Complaints for Detection of Epidemics , 2002, J. Am. Medical Informatics Assoc..

[6]  Peter J. Haug,et al.  Rapid deployment of an electronic disease surveillance system in the state of Utah for the 2002 Olympic Winter Games , 2002, AMIA.

[7]  Y. Elbert,et al.  Disease outbreak detection system using syndromic data in the greater Washington DC area. , 2002, American journal of preventive medicine.

[8]  Michael M. Wagner,et al.  Automatic Electronic Laboratory-Based Reporting of Notifiable Infectious Diseases , 2002, Emerging infectious diseases.

[9]  J. Marc Overhage,et al.  Research Paper: Detection of Pediatric Respiratory and Diarrheal Outbreaks from Sales of Over-the-counter Electrolyte Products , 2003, J. Am. Medical Informatics Assoc..

[10]  D. Talan,et al.  Syndromic surveillance for bioterrorism following the attacks on the World Trade Center--New York City, 2001. , 2003, MMWR. Morbidity and mortality weekly report.

[11]  Michael M. Wagner,et al.  Technical Description of RODS: A Real-time Public Health Surveillance System , 2003, Journal of the American Medical Informatics Association.

[12]  Eric S. Raymond,et al.  The cathedral and the bazaar - musings on Linux and Open Source by an accidental revolutionary , 2001 .

[13]  Robert T. Olszewski.  Bayesian Classification of Triage Diagnoses for the Early Detection of Epidemics , 2003, FLAIRS.

[14]  Andrew W. Moore,et al.  Data, network, and application: technical description of the Utah RODS Winter Olympic Biosurveillance System , 2002, AMIA.

[15]  Denise Koo,et al.  Statutory basis for public health reporting beyond specific diseases , 2003, Journal of Urban Health.

[16]  Wendy W. Chapman,et al.  Accuracy of three classifiers of acute gastrointestinal syndrome for syndromic surveillance , 2002, AMIA.

[17]  Daniel B. Neill,et al.  National Retail Data Monitor for public health surveillance. , 2004, MMWR supplements.

[18]  Fu-Chiang Tsui,et al.  Application of Information Technology: Design of a National Retail Data Monitor for Public Health Surveillance , 2003, J. Am. Medical Informatics Assoc..

[19]  Wendy W. Chapman,et al.  Fever detection from free-text clinical records for biosurveillance , 2004, Journal of Biomedical Informatics.

[20]  Claire V Broome,et al.  On the threshold. , 2002, American journal of preventive medicine.

[21]  A. Moore,et al.  Wsare: What’s strange about recent events? , 2003, Journal of Urban Health.

[22]  K. R. Pemble,et al.  The frontlines of medicine project: A proposal for the standardized communication of emergency department data for public health uses including syndromic surveillance for biological and chemical terrorism , 2002, Journal of urban health.

[23]  Lisa J. Trigg,et al.  Syndromic surveillance using automated collection of computerized discharge diagnoses , 2003, Journal of Urban Health.

[24]  A. Reingold,et al.  If syndromic surveillance is the answer, what is the question? , 2003, Biosecurity and bioterrorism : biodefense strategy, practice, and science.