Implementing Syndromic Surveillance: A Practical Guide Informed by the Early Experience

Mandl, Kenneth D.; Overhage, J. Marc; Wagner, Michael M.; Lober, William B.; Sebastiani, Paola; Mostashari, Farzad; Pavlin, Julie A.; Gesteland, Per H.; Treadwell, Tracee A.; Koski, Eileen; Hutwagner, Lori; Buckeridge, David L.; Aller, Raymond D.; Grannis, Shaun J.

doi:10.1197/jamia.m1356

Cited by 334 publications

(261 citation statements)

References 43 publications

Supporting

Mentioning

245

Contrasting

Unclassified

Order By: Relevance

“…Established in 2006 by the International Society for Disease Surveillance (ISDS), DiSTRIBuTE is organized around existing state and local surveillance capabilities and expertise. 32 The system relies on summarized counts of fever and respiratory and influenza-likeillness (ILI) syndromes reported by age group from state and local systems. The data are visualized and used to provide public health practitioners with age-specific weekly influenza trends on an ongoing basis.…”

Section: Connecting For Health: Lessons Learnedmentioning

confidence: 99%

Collecting And Sharing Data For Population Health: A New Paradigm

Diamond¹,

Mostashari²,

Shirky³

2009

Health Affairs

View full text Add to dashboard Cite

Health information technology (IT) has great potential to transform health care and inform population health goals in clinical research, quality measurement, and public safety. To fully realize the benefits of health IT for population health, we must focus on new models that maximize efficiency, encourage rapid learning, and protect patients' privacy. In this paper we explore the advantages of a networked model for analyzing population health information, providing several examples. Although broadening the use of networked models is challenging, the societal benefits of a networked model merit continued exploration and the development of workable solutions. [Health Affairs 28, no. 2 (2009) T h e r e i s g r e at p o t e n t i a l f o r health information technology (IT) to aid in achieving population health goals in the areas of clinical research, quality measurement, and public safety. 1 The need to improve health IT is driven by several factors: rising health care costs; well-documented gaps in quality; concern about safety and efficiency; a need for improved accountability; an increased awareness of bioterrorism as a possible threat; a need to monitor the safety and outcomes of drugs and treatments; and a call for studies of the comparative effectiveness of procedures for diagnosis and treatment. 2 IT can facilitate data collection and analysis across data sources and support the sharing of information in near real time across institutions, scientific disciplines, and geographic boundaries.

show abstract

Section: Connecting For Health: Lessons Learnedmentioning

confidence: 99%

Collecting And Sharing Data For Population Health: A New Paradigm

Diamond¹,

Mostashari²,

Shirky³

2009

Health Affairs

View full text Add to dashboard Cite

show abstract

“…An emerging approach to more timely detection is syndromic surveillance [10], which identifies infected individuals early in the course of their disease, generally before a confirmed diagnosis is made. Patients are classified by syndrome, such as acute respiratory infection or gastrointestinal illness, based on a variety of data sources ranging from purchase of over the counter medications [11] to primary care physician and emergency department (ED) logs [12,13].…”

Section: Introductionmentioning

confidence: 99%

A Bayesian dynamic model for influenza surveillance

Sebastiani¹,

Mandl²,

Szolovits³

et al. 2006

Statist. Med.

View full text Add to dashboard Cite

SUMMARYThe severe acute respiratory syndrome (SARS) epidemic, the growing fear of an influenza pandemic and the recent shortage of flu vaccine highlight the need for surveillance systems able to provide early, quantitative predictions of epidemic events. We use dynamic Bayesian networks to discover the interplay among four data sources that are monitored for influenza surveillance. By integrating these different data sources into a dynamic model, we identify in children and infants presenting to the pediatric emergency department with respiratory syndromes an early indicator of impending influenza morbidity and mortality. Our findings show the importance of modelling the complex dynamics of data collected for influenza surveillance, and suggest that dynamic Bayesian networks could be suitable modelling tools for developing epidemic surveillance systems.

show abstract

“…The RRTs compile and analyze data to identify the deficiencies experienced in the implementation of the response measures. The necessary modifications are then incorporated in the contingency plan for future [11].…”

Section: Introductionmentioning

confidence: 99%

“…Syndrome surveillance systems seek to use existing health data in real time to provide immediate analysis and feedback to those charged with investigation and follow-up of potential outbreaks. The model of large scale exposure to the agents of bioterrorism (by use of vaccines and antibiotics) has dramatic potential for saving lives and expense [10][11][12]. The public health approach to bioterrorism must begin with the development of local and state-level plans.…”

Section: Introductionmentioning

confidence: 99%

Bioterrorism : A Public Health Perspective

Das¹,

Kataria

2010

Medical Journal Armed Forces India

View full text Add to dashboard Cite

The intentional release or threat of release of biologic agents (i.e. viruses, bacteria, fungi or their toxins) in order to cause disease or death among human population or food crops and livestock to terrorize a civilian population or manipulate the government in the present scenario of increased terrorist activity has become a real possibility. The most important step in the event of a bioterrorist attack is the identification of the event. This can be achieved by generating awareness, having high degree of suspicion and having a good surveillance system to assist quick detection. Bioterrorist attacks could be covert or announced and caused by virtually any pathogenic microorganism. Bioterrorist agents of major concern have been categorized as A, B and C based on the priority of the agents to pose a risk to the national security and the ease with which they can be disseminated. The five phases of activities in dealing with a bioterrorist attack are preparedness phase, early warning phase, notification phase, response phase and recovery phase. A bioterrorism attack in a public place is a public health emergency. Early detection and rapid investigation is the key to contain such attacks. The role of public health epidemiologist is critical not only in determining the scope and magnitude of the attack but also in effective implementation of interventions. MJAFI 2010; 66 : 255-260

show abstract

Implementing Syndromic Surveillance: A Practical Guide Informed by the Early Experience

Cited by 334 publications

References 43 publications

Collecting And Sharing Data For Population Health: A New Paradigm

Collecting And Sharing Data For Population Health: A New Paradigm

A Bayesian dynamic model for influenza surveillance

Bioterrorism : A Public Health Perspective

Contact Info

Product

Resources

About