ArticleJournal of public health management and practice : JPHMP
Evaluation of Syndromic Surveillance Systems in 6 US State and Local Health Departments.
Article in Journal of public health management and practice : JPHMP. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
18 citing papers in PubMed, 31 citations in OpenAlex.
- Drawing on the Development Experiences of Infectious Disease Surveillance Systems Around the World.China CDC weekly · 2024Article
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- Early warning system using primary health care data in the post-COVID-19 pandemic era: Brazil nationwide case-study.Cadernos de saude publica · 2024Article
- DiD IT?: a differences-in-differences investigation tool to quantify the impact of local incidents on public health using real-time syndromic surveillance health data.Epidemiology and infection · 2023Article
- Linking coastal environmental and health observations for human wellbeing.Frontiers in public health · 2023Article
- Forecasting Hospital Visits Due to Influenza Based on Emergency Department Visits for Fever: A Feasibility Study on Emergency Department-Based Syndromic Surveillance.International journal of environmental research and public health · 2022Article
- Understanding occupational safety and health surveillance: expert consensus on components, attributes and example measures for an evaluation framework.BMC public health · 2022Review
- Public health surveillance in the U.S. Department of Veterans Affairs: evaluation of the Praedico surveillance system.BMC public health · 2022Article
- Towards integrated modeling of the long-term impacts of oil spills.Marine policy · 2021Article
- Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE): Overview, Components, and Public Health Applications.JMIR public health and surveillance · 2021Article
- Outbreak of Severe Vomiting in Dogs Associated with a Canine Enteric Coronavirus, United Kingdom.Emerging infectious diseases · 2021Article
- Evaluating multi-purpose syndromic surveillance systems - a complex problem.Online journal of public health informatics · 2021Article
- Approaching precision public health by automated syndromic surveillance in communities.PloS one · 2021Article
- Usefulness of Clinical Definitions of Influenza for Public Health Surveillance Purposes.Viruses · 2020Article
- Opportunities and Challenges for Developing Syndromic Surveillance Systems for the Detection of Social Epidemics.Online journal of public health informatics · 2020Article
- Demand Analysis and Management Suggestion: Sharing Epidemiological Data Among Medical Institutions in Megacities for Epidemic Prevention and Control.Journal of Shanghai Jiaotong University (science) · 2020Article
- Natural language generation for electronic health records.NPJ digital medicine · 2018Article
- An Evaluation of Syndromic Surveillance-Related Practices Among Selected State and Local Health Agencies.Journal of public health management and practice : JPHMPArticle
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveEvaluating public health surveillance systems is critical to ensuring that conditions of public health importance are appropriately monitored. Our objectives were to qualitatively evaluate 6 state and local health departments that were early adopters of syndromic surveillance in order to (1) understand the characteristics and current uses, (2) identify the most and least useful syndromes to monitor, (3) gauge the utility for early warning and outbreak detection, and (4) assess how syndromic surveillance impacted their daily decision making.
designWe adapted evaluation guidelines from the Centers for Disease Control and Prevention and gathered input from the Centers for Disease Control and Prevention subject matter experts in public health surveillance to develop a questionnaire.
participantsWe interviewed staff members from a convenience sample of 6 local and state health departments with syndromic surveillance programs that had been in operation for more than 10 years.
resultsThree of the 6 interviewees provided an example of using syndromic surveillance to identify an outbreak (ie, cluster of foodborne illness in 1 jurisdiction) or detect a surge in cases for seasonal conditions (eg, influenza in 2 jurisdictions) prior to traditional, disease-specific systems. Although all interviewees noted that syndromic surveillance has not been routinely useful or efficient for early outbreak detection or case finding in their jurisdictions, all agreed that the information can be used to improve their understanding of dynamic disease control environments and conditions (eg, situational awareness) in their communities.
conclusionIn the jurisdictions studied, syndromic surveillance may be useful for monitoring the spread and intensity of large outbreaks of disease, especially influenza; enhancing public health awareness of mass gatherings and natural disasters; and assessing new, otherwise unmonitored conditions when real-time alternatives are unavailable. Future studies should explore opportunities to strengthen syndromic surveillance by including broader access to and enhanced analysis of text-related data from electronic health records. Health departments may accelerate the development and use of syndromic surveillance systems, including the improvement of the predictive value and strengthening the early outbreak detection capability of these systems. These efforts support getting the right information to the right people at the right time, which is the overarching goal of CDC's Surveillance Strategy.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.