ArticleMMWR supplements2005
High-fidelity injection detectability experiments: a tool for evaluating syndromic surveillance systems.
Article in MMWR supplements, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- A test of syndromic surveillance using a severe acute respiratory syndrome model.The American journal of emergency medicine · 2009Trial
- Evaluating multi-purpose syndromic surveillance systems - a complex problem.Online journal of public health informatics · 2021Article
- Comparison of Statistical Algorithms for the Detection of Infectious Disease Outbreaks in Large Multiple Surveillance Systems.PloS one · 2016Article
- Validity of evaluation approaches for outbreak detection methods in syndromic surveillance systems.Iranian journal of public health · 2012Article
- An empirical comparison of spatial scan statistics for outbreak detection.International journal of health geographics · 2009Article
- Detection of disease outbreaks by the use of oral manifestations.Journal of dental research · 2009Article
- Template-driven spatial-temporal outbreak simulation for outbreak detection evaluation.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2008Article
- Using GIS to create synthetic disease outbreaks.BMC medical informatics and decision making · 2007Article
- Approaches to the evaluation of outbreak detection methods.BMC public health · 2006Article
- High-fidelity injection detectability experiments: a tool for evaluating syndromic surveillance systems.MMWR supplements · 2005Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
introductionWhen public health surveillance systems are evaluated, CDC recommends that the expected sensitivity, specificity, and timeliness of surveillance systems be characterized for outbreaks of different sizes, etiologies, and geographic or demographic scopes. High-Fidelity Injection Detectability Experiments (HiFIDE) is a tool that health departments can use to compute these metrics for detection algorithms and surveillance data that they are using in their surveillance system.
objectiveThe objective of this study is to develop a tool that allows health departments to estimate the expected sensitivity, specificity, and timeliness of outbreak detection.
methodsHiFIDE extends existing semisynthetic injection methods by replacing geometrically shaped injects with injects derived from surveillance data collected during real outbreaks. These injects maintain the known relation between outbreak size and effect on surveillance data, which allows inferences to be made regarding the smallest outbreak that can be expected to be detectable.
resultsAn example illustrates the use of HiFIDE to analyze detectability of a waterborne Cryptosporidium outbreak in Washington, DC.
conclusionHiFIDE enables public health departments to perform system validations recommended by CDC. HiFIDE can be obtained for no charge for noncommercial use (http://www.hifide.org).
Indexed as
Identifiers
16177698PMC3586808What 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.