Displaying results 1 - 7 of 7
-
Estimating the incidence of influenza cases that present to emergency departments
Content Type: Abstract
Our laboratory previously established the value of over-the-counter (OTC) sales data for the early detection of disease outbreaks. We found that thermometer sales (TS) increased significantly and early during influenza (flu) season.… read more… present to emergency departments R Villamarı́n, G Cooper, F-C Tsui, M Wagner, and J Espino Department of Biomedical … the following formula, which assumes that TS and ED visits are proportional to population size (pop) and that … of predicting outcomes that are related to flu ED visits based on TS. Our results suggest that the use of TS, … -
Modeling Clinician Detection Time of a Disease Outbreak Due to Inhalational Anthrax
Content Type: Abstract
We developed a probabilistic model of how clinicians are expected to detect a disease outbreak due to an outdoor release of anthrax spores, when the clinicians only have access to traditional clinical information (e.g., no computer-based alerts). We… read more… for clinicians to detect such an outbreak. Such estimates may be useful in planning for outbreaks and in assessing the … for clinicians to detect such an outbreak. Such estimates may be useful in planning for out- breaks and in assessing … is only seen by a health care provider once (no return visits) and each clinician diagnoses a given case of IA … -
A Comparison of Chief Complaints and Emergency Department Reports for Identifying Patients with Acute Lower Respiratory Syndrome
Content Type: Abstract
Automated syndromic surveillance systems often classify patients into syndromic categories based on free-text chief complaints. Chief complaints (CC) demonstrate low to moderate sensitivity in identifying syndromic cases. Emergency Department (ED)… read more… reports promise more detailed clinical information that may increase sensitivity of detection. Objective: Compare … a Random Forests Classifier. Gold Standard Classification com- prised majority vote of three physicians reading ED … classifiers by randomly split- ting the 272 cases into 70% train and 30% test sets and averaging performance over … -
A Method for Detecting and Characterizing Multiple Outbreaks of Infectious Diseases
Content Type: Abstract
We describe an automated system that can detect multiple outbreaks of infectious diseases from emergency department reports. A case detection system obtains data from electronic medical records, extracts features using natural language… read more… a probability distribution over the diseases each patient may have. Then, a multiple outbreak detection system (MODS) … a probability distribution over the diseases each patient may have. Then, a multiple outbreak detection system (MODS) … -
SyCo: A Probabilistic Machine Learning Method for Classifying Chief Complaints into Symptom and Syndrome Categories
Content Type: Abstract
Scientists have utilized many chief complaint (CC) classification techniques in biosurveillance including keyword search, weighted keyword search, and naïve Bayes. These techniques may utilize CC-to-syndrome or CC-… read more… keyword search, and naïve Bayes. These techniques may utilize CC-to-syndrome or CC-to-symptom-to-syndrome … keyword search,3 and naïve Bayes.4 These techniques may utilize CC-to-syndrome or CC-to-symptom-to-syndrome … keyword search, and naïve Bayes. These techniques may utilize CC-to-syndrome or CC-to-symptom-to-syndrome … -
Detecting Overlapping Outbreaks of Influenza
Content Type: Abstract
Influenza is a contagious disease that causes epidemics in many parts of the world. The World Health Organization estimates that influenza causes three to five million severe illnesses each year and 250,000-500,000 deaths. Predicting and… read more… temporally overlapping outbreaks are also common. These may be caused by different subtypes or outbreaks in multiple … temporally overlapping outbreaks are also common. These may be caused by different subtypes or outbreaks in multiple … -
A Multivariate Bayesian Scan Statistic
Content Type: Abstract
This paper develops a new method for multivariate spatial cluster detection, the ìmultivariate Bayesian scan statisticî (MBSS). MBSS combines information from multiple data streams in a Bayesian framework, enabling faster and more accurate… read more… and a set of data streams D = {Dm}. The outbreak types may be either specific ill- nesses (influenza, anthrax, … may include sources such as emergency department (ED) visits, with each stream representing a different chief … Communications in Sta- tistics: Theory and Methods, 1997, 26(6): 1481-1496. [3] Neill DB, Detection of spatial and …