Skip to main content

Data Analysis

Description

The Activity Monitoring Operating Characteristic (AMOC) curve is a useful and popular method for assessing the performance of algorithms that detect outbreaks of disease [1]. As it is typically applied in biosurveillance, the AMOC curve plots the expected time to detection (since the outbreak began) as a function of the false alert rate. An ideal algorithm has zero false alerts and a detection time of zero. An al-ternative, conceptually equivalent version of the AMOC curve plots (T – detection_time) as a function of the false alert rate, where T is a maximum mean-ingful detection time. We focus on this version. 

Objective

We introduce a new measure for evaluating alerting algorithms, which is a generalization of the AMOC curve [1]. For a given rate of false positives alerts, the new measure estimates the time between when an alert is raised and when clinicians are expected to detect the outbreak on their own. We call this measure the Expected Warning Time (EWT).

Referenced File
Submitted by elamb on
Description

Investigators have used the volume of internet search queries to model disease incidence, especially influenza and general consumer behavior [1]. Our group has used search volume to model interest in FDA safety alerts and adverse drug event incidence. We found evi- dence of changes in search behavior following warnings and the ex- pected relationship between search volume and adverse drug event incidence. Thus, search volume may help provide near real time sur- veillance of drug use patterns to help monitor and mitigate risk to the population from adverse drug events. However, the use of search query volume as a proxy for drug use has yet to be validated.

We attempt to validate search volume estimation of drug utilization in three ways: 1) explore seasonal variations in search volume and outpatient utilization, 2) monitor change between substitute drugs fol- lowing patent expirations and 3) use search volume estimation meth- ods to estimate TB incidence.

Objective

To validate search volume estimation for outpatient medication prescribing.

Submitted by dbedford on
Description

A large part of the applied research on syndromic surveillance targets seasonal epidemics, e.g. influenza, winter vomiting disease, rotavirus and RSV, in particular when dealing with preclinical indicators, e.g. web traffic. The research on local outbreak surveillance is more limited. Two studies of teletriage data (NHS Direct) have shown positive and negative results respectively. Studies of OTC pharmacy sales have reported similar equivocal performance. As far as we know, no systematic comparison of data sources with respect to multiple point-source outbreaks has so far been published. In the current study, we evaluated the potential of three data sources for syndromic surveillance by analyzing the correspondence between signal properties and point-source outbreak characteristics.

 

Objective

For the purpose of developing a national system of outbreak surveillance, we compared local outbreak signals in three sources of syndromic data – telephone triage of acute gastroenteritis (Swedish Health Care Direct 1177), web queries about symptoms of gastrointestinal illness (Stockholm County’s website for healthcare information), and OTC pharmacy sales of anti-diarrhea medication.

Submitted by teresa.hamby@d… on
Description

On July 11, 2012, New Jersey Department of Health (DOH) Communicable Disease Service (CDS) surveillance staff received email notification of a statewide anomaly in EpiCenter for Paralysis. Two additional anomalies followed within three hours. Since Paralysis Anomalies are uncommon, staff initiated an investigation to determine if there was an outbreak or other event of concern taking place. Also at question was whether receipt of multiple anomalies in such a short time span was statistically or epidemiologically significant.

Objective

To describe the investigation of a statewide anomaly detected by a newly established state syndromic surveillance system and usage of that system.

Submitted by dbedford on
Description

The French syndromic surveillance system SurSaUD was set up by the French institute for public health surveillance (InVS) in 2004. The system is based on three main data sources: 1) the attendances in the Emergency departments (ED), 2) the consultations to emergency General Practitioners’ associations SOS Médecins, 3) the mortality data from civil status offices and e-certificates.

In 2012, 400 of the 710 ED and 59 of the 62 GP’s associations are involved in the system. 80% of the national mortality is also collected. Given this large database and the need to analyze data in a short delay to reach the early warning objective of the system, a specific software has been developed.

 

Objective

The presentation describes the design and the main functionalities of the software developed to support the data management and data analysis of the French syndromic surveillance system.

Submitted by hparton on
Description

The National Collaborative for Bio-Preparedness (NCB-Prepared) was established in 2010 to create a biosurveillance resource to enhance situational awareness and emergency preparedness. This jointinstitutional effort has drawn on expertise from the University of North Carolina- Chapel Hill, North Carolina State University, and SAS Institute, leveraging North Carolina’s role as a leader in syndromic surveillance, technology development and health data standards. As an unprecedented public/private alliance, they bring the flexibility of the private sector to support the public sector. The project has developed a functioning prototype system for multiple states that will be scaled and made more robust for national adoption.

Objective:

Demonstrate the functionality of the National Collaborative for Bio-Preparedness system.

 

Submitted by Magou on
Description

Analyses produced by epidemiologists and public health practitioners are susceptible to bias from a number of sources including missing data, confounding variables, and statistical model selection. It often requires a great deal of expertise to understand and apply the multitude of tests, corrections, and selection rules, and these tasks can be time-consuming and burdensome. To address this challenge, Aptima began development of CARRECT, the Collaborative Automation Reliably Remediating Erroneous Conclusion Threats system. When complete, CARRECT will provide an expert system that can be embedded in an analyst’s workflow. CARRECT will support statistical bias reduction and improved analyses and decision making by engaging the user in a collaborative process in which the technology is transparent to the analyst.

Objective

The objective of the CARRECT software is to make cutting edge statistical methods for reducing bias in epidemiological studies easy to use and useful for both novice and expert users.

 

Submitted by uysz on
Description

ECDC long term strategies for surveillance include analysis of trends of communicable disease of public health importance for European Union countries to guide public health actions. The European Surveillance System (TESSy) holds data on 49 communicable diseases reported by 30 countries for at least the past five years. To simplify time related analysis using surveillance data, ECDC launched a project to enable descriptive and routine TSA without the need for complex programming.

Objective

To discuss challenges and opportunities in the introduction of an automated approach for time series analysis (TSA) regarding epidemiological methodology for generation of hypotheses, steps to be performed and interpretation of outputs.

 

Submitted by uysz on
Description

Under the revised International Health Regulations (IHR [2005]) one of the eight core capacities is public health surveillance. In May 2012, despite a concerted effort by the global community, the World Health Organization (WHO) reported out that a significant number of member states would not achieve targeted capacity in the IHR (2005) surveillance core capacity. Currently, there is no model to identify and measure these gaps in surveillance performance. Likewise, there is no toolset to assess interventions by cost and estimate the ROI. We developed a new conceptual framework that: (1) described the work practices to achieve effective and efficient public health surveillance; (2) could identify impediments or gaps in performance; and (3) will assist program managers in decision making.

Objective

To conceive and develop a model to identify gaps in public health surveillance performance and provide a toolset to assess interventions, cost, and return on investment (ROI).

Submitted by teresa.hamby@d… on