Skip to main content

Gel Yulia

Description

Each year, influenza results in increased Emergency Department crowding which can be mitigated through early detection linked to an appropriate response. Although current surveillance systems, such as Google Flu Trends, yield near real-time influenza surveillance, few demonstrate ability to forecast impending influenza cases.

Objective

We sought to develop a practical influenza forecast model, based on real-time, geographically focused, and easy to access data, to provide individual medical centers with advanced warning of the number of influenza cases, thus allowing sufficient time to implement an intervention. Secondly, we evaluated how the addition of a real-time influenza surveillance system, Google Flu Trends, would impact the forecasting capabilities of this model.

Submitted by teresa.hamby@d… on
Description

Public health departments need enhanced surveillance tools for population monitoring, and external researchers have expertise and methods to provide these tools. However, collaboration with potential solution developers and students in academia, industry, and government has not been sufficiently close or well informed for rapid progress. Many peer-reviewed papers on biosurveillance methods have been published by researchers, but few methods have been adopted in systems used by health departments. In a 2013 BioSense User Group survey with responses from users in more than 40 U.S. states, access to improved analytic methods was a top priority. Among the tools most desired by respondents were the ESSENCE biosurveillance system with multiple analytic tools and statistical software packages such as SAS. Multiple obstacles have slowed the progress of practitioners and developers who seek the development and implementation of useful analytic tools. First, the epidemiological challenges and associated operational constraints are not sufficiently understood among academic developers. Many health departments do not have the resources to hire such developers beyond maintenance of information technology, and the health monitors are typically too busy to publish in peer-reviewed journals. Second, data cannot be shared because of privacy and proprietary limitations with varying local rules. Data-sharing has posed difficult administrative problems, both within and external to health departments, in the course of ISDS Technical Conventions committee efforts to promote interactions through use case problems. Third, aspects of situational awareness vary widely among health monitors at different jurisdictional levels, so analytical challenges and constraints vary widely among potential users. Practitioners have pointed out that “surveillance is local”, but local operational and data environments vary widely. A fourth main issue is cross-cultural: Understaffed health departments must respond to successive crises and often lack the time for requirements analysis and technical publication. Such client work situations complicate interaction with academic environments of semester schedules and limited grants and transient student support. This panel brings together academic statisticians who have had successful direct relationships with public health departments to discuss how they have dealt with these challenges.

Objective

The session will explore past collaborations between the scientist panelists and public health departments to highlight approaches that have and have not been effective and to recommend effective, sustainable relationship strategies for the mutual advancement of practical disease surveillance and relevant academic research.

Submitted by teresa.hamby@d… on