Grant: Operating Grant - PA: Existing and Emerging Threats & Chronic Disease

The recent H1N1 and SARS pandemics demonstrate that being well-prepared for the national and international spread of infectious diseases is vital for public health and healthcare agencies worldwide. Syndromic surveillance is a way to track the incidence of infectious diseases by monitoring signs and symptoms and the population's use of healthcare services. This information can provide an earlier indication of unexpected increases, thus allowing more efficient and effective emergency public health responses. In 2006, a syndromic surveillance system was developed in Alberta, the Alberta Real Time Syndromic Surveillance Net (ARTSSN), to track information from emergency department (ED) visits, HealthLink calls to trained nurses, and school absence reports to provide advanced warnings about unexpected increases to Alberta Health Services (AHS). Through an engaged project with AHS, we want to use ARTSSN data to provide an even earlier indication of increases in healthcare use related to influenza-like illness (ILI) by predicting these increases before they occur rather than waiting until they have already happened. To do this, we will develop prediction models based on historic patterns of ILI-related healthcare use and, based on this information, predict when ILI-related healthcare use is expected to increase. We will then use our models to provide an early warning to AHS that healthcare use is expected to increase, providing the critical time needed for them to respond effectively. AHS can prepare for these high volumes of healthcare use by, for example, increasing staffing levels at hospitals; distributing necessary supplies; providing the public with up-to-date information; and opening an influenza assessment centre to divert excess volume at EDs. Advanced knowledge about an infectious disease epidemic should enable earlier and more effective preparation, which will help to minimize the spread of disease and improve the outcomes for those infected.