Goodin Kate

A seroprevalence survey carried out in four counties in the Tampa Bay area of Florida (Hillsborough, Pinellas, Manatee and Pasco) provided an estimate of cumulative incidence of infection due to the 2009 influenza A (H1N1) as of the end of that year’s pandemic. During the pandemic, high-level decison-makers wanted timely, credible forecasts as to the likely near-term course of the pandemic. The cumulative percentage of people who will be infected by the end of the epidemic can be estimated from the intrinsic reproductive number of the viral strain, its R0 , which can be measured early in the epidemic. If the current cumulative number of infections can be estimated, then one can determine what fraction of the eventual total number of infected people have already been infected.

Objective

To estimate the number of infections due to the novel 2009 influenza A/H1N1 virus corresponding to each ED visit for ILI in a four-county area of Florida. Knowing such ratios, one could (in future similar situations) estimate the cumulative number of infections due to a novel influenza virus in a population.

Super Bowl XLIX took place on February 1st, 2015 in Glendale, Arizona. In preparation for this large scale public event and related activities, the Maricopa County Department of Public Health (MCDPH) developed methods for enhanced surveillance, situational awareness and early detection of public health emergencies.

Objective

To describe the enhanced epidemiologic surveillance efforts in place during Super Bowl XLIX and related events, review epidemiologic surveillance results, discuss novel approaches for near real-time surveillance for situational awareness and early event detection and examine lessons learned for surveillance strategies during mass gatherings.

Monitoring heat-related illness (HRI) is a public health priority in Maricopa County, Arizona. Since 2006, Maricopa County Department of Public Health has utilized data from hospital discharges, medical examiner preliminary reports, and death certificates to quantify heat-related morbidity and mortality, but these surveillance methods take time. Identifying HRI more quickly would improve situational awareness and allow public health officials to launch a more immediate response to extreme heat events. Arizona began using BioSense 2.0 in July 2014 to collect chief complaint and diagnosis data for syndromic surveillance. The BioSense Front End Application uses a standard query definition for HRI (i.e., “Heat, excessive”), but this definition may perform differently for each jurisdiction.

Objective

To evaluate the pre-defined “Heat, excessive” query in BioSense 2.0 using recent Maricopa County, Arizona data; quantify the number of cases retrieved by the query due to chief complaint terms rather than clinical diagnosis; and provide a list of terms to be considered for exclusion criteria while developing a custom query

The mission of the Maricopa County Department of Public Health (MCDPH; Arizona) is to protect and promote the health and well-being of its residents and visitors. Surveillance efforts allow epidemiologists to quantify and characterize public health threats, but traditional methods take time. In an effort to enhance situational awareness, the Office of Epidemiology dedicated resources to begin developing a robust syndromic surveillance program. This abstract outlines steps for enhancing syndromic surveillance at a local public health department.

Objective

To demonstrate how a local public health department used the Centers for Disease Control and Prevention (CDC) Framework for Program Evaluation and a logic model to enhance its syndromic surveillance program.