Data Sharing Through Dashboards: The Who, What, Where, When, and Why

Presented April 26, 2019.

Description: Join us for this lightning talk webinar experience where you will see multiple examples of data dashboards and learn more about who they were created for, how they were developed, where and when the data is being shared, and what impact the dashboard has had on improving public health practice. We will hear from 5 presenters from around the public health community as they discuss their work on opioid, flu, and general disease surveillance dashboards.

Presenters addressed the following questions:

April 30, 2019

A Novel Method for Rapid Mapping of the Spatial Intensity of Influenza Epidemics

Surveillance of influenza epidemics is a priority for risk assessment and pandemic preparedness. Mapping epidemics can be challenging because influenza infections are incompletely ascertained, ascertainment can vary spatially, and often a denominator is not available. Rapid, more refined geographic or spatial intelligence could facilitate better preparedness and response.

June 18, 2019

Calendar effects to forecast influenza seasonality: A case study in Milwaukee, WI

Influenza viral infection is contentious, has a short incubation period, yet preventable if multiple barriers are employed. At some extend school holidays and travel restrictions serve as a socially accepted control measure. A study of a spatiotemporal spread of influenza among school-aged children in Belgium illustrated that changes in mixing patterns are responsible for altering disease seasonality3.

June 18, 2019

Effects of the El Nino Southern Oscillation on Influenza Peak Activity Timing

Influenza causes a significant burden to the world every year. In the temperate zone, influenza usually prevalent in the winter season, however, it is hardly predictable when the influenza epidemic will begin and when the peak activity will come. Influenza has a peak in early winter sometimes and a peak in late winter in another year. However, it is not well known what determines these epidemics timing, and the global climate change is expected to influence the timing of influenza epidemics.

June 18, 2019

Enhancing Syndromic Surveillance with Procedure Data: A 2017-8 Influenza Case Study

Syndromic surveillance achieves timeliness by collecting prediagnostic data, such as emergency department chief complaints, from the start of healthcare interactions. The tradeoff is less precision than from diagnosis data, which takes longer to generate. As the use and sophistication of electronic health information systems increases, additional data that provide an intermediate balance of timeliness and precision are becoming available. Information about the procedures and treatments ordered for a patient can indicate what diagnoses are being considered.

June 18, 2019

ICU respiratory admissions data for influenza severity surveillance?

While influenza-like-illness (ILI) surveillance is well-organized at primary care level in Europe, little data is available on more severe cases. With retrospective data from ICU's we aim to fill this current knowledge gap and to explore its worth for prospective surveillance. Using multiple parameters proposed by the World Health Organization we estimated the burden of severe acute respiratory infections (SARI) to ICU and how this varies between influenza epidemics.

June 18, 2019

Influenza laboratory testing and its application in timely Department of Defense biosurveillance

Timely influenza data can help public health decision-makers identify influenza outbreaks and respond with preventative measures. DoD ESSENCE has the unique advantage of ingesting multiple data sources from the Military Health System (MHS), including outpatient, inpatient, and emergency department (ED) medical encounter diagnosis codes and laboratory-confirmed influenza data, to aid in influenza outbreak monitoring. The Influenza-like Illness (ILI) syndrome definition includes ICD-9 or ICD-10 codes that may increase the number of false positive alerts.

June 18, 2019

Influenza Surveillance Using Wearable Mobile Health Devices

Influenza surveillance has been a major focus of Data Science efforts to use novel data sources in population and public health. This interest reflects the public health utility of timely identification of flu outbreaks and characterization of their severity and dynamics. Such information can inform mitigation efforts including the targeting of interventions and public health messaging. The key requirement for influenza surveillance systems based on novel data streams is establishing their relationship with underlying influenza patterns.

June 18, 2019

Leaving a Mobile Footprint: Utilizing Data to Combat the 2017 - 2018 Influenza Season

The 2017 - 2018 influenza season was classified by the Centers for Disease Control and Prevention (CDC) as "high severity"™ across all age groups. Furthermore, CDC noted that this was the first year to be categorized as such, with the highest peak percentage of influenza-like-illnesses (ILI), since 2009. In Harris County alone, there were 2,665 positive flu tests reported in comparison to the previous season at 1,395 positive tests.

June 18, 2019

National Surveillance for Health-Related Workplace Absenteeism, United States 2017-18

During an influenza pandemic, when hospitals and doctors'™ offices are or are perceived to be overwhelmed, many ill people may not seek medical care. People may also avoid medical facilities due to fear of contracting influenza or transmitting it to others. Therefore, syndromic methods for monitoring illness outside of health care settings are important adjuncts to traditional disease reporting. Monitoring absenteeism trends in schools and workplaces provide the archetypal examples for such approaches.

June 18, 2019


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