A Method for Detecting and Characterizing Multiple Outbreaks of Infectious Diseases

We describe an automated system that can detect multiple outbreaks of infectious diseases from emergency department reports. A case detection system obtains data from electronic medical records, extracts features using natural language processing, then infers a probability distribution over the diseases each patient may have. Then, a multiple outbreak detection system (MODS) searches for models of multiple outbreaks to explain the data. MODS detects outbreaks of influenza and non-influenza influenza-like illnesses (NI-ILI).

August 07, 2017

Situational Awareness of Health Events Using Social Media and the SMART Dashboard

 Numerous methods using social media for syndromic surveillance and disease tracking have been developed. Many websites use Twitter and other social media to track specific diseases or syndromes.1 Many are intended for public use and the extent of use by public health agencies is limited.2 Our work builds on 4 years of experience by our multi-disciplinary team3 with a focus on local surveillance of influenza. 4,5

Objective

September 18, 2017

Towards Influenza Surveillance in Military Populations Using Novel and Traditional Sources

Influenza-like illness (ILI) remains a significant public health burden to both the general public and the U.S. Department of Defense. Military personnel are especially susceptible to disease outbreaks owing to the often-crowded living quarters, substantial geographic movement, and physical stress placed upon them. Currently, the military employs syndromic surveillance on electronic reporting of clinical diagnoses.

September 19, 2017

Syndromic Surveillance Evaluation of Influenza Activity in At-Risk Sub-Populations

Near real-time emergency department chief complaint data is accessed through Florida’s syndromic surveillance system: Electronic Surveillance System for the Early Notification of Communitybased Epidemics-Florida (ESSENCE-FL). The Florida Department of Health relies heavily upon these data for timely surveillance of influenza and influenza-like illness (ILI). Hospital discharge data available from the Florida Agency for Health Care Administration (AHCA) captures information about influenza-associated ED visits and is considered complete.

September 19, 2017

Using Laboratory Data to Aid Early Warning in Prospective Influenza Mortality Surveillance

Several countries prospectively monitor influenza-attributable mortality using a variation of the Serfling seasonal time series model that uses sinusoidal terms for seasonality. Typically, a seasonal model from previous years is used to forecast current expected mortality. Using laboratory surveillance time series data in the model may enhance interpretation of the surveillance information.

Objective

September 20, 2017

Avian Flu, Ebola, MERS, and Other Emerging Challenges for Influenza Surveillance Practitioners

Public health practitioners endeavor to expand and refine their syndromic and other advanced surveillance systems which are designed to supplement their existing laboratory testing and disease surveillance toolkit. While much of the development and widespread implementation of these systems was previously supported by public health preparedness funding, the reduction of these monies has greatly constrained the ability of public health agencies to staff and maintain these systems.

August 23, 2017

Data Blindspots: High-Tech Disease Surveillance Misses the Poor

Evidence from over 100 years of epidemiological study demonstrates a consistent, negative association between health and economic prosperity. In many settings, it is clear that causal links exist between lower socioeconomic status and both reduced access to healthcare and increased disease burden. However, our study is the first to demonstrate that the increased disease burden in at-risk populations interacts with their reduced access to healthcare to hinder surveillance.

Objective

August 31, 2017

Estimating FluNearYou Correlation to ILINet at Different Levels of Participation

Flu Near You allows individuals to volunteer to be a sentinel node of the syndromic surveillance (SyS) network. The platform has the potential to provide insight into the spread of influenza-like illness (ILI). CDC’s ILINet is the gold standard for tracking ILI at the national level, but does not track into the local level. Local health departments (LHD) frequently express a need for granular data specific to their jurisdictions. FNY attempts to meet this need by collecting and sharing data at the zip code level.

August 31, 2017

Impact of Interventions on Influenza A(H7N9) Virus Activity in Live Poultry Markets

H7N9 virus emerged in Eastern China in March 2013, which led to >550 human cases and >200 deaths in 2 years. Live poultry markets (LPMs) are considered as a major source of human H7N9 infections. In late 2013, the virus had spread to the southern provinces including Guangdong. Its provincial capital Guangzhou, detected its first local H7N9 human case in mid-January 2014 and reaching 10 cases in a month. As a response, Guangzhou government announced a two-week city-wide market closure, banning trading and storing of live poultry.

October 10, 2017

Utility and Acceptability of Influenza Surveillance amongst Emergency Providers

Each year, influenza affects approximately 5-20% of the United States population causing over 200,000 hospitalizations and 3,000 – 49,000 death. As a key point of entry to the health care system, EDs are responsible for the initial management and treatment of a substantial proportion of these influenza patients, thus directly impacting overall public health. As the front line of influenza diagnosis and treatment, ED providers may benefit from real-time easily shared influenza surveillance information.

Objective

December 29, 2017

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