How Missing Discharge Diagnosis Data in Syndromic Surveillance Leads to Coverage Gaps

Indiana utilizes the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE) to collect and analyze data from participating hospital emergency departments. This real-time collection of health related data is used to identify disease clusters and unusual disease occurrences. By Administrative Code, the Indiana State Department of Health (ISDH) requires electronic submission of chief complaints from patient visits to EDs. Submission of discharge diagnosis is not required by Indiana Administrative Code, leaving coverage gaps.

January 25, 2018

Opioid Surveillance using Social Media: How URLs are shared among Reddit members

Nearly 100 people per day die from opioid overdose in the United States. Further, prescription opioid abuse is assumed to be responsible for a 15-year increase in opioid overdose deaths. However, with increasing use of social media comes increasing opportunity to seek and share information. For instance, 80% of Internet users obtain health information online, including popular social interaction sites like Reddit (http://www.reddit.com), which had more than 82.5 billion page views in 20153.

January 21, 2018

Machine Learning for Identifying Relevance to Biosurveillance in Multilingual Text

Global biosurveillance is an extremely important, yet challenging task. One form of global biosurveillance comes from harvesting open source online data (e.g. news, blogs, reports, RSS feeds). The information derived from this data can be used for timely detection and identification of biological threats all over the world. However, the more inclusive the data harvesting procedure is to ensure that all potentially relevant articles are collected, the more data that is irrelevant also gets harvested. This issue can become even more complex when the online data is in a non-native language.

January 25, 2018

Leveraging Discussions on Reddit for Disease Surveillance

In recent years, individuals have been using social network sites like Facebook, Twitter, and Reddit to discuss health-related topics. These social media platforms consequently became new avenues for research and applications for researchers, for instance disease surveillance. Reddit, in particular, can potentially provide more in-depth contextual insights compared to Twitter, and Reddit members discuss potentially more diverse topics than Facebook members. However, identifying relevant discussions remains a challenge in large datasets like Reddit.

January 21, 2018

Niche Modeling of Dengue Fever Using Remotely Sensed Environmental Factors and BRT

Dengue Fever (DF) is a vector-borne disease of the flavivirus family carried by the Aedes aegypti mosquito, and one of the leading causes of illness and death in tropical regions of the world. Nearly 400 million people become infected each year, while roughly one-third of the world’s population live in areas of risk. Dengue fever has been endemic to Colombia since the late 1970s and is a serious health problem for the country with over 36 million people at risk.

January 25, 2018

Qualitative and Quantitative Predictions of Infectious Diseases in Shirak Marz

The frequency of disease outbreaks varies as a result of complex biological processes. Analysis of these frequencies can reveal patterns that can serve as a basis for predictions.

Objective:

The goal of this study was to identify the periodicity of seven zooanthroponoses in humans, and set epidemic thresholds for future occurrences.

January 21, 2018

Quantifying Model Form Uncertainty of Epidemic Forecasting Models from Incidence Data

Uncertainty Quantification (UQ), the ability to quantify the impact of sample-to-sample variations and model misspecification on predictions and forecasts, is a critical aspect of disease surveillance. While quantifying the impact of stochastic uncertainty in the data is well understood, quantifying the impact of model misspecification is significantly harder. For the latter, one needs a "universal model" to which more restrictive parametric models are compared too.

Objective:

January 25, 2018

Animals positive for Yersinia pestis in Armenia

Plague was first identified in Armenia in 1958 when Y. pestis was isolated and cultured from the flea species Ct. teres collected from the burrows of common voles in the northwestern part of the country. In the process of digitalizing archived data, a statistical and spatial analysis of the species composition of mammals and parasites involved in the epizootic process of plague between 1958 and 2016 was performed.

Objective:

January 21, 2018

A Suite of Mechanistic Epidemiological Decision Support Tools

We present the EpiEarly, EpiGrid, and EpiCast tools for mechanistically-based biological decision support. The range of tools covers coarse-, medium-, and fine-grained models. The coarse-grained, aggregated time-series only data tool (EpiEarly) provides a statistic quantifying epidemic growth potential and associated uncertainties. The medium grained, geographically-resolved model (EpiGrid) is based on differential equation type simulations of disease and epidemic progression in the presence of various human interventions geared toward understanding the role of infection control, early vs.

January 25, 2018

Electronic case reporting of STIs: Are non-existent codes the reason for missing information?

Under the CDC STD Surveillance Network (SSuN) Part B grant, WA DOH is testing eICR of sexually transmitted infections (STI) with a clinical partner. Existing standard vocabulary codes were identified to represent previously-identified information gaps, or the need for new codes or concepts was identified.

Objective:

January 21, 2018

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