Surveillance Systems

Beginning on March 13, 2011, ACDC experienced an unusual increase in reported bacterial meningitis cases in Los Angeles (LA) County. Early in the investigation, there were few epidemiological links between the cases. Three cases were homeless; two resided at the same Skid Row shelter in downtown LA. ACDC assessed its syndromic surveillance databases to help gauge the scope of the outbreak and detect potentially overlooked cases.

Objective

To describe the complementary usage of electronic emergency department (ED) data, Coroner deaths, and 911 dispatch call center data in a bacterial meningitis outbreak.

INDICATOR provides an open source platform for biosurveillance and outbreak detection. Data sources currently include emergency department, patient advisory nurse, outpatient clinic, and school absence activity We are currently working with the University of Illinois College of Veterinary Medicine and will include veterinary data so that animal and human health data can be analyzed together.

Objective

INDICATOR, an existing biosurveillance system, required an updated user interface to support more data sources and more robust reporting and data visualization.

Influenza is a recurrent viral disease with potential to result in pandemics. Therefore it is necessary to have a timely, responsive and accurate detection. The use of Twitter as a source for data mining in biosurveillance has been previously shown useful, and it also has a potential for real-time visualization. However these efforts target messages in English, omitting from surveillance the part of users that speaks other languages, such as Spanish.

Objective

Identify the potential of Twitter as a source for monitoring and visualizing content regarding Influenza-like-Illness in Spanish-speaking populations for biosurveillance purposes.

Particularly in resource-poor settings, syndromic surveillance has been proposed as a feasible solution to the challenges in meeting the new disease surveillance requirements included in the World Health Organization's International Health Regulations (2005).

Objective

The aim of this study is to demonstrate how syndromic surveillance systems are working in low-resource settings while identifying the key best practices and considerations.

Animal bites may have potentially devastating consequences, including physical and emotional trauma, infection, rabies exposure, hospitalization, and, rarely, death. NC law requires animal bites be reported to local health directors. However, methods for recording and storing bite data vary among municipalities. NC does not have a statewide system for reporting and surveillance of animal bites. Additionally, many animal bites are likely not reported to the appropriate agencies. NC DETECT provides near-real-time statewide surveillance capacity to local, regional, and state level users with twice daily data feeds from NC EDs. Between 2008 and 2010, 110 to 113 EDs were submitting visit data to NC DETECT. Several animal bite-related on-line reports are available and provide aggregate and visit-level analyses customized to users' respective jurisdictions. The NC DETECT ED visit database currently provides the most comprehensive and cost-effective source of animal bite data in NC.

Objective

We describe the use of emergency department (ED) visit data collected through the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) for surveillance of animal bites in North Carolina (NC). Animal bite surveillance using ED visit data provides useful and timely information for public health practitioners involved in bite surveillance and prevention in NC.

Alcohol abuse is one of the major leading causes of preventable mortality in the United States. Binge drinking or excessive alcohol consumption, categorized as a pattern of drinking that brings a person's blood alcohol concentration to 0.08, has become a major cause for concern, especially in the 18 to 20 year old population. Iowa City is home to the University of Iowa, a large public university of 30,000 students. On June 1, 2010 the city council enacted a new ordinance prohibiting persons under 21 from entering or remaining in bars (establishments after 10:00 PM whose primary purpose is the sale of alcoholic beverages) after 10:00 PM. Prior to the ordinance, Iowa City was the only municipality in the region where underage patrons were allowed on premises. The new ordinance was enacted largely in response to public safety concerns, including perceptions of increased violence and sexual assaults, especially at bar closing time.

Our hypothesis is that the under 21 ordinance also resulted in changes to travel behavior, where prior to the ordinance, the campus bar culture constituted an "attractive nuisance," attracting a volatile mix of college students and non locals of all ages.

Objective

To study alcohol-related arrests during the time surrounding the introduction of an alcohol-related ordinance in the Iowa City, IA area.

According to the Substance Abuse and Mental Health Services Administration’s (SAMHSA) Drug Abuse Warning Network (DAWN) surveillance of drug-related ED visits, underage (B21 years) alcohol-alone visit rates have been increasing since 2004 to 2009 (1). Similarly, the ‘‘alcohol’’ syndrome for underage (12-20 years) ED visits also shows an overall increase from 2003 to 2009 in the percentage of alcohol-related visits (2). College-aged drinkers tend to binge drink at a higher frequency than the general population, putting them at greater risk for unintentional injuries and unsafe sex practices (3). Identifying collegespecific patterns for alcohol-associated morbidity have important policy implications to reduce excessive drinking and associated harms on and around college campuses.

Objective

To develop and implement a method for using emergency department records from a syndromic surveillance system to identify alcohol-related visits in New York City, estimate trends, and describe age-specific patterns. In particular, we are interested in college-aged morbidity patterns and how they differ from other age groups.

Adverse drug events (ADEs) are a major cause of morbidity and mortality. However, post-marketing surveillance systems are passive and reporting is generally not mandated. Thus, many ADEs go unreported, and it is difficult to estimate and/or anticipate side effects that are unknown at the time of approval. ADEs that are reported to the FDA tend to be severe, and potentially common, but less serious side effects are more difficult to characterize and document. Drugs with a high risk of harm outweighing the therapeutic value have recently been subjected to a greater level of interest with the Food and Drug Administration's Risk Evaluation and Mitigation Strategies (REMS). However, no rapid method to detect if the REMS produce the desired effect and assessment of the impact is conducted by the drug manufacturer. Increasingly, Americans have been turning to the internet for health related information, largely by the use of search engines such as Google. The volume of searches for drugs and ADEs provides a unique insight about the interest in various medications and side effects as well as longitudinal changes.

Objective

To investigate the use of search volume data from Google Insight for the detection and characterization of adverse drug events.

Adverse drug events (ADEs) are a significant source of morbidity and mortality. The majority of post-marketing surveillance for ADEs is passive. Information regarding ADEs is reported to the medical community in peer-reviewed journals. However, in most cases there is significant lag in the publication of peer-reviewed articles concerning ADEs. Within medical journals, our intuition is that letters to the editor may provide the earliest reports of ADEs. They often report single case reports or a collection of cases and usually precede more formal investigations and reports. Although these letters may contain useful and timely information, the challenge is that letters to the editor may be "buried" inside print journals. Furthermore, they may be more difficult to find and access even when using electronic searches because unlike other published reports, there is no corresponding abstract to view. Due to the lack of an abstract, detection depends almost exclusively upon words in a title, or manually applied Medical Subject Headings (MeSH). We propose that searching the full text of letters to the editor can provide a faster and perhaps more complete detection of ADEs compared to searches based on MeSH terms or titles alone.

Objective

Our objective was to explore the intuition that letters to the editor in leading medical journals contain early signals about adverse drug events. We explored this with letters in two leading journals.

A case study presented at the November 2010 Iowa Annual Swine Disease Conference for Swine Practitioners detailed increases in STB lesions beginning January 2010 [1]. Producers were informed of the problem by their swine processing facility. Tissue samples from affected producers were culture-positive for Mycobacterium avium. In the spring of 2010, USDA Veterinary Services (VS) began monitoring weekly ADRS STB carcass condemn data after a VS Staff Officer was made aware of unusual increases in STB condemns in another region. By June 2010, STB condemn rates in both of the affected areas decreased to typical seasonal levels; however, beginning January 2011 rates again rose beyond baseline seasonal highs, exceeding those seen in the 2010 outbreak.

Objective

This paper characterizes a regional outbreak of tuberculosis (TB) in market swine by combining local swine producer-based information on condemned stock at slaughter with geographically broader FSIS Animal Disposition Reporting System (ADRS) data. This study aims to obtain summary information on anomalous swine TB (STB) condemns at slaughter, compare critical outbreak time frames between outbreak areas, and identify the geographical spread of abnormally high STB condems.