Skip to main content

OTC Data

Description

It has been postulated that school absenteeism, a non-traditional surveillance data source, may allow for early detection of disease outbreaks, particularly among school-aged children who may not seek emergency medical attention. Although a New York City-based study showed moderate utility of school absenteeism in biosurveillance, no study to date has been reported on school absenteeism in Los Angeles County, which contains the second largest school district in the US.

 

Objective

To evaluate the utility of school absenteeism surveillance data in Los Angeles County during the 2009–2010 influenza season.

Submitted by hparton on
Description

Our laboratory previously established the value of over-the-counter (OTC) sales data for the early detection of disease outbreaks. We found that thermometer sales (TS) increased significantly and early during influenza (flu) season. Recently, the 2009 H1N1 outbreak has highlighted the need for developing methods that not only detect an outbreak but also estimate incidence so that public-health decision makers can allocate appropriate resources in response to an outbreak. Although a few studies have tried to estimate the H1N1 incidence in the 2009 outbreak, these were done months afterward and were based on data that are either not easy to collect or not available in a timely fashion (for example, surveys or confirmed laboratory cases).

Here, we explore the hypothesis that OTC sales data can also be used for predicting a disease activity. Towards that end, we developed a model to predict the number of Emergency Departments (ED) flu cases in a region based on TS. We obtain sales information from the National Retail Data Monitor (NRDM) project. NRDM collects daily sales data of 18 OTC categories across the US.

 

Objective

We developed a model that predicts the incidence of flu cases that present to ED in a given region based on TS.

Submitted by hparton on
Description

In disease surveillance, an outbreak is often present in more than one data type. If each data type is analyzed separately rather than combined, the statistical power to detect an outbreak may suffer because no single data source captures all the individuals in the outbreak. Researchers, thus, started to take multivariate approaches to syndromic surveillance. The data sources often analyzed include emergency department data, categorized by chief complaint; over-thecounter pharmaceutical sales data collected by the National Retail Data Monitor (NRDM), and some other syndromic data.

 

Objective

This study proposes a simulation model to generate the daily counts of over-the-counter medication sales, such as thermometer sales from all ZIP code areas in a study region that include the areas without retail stores based on the daily sales collected from the ZIP codes with retail stores through the NRDM. This simulation allows us to apply NRDM data in addition to other data sources in a multivariate analysis in order to rapidly detect outbreaks.

Submitted by hparton on
Description

Respiratory infectious diseases are the most common diseases reported in rural China. Studies have suggested that the OTC retail sale data could be used to detect early outbreak (1, 2). However, few researches have performed to identify whether OTC retail sales data could also predict the outbreak in developing countries and resource poor settings. Here, we conducted a web-based syndromic surveillance system with OTC retail sales to detect respiratory epidemics in rural area in China.

Objective

To explore the feasibility of using OTC medication sales data for early detection of respiratory epidemics in rural China.

Submitted by elamb on
Description

The United States Environmental Protection Agency (U.S. EPA) has developed a prototype contamination warning system (CWS) for drinking water in response to Homeland Security Presidential Directive 9 (HSPD9). The goal of HSPD9 and the CWS is to expedite contamination containment and emergency response, thereby minimizing public health and economic impacts.

U.S. EPA’s conceptual CWS system, named WaterSentinel, is currently being pilot tested by U.S. EPA and its research partners. WaterSentinel is a multi-faceted approach involving water quality monitoring at optimal locations throughout the drinking water distribution system, enhanced security monitoring at key water utility infrastructure assets, consumer complaint surveillance, and innovative uses of public health surveillance data streams.

 

Objective

This paper summarizes the use and evaluation of various types of public health surveillance data for the early detection of chemical and biological contamination of drinking water.

Submitted by elamb on
Description

Safe drinking water is essential for all communities. Intentional or unintentional contamination of drinking water requires water utilities and local public health to act quickly. The Water Security (WS) initiative of the U.S. Environmental Protection Agency is a multi-faceted approach involving water utilities and local public health officials (LPH) to identify, communicate, contain, and mitigate a drinking water contamination event. Components of WS include: online water quality monitoring, enhanced security monitoring, consumer complaint surveillance, and innovative uses of public health surveillance data streams. LPH already use multiple surveillance data systems to recognize disease events in a timely manner. However, few of these systems can be integrated or specifically designed for detection of drinking water contamination incidents.

 

Objective

This poster describes the integration of public health surveillance data as a component of an early warning system for detection of a drinking water contamination incident.

Submitted by elamb on
Description

On June 22, 2007 increases in over-the-counter (OTC) electrolyte and child anti-fever medication sales were detected through routine OTC surveillance. Increases in emergency department (ED) data for gastrointestinal (GI) illness among <5 year olds were observed on June 23 and 24. Further analyses indicated clustering within one borough of NYC, with three EDs having most of the visits. Because NYC has had limited success in detecting spatial outbreaks using syndromic surveillance in the past, an investigation was not immediately initiated.

DOHMH was notified of a multi-state outbreak of S. wandsworth suspected to be associated with the snack food Veggie Booty® on June 26. Cases were predominantly young children and included 8 confirmed cases among NYC residents with onset dates from March 4 – May 19.

 

Objective

To determine whether increases in GI illness detected through OTC drug sales and ED syndromic surveillance were linked to a multi-state outbreak of S. wandsworth associated with the consumption of Veggie Booty® snack food.

Submitted by elamb on
Description

San Diego County Public Health has been conducting syndromic surveillance for the past few years. Currently, the system has become largely automated and processes and analyzes data from a variety of disparate sources including hospital emergency departments, 911 call centers, prehospital transports, and over-the-counter drug sales. What has remained constant since the system’s initial conceptualization is the local opinion that the data should be analyzed and interpreted in a variety of ways, in anticipation for the variety of contexts in which events that are of public health interest may unfold. Relatively small increases in volume that are sustained over time will likely be detected by methods designed to detect “small process shifts”, and include the CUSUM and EWMA methods. Larger increases in volume that are not sustained over time will likely be detected by other employed methods (P-Chart in the event of a non-proportional increase in volume, U-Chart in the event of a proportional increase in volume). A retrospective analysis was conducted on historical data from various data sources to determine the frequency of signals and detected events as well as the context within which the alert occurred (i.e., the “shape” of the data). Findings regarding several actual public health events will also be discussed.

 

Objective

This paper describes the frequency, various “shapes” and magnitudes of data anomalies, and varying ways actual public health events may present themselves in syndromic data.

Submitted by elamb on
Description

Overseas studies showed that increases in over-the-counter (OTC) drug sales might serve as an indicator of community disease outbreaks before they are detected by conventional surveillance systems. Using data collected retrospectively from commercial drug retailers, the Department of Health of Hong Kong conducted an exploratory study to examine the potential of monitoring OTC drug sales for early detection of community disease outbreaks.

 

Objective

This study evaluates whether OTC drug sales can serve as an earlier indicator for detecting community disease outbreaks in Hong Kong.

Submitted by elamb on
Description

National Retail Data Monitor (NRDM) is a public health surveillance tool that collects and analyzes daily sales data for over-the-counter (OTC) health-care products from >15,000 retail stores nationwide. This is a system developed by Real-Time Outbreak and Disease Surveillance Laboratory. NRDM has been in continuous operation since December 2002. The Washoe County District Health Department implemented this system in November 2003. During initial phase of implementation, NRDM was used retrospectively on as-needed basis. Since September 2004, monitoring NRDM for volume of OTC sales for anti-diarrhea medications became a daily routine.

 

Objective

The objective of this paper is to evaluate the role of NRDM in gastrointestinal illness outbreak investigation in Washoe County, Nevada. The evaluation will focus on usefulness of system, sensitivity, positive predictive value, representativeness, and timeliness followed by updated CDC guidelines.

Submitted by elamb on