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Monitoring

Description

National and state surveillance systems for oral health have relied on sample-based screenings and self-reported surveys.1 Recent publications suggest the need and potential for use of data from syndromic surveillance systems and insurers to monitor indicators of oral health status, utilization of care, and costs of treatment.2,3 Few consensus indicators for oral health derived from these data sources exist, with the exception of a set of five ICD-9 codes comprising ambulatory care sensitive dental problems (ACS-DP).4 This paper describes North Carolina’s Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) data analyzed within CDC’s BioSense System to report state and county population-based rates of hospital emergency department (ED) utilization for ACS dental conditions.

Objective

This paper describes use of national and state syndromic surveillance systems for monitoring and evaluating usage of hospital emergency departments for ambulatory care sensitive dental problems.

 

Submitted by Magou on
Description

Timeliness of information has a key role in disease reporting, and may be easily impaired by several factors affecting data entry and utilization.1 Regarding data entry, previous studies have shown that monitoring strategies, such as telephone reminders and supervision visits ensure reporting timeliness.2 Likewise, limited reporting infrastructure may prevent adequate reporting and effective data utilization.3,4 The Peruvian Air Force, in collaboration with the US Naval Medical Research Center Detachment in Lima, Peru, implemented in 2009 an electronic disease surveillance system with the objective of establishing near real-time baseline estimates of disease trends, and detecting disease outbreaks in a timely manner. This system has proven to perform well, although reporting sites vary in their reporting infrastructure. Therefore, we attempted to test the effect of a lack of monitoring on the performance of reporting sites, and explore the influence of other factors potentially affecting timeliness.

Objective

The objective of this paper is to describe the effect of close monitoring on performance of the electronic disease surveillance system of the Peru Air Force.

Submitted by Magou on
Description

In 2015, ISDH responded to an HIV outbreak among persons using injection drugs in Scott County [1]. Information to manage the public health response to this event and aftermath included data from multiple sources (e.g., HIV testing, surveillance, contact tracing, medical care, and HIV prevention activities). During the outbreak, access to timely and accurate data for program monitoring and reporting was difficult for health department staff. Each dataset was managed separately and tailored to the relevant HIV program area’s needs. Our challenge was to create a platform that allowed separate systems to communicate with each other and design a DP that offered a consolidated view of data. ISDH initiated efforts to integrate these HIV data sources to better track HIV prevention, diagnosis, and care metrics statewide, support decision-making and policies, and facilitate a more rapid response to future HIV-related investigations. The Centers for Disease Control and Prevention (CDC) through its Info-Aid program provided technical assistance to support ISDH’s data integration process and develop a DP that could aggregate these data and improve reporting of crucial statewide metrics. After an initial assessment phase, an in-depth analysis of requirements resulted in several design principles and lessons learned that later translated into standardization of data formats and design of the data integration process.

Objective: The objective was to design and develop a dashboard prototype (DP) that integrates HIV data from disparate sources to improve monitoring and reporting of HIV care continuum metrics in Indiana. The tool aimed to support Indiana State Department of Health (ISDH) to monitor key HIV performance indicators, more fully understand populations served, more quickly identify and respond to crucial needs, and assist in planning and decision-making.

Submitted by elamb on
Description

To date, most syndromic surveillance systems rely heavily on complicated statistical algorithms to identify aberrations. The assumption is that when the statistics identify something unusual, follow-up should occur. However, with multiple strata analyzed, small numbers for some strata, and wide variances in daily counts, the statistical algorithms will generate flags too often. Experience has shown that these flags usually have little or no public health significance. As a result, syndromic surveillance systems suffer from the ‘boy who cried wolf’ syndrome. It is clear that the analyst’s ability to use professional judgment to sift through multitudes of flags is very important to the success of the system, which suggests that statistics alone cannot identify issues of public health importance from ED data.

Objective

This study's aim was to refine an automated biosurveillance system in order to better suit the daily monitoring capabilities and resources of a health department.

Submitted by elamb on
Description

Yearly epidemics of respiratory diseases occur in children. Early recognition of these and of unexpected epidemics due to new agents or as acts of biological/chemical terrorism is desirable. In this study, we evaluate the ordering of chest radiographs as a proxy for early identification of epidemics of lower respiratory tract disease. This has the potential to act as a sensitive real-time surveillance tool during such outbreaks.

Objective:

Create a tool for monitoring respiratory epidemics based on chest radiograph ordering patterns.

Submitted by elamb on
Description

Epidemiologists, public health agencies and scientists increasingly augment traditional surveillance systems with alternative data sources such as, digital surveillance systems utilizing news reports and social media, over-the-counter medication sales, and school absenteeism. Similar to school absenteeism, an increase in reservation cancellations could serve as an early indicator of social disruption including a major public health event. In this study, we evaluated whether a rise in restaurant table availabilities could be associated with an increase in disease incidence.

 

Objective

The objective of this study is to evaluate whether trends in online restaurant table reservations can be used as an early indicator for a disease outbreak.

Submitted by hparton on
Description

BioSense is a national human health surveillance system for disease detection, monitoring, and situation awareness through near realtime access to existing electronic healthcare encounter information, including information from hospital emergency departments (EDs). MCM include antibiotics, antivirals, antidotes, antitoxins, vaccinations, nuclide-binding agents, and other medications. Although some MCM have been extensively evaluated and have FDA approval, many do not (1). Current FDA and CDC systems that monitor drug and vaccine safety have limited ability to monitor MCM safety, and in particular to conduct rapid assessments during an emergency.

Objective

To conduct an initial examination of the potential use of BioSense data to monitor and rapidly assess the safety of medical countermeasures (MCM) used for prevention or treatment of adverse health effects of biological, chemical, and radiation exposures during a public health emergency.

Submitted by uysz on
Description

Salmonella Enteritidis is dangerous for human due the reason of toxicoinfaction. These pathogen demonstrate high virulence for small children and people with chronic pathologies and can causes people die. The main source of infection to humans is birds (poultry and wild).

Wild birds represent the natural reservoir of same bacterial pathogens. It is known that Salmonella can occupy an intestinal tract of birds. This colonization in general is constant, sometimes proceeds with an alternating fever, and usually, without clinical signs. Infected birds can transmit pathogens to other isolates in close contact. This usually occurs on the nesting during seasonal migrations. In the southern region of Ukraine are several points of intersection of migration routes of wild birds on the way from Europe to Africa and Asia (National Park “Askania Nova”and others).

 

Objective

The aim of our study was to identify possible natural reservoirs of Salmonella Enteritidis among wild birds.

Submitted by hparton on
Description

Timely and accurate syndromic surveillance depends on continuous data feeds from healthcare facilities. Typical outlier detection methodologies in syndromic surveillance compare predictions of counts for an interval to observed event counts, either to detect increases in volume associated with public health incidents or decreases in volume associated with compromised data transmission. Accurate predictions of total facility volume need to account for significant variance associated with the time of day and week; at the extreme are facilities which are only open during limited hours and on select days. Models need to account for the cross-product of all hours and days, creating a significant data burden. Timely detection of outages may require sub-hour aggregation, increasing this burden by increasing the number of intervals for which parameters need to be estimated. Nonparametric models for the probability of message arrival offer an alternative approach to generating predictions. The data requirements are reduced by assuming some time-dependent structure in the data rather than allowing each interval to be independent of all others, allowing for predictions at sub-hour intervals.

Objective:

Characterize the behavior of nonparametric regression models for message arrival probability as outage detection tools.

Submitted by elamb on