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Surveillance Systems

Description

Centers for Disease Control and Prevention’s (CDC) BioSense system receives near real-time health care utilization data from number of sources, including DoD and VA outpatient facilities, and nonfederal hospital EDs in the US to support all-hazards surveillance and situational awareness. However, the BioSense system lacks some critical functions such as creating ad hoc definition of syndrome or ad hoc query tool development. This limits CDC Emergency Operations Center’s (EOC) ability to monitor new health events such as MERS - a viral respiratory illness first reported in Saudi Arabia in 2012. In May 2014, CDC confirmed two unlinked imported cases of MERS in the US - one in Indiana, the other in Florida. Upon report of a MERS case in Indiana, staff initiated joint efforts with EOC and several affected jurisdictions to enhance the surveillance of MERS irrespective of jurisdictions’ preferred surveillance system.

Objective

To identify and monitor Middle East Respiratory Syndrome (MERS) like syndromes cases in the syndromic surveillance system.

Submitted by teresa.hamby@d… on
Description

Surveillance for STD in the United States (US) relies primarily on case reports from clinicians and laboratories and sentinel surveillance; however, nationwide reporting is not required for viral STD and clinical sequelae of STD.

Objective

To evaluate the potential usefulness of 3 sources of administrative health care data for sexually transmitted disease (STD) surveillance.

Submitted by teresa.hamby@d… on
Description

Drug overdoses and related deaths have been escalating nationally since 1970. In Virginia, the rate of drug overdose deaths increased 36% from 5.0 to 6.8 deaths per 100,000 population between 1999 and 2010. While initiated for bioterrorism event detection, syndromic surveillance has shown utility when extended to other health issues. ED visits may complement information from Overdose Deaths investigated by the Office of the Chief Medical Examiner (OCME) in describing drug overdose trends. Due to its real-time nature, syndromic surveillance data could act as an early indicator for emerging drug problems in the community, serving as an alert to public health.

Objective

Determine if syndromic surveillance data can be used to provide a real-time picture of the drug using population by analyzing trends of emergency department (ED) visits for unintentional drug overdose (Overdose Visits) in conjunction with unintentional deaths that prescription or illicit opiates contributed to or caused (Overdose Deaths).

Submitted by teresa.hamby@d… on
Description

HIV post-exposure prophylaxis (PEP) involves taking antiretroviral medication after potential exposure to HIV to reduce the probability of becoming infected. New York State recommends PEP following certain occupational (e.g., needle sticks by healthcare workers) and non-occupational (e.g., sexual and needle-sharing activities) exposures. Little information exists on the uptake of PEP for HIV in the United States, particularly with regard to nonoccupational exposures. ED data have been used previously to identify occupational PEP visits but have not been used extensively to describe trends in PEP visits overall. We aimed to identify HIV-related PEP visits in NYC EDs to track uptake and inform outreach efforts.

Objective

To describe trends in HIV post-exposure prophylaxis uptake in New York City (NYC) emergency departments (EDs).

Submitted by teresa.hamby@d… on
Description

Effective use of data for disease surveillance depends critically on the ability to trust and quantify the quality of source data. The Scalable Data Integration for Disease Surveillance project is developing tools to integrate and present surveillance data from multiple sources, with an initial focus on malaria. Consideration of data quality is particularly important when integrating data from diverse clinical, population-based, and other sources. Several global initiatives to reduce the burden of malaria (Presidents Malaria Initiative, Roll Back Malaria Initiative and The Global Fund to Fight AIDS, Tuberculosis and Malaria) have published lists of recommended indicators. Values for these indicators can be obtained from different data sources, with each source having different data quality properties as a consequence of the type of data collected and the method used to collect the data. Our goal is to develop a framework for organizing the data quality (DQ) properties of indicators used for disease surveillance in this setting.

Submitted by teresa.hamby@d… on
Description

Stillbirth is an unfortunate event in a woman life which remains uncounted in developing countries, thus, seldom caught attention until recently. Among 3.2 million stillbirths globally, 98% occurs in LMICs with majority in South Asia, and 75% of those are preventable. Globally, it counts as equal to neonatal deaths and is not mentioned in MGDs, global charters and programs priority. Besides immense information gap, it is mostly not part of vital registration system. Mostly, the data for stillbirths is mostly collected in demographic surveys, clinical studies or retrospective records, underestimating the counts. Besides, lack of optimal national vital registration system, Pakistan has highest rate of stillbirth. Hence, to collect prospective data, efforts are made by Department of Paediatrics of Aga Khan University to maintain a Demographic & Health Surveillance System (DHSS) at Karachi to provide more robust data over years.

Objective

To describe characteristic of stillbirth in a diverse population in Karachi health and demographic surveillance system.

Submitted by teresa.hamby@d… on
Description

Biosurveillance Portal (BSP) is a web-based enterprise environment that is aimed to facilitate international collaboration, communication, and information-sharing in support of the detection, management, and mitigation of biological events in Korea. In Oct 2013, Republic of Korea (ROK) Ministry of National Defense has made the project agreement with United States (US) Department of Defense Joint Program Executive Office of Chemical and Biological Defense to develop Biosurveillance Portal which will provide tools and capabilities to facilitate timely identification and detection of biological events to minimize operational impacts on ROK-US Forces. As a part of this project, Armed Forces Medical Command (AFMC) undertook the initiative to develop the Military Active Realtime Syndromic Surveillance system.

Objective

This presentation aims to elaborate our experiences from initiating a syndromic surveillance system as a part of current biosurveillance developments in Korea. We developed Military Active Realtime Syndromic Surveillance (MARSS) system with data from all of 19 Korean military hospitals as a part of the US-ROK joint Biosurveillance Project.

Submitted by teresa.hamby@d… on
Description

In order to transition the forecasting, estimation and management of epidemic risks to individual administrative areas, the Agency for Consumer Rights Protection of Kazakhstan has developed a concept for modernizing the existing national system of the epidemiological surveillance (SES).

It is proposed that the data from the SES (epidemiology, sanitary and epidemiological background, external environmental objects and database) will be consolidated to generate a new epidemic risk control and management tool called the Regional Sanitary-Epidemiological Passport (RSEP) for each of Kazakhstan’s districts. The RSEP will contain infectious incidence rate dynamics according to the primary (marker) infections (7 nosologies) including a forecast for 2-3 years, and natural and soil foci GIS maps for especially dangerous pathogens (EDP) with a 3-5 year forecast of their activity.

The RSEP is planned as a new working tool for epidemiologists to aid in making objective estimates, forecasting epidemic risks in particular areas of Kazakhstan, and taking preventive steps to lower epidemic risks.

Objective

Development and approbation of the epidemic risk estimation and management methodology based on multivariate analysis per administrative clusters of Kazakhstan using the Electronic Integrated Disease Surveillance System (EIDSS) technical capabilities.

Submitted by teresa.hamby@d… on
Description

Public health surveillance practice is evolving rapidly. In the past decade we have witnessed the globalization of health threats, the emergence and re-emergence of infectious diseases, and an explosion of easily accessible new technologies. This fluid environment challenges the public health community, but also provides it with a unique and fertile environment to innovate and improve its practice. As surveillance is a core function of public health practice, public health practitioners need to be well equipped to achieve this function and address present and future public health challenges. We developed a five day training course that focused on the practical use of surveillance concepts and principles in public health. We are sharing findings on the development of the course and learner outcomes.

Objective

To enhance the knowledge and ability of public health practitioners to integrate and apply surveillance concepts, principles, and emerging tools into their practice.

Submitted by teresa.hamby@d… on
Description

Typical approaches to monitoring ED data classify cases into pre-defined syndromes and then monitor syndrome counts for anomalies. However, syndromes cannot be created to identify every possible cluster of cases of relevance to public health. To address this limitation, NC DETECT’s approach clusters cases by arrival times and monitors the textual chief complaint data associated with each identified cluster for relevant similarities [1]. This approach is time consuming and limited in its ability to detect emerging outbreaks that are dispersed across time. A new method is needed to automatically identify clusters of interest that would not be detected by existing syndromes. Clusters may be based on symptoms, events, place names, arrival time, or hospital location. The NC DPH dataset describes 198,511 de-identified ED visits over one year at 3 North Carolina hospitals. The data include chief complaint, altered date and time of arrival, hospital A/B/C, and age group. About 40 simulated outbreaks were injected into the data set by the NC DETECT team. For example, an inject cluster might consist of 4 patients who report getting sick after eating at a particular restaurant.

Objective

We apply a novel semantic scan statistic approach to solve a problem posed by the NC DETECT team, North Carolina Division of Public Health (NC DPH) and UNC Department of Emergency Medicine Carolina Center for Health Informatics, and facilitated by the ISDS Technical Conventions Committee. This use case identifies a need for methodology that detects emerging, potentially novel outbreaks in free-text emergency department (ED) chief complaint data.

 

Submitted by Magou on