Surveillance Systems

The Electronic Integrated Disease Surveillance System (EIDSS) is a computer-based disease reporting application funded under the Cooperative Biological Engagement Program of the U.S. Defense Threat Reduction Agency. EIDSS deployment includes the Republics of Georgia (GG) and Azerbaijan (AJ) where personnel in the Ministry of Health and the Ministry of Agriculture in each country enter case-based disease reports. The potential benefits obtained through surveillance of infectious diseases across species have been widely discussed. A limitation of such practice has been the paucity of single applications that collect information about disease in both human and other animal populations (Scotch 2009). A unique feature of EIDSS is the use of a single platform to enter reports of disease in humans and other animals. Records are stored in a common database enabling ready access to information on multiple diseases and provide a quantitative linkage between human and animal data. An integrated analysis and reporting (AVR) module further supports timely investigation of disease events across the epizootic barrier.

Objective

We describe an electronic disease reporting system that integrates case-based disease information from humans and other animals in a single database and examine the utility for supporting disease surveillance functions through access to longitudinal case reports of multiple diseases across multiple species provided by the system.

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.

ORBiT is implemented as a distributed analytic platform consisting of a software stack atop of Hadoop and makes use of Titan, a distributed graph database as a backend for data storage. Data from each of the traditional and non-traditional sources are hosted as a massive linked structure, with extensible interfaces for each stream. The data from the linked structure is interfaced with streaming and graph-data analytic modules. The outputs from the analytic modules are interfaced with visualization tools that enable analysts to detect spatial and temporal patterns/correlations across multiple data sources.

Objective

Our objective is to provide 1) forecasting and early warning, and 2) an extensible data analytics platform for biosurveillance by enabling the use of traditional and non-traditional datasets, consisting of heterogeneous data types and modalities.

The illegal wildlife trade is a multi-faceted, clandestine industry that has led to the disruption of fragile ecosystems, facilitated the spread of pathogens, and has led to the emergence of novel infectious diseases in humans, domestic animals, and native wildlife(1, 2). The trade is as diverse as it is large, with live and dead wildlife representing multiple species sold to satisfy human demands for food, medicine, pets and trophies. Wildlife are harvested at astonishing numbers and used for such things as exotic pets, ornamental jewelry and clothing, and traditional Chinese medicine(3). An estimated 75% of recently emerging infectious diseases originated from animals(4), which can include both live animals and animal products.

Objective

We aim to develop an automated, real-time, comprehensive, global system for monitoring official and unofficial reports of illegal wildlife trade activity, and to determine potential hot-spot regions for emerging zoonotic pathogens along commonly utilized illegal wildlife trade routes.

Syndromic surveillance of ED and PCC data has been widely used for the detection, tracking monitoring and monitoring of health events (e.g. bioterrorism, , disease outbreaks, environmental exposures) over the past decade. In recent years, these data have been found to be useful for public health programs not normally associated with syndromic surveillance (e.g. injury prevention, drug abuse, environmental health). In 2010, the first calls referencing exposure to products marketed as "legal highs" and "bath salts" were received by PCCs in the United States. Synthetic drugs, such as those commonly known as "bath salts," often are labeled as "not for human consumption" and thereby circumvent normal legal control procedures that control the sale and distribution of recreational drugs. The purpose of this study was to evaluate the emerging trends for the use of "bath salts" in Ohio.

Objective

Correlation and time series analyses were completed to evaluate the emerging trends in designer drug use for "Bath Salts" in Ohio using emergency department (ED) chief complaint and poison control center (PCC) human exposure data.

Heat waves have serious health impacts such as heat exhaustion, heat stroke, dehydration, and death. Heat illness morbidity and mortality can be reduced with the identification of vulnerable populations and targeted public health interventions. In June and July of 2011, a heat wave occurred in Nebraska in which 28 days reached 90 degrees F or higher. Syndromic surveillance data were used to describe heat-related illness emergency department (ED) visits during this time.

Objective

The purpose of this study was to develop methodology to accurately identify and track heat illness in a timely manner using syndromic surveillance data.

Mining text for real-time syndromic surveillance usually requires a comprehensive knowledge base (KB) which contains detailed information about concepts relevant to the domain, such as disease names, symptoms, drugs, and radiology findings. Two such resources are the Biocaster Ontology [1] and the Extended Syndromic Surveillance Ontology (ESSO) [2]. However, both these resources are difficult to manipulate, customize, reuse and extend without knowledge of ontology development environments (like Protege) and Semantic Web standards (like RDF and OWL). The cKASS software tool provides an easy-to-use, adaptable environment for extending and modifying existing syndrome definitions via a web-based Graphical User Interface, which does not require knowledge of complex, ontology-editing environments or semantic web standards. Further, cKASS allows for - indeed encourages - the sharing of user-defined syndrome definitions, with collaborative features that will enhance the ability of the surveillance community to quickly generate new definitions in response to emerging threats.

Objective

We describe cKASS (clinical Knowledge Authoring & Sharing Service), a system designed to facilitate the authoring and sharing of knowledge resources that can be applied to syndromic surveillance.

During 2007 - 2010 the Center for Health service Management (CHSM) conducted training and consultations to strengthen the Maternal, Neonatal & Child Health (MNCH) Surveillance-Response (S-R) Systems of 10 districts and 5 municipalities of 5 provinces in Indonesia (Bali, Sulawesi Tengah, Bengkulu, Riau, and Yogyakarta). These districts and municipalities represent a mix of high and low Fiscal Capacity of the local governments and high & low Economic Capacity of the population. MNCH S-R Systems strengthening was carried out by means of two 2-day training sessions (of approximately one year apart) at the District/Municipal Health Offices (D/M HOs) and consultations via electronic telecommunication. The subject matter of the training sessions courses and consultations consisted of: (1) controlling MNCH priority diseases; (2) applying S-R core and support functions by the D/M HO and health service providers; (3) managing a S-R Support Unit at the D/M HO; and, (4) setting up a D/M HO internet web-site and publishing S-R electronic bulletins.

Objective 

To evaluate the efficacy of the MNCH S-R Systems strengthening approach used by the CHSM, Gadjah Mada University School of Medicine.

Epi-X is an internet-based secure website for the exchange of information regarding developing public health events. Reports are exchanged with state epidemiologists, state health officers, and other key public health officials. Provisional and secure information is regularly posted on Epi-X. The Epi-X user base is restricted to public health officials at the local, state, federal, and international levels. Private health-care practitioners who do not otherwise hold a government position are not given access to Epi-X. As of August 2011, Epi-X has approximately 6,000 users, of which approximately 1,600 are authorized to directly contribute reports regarding developing public health events. Epi-X is frequently used to seek reports of cases of illness related to an outbreak, cluster, or increased occurrence of a specific infectious disease. The usability and usefulness of Epi-X in this capacity has not previously been assessed.

Objective

To evaluate the usability and usefulness of the Epidemic Information Exchange (Epi-X) system, a secure online information exchange provided by the Centers for Disease Control and Prevention (CDC), in assisting with case finding in response to infectious disease outbreaks and clusters that involve, or have the potential to involve, cases in multiple state-level jurisdictions within the United States

Argus is an event-based surveillance system which captures information from publicly available Internet media in multiple languages. The information is contextualized and indications and warning (I&W) of disease are identified. Reports are generated by regional experts and are made available to the system's users. In this study a small-scale disease event, plague emergence, was tracked in a rural setting, despite media suppression and a low availability of epidemiological information.

Objective

To demonstrate how event-based biosurveillance can be utilized to closely monitor disease emergence in an isolated rural area, where medical information and epidemiological data are limited, toward identifying areas for public health intervention improvements.