BioSurveillance

Data quality monitoring is necessary for accurate disease surveillance. However it can be challenging, especially when “real-time” data are required. Data quality has been broadly defined as the degree to which data are suitable for use by data consumers. When compromised at any point in a health information system, data of low quality can impair the detection of data anomalies, delay the response to emerging health threats, and result in inefficient use of staff and financial resources. While the impacts of poor data quality on biosurveillance are largely unknown, and vary depending on field and business processes, the information management literature includes estimates for increased costs amounting to 8-12% of organizational revenue and, in general, poorer decisions that take longer to make.

Objective

To highlight how data quality has been discussed in the biosur- veillance literature in order to identify current gaps in knowledge and areas for future research. 

The Defense Threat Reduction Agency Chemical and Biological Technologies Directorate (DTRA CB) has initiated the Biosurveillance Ecosystem (BSVE) research and development program. Work process flow diagrams, with associated explanations and historical examples, were developed based on in-person, structured interviews with public health and preventative medicine analysts from a variety of Department of Defense (DoD) organizations, and with one organization in the Department of Health and Human Services (DHHS) and with a major U.S. city health department. The particular nuanced job characteristics of each organization were documented and subsequently validated with the individual analysts. Additionally, the commonalities across different organizations were described in meta-workflow diagrams and descriptions.

Objective

Operational biosurveillance capability gaps were analyzed and the required characteristics of new technology were outlined, the results of which will be described in this contribution.

Next-generation software environments for disease surveillance will need to have several important characteristics, among which are collaboration and search and discovery features, access to various data sets, and a variety of analytic methods. However, perhaps the most important feature is the least often mentioned – the ability to have the system adapt over time without high reengineering cost. The public health community cannot afford software redesigns every few years as data sets expand, analysis needs evolve, and software deficiencies are exposed. In addition to the need to adapt an environment over longer time periods, epidemiologists have high variability in their day-to-day needs that require adaptability over short time periods as well. Each outbreak or health situation has unique aspects, and analysts need to be able to bring in data and methods unique to that situation that may not be easily anticipated a priori. The most common approach to increasing reusability and decreasing upgrade costs are open architecture software frameworks such as Service-Oriented Architectures (SOAs). If well implemented, SOAs can significantly reduce software upgrade costs by allowing services (a software module) to be easily swapped out for improvements or supplemented with additional services. SOAs can help with long-term adaptability, but are not useful in short-term adaptability, since the software development team must be engaged in each cycle. Another approach is to include an App Store. Unfortunately, App Stores for government use have often been disappointing. Apps can tend to be quite simple, and even slight changes from what is programmed – a predictable situation with the variability seen in disease surveillance realm - will result in an epidemiologist having to get a software developer to make them a new App.

Objective:

This abstract discusses the BioAFTER project, which builds upon SOA and App Store concepts by allowing Apps to be strung together in unique combinations, according to the problem of the day.

Social media is of considerable interest as a sensor into the thoughts, interests and health of a population. We consider three types of health events that an analyst may wish to be made aware of:

- Given a known disease, such as MERS, SARS, Measles, etc., an event corresponds to individuals contracting the disease.

- Given a set of symptoms (fever, stomach pain, etc.), an event is an unusual number of individuals1 complaining of the symptoms.

- Most generally: an event is an unusually large group of individuals who can be identified as being effected by some personal illness.

Note that to detect an “unusual number” of something, we need to count the indicators of the event, and we need to compare the current count with past counts. Further, we are generally interested in geographically constrained events, and so for this work we will focus on county-based counts. We will count the number of items (tweets or individuals) expressing the event indicator (a disease name, symptom, or classified as “personal health related” as indicated by our classifier). Our approach to detecting health related events is: filter -> classify -> detect. We first filter out tweets that contain no “health related” terms, then apply a classifier to each tweet. This classifier is designed to flag a tweet as being about “personal health” or not. We then aggregate the positive instances per day at the county level and detect as an event any county/day pair with an unusually high count (as compared to the recent past).

Objective

In this work we investigate the extent to which social media, in particular Twitter, can be used to detect an outbreak of a disease or illness. We term these outbreaks “events”, and we will describe methodologies for detecting events.

The SAGES (Suite for Automated Global Electronic bioSurveillance) team at the John Hopkins University Applied Physics Laboratory was approached by the Public Health Division of the Research, Evidence and Information Programme of the Secretariat of the Pacific Community (SPC) to explore the feasibility of using the SAGES disease surveillance toolkit for two mass gathering events, the 8th Micronesian Games held from 19-31 July in Pohnpei Federated States of Micronesia and the 3rd International Conference on Small Island Developing States (SIDS) held from 1-4 September 2014 in Apia Samoa.

Mass gatherings are congregations of large numbers of people in a specific location(s) for a defined period of time such as major sporting events, concerts and festivals. A downside of these gatherings is the potential for communicable/infectious diseases to spread efficiently and rapidly. Infected individuals may subsequently return home and disseminate these infections in their local populations.

The Pacific syndromic surveillance system commenced in 2010. Enhanced syndromic surveillance is increasingly being used in mass gatherings. This involves inclusion of more syndromes and more regular reporting than routine syndromic surveillance. While enhanced syndromic surveillance is an important mechanism at mass gatherings, also, and somewhat opportunistically, mass gatherings can provide a unique chance to initiate or strengthen existing surveillance systems.

Objective

Present how a surveillance tool such as SAGES was used for disease surveillance for mass gathering activities.

The United States Department of Agriculture (USDA) Animal and Plant Inspection Service (APHIS) announced the first diagnosed case of PEDV in U.S. swine in Iowa on May 17, 2013. PEDV subsequently spread rapidly among the domestic swine herds throughout the United States. As of August 20, 2014, PEDV had been detected in 30 U.S. states affecting more than seven million pigs since the epidemic began. In the first year of emergence, PEDV reporting was voluntary, but on June 5, 2014, the Secretary of Agriculture issued a Federal Order that all cases of swine enteric coronavirus diseases (SECDs), including PEDV, were required to be reported to the USDA APHIS.

PEDV only affects swine and is not a public health concern. However, NBIC was interested in reporting on this disease due to the economic impact. Swine and pork products are valuable contributors to the domestic and international markets.

Objective

NBIC utilized information from various sources to communicate pertinent information on the emergence of Porcine Epidemic Diarrhea Virus (PEDV) in the United States in written products to be distributed to its Federal partners.

Dengue is a major cause of morbidity in Thailand. Annual outbreaks of varying sizes provide a particular challenge to the public health system because treatment of severe cases requires significant resources. Advanced warning of increases in incidence could help public health authorities allocate resources more effectively and mitigate the impact of epidemics.

Objective

To develop a statistical model for dengue fever surveillance that uses data from across Thailand to give early warning of developing epidemics.

The 2012 National Strategy for Biosurveillance1 calls for improved integration, synchronization, and coordination of national biosurveillance activities and acknowledges the benefits of collective knowledge through sharing and receiving of biosurveillance information via strengthened partnerships amongst international, federal, state, local, tribal, territorial, private sector, nongovernmental, academic and other participants. To assist in meeting these goals and goals specifically called out by United States (U.S.) Military and international partners, the Joint Program Executive Office for Chemical and Biological Defense began developing a software suite to support biosurveillance needs. In October 2014, the Biosurveillance Portal (BSP) will be deployed to support biosurveillance operations in the Korean Theater. In October 2016, the BSP will be available globally

Objective

This presentation aims to describe the development, initial use, and future directions of the Biosurveillance Portal.

To identify the disciplines and journal titles of surveillance-related publications from a wide range of indexed repositories and to draw attention to the publication repository created by the ISDS Research Committee.

Introduction

The ISDS Research Committee (RC) is an interdisciplinary group of researchers interested in a wide range of topics related to disease surveillance. The RC hosts a literature review process that results in a permanent repository1 of relevant journal articles; some of which are presented in bi-monthly calls/webinars that provide a forum for discussion and author engagement.2 The webinars have led to workgroups and society-wide events, boosted interest in ISDS, the annual conference, and fostered networking among members and guests. Since 2007, the RC has identified and classified published articles using an automated search method with the aim of progressing ISDS’s mission of advancing the science and practice of disease surveillance by fostering collaboration and increasing awareness of current advances in the field of surveillance. In 2012 the RC refined the method of automated literature retrieval resulting in increases in relevant articles identified. The RC literature review efforts have provided an opportunity for interdisciplinary collaboration and have resulted in a repository of 1920 articles from March 2012-August 2014 (2012=37.4% of articles in the repository, 2013=35.1%, 2014=27.5%).