General - ISDS

There appears to be a growing number of prioritization exercises, for example of diseases, in health related settings (1). The decision process around these exercises involves comparing competing alternatives, i.e. diseases, and irreducible objectives. In addition to the multi-dimensional nature of the problem, the lack of reliable data, group dynamics associated to the involvement of experts, and the multiplicity of stakeholders, among other contextual factors, add complexity to the decision process. Here we review trends in such prioritization exercises and applications in different settings and for different events of interest, for example the management of emerging risks. Based on our findings, we discuss a conceptual framework based on multi-attribute utility theory presented to the World Organization for Animal Health (OIE) for the modification of its qualitative assessment of veterinary services performance into a quantifiable decision support system.

 

The ISDS Research Committee (RC) is an interdisciplinary group of researchers interested in various topics related to disease surveillance. The RC hosts a literature review process with a permanent repository of relevant journal articles and bimonthly calls that provide a forum for discussion and author engagement. The calls have led to workgroups and society-wide events, boosted interest in the ISDS Conference, and fostered networking among participants. 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 innovations in the field of surveillance. The RC literature review efforts have provided an opportunity for interprofessional collaboration and have resulted in a repository of over 1,000 articles, but feedback from ISDS members indicated relevant articles were not captured by the existing methodology. The method of automated literature retrieval was thus refined to improve efficiency and inclusiveness of stakeholder interests.

 Objective

To improve the method of automated retrieval of surveillance-related literature from a wide range of indexed repositories.

The International Society for Disease Surveillance held its eleventh annual conference in San Diego on December 4th and 5th, 2012, under the theme Expanding Collaborations to Chart a New Course in Public Health Surveillance.  During these two days, practitioners and researchers across many disciplines gathered to share best practices, lessons learned and cutting edge approaches to timely disease surveillance.  A record number of abstracts were received, reviewed and presented – the schedule included 99 orals, 4 panels, 94 posters, 5 roundtables and 12 system demonstrations.  Presenters represented 24 different countries from Africa, North and South America, Europe, and Asia .  Topics covered included, but were not limited to, statistical methods for outbreak detection, border health, data quality, evaluation of novel data streams, influenza surveillance, best practices and policies for information sharing, social network analysis, data mining techniques, surveillance during weather events and mass gatherings, syndrome development, and novel uses of syndromic surveillance data.  There were also discussions on the impact of regulations and standards development on disease surveillance, including Meaningful Use and the International Health Regulations.

The International Society for Disease Surveillance held its eleventh annual conference in San Diego on December 4th and 5th, 2012, under the theme Expanding Collaborations to Chart a New Course in Public Health Surveillance. During these two days, practitioners and researchers across many disciplines gathered to share best practices, lessons learned and cutting edge approaches to timely disease surveillance. A record number of abstracts were received, reviewed and presented – the schedule included 99 orals, 4 panels, 94 posters, 5 roundtables and 12 system demonstrations. Presenters represented 24 different countries from Africa, North and South America, Europe, and Asia . Topics covered included, but were not limited to, statistical methods for outbreak detection, border health, data quality, evaluation of novel data streams, influenza surveillance, best practices and policies for information sharing, social network analysis, data mining techniques, surveillance during weather events and mass gatherings, syndrome development, and novel uses of syndromic surveillance data. There were also discussions on the impact of regulations and standards development on disease surveillance, including Meaningful Use and the International Health Regulations.

The 2012 Conference was also host to several exciting keynote and plenary talks, including those given by James Fowler, Professor of Medical Genetics and Political Science at the University of California, San Diego and Bill Davenhall, Global manager of Esri's Health and Human Service Solutions Group. Plenary speakers Steve Waterman, Centers for Disease Control and Prevention (CDC); Simon Hay, University of Oxford; and Brian McCloskey, Health Protection Agency in London, reflected on the importance of effective collaborations in their respective topics of migrant and border health, malaria disease epidemiology and mass gathering health. National and international representatives from the CDC, the World Health Organization and the Department of Homeland Security also discussed their respective strategic plans for disease surveillance.

In addition, the 2012 Data Visualization Event enabled conference attendees to collaborate and gain knowledge of visualization tools and techniques applied to a rich, de-identified set of ambulatory electronic health record (EHR) data. Participants developed visualizations of chronic disease events using this common data set and presented their work during the evening poster session. The goals for this event were to demonstrate and share visualization tools and techniques that attendees could learn to apply to their own data and also to provide exposure to data elements available in ambulatory EHR systems and highlight their potential for surveillance and research.

My hope is that attendees of the 2012 ISDS Conference strengthened existing collaborations and fostered new ones, and returned to their places of work or study energized with new ideas and approaches to disease surveillance. The challenge for all of us is to sustain this new energy throughout the coming year and to leverage the tools available to us to share best practices and reach out for assistance when needed. We all want to improve the health of our populations, and collaborations will enable us to achieve that goal.

Twelve years into the 21st century, after publication of hundreds of articles and establishment of numerous biosurveillance systems worldwide, there is no agreement among the disease surveillance community on most effective technical methods for public health data monitoring. Potential utility of such methods includes timely anomaly detection, threat corroboration and characterization, follow-up analysis such as case linkage and contact tracing, and alternative uses such as providing supplementary information to clinicians and policy makers. Several factors have impeded establishment of analytical conventions. As immediate owners of the surveillance problem, public health practitioners are overwhelmed and understaffed. Goals and resources differ widely among monitoring institutions, and they do not speak with a single voice. Limited funding opportunities have not been sufficient for cross-disciplinary collaboration driven by these practitioners. Most academics with the expertise and luxury of method development cannot access surveillance data. Lack of data access is a formidable obstacle to developers and has caused talented statisticians, data miners, and other analysts to abandon the field. The result is that older research is neglected and repeated, literature is flooded with papers of varying utility, and the decision-maker seeking realistic solutions without detailed technical knowledge faces a difficult task. Regarding conventions, the disease surveillance community can learn from older, more established disciplines, but it also poses some unique challenges. The general problem is that disease surveillance lies on the fringe of disparate fields (biostatistics, statistical process control, data mining, and others), and poses problems that do not adequately fit conventional approaches in these disciplines. In its eighth year, the International Society of Disease Surveillance is well positioned to address the standardization problem because its membership represents the involved stakeholders including progressive programs worldwide as well as resource-limited settings, and also because best practices in disease surveillance is fundamental to its mission. The proposed panel is intended to discuss how an effective, sustainable technical conventions group might be maintained and how it could support stakeholder institutions.

Objective

The panel will present the problem of standardizing analytic methods for public health disease surveillance, enumerate goals and constraints of various stakeholders, and present a straw-man framework for a conventions group.

 

Today, surveyors in both the private and public sectors are facing considerable challenges with random digit dialed (RDD) landline telephone samples. The population coverage rates for landline telephone surveys are being eroded by wireless-only households, portable telephone numbers, telecommunication barriers (e.g., call forwarding, call blocking and pager connections), technological barriers (call-blocking, busy circuits) and increased refusal rates and privacy concerns. Addressing these issues increasingly drives up the costs associated with dual-frame telephone surveys designed to be representative of the target population as well as hinders their ability to be fully representative of the adult population of each state and territory in the United States. In an effort to continue to meet these challenges head on and assist state and territorial public health professionals in the continued collection of data that are representative of their respective populations, novel approaches to behavioral health surveillance need continued examination. Both private and public sector researchers are evaluating the use of Internet opt-in panels to augment dual-frame RDD survey methods. Compared to dual-frame RDD, opt-in Internet panels offer lower costs, quick data collection and dissemination, and the ability to gather additional data on panelists over time. However, as with dual-frame RDD, this mode has similar challenges with coverage error and non-response. Nevertheless, survey methodologists are moving forward and exploring ways to reduce or eliminate biases between the sample and the target population.

Objective

To present the design and preliminary results of a pilot study to investigate the use of opt-in Internet panel surveys for behavioral health surveillance.

 

The international Society for Disease Surveillance has successfully brought together practitioners and researchers to share tools, ideas, and strategies to strengthen health surveillance systems. The Society has evolved from an initial focus on syndromic surveillance to a broader consideration of innovation in health surveillance. More recently, ISDS has also worked to support surveillance research and practice in International resource-constrained settings. Individuals who work in surveillance in developed countries outside the USA, however, have received little direct attention from ISDS. The policy and practice contexts in these countries are often quite different than the USA, so there is a need to support surveillance innovation in these countries in a manner that fits the context. Canadian surveillance practitioners and researchers comprise the largest International group of ISDS members, and these members have expressed an interest in working with ISDS to translate surveillance innovations into practice in Canada, where a national surveillance network and forum is lacking. This Round Table will consider how ISDS can help to support members in countries like Canada and will identify next steps for promoting the science and practice of disease surveillance in the Canadian context.

Objective

1) To explore how ISDS can better support researchers and public health practitioners working in the field of disease surveillance outside the United States;

and

2) To identify current surveillance issues in the Canadian public health system where ISDS can support dialogue and action.

 

Meat inspection data are routinely collected over several years providing the possibility to use historical data for constructing a baseline model defining the expected normal behaviour of the indicator monitored. In countries in which the reporting of data is compulsory (e.g. in the EU), coverage of the majority of the slaughtered population is ensured.

Objective

We evaluate the performance of the improved Farrington algorithm for the detection of simulated outbreaks in meat inspection data.