2012 ISDS Conference – International Society for Disease Surveillance


Sheraton San Diego Hotel and Marina, San Diego, California, USA

December 3-5, 2012


The ISDS Annual Conference is the premier event dedicated to the advancement of the science and practice of biosurveillance. This year’s theme, Expanding Collaborations to Chart a New Course in Public Health Surveillance, will highlight the importance of working together across agencies, sectors, and disciplines to improve surveillance methods and population health outcomes. The conference will be held at the Sheraton San Diego Hotel and Marina in San Diego, CA, December 4-5, 2012, with Pre-Conference Workshops on December 3rd.

The ISDS Conference draws professionals from a broad range of disciplines— epidemiology and computer science to mathematical modeling and health policy—to learn and contribute the latest achievements, methodologies, best practices, conceptual frameworks, and technical innovations in the rapidly evolving field of biosurveillance. This year’s conference will provide fertile ground for cultivating new ideas and partnerships with roundtable discussions, panels and other opportunities to collaborate.


2012 ISDS Conference Proceedings (pdf)

The 2012 ISDS Conference Proceedings are also published in a special issue of the Online Journal of Public Health Informatics (OJPHI); Volume 5, Number 1 (2013).


To view the 2012 ISDS Pre-Conference Workshops and Conference agendas, please click here (pdf).

Pre-Conference Workshops

The goal of the 2012 ISDS Pre-Conference Workshops was to provide the target audiences with the tools and methods that will help them to advance the field of disease surveillance.

Syndromic Surveillance, Informatics, Data Analysis, and Anomaly Investigation: The 101 Series


This Workshop (referred to as the 101 Series) provided an overview of key topics to introduce professionals to core public health and surveillance competencies. The workshop included an overview of syndromic surveillance, public health informatics, data analysis methods, anomaly detection, investigation techniques, and data visualization methods using “R” statistical software. The objective of this workshop was to “bridge the knowledge gap” in order to better understand and apply public health data for informed and meaningful decision-making.


  • Introduce key topics and increase knowledge of syndromic surveillance for public health practitioners, physicians, and others who are not familiar with syndromic surveillance.
  • Stimulate cooperation and involvement among syndromic surveillance system stakeholders.
  • Introduce biosurveillance data types, their characteristic features, and key issues regarding data acquisition and data quality.
  • Describe common data analysis methods necessary for public health surveillance practice.
  • Introduce the open-source R software and explain how to perform the common data analysis procedures using hypothetical data.
  • Explain how to obtain common statistical summary measures using hypothetical data in R.
  • Highlight useful visualization tools in R.
  • Describe the objectives and limitations of anomaly detection methods.
  • Explain underlying ideas of several types of anomaly detection techniques, when to apply them, and how to interpret results.
  • Provide an in-depth explanation of the results of a standard anomaly detection method applied on an example scenario.
  • Describe anomaly investigation techniques and provide a state and local perspective on the techniques.
  • Identify and provide possible solutions to common barriers in anomaly investigation.

Public Health and Meaningful Use: Closing the Surveillance Loop


This workshop was designed to facilitate discussions around Meaningful Use and the need for closing the surveillance loop between healthcare providers and public health practitioners in order to increase the effectiveness and capacity of disease surveillance. The track included an overview of Meaningful Use and Health Information Exchanges (HIEs), including best practices, lessons learned, and next steps. Interactive break-out sessions focused on the healthcare provider onboarding process, data transport mechanisms, data quality issues, analytics, attestation, and other group-specified topics. The break-out groups also had an opportunity to summarize and report their findings to the larger group. The Workshop concluded with a panel discussion, integrating the perspectives of public health practitioners and healthcare providers on the “meaning” of Meaningful Use data.


  • To increase understanding among participants of the Meaningful Use and what it means for them.
  • To increase knowledge of health information exchange best practices so that those at an earlier stage of implementation can learn from the experiences of others.
  • To increase collaboration among participants and the development of support networks.
  • To increase understanding among public health practitioners of the public surveillance information and reporting format that providers would find most useful in their work.

Assessment tools to meet the core capacities of the surveillance goal of the International Health Regulations (2005)


This hands-on workshop introduced participants to the concepts and tools used to assess the gaps in performance of public health surveillance that should be addressed to meet the core surveillance requirements under the 2005 International Health Regulations (IHRs). Attendees learned IHR surveillance requirements and assessment concepts, plus used hands-on tools to measure anonymous, real country-specific opportunities and challenges (gaps) and costs to improve surveillance. They discussed specific approaches to meet IHR targets by correlating assessment findings into recommendations for action and funding by stakeholders.


  • Review the core requirements for surveillance as defined by the IHRs
  • Understand the conceptual framework used to assess the country-specific opportunities and challenges to meet surveillance goals
  • Understand the methodology to apply the conceptual framework including:
    • Logic models
    • Indicators
    • Principal component analysis (PCA)
    • Cost/benefit analysis
    • Dashboard of results
    • Apply these tools and methodology using anonymous, real country-specific data
  • Participate in a round table review of results

Scientific Program Committee