Chapter 13 INFECTIOUS DISEASE INFORMATICS AND OUTBREAK DETECTION Daniel zeng', Hsinchun hen', Cecil ~~nch~,Millicent ids son^, and Ivan ~otham~ '~ana~ementInformation Systems Department, Eller College of Management, University of Arizona, Tucson, Arizona 85721; '~ivisionof Medical Informatics, School of Medicine, University of California, Davis, California 95616; also with California Department of Health Services; 3~ewYork State Department of Health, Albany, New York 12220; also with School of Public Health, University at Albany Chapter Overview Infectious disease informatics is an emerging field that studies data collection, sharing, modeling, and management issues in the domain of infectious diseases. This chapter provides an overview of this field with specific emphasis on the following two sets of topics: (a) the design and main system components of an infectious disease information infrastructure, and (b) spatio-temporal data analysis and modeling techniques used to identify possible disease outbreaks. Several case studies involving real- world applications and research prototypes are presented to illustrate the application context and relevant system design and data modeling issues. Keywords infectious disease informatics; data and messaging standards; outbreak detection; hotspot analysis; data visualization Infectious Disease Informatics and Outbreak Detection 361 1. INTRODUCTION Infectious or communicable diseases have been a risk for human society since the onset of the human race. The large-scale spread of infectious diseases often has a major impact on the society and individuals alike and sometimes determines the course of history (McNeill, 1976). Infectious diseases are still a fact of modern life. Outbreaks of new diseases such as AIDS are causing major problems across the world and known, treatable diseases in developing countries still pose serious threats to human life and exact heavy tolls from nations' economies (Pinner et al., 2003). For instance, the estimated economic cost of Tuberculosis (TB) is 3 billion US dollars per year in India (http://www.healthinitiative.org). In addition to diseases that occur naturally, there has been increasing concern that terrorists may choose to attack by deliberate transmission of infectious disease using biological agents. With greatly expanded trade and travel, infectious diseases, either naturally occurring or caused by bioterrorism attacks, can spread at a rapid rate, resulting in potentially significant loss of life, major economic crises, and political instability (Chang et al., 2003). Information systems play a central role in developing an effective compre- hensive approach to prevent, detect, respond to, and manage infectious disease outbreaks of plants, animals, and humans (Damianos et al., 2002; Buehler et al., 2004). Currently, a large amount of infectious disease data is being collected by various laboratories, health care providers, and government agencies at local, state, national, and international levels (Pinner et al., 2003). Furthermore, many agencies have developed information access, analysis, and reporting systems of varying degrees of sophistication. For example, in its role as the key agency responsible for human reportable diseases in the U.S., the Centers for Disease Control and Prevention (CDC) has developed computerized reporting systems for local and state health departments. Similarly, the US. Department of Agriculture (USDA) is enhancing data systems for certain animal diseases (eg, mad cow disease and foot-and-mouth disease), and the U.S. Geological Survey (USGS), through its National Wildlife Health Center (NWHC) and numerous partners, manages databases for wildlife diseases. Databases may also be available at other federal and state or local health, agriculture, and environment/wildlife agencies and laboratories. In addition to infectious disease-related data sources, the research and public health communities have developed a wide array of analytical and statistical models targeted at analyzing disease data for surveillance and outbreak prediction purposes. For instance, such models have been employed to predict outbreaks of West Nile Virus (WNV) (Eidson, 2001; Eidson et al., 2001; Julian et al., 2002; Guptill et al., 2003; Mostashari et al., 2003; Ruiz et al., 2004; Wonham et al., 2004) and of influenza (Hyman and LaForce, 2003). 3 62 MEDICAL INFORMATICS This chapter introduces infectious disease informatics (IDI), an emerging subfield of biomedical informatics that systematically studies these information management and analysis issues in the domain of infectious diseases. More specifically, the objective of ID1 research can be summarized as the development of the science and technologies needed for collecting, sharing, reporting, analyzing, and visualizing infectious disease data and for providing data and decision-making support for infectious disease prevention, detection, and management. ID1 research directly benefits public health agencies in their infectious disease surveillance activities at all levels of government and in the international context. It also has important applications in law enforcement and national security concerning potential bioterrorism attacks (Siegrist, 1999). Aimed at providing an overview of the emerging field of IDI, this chapter emphasizes the technical side of ID1 research with detailed discussions on (a) the design and various system components of an infectious disease information infrastructure and (b) an important class of ID1 data analysis techniques concerning the identification of possible outbreaks. In order to provide the readers with a concrete sense of ID1 application contexts and relevant system design choices, we discuss both infectious disease information systems and standards that have been deployed in real-world applications and research prototypes for illustrative purposes. The majority of these case studies involve system development and deployment, and research projects in which we have been actively participating. The rest of the chapter is structured as follows. Section 2presents an overview of IDI. It discusses practical challenges arising when managing infectious disease data and presents the main technical components of an infectious disease information infrastructure and related research and system development issues. It also provides the readers with an introduction to analytical models and tools useful for infectious disease data analysis, in particular, outbreak prediction. Section 3 contains three case studies based on real-world applications and research prototypes to illustrate how to apply and synthesize in practice ID1 system development and data analysis techniques introduced in Section 2. Section 4 concludes the chapter by summarizing the main learning objectives of this chapter and discussing future directions in ID1 research and practice. 2. INFECTIOUS DISEASE INFORMATICS: BACKGROUND AND OVERVIEW 2.1 Practical Challenges and Research Issues In practice, infectious disease data collection and analysis are complex and in most cases involve a multi-stage process with multiple stakeholders across organizational boundaries. Due to the nature of epidemics, there is also a critical need for timely data collection and processing. Infectious Disease Informatics and Outbreak Detection 363 The traditional approach to infectious data collection, dissemination, and reporting is a paper-based system that depends on telephone conversations for transmission of data and multiple personnel entering or updating paper-based case report forms. This approach leads to many problems related to information processing. Figure 13-1 illustrates a typical paper-based state and local data management approach for Botulism, a rare but significant infectious disease caused by a disease agent that can be used in a bioterrorism attack. This figure summarizes the information flow between various roles and organizations for Botulism case reporting and demonstrates the multiple areas of potential breakdown in communication (indicated by the 61 sign.) Deternlines Nerd P.oWlisna ..-- for Outbredk Investigation T, 1.d11"' . Seeks subn~its Morbidity Reporl or Reports Colllirnied Food bonw restock San~yledraw Checks spedmes , I S~cci~tien Srnds to State Figure 13-1. Paper-based Botulism Case Reporting Many of these areas of potential breakdown in communication could be overcome with an automated process of data flow provided by a computerized infectious disease information system. Having historical data collected on outbreaks that are readily available for predictive modeling would also lead to improved surveillance activities, fewer data entry errors, and better public health data. Data in an information system would facilitate the required reporting of infectious diseases from local public health jurisdictions to state organizations and from state organizations to national surveillance entities such as the CDC. Additionally, information systems would streamline the reporting requirements for bioterrorism agents to the Department of Justice. Such systems also simplify dramatically the required chain of custody analysis for samples being tested for biological or chemical hazards. Infectious disease information systems also 364 MEDICAL INFORMATICS provide the ability for application of the ever expanding collection of statistical algorithms to data in real time that would not be possible without such systems. Increasingly, infectious disease data are being collected in an electronic form by various laboratories,