Disease Surveillance

Technological Contributions to Global Health Security

David L. Blazes, Sheri H. Lewis, David L. Blazes, Sheri H. Lewis

• Publisher: CRC Press
• Year: 2016
• ISBN:
  9780429585999
• Edition: 1
• Topic: Medicine
• Subtopic: Medical Theory, Practice & Reference

Disease Surveillance: Technological Contributions to Global Health Security reminds us of the continued vulnerability of the world to contagious infections. The book presents examples of disease surveillance systems and evaluates promising advances as well as opportunities for new systems. It also explains how newer technologies can allow countries

PART 1

Disease surveillance concepts

1 Introduction to electronic disease surveillance

David L. Blazes and Sheri H. Lewis

2 International health regulations: Policy

Rebecca Katz, Sarah Kornblet, Erin M. Sorrell, Claire Standley, and Julie Fischer

3 Public health surveillance system considerations

Carmen C. Mundaca-Shah, John Mark Velasco, and Julie A. Pavlin

4 Surveillance challenges in resource-limited settings

Karen Saylors

5 The role and functional components of statistical alerting methods for biosurveillance

Howard S. Burkom

6 Effective public health data visualization

Neil F. Abernethy and Lauren N. Carroll

1

Introduction to electronic disease surveillance

DAVID L. BLAZES AND SHERI H. LEWIS

Introduction

Modern historical perspective

Organization of the text

Controversial points

The future

References

INTRODUCTION

Disease surveillance has been conducted informally since the dawn of civilization as a means of protecting oneself and ones in-group from infections and other illnesses, mainly through avoidance of high prevalence areas or practices. As human societies became more complex, so did methods for disease surveillance. Increasing interactions between societies, and the resultant interdependence on trade for survival and growth, led to a greater need for more detailed information concerning the spread of disease by people, animals, and trading goods such as food. Unfortunately, medical knowledge of how to treat or prevent illnesses has frequently lagged behind the simple recognition of conditions that are threatening to our health. But it has become conventional wisdom that, in order to fully control a particular disease, an accurate understanding of the epidemiology is required. In today’s globalized and fully interconnected world, the potential speed of disease transmission is remarkably fast and often shorter than the incubation period of many infectious diseases. In order to keep pace, rapid disease surveillance methods are required, and simple collection and reporting via traditional paper methods that worked well for many years is no longer considered adequate in an increasingly connected world. Electronic disease surveillance offers numerous benefits to include more rapid transmission of information, more accurate representation of the data, and a greater ability to aggregate individual data streams to provide a more comprehensive understanding of a disease through a big data approach.

MODERN HISTORICAL PERSPECTIVE

Disease surveillance was defined by Langmuir in 1963 as “the continued watchfulness over the distribution and trends of incidence through the systematic collection, consolidation and evaluation of morbidity and mortality reports and other relevant data,” with the “…regular dissemination of the basic data and interpretations to all who have contributed and to all others who need to know” (Langmuir 1963). Thacker expanded and refined this definition in 1988 when he wrote, “Public health surveillance is the ongoing systematic collection, analysis and interpretation of outcome-specific data for use in the planning, implementation, and evaluation of public health practice” (Thacker and Berkelman 1988). This linking of public health surveillance with the evaluation of public health practice emphasizes its primary purpose—to direct the expenditure of limited public health resources in a manner that yields the greatest return on investment (Thacker 1994).

Public health surveillance involves clearly defining events of public health interest, counting those events, and then analyzing those events with respect to person, place, and time. For example, the U.S. Centers for Disease Control and Prevention’s (CDC) case definition for an influenza-like illness (ILI) is “Fever (temperature of 100°F [37.8°C] or greater) and a cough and/or sore throat without a known cause other than influenza” (U.S. Centers for Disease Control and Prevention 2014). Patients meeting the case definition of ILI are counted by sex and age category (person), characterized by site (place), and date of onset (time). This conceptually simple process not only characterizes the level, distribution, and spread of ILI in the community but also suggests useful information such as determinants of disease transmission, possible mitigation strategies, and future prevention strategies. Public health surveillance may be performed on all patients, the so-called universal surveillance, or may be performed at designated sites felt to be representative of the population as a whole, the so-called sentinel surveillance. Surveillance may also be described as active, when public health officials contact health-care providers, or passive, when public health officials rely on reports from health-care providers. A wide variety of data sources are used in public health surveillance, including vital statistics, health reports, hospital records, laboratory reports, outpatient visits, registries, and health surveys.

Disease surveillance is commonly recognized for its ability to detect disease outbreaks. Simply put, unless the baseline level of disease is well understood, it is difficult to identify disease levels significantly in excess of what is normal (Thacker and Berkelman 1988). This is an important function, and the early detection of anomalous disease events, particularly the intentional release of pathogens, has received much attention in recent years. Critics point out that disease surveillance, particularly syndromic surveillance, may not catch small outbreaks of disease that remain hidden in the background noise, and also note that diseases with shocking presentations, such as hemorrhagic fevers, are generally identified by astute health-care providers or laboratory technicians (Reingold 2003). Nevertheless, disease surveillance plays a critical role in the detection and ongoing monitoring of disease outbreaks (Langmuir 1963; Thacker and Berkelman 1988; Thacker 1994; Lombardo and Ross 2007; CIFOR 2009). Importantly, in the case of small- to medium-size outbreaks distributed over a wide geographic area—now common in the case of gastrointestinal outbreaks due to large, centralized food processing plants—coordinated disease surveillance identifies problems that might otherwise go unnoticed in each local jurisdiction (CIFOR 2009). Disease surveillance accomplishes several additional important functions to direct the practice of public health (Thacker and Berkelman 1988). It identifies and quantifies the diseases most burdensome to a given population, allowing for allocation of sometimes scarce resources. Disease surveillance can carefully document how a disease spreads through the population of interest and how it affects individuals over time, and, as a result, can lead to real-time interventions. Importantly, disease surveillance can be used to evaluate public health interventions and identify effective and ineffective public health practices. Finally, disease surveillance can suggest hypotheses, direct research, and detect changes in the practice of clinical (or veterinary) medicine over time. Effective disease surveillance, though not always exciting, is the foundation of successful public health practice.

For centuries, disease surveillance was a paper-based process. In the 1990s, with the emergence of inexpensive, powerful information technology (IT) tools, disease surveillance became an electronic process in wealthy countries (Lombardo and Ross 2007). The incorporation of IT advances led to startling improvements in the timeliness of public health reporting and sophistication of data analysis. These systems initially were stood up to detect a possible intentional biological attack, and as such, their use and acceptance increased exponentially after the events of September 11, 2001 and the anthrax attacks of October 2001. While initially hesitant to adopt these types of systems, public health officials quickly realized their benefit in monitoring the community for the more common conditions such as influenza-like illness, gastrointestinal disease, etc. When systems are used on a daily basis by epidemiologists to monitor their community, they are much more likely to be able to successfully use the system to detect any type of intentional agent release. Such systems have become versatile, commonplace tools in many health departments in the United States, and these electronic disease surveillance tools hold promise to improve health security in resource-limited environments that may benefit from the lessons learned by others to date (Lombardo et al. 2003; Jajosky and Groseclose 2004; The Centers for Disease Control and Prevention 2007; Chretien et al. 2008; Soto et al. 2008). Epidemiologists using electronic disease surveillance not only have the potential to detect anomalous disease activity earlier than traditional laboratory-based surveillance, but they also have the ability to monitor the longitudinal health of their community in the face of a known threat (Lombardo et al. 2003; Jajosky and Groseclose 2004; The Centers for Disease Control and Prevention 2007). Additionally, many electronic disease surveillance systems are able to automatically ingest large amounts of pre-existing electronic data streams for analysis. These data sources, such as insurance claims, prescription data, school absentee data, and commercial sales of over-the-counter medicines, are not traditional health data from medical treatment facilities, yet they often have high public health informational content (Lombardo et al. 2003).

Emerging and re-emerging infectious diseases are among the most serious threats to global public health (Binder et al. 1999; Morens et al. 2004). The World Health Organization (WHO) has identified more than 1100 epidemic events worldwide in the last 10 years alone (The World Health Organization 2007). The emergence of the novel 2009 influenza A (H1N1) virus and the SARS coronavirus in 2002–2003 have demonstrated how rapidly pathogens can spread worldwide (Binder et al. 1999; Morens et al. 2004; Hollingsworth et al. 2007; The World Health Organization 2007). This infectious disease threat, combined with a concern over man-made biological or chemical events, spurred WHO to update their regulations concerning health and the spread of diseases in 2005 (The World Health Organization 2005). These modified International Health Regulations (IHR), a legally binding instrument for all 194 WHO member signatory countries, significantly expanded the scope of reportable conditions and are intended to help prevent and respond to global public health threats. Specifically, the IHR require strengthening of disease detection and response capacities in order to report, within 24 hours of assessment, any public health event of international concern. A clear way forward to satisfy both the letter and spirit of these IHR is to facilitate reporting of events, a well defined benefit of electronic disease surveillance platforms.

In addition to the updated IHRs, there has been growing political interest in the concept of global health security. The WHO and many countries have overtly addressed these “global commons” threats through initiatives such as the Global Health Security Agenda (GHSA) of the United States, whose goal is to accelerate progress in the prevention of, detection of, and response to infectious disease threats over a 5-year period. A key component of the GHSA is public health surveillance. The GHSA specifically targets infectious diseases and includes the topics of novel disease propagation and globalization of trade and travel, in addition to highlighting concerns about increasing antimicrobial drug resistance as well as the threat of disease from the accidental release, theft, or illicit use of a dangerous disease agent. This latter point—accidental release, theft, or illicit use of a disease agent—also draws attention to the growing field of “do-it-yourself (DIY) biology” as well as to research ethics. DIY biology, while often well intentioned and practiced as an after-hours hobby by many trained researchers in academia and corporations, is an unregulated or self-regulated activity. Some in the scientific community fear this DIY work could result in inadvertent or malicious development and release of a biological weapon, heightening the need for increased surveillance capacity.

Also of concern is the ability of scientists to replicate diseases in such a way that modifies their lethality. Although it is truly awe inspiring that science has come so far, charged discussions result when researchers want to share their findings worldwide through publication in peer-reviewed scientific journals, which is the norm for those working in the field. In recent years, there has been debate over the ethics of publishing research that exposes the “recipes” for replicating viruses and changing the virulence of viruses such as avian influenza (H5N1). Many fear that such publications could provide those with nefarious intent with the information needed to develop a “superbug.” As scientists continue to make advances in the rapid identification and experimentation of novel pathogens, this debate will likely continue for years at the highest levels of government and academia. In the end, it has proven very difficult to control or contain the spread of such technology, so many public health officials have instead decided to focus on the early detection of a release of such an agent, mainly through enhanced disease surveillance around the globe.

In answer to these challenges, numerous teams of software engineers, analysts, and epidemiologists have been working for more than 15 years to develop advanced electronic disease surveillance technologies, in both the developed setting such as the United States and increasingly in developing settings as well (Dean et al. 1994; Loschen et al. 2007; Burkom et al. 2008; Ashar et al. 2010). Today in the United States, public health professionals in most states have the capability to collect, analyze, and visualize data to assess the health of their communities. Additionally, there are public health “superusers” who are taking electronic disease surveilla...