Biosurveillance refers to the integration of a wide variety of data to predict and quickly detect health events and forecast their impacts in a way that improves response decisions. As a practice, biosurveillance emerged out of public health surveillance with the goal of integrating significantly more data (and more types of data) for earlier and more accurate detection of health events. Practitioners believe that biosurveillance could lead to a more nuanced understanding of the early signs of the emergence and spread of diseases. Analysts look for a clearer disease signal in all the noisy data that can be gathered from human and animal activity. The conduct of biosurveillance, whether for public health or national security purposes, raises questions of individual privacy when so much of an individual’s detailed personal information is stored, shared, and accessible to public and private entities—foreign and domestic—for the stated purpose of the individual’s own health, well-being, and safety.

The variety of data that can be gathered is significant and expanding all the time. How those data are being collected, shared, and used is also changing as more applications of the data become apparent and more networks are created to exploit the data. All of this activity does, on reflection, beg consideration of the balance of risk and benefit to the individual, to society, and to global populations.

Types of Data Captured

There is a significant amount of very specific personal data that are captured today in electronic formats that simplify data sharing and analysis. This includes medical, laboratory, genetic, and health information as well as online and social media activities.

Every medical encounter, from an ambulance run to a hospital visit, can be collected as an electronic record. In such medical records are many traditional statistics such as the history of an individual’s vaccinations, diagnoses, lab results, and prescriptions; indicators of health status; and occurrences of infections and broken bones. To these are being added genetic tests that provide an even more unique description of who an individual is. Taken together, a significant amount of information exists about an individual’s past and present health at the molecular and clinical levels.

Access to mobile technologies creates numerous other sets of potentially useful data. Individuals reveal a lot about their personal habits, their social networks, their health status and that of their friends and family through chats, tweets, and other online posts.

These data sets can be mined for a fairly complete picture of who individuals are; what they do, think, and feel; and with whom and where they spend their time. Individual human health information can then be combined with other kinds of data, such as weather patterns, vector prevalence, travel patterns, and animal and plant health indicators, to begin to understand the correlates of health and disease.

Many infectious diseases of public health concern are prevalent outside the United States. Polio, measles, and viral hemorrhagic fevers such as Ebola all pose risks in other countries if not quickly detected and contained. Detecting outbreaks outside the United States requires both a voluntary network of reporting through state ministries of health and the monitoring of news and social media. The World Health Organization requires that all countries report certain diseases or health events known as “public health events of international concern.” In addition, private entities such as HealthMap and ProMED gather information from the news media and from individuals who report on local outbreaks in their cities or town and quickly post that information in ways useful to both specialists and a general audience.

Using Data for Biosurveillance

Biosurveillance can be used as a way to enhance public health surveillance and enable precision medicine, including improvements to pharmaceutical research. Currently, the benefits of biosurveillance are more speculative rather than scientifically established. This is due to a combination of technical and knowledge gaps. Knowing what data are relevant—beyond medical encounters, lab results, and prescription information—and being able to gather such data on a regular basis is an ongoing challenge. Even if useful data can be accessed, it is still often a challenge to develop systems that can exploit the data in ways useful to any of these purposes. How data have been or could be used for two different purposes is discussed in the following subsections.

Public Health

Public health refers to measures used by the state to prevent disease, promote health, and prolong life. Public health offices focus on the health of the population as a whole and not on any one specific individual. A standard use of biosurveillance methods is for the enhancement of public health surveillance.

Medical encounters form the core of biosurveillance for public health purposes. Epidemiologists at the state and local levels regularly look to such data for early signs of disease clusters in their populations. They often combine these data with other data sources such as poison control center calls, prescriptions, laboratory data, and morgue data—where available—to look for any other signs indicating an abnormal level of disease of some type.

State and local public health officials want to be able to intervene early in an outbreak to protect the health of their communities. Because biosurveillance provides access to much more data than can be traditionally accessed, earlier detection is becoming more possible. However, there are still challenges in understanding what kinds of nontraditional data can provide earlier signs of a disease outbreak.

Another challenge is in generalizing the results. Different communities may react differently to outbreaks within their populations. Therefore, the data and analysis that serve one community well may not apply equally to others. There is always the need for well-informed public health officers who know the habits of their specific populations.

Overall, biosurveillance data and practices can enhance situational awareness of the health of a community through an analysis of its longitudinal data. This can support research studies and lead to better intervention strategies for at-risk populations and support any investigation and response to a health event.

Precision Medicine

Precision medicine is an emerging area of research that seeks to provide treatments that are tailored to an individual’s specific genetic makeup, environmental influences, and lifestyle. Under this model, diagnostic testing is done to select therapies based on such individual characteristics. Precision medicine further expands the data used for biosurveillance purposes. In contrast to public health, however, precision medicine is designed to optimally serve the individual and not the public.

This does not mean that these two practices are divergent. Instead, there are closer connections emerging between clinical medicine and public health. To serve the individual, precision medicine requires the context of a much larger set of data. This would help determine what is unique in the individual’s biology and upbringing that would have an impact on the individual’s treatment.

Like politics, though, public health is local. The habits and environment that shape the health of one community can be quite distinct from those of another community in the same state and region. Context for an individual is further complicated by travel and mixing with multiple communities. Understanding what factors are causative and which ones correlate with health outcomes is not easy.

Advancements in the ability to tailor treatments will be built both on the continuing development of expertise in public health and the practice of clinical medicine and, critically, on the sharing of information between these very different professional communities. Data will need to be shared—and appropriate sharing will need to be defined.

There are groups who believe that sufficient computing power and appropriately calibrated models can provide the necessary answers given the right data. Others insist on the need for human experts, whose training and experience cannot be replaced by algorithms. The practice of biosurveillance appears to require both to continually improve the understanding of the other. Experts train systems. In turn, systems provide meaningful analyses and visualizations that prompt further expert inquiry, leading to further system improvements.

Privacy and Public Benefit

Each individual generates a significant amount of data about himself or herself that are captured for personal, public, commercial, or other uses every day. Individuals have very little control over their private information once it is collected in an information system—whether they voluntarily contributed the information or not. All this information, if shared, collected, and analyzed, could benefit biosurveillance practices—which in turn could benefit the individual. However, a number of privacy questions are associated with this activity. Fundamentally, how much authority do individuals possess over the sharing and use of their personal information? And how much should individuals have going forward?

Who has rights to the health and medical information that individuals provide to a hospital, clinician, or laboratory for their own medical care? To provide safe and efficacious medical care, it is important for a medical provider to know an individual’s medical history and the medical history of the individual’s close relatives. Currently, much of this information is automatically shared with local and state public health staff to monitor the community’s health—that is, for biosurveillance. Such “line-level” data (e.g., name, age, address, symptoms) are readily visible to the government’s public health staff to aid in their determination of whether there is an unusual disease cluster worth further investigation, and the individual has no right to prohibit this data sharing. Essentially, the right of the larger community to protect itself from infectious diseases outweighs an individual’s right to withhold his or her health information. This is a long-established practice in public health. The case of Mary Mallon, often referred to as “Typhoid Mary,” is an example of how much authority the state has to take action to protect the health of the public. In 1915, Mallon was forcibly isolated by the New York City Health Department because she was an asymptomatic carrier of typhoid fever. In her work as a cook, she unknowingly infected 51 people, causing three deaths.

There are questions both as to whether individuals have a right to control the uses of their private information and as to how that can be enforced. For example, there is a public benefit from public health biosurveillance activities. However, could this information be used for national security or commercial purposes without an individual’s consent as well?

Can individuals’ personal information be sold or exploited for other purposes without their knowledge or consent once it is acquired? For example, when individuals submit samples for genetic sequencing, can the sequencing company keep the samples and exploit the database of sequences for commercial or other purposes? Informed consent for the use of biological samples is evolving as various countries adopt different rules surrounding the subsequent use of such samples, particularly in biobanks.

Can the government compel release of this information to respond to a public health emergency or to assist in a criminal investigation? If the information could be used to identify subpopulations that are particularly susceptible or unusually resistant to certain diseases, should that be done to prioritize treatments in an emergency? And if evidence from a crime points to an individual with certain genetic traits, should the law enforcement authorities be allowed to use biosurveillance information to narrow the list of suspects based on their genetic profiles?

These kinds of considerations lead to a question of whether the state should establish protections for the individual in cases of misapplication of the data. If an individual is harmed from the misuse of data that are generally used for biosurveillance purposes, should the state provide a means of redress? Similarly, a widely discussed topic is genetic discrimination—the concern that employers or insurance companies could use the results of genetic testing to deny employment or coverage, respectively, for individuals based on those results. Should genetic discrimination be prohibited, or should insurance companies ensure coverage for specific tests for individuals with certain predispositions to yield earlier diagnoses?

Opting Out

It is worth considering whether protective measures should be adopted in the area of biosurveillance. Such a debate would likely be as contentious as the ongoing debate regarding the right to be forgotten on the Internet. There are valid and compelling arguments on both sides. However, if too many people opt out of sharing their information, whole communities can be put at risk. Over time, the ability of public health officials to quickly detect and control a disease outbreak would be weakened by the lack of such information, and more people would have to suffer than would otherwise have been the case.

If individuals should not have total control over the use of their information, however, there is a question of whether there should be some opportunity for their intent to be reflected. That is, should there be a set of choices for the further storing and sharing of their information for biosurveillance purposes, as there is for medical research?

Individuals are creating billions of records that can tell a lot about how they are shaped by numerous daily choices in their travel, diet, emotional state, work, and play in combination with their genetic makeup. Technology is indifferent to the intent of the user, but it increasingly enables greater mass benefit and mass harm. The practice of biosurveillance, by definition, involves the acquisition and use of private health and medical information at its core, and it is expanding to include a variety of other related data about individuals’ personal habits, environment, and genetics. It is timely to consider these questions of ownership, intent, potential benefit and harm, and appropriate protections as technology allows for the creation, storage, exploitation, and sharing of ever more data about individuals.

Stacy M. Okutani

See also Bioinformatics ; Biometrics ; DNA Technology ; Global Surveillance ; Public Health, Surveillance in

Further Readings

Bravata, D. M., et al. “Evaluating Detection and Diagnostic Decision Support Systems for Bioterrorism Response.” Emerging Infectious Diseases, v.10/1 (2004).

Dato, Virginia, et al. “How Outbreaks of Infectious Disease Are Detected: A Review of Surveillance Systems and Outbreaks.” Public Health Reports, v.119 (2004).

Friedman, Laine, et al. “Technical Report: Ethical and Policy Issues in Genetic Testing and Screening of Children.” Genetics in Medicine, v. 15 (2013). doi:10.1038/gim.2012.176

Fulda, K. G. and K. Lykens. “Ethical Issues in Predictive Genetic Testing: A Public Health Perspective.” Journal of Medical Ethics, v.32/3 (2006).

McNabb, Scott, et al., eds. Transforming Public Health Surveillance (1st ed.). London, England: Elsevier, 2016.

National Research Council. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease. Washington, DC: National Academies Press, 2011.

Ng, Jane, et al. “The Role of Longitudinal Cohort Studies in Epigenetic Epidemiology: Challenges and Opportunities.” Genome Biology, v.13 (2012). doi: 10.1186/gb-2012-13-6-246

Public Health Informatics Institute. Redesigning Public Health Surveillance in an eHealth World (June 2012). (Accessed August 2017).

Scheuner, Maren T., et al. “Are Electronic Health Records Ready for Genomic Medicine?” Genetics in Medicine, v.11 (2009). doi:10.1097/GIM.0b013e 3181a53331

Sintchenko, Vitali, et al. “Towards Bioinformatics Assisted Infectious Disease Control.” BioMed Central Bioinformatics, v.10/Suppl. 2 (2009). doi: 10.1186/1471-2105-10-S2-S10

White House. National Strategy for Biosurveillance (July 31, 2012). (Accessed August 2017).

Wild, C. P. “The Exposome: From Concept to Utility.” International Journal of Epidemiology, v. 41 (2012). doi:10.1093/ije/dyr236

Zeng, D., et al., eds. Infectious Disease Informatics and Biosurveillance (Integrated Series in Information Systems). New York, NY: Springer, 2011.