What is biosurveillance? |

Definition

Biosurveillance is a systematic process of surveying the environment for viruses, bacteria, fungi, and other pathogens to detect disease in humans, animals, and plants. The process also characterizes outbreaks of such disease.

Overview

Biosurveillance combines disease surveillance with public health surveillance,
both of which depend upon data collection and analysis with the goal of early
disease detection to thwart a potential outbreak. Diseases may be defined by
incubation and infectious periods, source, and transmission route, while outbreak
characterization uses general analytic techniques, such as spatiotemporal
distribution, incidence, mortality, and cohort or case-control studies.
Biosurveillance proceeds from continuous data collection to confirmation of cases
with a feedback loop back to data aggregation. Environmental investigations
include food chains, vectors, weather, geography, the number of people who became
ill, and those at risk.

In the United States, the major use of biosurveillance is to track emerging and
reemerging infectious diseases such as H1N1 influenza, food-borne diseases
caused by resistant strains of Escherichia coli and
Salmonella, sexually transmitted diseases (STDs),
and human
immunodeficiency virus infection, which may also be
transmitted by contaminated blood products or through maternal transmission.

In the United States, government agencies conduct biosurveillance at the levels
of state and local health departments, which then report to federal agencies such
as the Centers
for Disease Control and Prevention (CDC), a division of the Department of Health and Human Services
(HHS). The CDC is responsible for collecting, analyzing, and distributing national
disease occurrence and mortality rates to state and local health authorities and
to the public. Other federal agencies conducting biosurveillance include the
Department of Defense (DoD), the Department of Homeland Security (DHS), and, globally, U.S. collaborative partners such as the
World Health
Organization (WHO), the Pan American Health Organization (PAHO), and the South East Asia Regional Office (SEARO).

Before 2000, biosurveillance systems included the National Electronic
Telecommunications System for Surveillance (NTESS) and PulseNet, the national
subtyping network comprising state and local public health laboratories and
federal food regulatory laboratories that perform molecular surveillance of
food-borne infections. Systems in place after 2000 include BioSense and other
early warning systems, such as the Real-time Outbreak and Disease Surveillance
System (RODS).

Numerous decision-making tools, such as Bayesian
inference, may be applied to the detection of an outbreak of
infectious disease. The importance of the decision-making process cannot be
overestimated when providing alerts to the public. The costs versus benefits of
false alerts must be weighed against the goal of protecting the population at
risk.

Influenza Surveillance

The CDC maintains a comprehensive surveillance system for influenza
viruses, which mutate from year to year, requiring the collection and
characterization of varying types of pathogens. Flu vaccines have to be annually
updated in accordance with surveillance data to include relevant strains.
Treatment for influenza is determined by laboratory surveillance for antiviral
resistance. The impact of influenza on hospitalizations and mortality must also be
assessed.

The epidemiology and prevention branch of the influenza division at the CDC collects and analyzes information on influenza activity throughout the year in the United States. This surveillance results in “FluView,” a weekly report, which is issued from October through mid-May of each year. The influenza surveillance system is a collaborative effort between the CDC and its many partners in state, local, and territorial health departments; public health and clinical laboratories; health care providers; clinics; and emergency departments.

The CDC employs five categories of influenza surveillance: viral, outpatient influenza-like illness (ILI), mortality, hospitalization, and Flu-SurvNET. ILI is defined as a fever (100° Fahrenheit or 37.8° Celsius or greater) and a cough or sore throat (or both) in the absence of a known cause other than influenza. Flu-SurvNET provides population-based, laboratory-confirmed estimates of influenza-related hospitalizations. Each week, approximately eighteen hundred outpatient care sites around the United States provide data to the CDC. This data includes the total number of patients with ILI, according to age group. The data by age had confirmed, for example, that young people were more adversely affected by H1N1 influenza in 2009, relative to those age sixty-five years and older (when compared with seasonal flu).

Also included in national data are human infections with novel influenza A viruses, pneumonia, influenza mortality from the 122 Cities Mortality System, influenza-associated pediatric deaths, and Aggregate Hospitalizations and Death Reporting Activity. The Emerging Infections Program (EIP) is a population-based network of the CDC and state health departments that assesses the public health impact of emerging infections and examines ways to prevent and control these infections.

Viral Surveillance

Approximately eighty U.S. and WHO collaborating laboratories and sixty labs from the National Respiratory and Enteric Virus Surveillance System (NREVSS) participate in influenza surveillance. The U.S.-WHO and NREVSS collaborating labs report to the CDC the total number of respiratory specimens tested and the number of positives for influenza types A and B each week. Reports from both U.S.-WHO and NREVSS are combined and presented in “FluView.”

Routine seasonal surveillance does not count individual flu cases, hospitalizations, or deaths (except for pediatric influenza deaths); rather, it monitors flu activity levels, trends, and viral characteristics through a nationwide surveillance system. The reporting of hospitalizations and deaths by state health departments was initiated at the start of the pandemic H1N1 outbreak in 2009. To avoid the underestimation of cases, the CDC altered this system and asked states to report both laboratory confirmed hospitalizations and deaths and presumed influenza or pneumonia deaths on cases coded as ICD-9 (International Classification of Diseases). The CDC also created a Web-based data application for states to submit their numbers each week. This data is compiled for publication in the CDC’s Morbidity and Mortality Weekly Report (MMWR) and in “FluView.”

HIV and AIDS Surveillance

The annual HIV Surveillance Report
provides an overview of the most up-to-date epidemiology data on HIV infection in the United States and five U.S. territories. The CDC funds state and territorial health departments so they can collect data on persons with HIV infection; all personal identifiers are removed before data is transmitted to the CDC through a secure data network. Data are analyzed by the CDC and then displayed by age, race and ethnicity, gender, and transmission category, a significant change in the operation of the surveillance system. Moreover, the HIV Surveillance Report for 2012 (to be issued in 2014) marks the first time that data is included from each of the fifty states.

In 2008, changes were made to the case definition of HIV infection. To
accurately track the epidemic, emphasis is now be placed on HIV surveillance
rather than on acquired immunodeficiency disease syndrome (AIDS)
surveillance. HIV testing and linkage to care are essential for identifying
persons early.

Approximately 1.1 million persons in the United States are HIV-positive. The CDC used 2001 to 2009 data from the National Health Interview Survey to estimate percentages of persons age eighteen through sixty-four years who reported being tested (at any time) for HIV in the United States. Data from the national HIV surveillance system were employed to estimate cases and rates of HIV infection, AIDS diagnoses, and late diagnoses of HIV infection. In turn, these data were used to determine the populations and regions most affected by HIV and AIDS and to determine the trends in HIV testing and late diagnoses.

Food-borne Disease Outbreak Surveillance

Food-borne pathogens cause an estimated seventy-six million illnesses annually in the United States. Data from outbreak surveillance provides insights into the etiology of these illnesses, the foods in question, and their settings. State, local, and territorial health departments use a standard, Web-based form to report food-borne outbreaks to the Foodborne Disease Outbreak Surveillance System.

As reported to the CDC, 1,097 food-borne outbreaks occurred in 2007, which
resulted in 21,244 cases of illness and 18 deaths; of the single, laboratory
confirmed agents of outbreak-associated illnesses, 12,767 were caused by norovirus
(47 percent) and Salmonella (27 percent). In July, 2010, the CDC
collaborated with public health officials in several states and with the HHS, FDA,
and the Department of Agriculture (USDA) Food Safety and Inspection
Service to investigate a nationwide rise in S. enteritidis (SE)
infections. Investigators used deoxyribonucleic acid (DNA) analysis of SE bacteria
obtained through diagnostic testing to identify cases of illness. They also
identified restaurant and event clusters that may have been associated with this
outbreak. Investigators determined that eggs contaminated by
Salmonella were responsible for the outbreak. In late
November, 2010, following a recall and ban, the FDA issued permits to some of the
affected farms, allowing the resumption of egg sales.

Impact on Global Public Health

The age of public health globalization has arrived. Global health and global
health surveillance have come to the fore, in part because of newly emerging and
reemerging infectious diseases. In addition, climate change, poor hygiene and
sanitation, lack of economic and food security, political unrest, war, and
accelerating threats of bioterrorism have greatly increased global morbidity and mortality from
infectious diseases, especially in developing countries.

To counter these challenges, global health surveillance procedures have been updated. Changes were made to the new International Health Regulations (IHR), new global networks were developed, and specific guidelines to monitor emerging diseases and acts of bioterrorism were developed. Global surveillance now provides real-time information about potential outbreaks and epidemics.

Global response to the 2009 H1N1 influenza pandemic demonstrated the benefits of the new global monitoring systems and the importance of WHO in coordinating the global public-health community. As a result, valuable models were developed on how to respond to novel strains of influenza and other pathogenic entities, such as the severe acute respiratory syndrome (SARS) virus. As the number of cases H1N1 influenza cases increased and rapidly spread, it was apparent that significant resources, intervention, and biosurveillance at the international level would be necessary.

Bibliography

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Lazarus, R., et al. “Using Automated Medical Records for Rapid Identification of Illness Syndromes (Syndromic Surveillance): The Example of Lower Respiratory Infection.” BMC Public Health 1 (2001): 9. Discusses how information gleaned from automated medical records complements current surveillance programs by evaluating most episodes of illness for which no etiologic agent is defined.

Lober, W. B., L. Trigg, and B. Karras. “Information System Architectures for Syndromic Surveillance.” Morbidity and Mortality Weekly Report 5, suppl. (2004): 203-208. Describes the information-architecture components of a particular surveillance data system.Discusses existing and potential approaches to data integration.

O’Neil, Eileen A., and Elena N. Naumova. “Defining Outbreak: Breaking Out of Confusion.” Journal of Public Health Policy 28 (2007): 442-455. Illustrates the complexity of defining terms used to describe emerging and reemerging infectious diseases that have resulted in the use of emotionally charged terms such as “outbreak.” Argues that public health may benefit from strengthening the definitions of key terms.