Early detection for protection
Two new Los Alamos National Laboratory projects, both internally funded by the Laboratory-Directed
Research and Development program, seek to address these identification and communication challenges,
one from the approach of a specific detection tool, and the other from a broader analysis of the system
and the varied tools that could speed a national response.
Early identification of influenza and hantavirus
One of the new projects is based on the detection of signature proteins that decorate the
surface of the influenza virus particle. In collaboration with University of New Mexico
Medical School, Lab researchers are developing a compact sensor system using thin films
that mimic cell membranes and wave-guide-based optical detection. This small
hand-held device will be simple to use and
capable of detecting influenza early after
infection. The project's objective is a simple
inexpensive device that could be used in a doctor's
office to guide treatment or in the field to provide information on the
spread of the infection.
The initial effort for this detector is focused on influenza and hantavirus.
Influenza is one of the leading causes of death in the United States, and
health experts are predicting a likely occurrence of a virulent new
influenza strain striking in the near future, similar to the 1918 pandemic
that killed more than 20 million people worldwide. Hantavirus, which is
common in many South American countries, has now been found in more
than 25 states, and its hemorrhagic fever kills approximately 45 percent of
its victims. In many cases, at rural clinics patients with flu-like symptoms
are sent home with a diagnosis of influenza, only to return in shock and
quickly succumb to the infection before proper treatment can be initiated.
With early diagnosis, patient survival rates improve significantly because they quickly can be referred to advanced care
facilities for appropriate treatment.
Infection from many biothreat agents (e.g., Bacillus anthracis that causes anthrax) also
produce flu-like symptoms. Accordingly, in the event of a bioterrorist attack, one of the
problems facing first responders and health-care workers is to be able to distinguish
bioagent infection from influenza. Without the disease's early identification, the patient
would likely be sent home only to die days later when the infection moved beyond the
treatable stage. A robust hand-held device that could quickly screen potential victims to
distinguish between influenza and infection or exposure to a biothreat agent is critical
for triage and will help save lives.
Early Warning — A prognostic epidemiology network
The need for rapid identification combined with the ability to swiftly notify other
members of the health-care community forms the basis of a second Los Alamos effort, that of an integrated early warning system for influenza.
The researchers are working to combine the skills of chemistry, biology, space science
and systems analysis to anticipate the course of an influenza outbreak and speedily
mitigate or eliminate its impact. Talent in genomics, cell biology, sensor development,
modeling and simulation, statistics and advanced systems engineering will all come into
play for this project, as will relationships with the Centers for Disease Control and
Prevention, the UNM School of Medicine and the New Mexico Department of Health.
Once perfected in the influenza application, the components will then be adapted to a
range of other natural and terrorist-derived threats.
Such a program requires a multi-level approach, an approach that Los Alamos is an
acknowledged leader. Among the components of the system will be the following:
- new data sources for influenza strain identification,
- new computer models for predicting disease spread and
- a nationwide network for communicating key informa-
tion and planning a response.
The first part of this effort, early identification of influenza
strains, will leverage the work already described, namely
the development of a small hand-held device capable of
detecting influenza early after infection. Further develop-
ment will identify genetic markers that are associated with
virulence of the virus and incorporate those into models
of influenza evolution and transmission. This research can
provide guidance as to which measures are most effective
in containing an impending outbreak.
In part two, detection sensor research will be expanded to identify and detect toxins, viruses and DNA
strands at vanishingly small concentrations. The sensor described previously uses a fluorescence-based
recognition system. Another promising effort already afoot, tags nucleotide ecognition elements to allow
identification of viral RNA sequences. Yet a third could be effective as well, that of using "molecular
beacons" that each detect a different target, marking single nucleotide variations in different virus strains.
Part three goes beyond the challenge of seeing what an infected patient is battling. In this phase, the objective is to determine what the patient has been exposed to, even before symptoms are evident. Chemical
changes within the epithelial lining of the lungs appear to provide useful information in this area. If patients
can be identified before they are either sick or infectious, simple public-health steps such as isolating and
breaking the expanding cycle of infection before it begins possibly can stop an impending epidemic.
The final phase of this aggressive program is called a Multi-Level Heterogenous Data Fusion. It addresses the
crippling isolation of the very health-care facilities that find and treat the earliest victims of an outbreak or
biological attack. Early detection of influenza-like illnesses is critical to the nation's ability to detect and
respond to a biological attack. Yet current medical reporting techniques involve a health-care worker writing
a case analysis some hours or days after a patient is seen. While the potential exists to gather extensive data
from the scattered health-care facilities, until these facilities are networked and reporting information in a
more timely, structured fashion, information is too little, too late.
On the local scale, health-care providers immediately need to recognize unusual events and take appropriate
action. Regionally or nationally, the local information must be transmitted to the decision-makers quickly
enough that mitigating measures can be put into place.
Existing prototype systems at Los Alamos can be tested to determine if they are of use in filling these information gaps. Current Los Alamos projects such as the Biological Aerosol Sentry Information System and a
medical surveillance system, called Rapid Syndrome Validation Project, (see "Rapid Syndrome Validation
Project ") both demonstrate the Laboratory's experience with networked sensor and information systems
and the ability to work with industry to provide open standards for combining clinic information systems.
Research that uses tools such as Mobile Software Agents that can perform detailed pattern searching on data
that educes an impenetrable mass of information to the key items can tell users whether or not a virulent
outbreak of the flu is at hand.