[Jaideep] Ray says that characterizing diseases requires observations of real outbreaks and then building computer models around them. He did this for a 1979 anthrax outbreak in Sverdlovsk (called Yekaterinburg, after the fall of the Soviet Union), a city of about 1.2 million people in central Russia. Initially the Soviets said the victims contracted the disease by eating anthrax-contaminated meat or having contact with dead animals. At the end of the Cold War American physicians reviewed documents published by pathologists who performed autopsies during the epidemic, confirming the pathogen was airborne. Records showed that 80 humans were infected, most of them by inhaling the pathogen. A total of 68 died of the disease.

Using the computer program, Ray ran the data obtained from hospital records of people who became sick in the early days of the epidemic. The program automatically tried many combinations of the unknown number of infected people, time and dose of anthrax exposure until it got as close to the real observation as possible. In the final runs, using data from the first nine days of the 42-day outbreak, the model inferred that almost certainly less than 100 people had been infected, with the most probable number around 55.

That was “pretty close,” to the real event, he says. The program, which also estimated the time of the release and the dose of anthrax inhaled, took 10 minutes to run.

“If they had had this program in 1979 the Soviet officials would have known that this was going to be a small outbreak,” Ray says. “Instead they got into a panic and vaccinated 50,000 to 60,000 people — the whole southern end of the city.”

Nigerian smallpox epidemic

After proving the software actually works, he turned his attention to communicable diseases, specifically smallpox. He modeled a documented smallpox outbreak in Nigeria in 1967, which broke out in a fundamentalist sect (Faith Tabernacle Church, FTC) in the town of Abakaliki. The sect consisted of 120 people who lived in nine different compounds, along with 177 of their nonsectarian brethren. The FTC members mixed strongly in their compounds and across compounds at church four times a week and social visits.

A small girl first introduced the disease into the population. It spread rapidly in her compound and jumped to other compounds via the church and social visits. The sect members refused medical treatment and did not quarantine the sick and contagious members. While the World Health Organization (WHO) monitored the outbreak and kept records of who got sick and when, it did not record the dates of recovery or deaths of the infected people.

Of the 32 people who became infected during the epidemic, 30 were FTC members.

Full story: Sandia researcher develops inference technique that estimates how many people will fall sick in an epidemic

More about the system:

MethShield™ can work on two different levels. First, it works as a simple electronic logbook allowing you to effortlessly comply with requirements of State and Federal laws. Photo ID information is simply typed or scanned into the system. The product requested is then selected from a live database of pseudoephedrine based products. The database tracks the amount of pseudoephedrine in each product sold to an individual and ensures compliance with daily and monthly limits.

The second and optional feature of MethShield™ is that it can alert you to suspicious purchase behavior. MethShield™ can tell you if the person at your counter is making their first visit to the pharmacy today or their fifteenth. The real power of MethShield™ comes with aggregation of the data. By taking the information you have entered and combining that with data from pharmacies across a state or nation, law enforcement can be provided with a real-time snapshot of any suspicious behavior. MethShield™ then provides law enforcement with a sophisticated set of intelligence tools to assist in the tracking and apprehension of potential pseudoephedrine runners.

MethShield homepage...

KWCH TV: MethShield Kicks off in Kansas...

In experiments over the past year, a research team at Lawrence Livermore National Laboratory has used their system to detect a tuberculosis surrogate, even when it is surrounded by sputum and mucus-like substances.

They also were able to differentiate between two similar bacteria, distinguishing between an avirulent strain of tuberculosis and a similar bacterium, Mycobacterium smegmatis.

Their research, using a system called Single-Particle Aerosol Mass Spectrometry, or SPAMS, is described in today's edition of Analytical Chemistry, a semi-monthly journal published by the American Chemical Society.

"Without reagents, we can rapidly detect avirulent tuberculosis that is coated in sputum-like materials and we can distinguish between two similar mycobacteria," said Kristl Adams, a LLNL postdoctoral biological physicist and the paper's lead author.

"The reason we used two similar mycobacteria in our research is that tuberculosis-like symptoms in a patient could be caused by many bacterial infections, not just tuberculosis. So we would like to differentiate between non-tuberculosis and tuberculosis infections," Adams explained.

While emphasizing that their work is only a first step toward using SPAMS for tuberculosis diagnostics, Frank and Adams said they believe SPAMS could potentially detect the disease within five minutes with concentrated samples.

The SPAMS researchers have spoken with doctors at two northern California university medical centers about the possibility of undertaking experiments in a clinical setting to detect virulent tuberculosis within sputum samples from infected people.

The biggest challenge going forward is determining if infectious tuberculosis in humans can be detected with our pattern-matching algorithm. It is undetermined if the virulent tuberculosis pattern will have enough similarity from patient-to-patient that we can train on a known TB patient and detect TB in a patient with an unknown infection," Adams said.

Press release: Instrument designed for biological pathogen monitoring can detect tuberculosis surrogate

Abstract in Analytic Chemistry: Reagentless Detection of Mycobacteria tuberculosis H37Ra in Respiratory Effluents in Minutes

Watch an interview by ABC News with Ben Berman, one of the co-founders of the project, where he explains the details of the project.

Project homepage: TakesAllTypes.org...

More the PLoS Medicine article:

The use of international news media for public health surveillance has a number of potential biases that merit consideration. While local news sources may report on incidents involving a few cases that would not be picked up at the national level, such sources may be less reliable, lacking resources and training, and may report stories without adequate confirmation. Furthermore, other biases may be intentionally introduced for political reasons through disinformation campaigns (false positives) or state censorship of information relating to outbreaks (false negatives). We have attempted to better understand some of these issues through ongoing analysis and evaluation research. We ran a 43-week evaluation of HealthMap data, covering the period of October 1, 2006 through July 18 2007. We found that pathogen diversity was substantial across news sources, with 141 unique infectious disease categories reported through the Google News feed alone. We found the frequency of reports about particular pathogens to be related not to their associated morbidity or mortality impact, but rather to the direct or potential economic and social disruption caused by the outbreak.

The system characterizes disease outbreak reports by means of a series of text mining algorithms. Characterization stages include: (a) identifying disease and location; (b) determining relevance—namely, whether a given report refers to any current outbreak; and (c) grouping similar reports together while removing exact duplicates. Once the reports are automatically processed, curators correct the misclassifications of the system where necessary. Currently, only one analyst reviews and corrects the posts. However, additional resources would enable more detailed multilingual curation and annotation of collected reports.

Extracting location and disease names from text reports presents the most formidable challenge. HealthMap draws from a continually expanding dictionary of pathogens (human, plant, and animal diseases) and geographic names (country, province, state, and city) to classify outbreak alert information. However, disease and place names are often ambiguous, colloquial, and subject to change, and may have multiple spellings (e.g., diarrhea, common in the US, and diarrhoea, common in the UK). Thus, the expansion and editing of the database requires extensive manual data entry.

Once location and disease have been identified, articles are automatically tagged according to their relevance. Specifically, we identify whether a given report refers to a current outbreak (“breaking news”), as opposed to reporting on other infectious disease–related news, such as vaccination campaigns, scientific research, or public health policy. In this case, HealthMap makes use of a Bayesian machine learning algorithm, trained on manually characterized existing reports, to automatically tag and separate breaking news. Finally, duplicate reports are filtered, identified, and grouped based on the similarity of the article's headline, body text, and disease and location categories. Using a similarity score threshold, the system groups related articles into clusters that provide the collective information on a given outbreak.

Knowledge integration and dissemination.

HealthMap is particularly focused on providing users with news of immediate interest and reducing information overload. Overwhelming public health officials with information on outbreaks of low public health impact may distract them from investigating outbreaks of greater priority that might receive reduced media attention. Thus, only articles classified as breaking news are posted to the site. Although they are filtered from the initial display, other article types and duplicate articles are shown in a related information window, providing a situational report on an ongoing outbreak as well as recent reports concerning either the same disease or location, and links for further research...

HealthMap also addresses the computational challenges of integrating multiple sources of unstructured information by generating meta-alerts of disease outbreaks. As false alarms can often be reduced by thorough aggregation and cross-validation of reported information, a composite activity score (or heat index) is calculated based on (a) the reliability of the data source (for instance, increased weight is given to WHO reports and reduced weight to local media reports); and (b) the number of unique data sources, with increased weight to multiple types of information (e.g., discussion sites and media reports on the same outbreak). This meta-alert derivation is based on the idea that multiple sources of information about an incident provide greater confidence in the reliability of the report than any one source alone.

Full article at PLoS Medicine: Surveillance Sans Frontières: Internet-Based Emerging Infectious Disease Intelligence and the HealthMap Project PLoS Medicine Vol. 5, No. 7, e151 doi:10.1371/journal.pmed.0050151

Children's Hospital Boston: Internet crawling: a new tool for tracking infectious disease...

HealthMap | Global disease alert map...

Flashbacks: HEALTHmap Global Disease Tracker ; WhoIsSick.org: Hypochondriacs Welcome!

The packaged rooftop air conditioner unit equipped with an air purification system featuring ‘virus washer’ technology has already been installed in 5 screens at 4 Warner Mycal Cinemas theaters thus far. The ‘virus washer’ function effectively suppresses airborne bacteria, viruses, pollen and odors using electrolyzed water produced by decomposing tap water with an electric current. The effectivness of electrolyzed water in this capacity has been proven by testing laboratories in various locations throughout the world (please see reference material 1). This technology is also installed in SANYO’s home air purification systems and humidifiers, portable air purifiers as well as commercial-grade air purification systems. With a broad product lineup and range, SANYO provides a clean air environmental solution for a variety of scenes ranging from the bedside of sleeping babies to spacious rooms where the public often frequent.

An experiment demonstrating the effect of the packaged rooftop air conditioner unit equipped with the air purification system already installed in 5 screens of the Warner Mycal Cinemas confirms that airborne bacteria was decreased in all screen areas, with purification levels equivalent to a bioclean room (please see reference material 2). The test installment has been received favorably by theater patrons, who have made comments on the difference in the quality of air (please see reference material 3). The additional installment concluding the exclusive agreement would allow the cinemas to welcome more guests for a safe and comfortable movie experience.

Press release: SANYO to install Air Purification Systems equipped with virus washer' technology in Warner Mycal Cinemas

SANYO Virus Washer technology page...

(hat tip: CrunchGear)

In their study, the NIST team investigated the dietary accumulation, elimination and toxicity of two types of fluorescent quantum dots using a simple, laboratory-based food chain with two microscopic aquatic organisms—Tetrahymena pyriformis, a single-celled ciliate protozoan, and the rotifer Brachionus calyciflorus that preys on it. The process of a material crossing different levels of a food chain from prey to predator is called “trophic transfer.”

Quantum dots are nanoparticles engineered to fluoresce strongly at specific wavelengths. They are being studied for a variety of uses including easily detectable tags for medical diagnostics and therapies. Their fluorescence was used to detect the presence of quantum dots in the two microorganisms.

The researchers found that both types of quantum dots were taken in readily by T. pyriformis and that they maintained their fluorescence even after the quantum dot-containing ciliates were ingested by the higher trophic level rotifers. This observation helped establish that the quantum dots were transferred across the food chain as intact nanoparticles and that dietary intake is one way that transfer can occur. The researchers noted that, “Some care should be taken, however, when extrapolating our laboratory-derived results to the natural environment.”

“Our findings showed that although trophic transfer of quantum dots did take place in this simple food chain, they did not accumulate in the higher of the two organisms,” says lead author David Holbrook. “While this suggests that quantum dots may not pose a significant risk of accumulating in aquatic invertebrate food chains in nature, additional research beyond simple laboratory experiments and a more exact means of quantifying transferred nanoparticles in environmental systems are needed to be certain.”

Abstract: Trophic transfer of nanoparticles in a simplified invertebrate food web Nature Nanotechnology doi:10.1038/nnano.2008.110

Full story: Research Measures Movement of Nanomaterials in Simple Model Food Chain...

From a NASA statement:

This biosensor will be used to help prevent the spread of potentially deadly biohazards in water, food and other contaminated sources.

NASA's Ames Research Center at Moffett Field in California licensed the biosensor technology to Early Warning Inc., Troy, N.Y. Under a Reimbursable Space Act Agreement, NASA and Early Warning jointly will develop biosensor enhancements. Initially, the biosensor will be configured to detect the presence of common and rare strains of microorganisms associated with water-borne illnesses and fatalities.

"The biosensor makes use of ultra-sensitive carbon nanotubes which can detect biohazards at very low levels," explained Meyya Meyyappan, chief scientist for exploration technology and former director of the Center for Nanotechnology at Ames. "When biohazards are present, the biosensor generates an electrical signal, which is used to determine the presence and concentration levels of specific micro-organisms in the sample. Because of their tiny size, millions of nanotubes can fit on a single biosensor chip."

Early Warning company officials say food and beverage companies, water agencies, industrial plants, hospitals and airlines could use the biosensor to prevent outbreaks of illnesses caused by pathogens - without needing a laboratory or technicians.

"Biohazard outbreaks from pathogens and infectious diseases occur every day in the U.S. and throughout the world," said Neil Gordon, president of Early Warning. "The key to preventing major outbreaks is frequent and comprehensive testing for each suspected pathogen, as most occurrences of pathogens are not detected until after people get sick or die. Biohazards can enter the water supply and food chain from a number of sources which are very difficult to uncover."

Early Warning expects to launch its water-testing products in late 2008.

NASA press release: NASA Nanotechnology-Based Biosensor Helps Detect Biohazards...

The researchers, led by Argonne senior biophysicist Marianne Schiffer, characterized the structure of one of the principal domains in a protein responsible for certain types of movement exhibited by the bacterium Geobacter sulfurreducens.

Geobacter lives in predominantly low oxygen environments and generates energy by transferring electrons to various metallic electron-accepting atoms such as iron or uranium. This ability suggests that Geobacter might be used for remediation of certain types of hazardous waste. For example, when uranium is reduced by this process to its insoluble form, it no longer leaks into groundwater and engineers can inexpensively remove the precipitated uranium.

To get to regions of high nutrient concentration (or to escape from harmful substances), certain types of bacteria use a mechanism called chemotaxis. For chemotaxis to work reliably, the cell must be able to convert external chemical information into internal chemical processes - this process is known as signal transduction. "One of the big questions in biology is how signals get from outside the cell to inside the cell," Schiffer said.

The researchers determined the three-dimensional structure of a sensory domain of a membrane-spanning protein which they believe is involved in signal transduction. Schiffer and her colleagues were particularly interested in this domain because it contains heme, a molecular component that is common in oxygen transport proteins, such as hemoglobin, or in other proteins involved in respiration or photosynthesis. While other sensor proteins that contain heme have also been described, this is the first example of a sensor protein that contains a heme covalently bound to the protein, Schiffer said.

Press release: Scientists characterize protein structure of environmentally friendly bacteria ...

Image caption: Three dimensional structure of the sensory domain of the bacterium Geobacter sulfurreducens showing two identical protein domains interacting with each other as observed in the crystal structure. The two protein domains are represented as ribbons (light blue and purple) and the heme in each protein domain is shown as "stick" model (green and gray).

The image is taken from a page at Rubbermaid: Rubbermaid food storage & beverage products that contain BPA