Novel method predicts impact of anthrax release

Bacillus anthracis Releasing highly pathogenic organisms into an urban population is a act of bioterrorism that could result in a large number of casualties. The first indication that a covert open-air release has occurred is quite likely to be individuals reporting for medical attention. If such an attack is suspected, then public health authorities would attempt to identify those individuals who have been infected in order to provide rapid treatment with the aim of reducing the possibility of disease and potential death. Aiming treatment at too small an area might miss individuals infected further down and/or up wind, whereas issues surrounding both treatment resources and serious side effects may rule out mass treatment campaigns of large sections of the population.

A new paper describes a statistical method that can estimate the origin and time of an aerosolized release of anthrax following detection of the first few cases. The method predicts where the most critically affected areas will be following the release of this highly pathogenic agent, which may enable preventative treatment of individuals at risk and protection from the disease. Previously published methods can estimate the date and scale of anthrax release but not the source location or geographic extent of human exposure. The new method uses information about the first people infected, including when they started to experience symptoms of infection and where they live and work, combined with recent weather information, such as wind direction. Anthrax has the potential to cause a large number of deaths in the event of a covert, open air release. If such a release were to occur, it is critical for public health decision makers to evaluate its extent and the potential impact on the population and then to identify the people most at risk of infection as soon as possible. It is critical to treat people as soon as possible after exposure to anthrax. While forecasts based on small numbers of early cases are less reliable than those obtained later in an outbreak, treating individuals based on early estimates is still likely to save lives overall.

Estimating the Location and Spatial Extent of a Covert Anthrax Release. 2009 PLoS Comput Biol 5(1): e1000356
Rapidly identifying the features of a covert release of an agent such as anthrax could help to inform the planning of public health mitigation strategies. Previous studies have sought to estimate the time and size of a bioterror attack based on the symptomatic onset dates of early cases. We extend the scope of these methods by proposing a method for characterizing the time, strength, and also the location of an aerosolized pathogen release. A back-calculation method is developed allowing the characterization of the release based on the data on the first few observed cases of the subsequent outbreak, meteorological data, population densities, and data on population travel patterns. We evaluate this method on small simulated anthrax outbreaks (about 25–35 cases) and show that it could date and localize a release after a few cases have been observed, although misspecifications of the spore dispersion model, or the within-host dynamics model, on which the method relies can bias the estimates. Our method could also provide an estimate of the outbreak’s geographical extent and, as a consequence, could help to identify populations at risk and, therefore, requiring prophylactic treatment. Our analysis demonstrates that while estimates based on the first ten or 15 observed cases were more accurate and less sensitive to model misspecifications than those based on five cases, overall mortality is minimized by targeting prophylactic treatment early on the basis of estimates made using data on the first five cases. The method we propose could provide early estimates of the time, strength, and location of an aerosolized anthrax release and the geographical extent of the subsequent outbreak. In addition, estimates of release features could be used to parameterize more detailed models allowing the simulation of control strategies and intervention logistics.

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