Detecting Bioterror Attacks by Screening Blood Donors: A Best-Case Analysis

To assess whether screening blood donors could provide early warning of a bioterror attack, we combined stochastic models of blood donation and the workings of blood tests with an epidemic model to derive the probability distribution of the time to detect an attack under assumptions favorable to blood donor screening. Comparing the attack detection delay to the incubation times of the most feared bioterror agents shows that even under such optimistic conditions, victims of a bioterror attack would likely exhibit symptoms before the attack was detected through blood donor screening. For example, an attack infecting 100 persons with a noncontagious agent such as Bacillus anthracis would only have a 26% chance of being detected within 25 days; yet, at an assumed additional charge of $10 per test, donor screening would cost$139 million per year. Furthermore, even if screening tests were 99.99% specific, 1,390 false-positive results would occur each year. Therefore, screening blood donors for bioterror agents should not be used to detect a bioterror attack

Detecting Bioterror Attacks by Screening Blood Donors: A Best-Case Analysis

To assess whether screening blood donors could provide early warning of a bioterror attack, we combined stochastic models of blood donation and the workings of blood tests with an epidemic model to derive the probability distribution of the time to detect an attack under assumptions favorable to blood donor screening. Comparing the attack detection delay to the incubation times of the most feared bioterror agents shows that even under such optimistic conditions, victims of a bioterror attack would likely exhibit symptoms before the attack was detected through blood donor screening. For example, an attack infecting 100 persons with a noncontagious agent such as Bacillus anthracis would only have a 26% chance of being detected within 25 days; yet, at an assumed additional charge of $10 per test, donor screening would cost$139 million per year. Furthermore, even if screening tests were 99.99% specific, 1,390 false-positive results would occur each year. Therefore, screening blood donors for bioterror agents should not be used to detect a bioterror attack

Burn severity influences postfire CO2 exchange in Arctic tundra

Author Posting. © Ecological Society of America, 2011. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Ecological Applications 21 (2011): 477–489, doi:10.1890/10-0255.1.Burned landscapes present several challenges to quantifying landscape carbon balance. Fire scars are composed of a mosaic of patches that differ in burn severity, which may influence postfire carbon budgets through damage to vegetation and carbon stocks. We deployed three eddy covariance towers along a burn severity gradient (i.e., severely burned, moderately burned, and unburned tundra) to monitor postfire net ecosystem exchange of CO2 (NEE) within the large 2007 Anaktuvuk River fire scar in Alaska, USA, during the summer of 2008. Remote sensing data from the MODerate resolution Imaging Spectroradiometer (MODIS) was used to assess the spatial representativeness of the tower sites and parameterize a NEE model that was used to scale tower measurements to the landscape. The tower sites had similar vegetation and reflectance properties prior to the Anaktuvuk River fire and represented the range of surface conditions observed within the fire scar during the 2008 summer. Burn severity influenced a variety of surface properties, including residual organic matter, plant mortality, and vegetation recovery, which in turn determined postfire NEE. Carbon sequestration decreased with increased burn severity and was largely controlled by decreases in canopy photosynthesis. The MODIS two-band enhanced vegetation index (EVI2) monitored the seasonal course of surface greenness and explained 86% of the variability in NEE across the burn severity gradient. We demonstrate that understanding the relationship between burn severity, surface reflectance, and NEE is critical for estimating the overall postfire carbon balance of the Anaktuvuk River fire scar.This work was supported by NSF grants #0632139 (OPP-AON), #0808789 (OPP-ARCSS SGER), #0829285 (DEB-NEON SGER), and #0423385 (DEBLTER) to the Marine Biological Laboratory