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Quantitative models of the dose-response and time course of inhalational anthrax in humans.

Publication ,  Journal Article
Toth, DJA; Gundlapalli, AV; Schell, WA; Bulmahn, K; Walton, TE; Woods, CW; Coghill, C; Gallegos, F; Samore, MH; Adler, FR
Published in: PLoS Pathog
August 2013

Anthrax poses a community health risk due to accidental or intentional aerosol release. Reliable quantitative dose-response analyses are required to estimate the magnitude and timeline of potential consequences and the effect of public health intervention strategies under specific scenarios. Analyses of available data from exposures and infections of humans and non-human primates are often contradictory. We review existing quantitative inhalational anthrax dose-response models in light of criteria we propose for a model to be useful and defensible. To satisfy these criteria, we extend an existing mechanistic competing-risks model to create a novel Exposure-Infection-Symptomatic illness-Death (EISD) model and use experimental non-human primate data and human epidemiological data to optimize parameter values. The best fit to these data leads to estimates of a dose leading to infection in 50% of susceptible humans (ID50) of 11,000 spores (95% confidence interval 7,200-17,000), ID10 of 1,700 (1,100-2,600), and ID1 of 160 (100-250). These estimates suggest that use of a threshold to human infection of 600 spores (as suggested in the literature) underestimates the infectivity of low doses, while an existing estimate of a 1% infection rate for a single spore overestimates low dose infectivity. We estimate the median time from exposure to onset of symptoms (incubation period) among untreated cases to be 9.9 days (7.7-13.1) for exposure to ID50, 11.8 days (9.5-15.0) for ID10, and 12.1 days (9.9-15.3) for ID1. Our model is the first to provide incubation period estimates that are independently consistent with data from the largest known human outbreak. This model refines previous estimates of the distribution of early onset cases after a release and provides support for the recommended 60-day course of prophylactic antibiotic treatment for individuals exposed to low doses.

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Published In

PLoS Pathog

DOI

EISSN

1553-7374

Publication Date

August 2013

Volume

9

Issue

8

Start / End Page

e1003555

Location

United States

Related Subject Headings

  • Virology
  • United States
  • Time Factors
  • Models, Statistical
  • Models, Biological
  • Humans
  • Bacillus anthracis
  • Anti-Bacterial Agents
  • Anthrax
  • Administration, Inhalation
 

Citation

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Toth, D. J. A., Gundlapalli, A. V., Schell, W. A., Bulmahn, K., Walton, T. E., Woods, C. W., … Adler, F. R. (2013). Quantitative models of the dose-response and time course of inhalational anthrax in humans. PLoS Pathog, 9(8), e1003555. https://doi.org/10.1371/journal.ppat.1003555
Toth, Damon J. A., Adi V. Gundlapalli, Wiley A. Schell, Kenneth Bulmahn, Thomas E. Walton, Christopher W. Woods, Catherine Coghill, Frank Gallegos, Matthew H. Samore, and Frederick R. Adler. “Quantitative models of the dose-response and time course of inhalational anthrax in humans.PLoS Pathog 9, no. 8 (August 2013): e1003555. https://doi.org/10.1371/journal.ppat.1003555.
Toth DJA, Gundlapalli AV, Schell WA, Bulmahn K, Walton TE, Woods CW, et al. Quantitative models of the dose-response and time course of inhalational anthrax in humans. PLoS Pathog. 2013 Aug;9(8):e1003555.
Toth, Damon J. A., et al. “Quantitative models of the dose-response and time course of inhalational anthrax in humans.PLoS Pathog, vol. 9, no. 8, Aug. 2013, p. e1003555. Pubmed, doi:10.1371/journal.ppat.1003555.
Toth DJA, Gundlapalli AV, Schell WA, Bulmahn K, Walton TE, Woods CW, Coghill C, Gallegos F, Samore MH, Adler FR. Quantitative models of the dose-response and time course of inhalational anthrax in humans. PLoS Pathog. 2013 Aug;9(8):e1003555.

Published In

PLoS Pathog

DOI

EISSN

1553-7374

Publication Date

August 2013

Volume

9

Issue

8

Start / End Page

e1003555

Location

United States

Related Subject Headings

  • Virology
  • United States
  • Time Factors
  • Models, Statistical
  • Models, Biological
  • Humans
  • Bacillus anthracis
  • Anti-Bacterial Agents
  • Anthrax
  • Administration, Inhalation