A dose response model for quantifying the infection risk of antibiotic-resistant bacteria.

ABSTRACT: Quantifying the human health risk of microbial infection helps inform regulatory policies concerning pathogens, and the associated public health measures. Estimating the infection risk requires knowledge of the probability of a person being infected by a given quantity of pathogens, and this relationship is modeled using pathogen specific dose response models (DRMs). However, risk quantification for antibiotic-resistant bacteria (ARB) has been hindered by the absence of suitable DRMs for ARB. A new approach to DRMs is introduced to capture ARB and antibiotic-susceptible bacteria (ASB) dynamics as a stochastic simple death (SD) process. By bridging SD with data from bench experiments, we demonstrate methods to (1) account for the effect of antibiotic concentrations and horizontal gene trans

SUBMITTER: Chandrasekaran S 

PROVIDER: S-EPMC6863845 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature