Modeling antibiotic resistance in hospitals: the impact of minimizing treatment duration.
Infections caused by antibiotic-resistant pathogens are a global public health problem. Numerous individual- and population-level factors contribute to the emergence and spread of these pathogens. An individual-based model (IBM), formulated as a system of stochastically determined events, was developed to describe the complexities of the transmission dynamics of antibiotic-resistant bacteria. To simplify the interpretation and application of the model's conclusions, a corresponding deterministic model was created, which describes the average behavior of the IBM over a large number of simulations. The integration of these two model systems provides a quantitative analysis of the emergence and spread of antibiotic-resistant bacteria, and demonstrates that early initiation of treatment and minimization of its duration mitigates antibiotic resistance epidemics in hospitals.
D'Agata
Erika M C
EM
Beth Israel Deaconess Medical Center, Harvard University, Boston, MA 02215, USA. edagata@bidmc.harvard.edu
Magal
Pierre
P
Olivier
Damien
D
Ruan
Shigui
S
Webb
Glenn F
GF
D000900:Anti-Bacterial Agents / Q000008:administration & dosage*; D001424:Bacterial Infections / Q000188:drug therapy / Q000382:microbiology / Q000635:transmission; D003428:Cross Infection / Q000188:drug therapy* / Q000382:microbiology / Q000635:transmission; D004334:Drug Administration Schedule; D024881:Drug Resistance, Bacterial; D006761:Hospitals; D006801:Humans; D007902:Length of Stay; D008954:Models, Biological
D000900:Anti-Bacterial Agents