RT Journal Article
SR Electronic
T1 Pathogen Population Structure Can Explain Hospital Outbreaks
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 210534
DO 10.1101/210534
A1 Fabrizio Spagnolo
A1 Pierre Cristofari
A1 Nicholas P. Tatonetti
A1 Lev R. Ginzburg
A1 Daniel E. Dykhuizen
YR 2017
UL http://biorxiv.org/content/early/2017/10/31/210534.abstract
AB Objective To analyze Hospital Acquired Infection (HAI) outbreaks using microbial population biology dynamics in order to understand outbreaks as a biological system.Design Computational modeling study.Methods The majority of HAI transmission models describe dynamics on the level of the host rather than on the level of the pathogens themselves. Accordingly, epidemiologists often cannot complete transmission chains without direct evidence of either host-host contact or large reservoir populations. Here, we propose an ecology-based model to explain the transmission of pathogens in hospitals. The model is based upon metapopulation biology, which describes a group of interacting localized populations and island biogeography, which provides a basis for how pathogens may be moving between locales. Computational simulation trials are used to assess the applicability of the model.Results Results indicate that pathogens survive for extended periods without the need for large reservoirs by living in localized ephemeral populations while continuously transmitting pathogens to new seed populations. Computational simulations show small populations spending significant portions of time at sizes too small to be detected by most surveillance protocols. The number and type of these ephemeral populations enable the overall pathogen population to be sustained.Conclusions By modeling hospital pathogens as a metapopulation, observations characteristic of hospital acquired infection outbreaks for which there has previously been no sufficient biological explanation, including how and why empirically successful interventions work, can now be accounted for using population dynamic hypotheses. Epidemiological links between temporally isolated outbreaks are explained via pathogen population dynamics and potential outbreak intervention targets are identified.