A spatially heterogeneous network-based metapopulation software model applied to the simulation of a pulmonary tuberculosis infection.

ABSTRACT: Tuberculosis (TB) is an ancient disease that, although curable, still accounts for over 1 million deaths worldwide. Shortening treatment time is an important area of research but is hampered by the lack of models that mimic the full range of human pathology. TB shows distinct localisations during different stages of infection, the reasons for which are poorly understood. Greater understanding of how heterogeneity within the human lung influences disease progression may hold the key to improving treatment efficiency and reducing treatment times. In this work, we present a novel in silico software model which uses a networked metapopulation incorporating both spatial heterogeneity and dissemination possibilities to simulate a TB infection over the whole lung and associated lymphatics.

SUBMITTER: Pitcher MJ 

PROVIDER: S-EPMC6214320 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature