The statistics of epidemic transitions.
PLoS Comput Biol
; 15(5): e1006917, 2019 05.
Article
in En
| MEDLINE
| ID: mdl-31067217
ABSTRACT
Emerging and re-emerging pathogens exhibit very complex dynamics, are hard to model and difficult to predict. Their dynamics might appear intractable. However, new statistical approaches-rooted in dynamical systems and the theory of stochastic processes-have yielded insight into the dynamics of emerging and re-emerging pathogens. We argue that these approaches may lead to new methods for predicting epidemics. This perspective views pathogen emergence and re-emergence as a "critical transition," and uses the concept of noisy dynamic bifurcation to understand the relationship between the system observables and the distance to this transition. Because the system dynamics exhibit characteristic fluctuations in response to perturbations for a system in the vicinity of a critical point, we propose this information may be harnessed to develop early warning signals. Specifically, the motion of perturbations slows as the system approaches the transition.
Full text:
1
Database:
MEDLINE
Main subject:
Epidemics
Type of study:
Prognostic_studies
/
Risk_factors_studies
Limits:
Humans
Language:
En
Journal:
PLoS Comput Biol
Journal subject:
BIOLOGIA
/
INFORMATICA MEDICA
Year:
2019
Type:
Article
Affiliation country:
United States