Coupled within-host and between-host dynamics and evolution of virulence
Zhilan Feng1, Xiuli Cen2, Yulin Zhao2
1Department of Mathematics, Purdue University, West Lafayette, IN 47907, USA.
Mathematical Biosciences
|March 10, 2015
Summary
This study introduces a new mathematical model for environmentally-driven diseases, revealing potential conflicts in parasite evolution between individual and population levels. The model highlights how within- and between-host dynamics influence disease persistence and control strategies.
Area of Science:
- Mathematical epidemiology
- Evolutionary biology
- Disease ecology
Background:
- Mathematical models coupling within- and between-host dynamics are crucial for understanding disease evolution and virulence trade-offs.
- Previous models have explored these dynamics for directly transmitted diseases, but not extensively for environmentally-driven ones.
Purpose of the Study:
- To analyze a new coupled mathematical model for environmentally-driven diseases, incorporating disease-induced host mortality.
- To investigate the evolution of virulence and potential conflicts between natural selection at individual and population levels.
Main Methods:
- Development of a novel mathematical model extending previous work by including disease-induced host mortality.
- Analysis of the model's dynamical behaviors, including backward bifurcation.
- Investigation of the relationship between within-host pathogen load, disease prevalence, and reproduction numbers (Rw0 and Rb0).
Main Results:
- The extended model exhibits similar dynamical behaviors to previous models, including the potential for backward bifurcation.
- Within-host pathogen load and disease prevalence increase with both within-host (Rw0) and between-host (Rb0) reproduction numbers.
- A conflict between optimal parasite strategies at individual and population levels may exist.
Conclusions:
- The interdependence of variables and parameters in fast and slow systems is critical for understanding disease persistence and pathogen evolution in environmentally-driven diseases.
- Explicitly linking within- and between-host dynamics is essential for accurate computation of disease control threshold conditions.
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