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Testing the Role of Multicopy Plasmids in the Evolution of Antibiotic Resistance
Published on: May 2, 2018
Epidemic spreading under mutually independent intra- and inter-host pathogen evolution
Xiyun Zhang1, Zhongyuan Ruan2, Muhua Zheng3
1Department of Physics, Jinan University, Guangzhou, Guangdong, 510632, China. xiyunzhang@jnu.edu.cn.
Abstract:
The dynamics of epidemic spreading is often reduced to the single control parameter R0 (reproduction-rate), whose value, above or below unity, determines the state of the contagion. If, however, the pathogen evolves as it spreads, R0 may change over time, potentially leading to a mutation-driven spread, in which an initially sub-pandemic pathogen undergoes a breakthrough mutation. To predict the boundaries of this pandemic phase, we introduce here a modeling framework to couple the inter-host network spreading patterns with the intra-host evolutionary dynamics. We find that even in the extreme case when these two process are driven by mutually independent selection forces, mutations can still fundamentally alter the pandemic phase-diagram. The pandemic transitions, we show, are now shaped, not just by R0, but also by the balance between the epidemic and the evolutionary timescales. If mutations are too slow, the pathogen prevalence decays prior to the appearance of a critical mutation. On the other hand, if mutations are too rapid, the pathogen evolution becomes volatile and, once again, it fails to spread. Between these two extremes, however, we identify a broad range of conditions in which an initially sub-pandemic pathogen can breakthrough to gain widespread prevalence.
Insights
Pathogen evolution can drive epidemics. This study introduces a model showing that mutations, not just reproduction rate (R0), shape pandemic transitions. A balance between mutation and spread timescales is key for initial sub-pandemic pathogens to become widespread.
Area of Science:
- Epidemiology
- Evolutionary Biology
- Mathematical Modeling
Background:
- Epidemic dynamics are often simplified using the basic reproduction number (R0).
- Pathogen evolution during spread can alter R0, potentially causing mutation-driven pandemics.
- Predicting pandemic emergence requires understanding coupled spread and evolution.
Purpose of the Study:
- To develop a modeling framework integrating inter-host spreading and intra-host evolution.
- To investigate how pathogen mutation dynamics influence pandemic phase transitions.
- To identify conditions enabling initially non-pandemic pathogens to spread widely.
Main Methods:
- Coupling network-based epidemic spreading models with evolutionary dynamics.
- Analyzing the impact of mutation rates and selection forces on pandemic potential.
- Defining a phase diagram influenced by both epidemic and evolutionary timescales.
Main Results:
- Mutations can fundamentally alter pandemic phase diagrams, even with independent selection.
- Pandemic transitions depend on R0 and the balance between epidemic and evolutionary timescales.
- A critical window exists where initially sub-pandemic pathogens can achieve widespread prevalence through mutation.
Conclusions:
- The interplay between pathogen evolution and epidemic spread is crucial for predicting pandemic emergence.
- Mutation speed critically influences whether a pathogen can achieve widespread prevalence.
- Understanding these coupled dynamics can inform public health strategies against evolving pathogens.
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