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Pathogen diversity in meta-population networks
Yanyi Nie1,2, Xiaoni Zhong1, Tao Lin2
1School of Public Health, Chongqing Medical University, Chongqing, 400016, China.
Abstract:
The pathogen diversity means that multiple strains coexist, and widely exist in the biology systems. The new mutation of SARS-CoV-2 leading to worldwide pathogen diversity is a typical example. What are the main factors of inducing the pathogen diversity? Previous studies indicated the pathogen mutation is the most important reason for inducing the pathogen diversity. The traffic network and gene network are crucial in shaping the dynamics of pathogen contagion, while their roles for the pathogen diversity still lacking a theoretical study. To this end, we propose a reaction-diffusion process of pathogens with mutations on meta-population networks, which includes population movement and strain mutation. We extend the Microscopic Markov Chain Approach (MMCA) to describe the model. Traffic networks make pathogen diversity more likely to occur in cities with lower infection densities. The likelihood of pathogen diversity is low in cities with short effective distances in the traffic network. Star-type gene network is more likely to lead to pathogen diversity than lattice-type and chain-type gene networks. When pathogen localization is present, infection is localized to strains that are at the endpoints of the gene network. Both the increased probability of movement and mutation promote pathogen diversity. The results also show that the population tends to move to cities with short effective distances, resulting in the infection density is high.
Insights
Pathogen diversity, driven by mutation and movement, is influenced by city networks. Traffic and gene networks shape how pathogen strains spread and evolve, impacting urban infection dynamics.
Area of Science:
- Epidemiology
- Mathematical Biology
- Network Science
Background:
- Pathogen diversity, characterized by coexisting strains, is a significant biological phenomenon, exemplified by SARS-CoV-2 mutations.
- While pathogen mutation is a known driver of diversity, the roles of traffic and gene networks in shaping pathogen diversity remain theoretically underexplored.
Purpose of the Study:
- To investigate the primary factors inducing pathogen diversity.
- To theoretically study the impact of traffic and gene networks on pathogen diversity dynamics.
Main Methods:
- A reaction-diffusion model for pathogens incorporating mutation on meta-population networks was proposed.
- The Microscopic Markov Chain Approach (MMCA) was extended to analyze the model dynamics.
- The study examined the influence of population movement, mutation rates, and network structures (traffic and gene) on pathogen diversity.
Main Results:
- Traffic networks promote pathogen diversity in cities with lower initial infection densities.
- Pathogen diversity is less likely in cities with short effective distances within the traffic network.
- Star-type gene networks are more conducive to pathogen diversity than lattice or chain-type networks.
- Increased movement and mutation probabilities enhance pathogen diversity.
- Population movement towards cities with short effective distances leads to higher overall infection densities.
Conclusions:
- Traffic and gene network structures significantly influence pathogen diversity.
- Movement and mutation are key drivers that can be modulated by network properties to control pathogen diversity.
- Understanding these network dynamics is crucial for managing infectious disease spread and evolution.
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