Wang L, Zhang K, Xu L, Wang J. Understanding underlying physical mechanism reveals early warning indicators and key elements for adaptive infections disease networks.
PNAS NEXUS 2024;
3:pgae237. [PMID:
39035039 PMCID:
PMC11259140 DOI:
10.1093/pnasnexus/pgae237]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 06/03/2024] [Indexed: 07/23/2024]
Abstract
The study of infectious diseases holds significant scientific and societal importance, yet current research on the mechanisms of disease emergence and prediction methods still face challenging issues. This research uses the landscape and flux theoretical framework to reveal the non-equilibrium dynamics of adaptive infectious diseases and uncover its underlying physical mechanism. This allows the quantification of dynamics, characterizing the system with two basins of attraction determined by gradient and rotational flux forces. Quantification of entropy production rates provides insights into the system deviating from equilibrium and associated dissipative costs. The study identifies early warning indicators for the critical transition, emphasizing the advantage of observing time irreversibility from time series over theoretical entropy production and flux. The presence of rotational flux leads to an irreversible pathway between disease states. Through global sensitivity analysis, we identified the key factors influencing infectious diseases. In summary, this research offers valuable insights into infectious disease dynamics and presents a practical approach for predicting the onset of critical transition, addressing existing research gaps.
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