Peer Review of “Chaotic and Stochastic Components in an Influenza Surveillance Series: Nonlinear Dynamics and Predictive Modeling Study”
Abstract
for "Chaotic and Stochastic Components in an Influenza Surveillance Series: Nonlinear Dynamics and Predictive Modeling Study." Round 1 Review General CommentsThis paper [1] presents an interesting application of chaos theory, nonlinear time series analysis, and topological machine learning to influenza epidemiological data.The methodology is strong and promising.However, the manuscript requires substantial improvements to enhance clarity and accessibility.
Fields of Study & Subjects
COVID-19 epidemiological studies
Influenza Virus Research Studies
Heart Rate Variability and Autonomic Control
Publication details
- Journal / source
- JMIRx Med
- Volume
- 7
- Pages
- e101473–e101473
- Publication date
- 5 June 2026
- Language
- EN