Epidemiology of Infectious Diseases: Time-Series Analysis and Nonlinear Dynamics

Dear Colleagues,

This Special Issue of Reports is dedicated to advancing our understanding of infectious diseases, including COVID-19, through time-series analysis and nonlinear dynamics. Recent epidemics have generated valuable datasets, allowing researchers to examine the various temporal structures and nonlinear properties of epidemic processes. By focusing on clinically relevant and data-driven analytical approaches, this issue aims to highlight new insights into the predictability, complexity, and mechanisms of epidemic waves that are meaningful for public health and clinical practice.

We welcome submissions in (but not limited to) the following areas:

Time-Series Analyses
- Maximum Entropy Method (MEM), Fast Fourier Transform (FFT), wavelet analysis, and related approaches;
- Identification of dominant cycles, seasonality, and temporal structures in infectious disease data;
- Comparative short-term versus long-term predictability of epidemic waves.

Nonlinear Dynamics of Epidemics
- Evidence of chaos, bifurcations, and period-doubling in epidemic time series;
- Cross-regional and cross-population analyses of epidemic dynamics;
- Population size, vaccination coverage, and their effects on temporal patterns.

Integration with Environmental and Social Drivers
- Climate change and global warming as modulators of epidemic dynamics;
- Temperature, humidity, and seasonal cycles in shaping epidemic waves;
- Impacts of mobility, public health interventions, and behavioral changes on temporal variation;
- Application of time-series and nonlinear analyses to public health policy and medical resource management.

Methodological and Interdisciplinary Perspectives
- Novel mathematical and physical methods for epidemic time series;
- Case studies linking clinical or epidemiological data with nonlinear modeling;
- Critical evaluations of forecasting approaches and their limitations.

We particularly encourage submissions that connect theory and practice—bridging mathematical modeling, epidemiological surveillance, and healthcare implementation. Case reports and regional studies demonstrate the power of time-series and nonlinear approaches to uncover hidden structures in infectious disease dynamics are also highly valued.

Prof. Dr. Ayako Sumi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Reports is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• epidemiology
• time-series
• nonlinearity
• dynamics
• predictability