Advances in Time Series Analysis in Health

Dear Colleagues,

As health systems generate increasingly large and heterogeneous datasets, robust mathematical frameworks for temporal analysis have become essential for improving surveillance, forecasting, and evaluating policy and intervention programs.

Classical approaches (e.g., state-space modeling, ARIMA, and their variants) have established the theoretical foundations of time series analysis. However, there is a growing body of work integrating deep learning architectures (e.g., Long Short-Term Memory (LSTM) networks and Transformer-based models), alongside multimodal frameworks that fuse diverse data streams such as genomic, clinical, and environmental data.

This Special Issue brings together contributions spanning both theoretical advances and applied methodologies across a wide range of health-related applications, including administrative electronic health records and high-frequency wearable sensor data. The tension between the interpretability required by clinical and policy audiences and the expressive power of modern machine learning makes mathematical rigor not only valuable but essential.

This issue showcases how sophisticated time series analysis is reshaping our ability to identify shifts in health dynamics and optimize intervention programs.

Dr. Joanna Dipnall
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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.