Analysis of Modeling and Statistics for COVID-19, 2nd edition
A special issue of COVID (ISSN 2673-8112).
Deadline for manuscript submissions: 31 January 2026 | Viewed by 888
Special Issue Editors
Interests: polymer physics; computational physics; applied mathematics; stochastic differential equations; coarse-graining; biophysics
Special Issues, Collections and Topics in MDPI journals
Interests: astrophysics; plasma physics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Modeling the COVID-19 outbreak requires considering a large amount of data, at the global level, related to the reported number of new cases, deaths, and people vaccinated, segmented by region, age group, and other groups.
These data must first be analyzed via statistical methods (time series analysis, principal component analysis, technical classification, etc.), before being used to build refutable models of different types, such as deterministic (differentiable or discrete) or stochastic models.
Considering the spatial dimension can lead to diffusion models, which can consider the ages of the patients for population dynamics models and advances in the dynamics of the infection for variable reproduction number models (due to the contagiousness, virulence, and susceptibility in the host and the virus changing over time due to viral mutations, environmental changes, host immunity, public health policy, etc.).
A combination of these three types of models is also possible, with the additional consideration of the stochastic variability on the observed data and the parameters introduced into the models. All articles dealing with the statistical and dynamic aspects of COVID-19, which allow for its statistical description, the study of its mechanisms, and the forecasting of its evolution, will be considered in this Special Issue, titled “Analysis of Modeling and Statistics for COVID-19, 2nd Edition”.
Prof. Dr. Martin Kröger
Prof. Dr. Reinhard Schlickeiser
Guest Editors
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 100 words) can be sent to the Editorial Office for announcement on this website.
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. COVID is an international peer-reviewed open access monthly 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 1200 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.
Keywords
- COVID-19 statistics
- epidemiological modeling
- time series analysis
- prediction techniques
- outbreak spatial diffusion
- daily reproduction number
- contagion modeling
- viral mutation modeling
- virulence mechanisms
- host immunity modeling
- mitigation measures dynamics
- vaccination policy
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