Special Issue "Analysis of Modeling and Statistics for COVID-19"

A special issue of COVID (ISSN 2673-8112).

Deadline for manuscript submissions: 31 October 2023 | Viewed by 1820

Special Issue Editors

Prof. Dr. Martin Kröger
E-Mail Website1 Website2
Guest Editor
Polymer Physics, Department of Materials, ETH Zurich, Leopold-Ruzicka-Weg 4, CH-8093 Zurich, Switzerland
Interests: polymer physics; computational physics; applied mathematics; stochastic differential equations; coarse-graining; biophysics
Special Issues, Collections and Topics in MDPI journals
Theoretical Physics Institute, Ruhr University Bochum, 44780 Bochum, Germany
Interests: astrophysics; space physics; cosmic rays; plasma physics; astroparticle physics
Special Issues, Collections and Topics in MDPI journals
Institut de Mathématiques de Bordeaux, Université de Bordeaux, 351 cours de la libération, 33400 Talence, France
Interests: disease mathematical modeling; computational epidemiology; data-based epidemiological modeling; population dynamics; differential equations; dynamical systems
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 world level concerning the reported number of new cases, deaths, and people vaccinated, by region and by age group or other groups. 

These data must first be analyzed with statistical methods (time series analysis, principal component analysis, technical classification, etc.), then be used to build refutable models of different types, deterministic (differentiable or discrete) or stochastic. 

The consideration of the spatial dimension can lead to diffusion models, that of the age of the patients to population dynamics models and that of the advance in the dynamics of the infection to variable reproduction number models (due to characteristics of contagiousness, virulence, and susceptibility in the host and the virus changing over time caused by 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 stochastic variability on the observed data and the parameters introduced into the models. All articles dealing with statistical and dynamic aspects of COVID-19 disease, allowing its statistical description, the study of its mechanisms, and the forecasting of its evolution will be considered in the Special Issue “Analysis of Modeling and Statistics for COVID-19”.

Prof. Dr. Martin Kröger
Prof. Dr. Reinhard Schlickeiser
Prof. Dr. Pierre Magal
Prof. Dr. Jacques Demongeot
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 1000 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

Published Papers (2 papers)

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Research

Article
Assessing COVID-19 Effects on Inflation, Unemployment, and GDP in Africa: What Do the Data Show via GIS and Spatial Statistics?
COVID 2023, 3(7), 956-974; https://doi.org/10.3390/covid3070069 - 28 Jun 2023
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Abstract
What are the effects of Corona Virus Disease 19 (COVID-19) on inflation, unemployment, and GDP in Africa? Using geo-coded cross-sectional data taken from the World Health Organization and International Monetary Fund, we investigate the spatial distribution of COVID-19 and its effects on inflation, [...] Read more.
What are the effects of Corona Virus Disease 19 (COVID-19) on inflation, unemployment, and GDP in Africa? Using geo-coded cross-sectional data taken from the World Health Organization and International Monetary Fund, we investigate the spatial distribution of COVID-19 and its effects on inflation, unemployment, and Gross Domestic Product (GDP) in Africa by employing the Geographic Information System (GIS), multivariate analysis of covariance (MANCOVA), and spatial statistics. The entire dataset was analyzed using Stata, ArcGIS, and R software. The result shows (1) that there is evidence of a spatial pattern of COVID-19 cases and death rate clustering behavior in Africa, verifying the existence of spatial autocorrelation. The result also reveals (2) that COVID-19 has a negative effect on unemployment, inflation, and GDP in Africa. We confirmed that (3) temperature, rainfall, and humidity were statistically significantly associated with the spread of the COVID-19 pandemic in Africa. The comparison of the GDP of African countries before and after the pandemic shows (4) a large decrease in GDP, the highest in Seychelles (23 percent). The result of the study shows (5) that there has been a significant increase in inflation and unemployment rates in all countries since the outbreak of the pandemic as compared to the time before the outbreak. There is also evidence that (6) there is a significant relationship between death rate due to COVID-19 and population density; temperature with COVID-19 cases and death rate; and precipitation with death rate due to COVID-19. Therefore, respective governments and the international community need to pay attention to controlling/reducing the impact of COVID-19 on inflation, unemployment, and GDP, focusing on the indicated demographic and environmental variables. Full article
(This article belongs to the Special Issue Analysis of Modeling and Statistics for COVID-19)
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Communication
Key Epidemic Parameters of the SIRV Model Determined from Past COVID-19 Mutant Waves
COVID 2023, 3(4), 592-600; https://doi.org/10.3390/covid3040042 - 13 Apr 2023
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Abstract
Monitored infection and vaccination rates during past past waves of the coronavirus are used to infer a posteriori two-key parameter of the SIRV epidemic model, namely, the real-time variation in (i) the ratio of recovery to infection rate and (ii) the ratio of [...] Read more.
Monitored infection and vaccination rates during past past waves of the coronavirus are used to infer a posteriori two-key parameter of the SIRV epidemic model, namely, the real-time variation in (i) the ratio of recovery to infection rate and (ii) the ratio of vaccination to infection rate. We demonstrate that using the classical SIR model, the ratio between recovery and infection rates tends to overestimate the true ratio, which is of relevance in predicting the dynamics of an epidemic in the presence of vaccinations. Full article
(This article belongs to the Special Issue Analysis of Modeling and Statistics for COVID-19)
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