Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.3
3.8
Journals
Viruses
Special Issues
Transmission Dynamics of Coronavirus Disease
share announcement

Transmission Dynamics of Coronavirus Disease

A special issue of Viruses (ISSN 1999-4915). This special issue belongs to the section "SARS-CoV-2 and COVID-19".

Deadline for manuscript submissions: closed (1 July 2022) | Viewed by 25090

Special Issue Editors

Prof. Dr. Tomasz Lipniacki

E-Mail Website
Guest Editor
Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
Interests: mathematical modelling; systems biology; epidemiology; immunology
Dr. Marek Kochańczyk

E-Mail Website
Guest Editor
Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
Interests: nonlinear dynamics; stochastic processes; quantitative biology; innate immunity; epidemiology
Dr. Marek Bodnar

E-Mail Website
Guest Editor
Department of Mathematics, Informatics and Mechanics, University of Warsaw, Warszawa, Poland
Interests: delay differential equations; non-linear dynamical systems; Mathematical modelling; immunology; epidemiology

Special Issue Information

Dear Colleagues,

SARS-CoV-2 led to the COVID-19 pandemic with a high death toll exceeding 0.5% in some countries, and with a severe impact on national economies and social life. After nearly two years, the dynamics of the epidemic is shaped on one side by vaccinations and lockdown restrictions, and on the other by arising mutations leading to new outbreaks caused by virus variants that acquire replicative advantage. Because of mutual interactions of anti-epidemic measures, infection spread, and virus mutations, we need studies going well beyond the classical approach of SEIR-type modeling with constant coefficients.

This Special Issue seeks original papers and reviews exploring interactions between vaccinations, lockdowns, epidemic spread, and mutations. To control the pandemic (or at some point endemic) or to potentially eradicate SARS-CoV-2, we must understand immuno-compromising mutations, their interactions with vaccines, and waning immunity over time.

Special consideration will be given to papers addressing virus mutations at the molecular, host, or population level. Mathematical studies are more than welcome, providing that they are based on realistic assumptions and lead to significant conclusions in the field of SARS-CoV-2 epidemiology.

Prof. Dr. Tomasz Lipniacki
Dr. Marek Kochańczyk
Dr. Marek Bodnar
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. Viruses 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 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.

Keywords

  • SARS-CoV-2
  • COVID-19 pandemic
  • mutations
  • replicative advantage
  • variants of concern
  • vaccinations and vaccines
  • immunity waning
  • lockdown restrictions

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Other

33 pages, 6965 KiB  
Article
Genomic Analysis of SARS-CoV-2 Alpha, Beta and Delta Variants of Concern Uncovers Signatures of Neutral and Non-Neutral Evolution
by Monika Klara Kurpas, Roman Jaksik, Pawel Kuś and Marek Kimmel
Viruses 2022, 14(11), 2375; https://doi.org/10.3390/v14112375 - 27 Oct 2022
Cited by 5 | Viewed by 1902 | Correction
Abstract
Due to the emergence of new variants of the SARS-CoV-2 coronavirus, the question of how the viral genomes evolved, leading to the formation of highly infectious strains, becomes particularly important. Three major emergent strains, Alpha, Beta and Delta, characterized by a significant number [...] Read more.
Due to the emergence of new variants of the SARS-CoV-2 coronavirus, the question of how the viral genomes evolved, leading to the formation of highly infectious strains, becomes particularly important. Three major emergent strains, Alpha, Beta and Delta, characterized by a significant number of missense mutations, provide a natural test field. We accumulated and aligned 4.7 million SARS-CoV-2 genomes from the GISAID database and carried out a comprehensive set of analyses. This collection covers the period until the end of October 2021, i.e., the beginnings of the Omicron variant. First, we explored combinatorial complexity of the genomic variants emerging and their timing, indicating very strong, albeit hidden, selection forces. Our analyses show that the mutations that define variants of concern did not arise gradually but rather co-evolved rapidly, leading to the emergence of the full variant strain. To explore in more detail the evolutionary forces at work, we developed time trajectories of mutations at all 29,903 sites of the SARS-CoV-2 genome, week by week, and stratified them into trends related to (i) point substitutions, (ii) deletions and (iii) non-sequenceable regions. We focused on classifying the genetic forces active at different ranges of the mutational spectrum. We observed the agreement of the lowest-frequency mutation spectrum with the Griffiths–Tavaré theory, under the Infinite Sites Model and neutrality. If we widen the frequency range, we observe the site frequency spectra much more consistently with the Tung–Durrett model assuming clone competition and selection. The coefficients of the fitting model indicate the possibility of selection acting to promote gradual growth slowdown, as observed in the history of the variants of concern. These results add up to a model of genomic evolution, which partly fits into the classical drift barrier ideas. Certain observations, such as mutation “bands” persistent over the epidemic history, suggest contribution of genetic forces different from mutation, drift and selection, including recombination or other genome transformations. In addition, we show that a “toy” mathematical model can qualitatively reproduce how new variants (clones) stem from rare advantageous driver mutations, and then acquire neutral or disadvantageous passenger mutations which gradually reduce their fitness so they can be then outcompeted by new variants due to other driver mutations. Full article
(This article belongs to the Special Issue Transmission Dynamics of Coronavirus Disease)
►▼ Show Figures

Figure 1

13 pages, 2260 KiB  
Article
SARS-CoV-2 Genetic Diversity and Lineage Dynamics in Egypt during the First 18 Months of the Pandemic
by Wael H. Roshdy, Mohamed K. Khalifa, James Emmanuel San, Houriiyah Tegally, Eduan Wilkinson, Shymaa Showky, Darren Patrick Martin, Monika Moir, Amel Naguib, Nancy Elguindy, Mokhtar R. Gomaa, Manal Fahim, Hanaa Abu Elsood, Amira Mohsen, Ramy Galal, Mohamed Hassany, Richard J. Lessells, Ahmed A. Al-Karmalawy, Rabeh EL-Shesheny, Ahmed M. Kandeil, Mohamed A. Ali and Tulio de Oliveiraadd Show full author list remove Hide full author list
Viruses 2022, 14(9), 1878; https://doi.org/10.3390/v14091878 - 25 Aug 2022
Cited by 7 | Viewed by 2405
Abstract
COVID-19 was first diagnosed in Egypt on 14 February 2020. By the end of November 2021, over 333,840 cases and 18,832 deaths had been reported. As part of the national genomic surveillance, 1027 SARS-CoV-2 near whole-genomes were generated and published by the end [...] Read more.
COVID-19 was first diagnosed in Egypt on 14 February 2020. By the end of November 2021, over 333,840 cases and 18,832 deaths had been reported. As part of the national genomic surveillance, 1027 SARS-CoV-2 near whole-genomes were generated and published by the end of July 2021. Here we describe the genomic epidemiology of SARS-CoV-2 in Egypt over this period using a subset of 976 high-quality Egyptian genomes analyzed together with a representative set of global sequences within a phylogenetic framework. A single lineage, C.36, introduced early in the pandemic was responsible for most of the cases in Egypt. Furthermore, to remain dominant in the face of mounting immunity from previous infections and vaccinations, this lineage acquired several mutations known to confer an adaptive advantage. These results highlight the value of continuous genomic surveillance in regions where VOCs are not predominant and the need for enforcement of public health measures to prevent expansion of the existing lineages. Full article
(This article belongs to the Special Issue Transmission Dynamics of Coronavirus Disease)
►▼ Show Figures

Figure 1

24 pages, 848 KiB  
Article
COVID-19 Modeling Outcome versus Reality in Sweden
by Marcus Carlsson and Cecilia Söderberg-Nauclér
Viruses 2022, 14(8), 1840; https://doi.org/10.3390/v14081840 - 22 Aug 2022
Cited by 6 | Viewed by 2724
Abstract
It has been very difficult to predict the development of the COVID-19 pandemic based on mathematical models for the spread of infectious diseases, and due to major non-pharmacological interventions (NPIs), it is still unclear to what extent the models would have fit reality [...] Read more.
It has been very difficult to predict the development of the COVID-19 pandemic based on mathematical models for the spread of infectious diseases, and due to major non-pharmacological interventions (NPIs), it is still unclear to what extent the models would have fit reality in a “do nothing” scenario. To shed light on this question, the case of Sweden during the time frame from autumn 2020 to spring 2021 is particularly interesting, since the NPIs were relatively minor and only marginally updated. We found that state of the art models are significantly overestimating the spread, unless we assume that social interactions significantly decrease continuously throughout the time frame, in a way that does not correlate well with Google-mobility data nor updates to the NPIs or public holidays. This leads to the question of whether modern SEIR-type mathematical models are unsuitable for modeling the spread of SARS-CoV-2 in the human population, or whether some particular feature of SARS-CoV-2 dampened the spread. We show that, by assuming a certain level of pre-immunity to SARS-CoV-2, we obtain an almost perfect data-fit, and discuss what factors could cause pre-immunity in the mathematical models. In this scenario, a form of herd-immunity under the given restrictions was reached twice (first against the Wuhan-strain and then against the alpha-strain), and the ultimate decline in cases was due to depletion of susceptibles rather than the vaccination campaign. Full article
(This article belongs to the Special Issue Transmission Dynamics of Coronavirus Disease)
►▼ Show Figures

Figure 1

8 pages, 3779 KiB  
Article
Estimation of Serial Interval and Reproduction Number to Quantify the Transmissibility of SARS-CoV-2 Omicron Variant in South Korea
by Dasom Kim, Sheikh Taslim Ali, Sungchan Kim, Jisoo Jo, Jun-Sik Lim, Sunmi Lee and Sukhyun Ryu
Viruses 2022, 14(3), 533; https://doi.org/10.3390/v14030533 - 4 Mar 2022
Cited by 53 | Viewed by 6467
Abstract
The omicron variant (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was the predominant variant in South Korea from late January 2022. In this study, we aimed to report the early estimates of the serial interval distribution and reproduction number to quantify [...] Read more.
The omicron variant (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was the predominant variant in South Korea from late January 2022. In this study, we aimed to report the early estimates of the serial interval distribution and reproduction number to quantify the transmissibility of the omicron variant in South Korea between 25 November 2021 and 31 December 2021. We analyzed 427 local omicron cases and reconstructed 73 transmission pairs. We used a maximum likelihood estimation to assess serial interval distribution from transmission pair data and reproduction numbers from 74 local cases in the first local outbreak. We estimated that the mean serial interval was 3.78 (standard deviation, 0.76) days, which was significantly shorter in child infectors (3.0 days) compared to adult infectors (5.0 days) (p < 0.01). We estimated the mean reproduction number was 1.72 (95% CrI, 1.60–1.85) for the omicron variant during the first local outbreak. Strict adherence to public health measures, particularly in children, should be in place to reduce the transmission risk of the highly transmissible omicron variant in the community. Full article
(This article belongs to the Special Issue Transmission Dynamics of Coronavirus Disease)
►▼ Show Figures

Figure 1

13 pages, 1610 KiB  
Communication
The Spread of SARS-CoV-2 Variant Omicron with a Doubling Time of 2.0–3.3 Days Can Be Explained by Immune Evasion
by Frederic Grabowski, Marek Kochańczyk and Tomasz Lipniacki
Viruses 2022, 14(2), 294; https://doi.org/10.3390/v14020294 - 30 Jan 2022
Cited by 72 | Viewed by 5788
Abstract
Omicron, the novel highly mutated SARS-CoV-2 Variant of Concern (VOC, Pango lineage B.1.1.529) was first collected in early November 2021 in South Africa. By the end of November 2021, it had spread and approached fixation in South Africa, and had been detected on [...] Read more.
Omicron, the novel highly mutated SARS-CoV-2 Variant of Concern (VOC, Pango lineage B.1.1.529) was first collected in early November 2021 in South Africa. By the end of November 2021, it had spread and approached fixation in South Africa, and had been detected on all continents. We analyzed the exponential growth of Omicron over four-week periods in the two most populated of South Africa’s provinces, Gauteng and KwaZulu-Natal, arriving at the doubling time estimates of, respectively, 3.3 days (95% CI: 3.2–3.4 days) and 2.7 days (95% CI: 2.3–3.3 days). Similar or even shorter doubling times were observed in other locations: Australia (3.0 days), New York State (2.5 days), UK (2.4 days), and Denmark (2.0 days). Log–linear regression suggests that the spread began in Gauteng around 11 October 2021; however, due to presumable stochasticity in the initial spread, this estimate can be inaccurate. Phylogenetics-based analysis indicates that the Omicron strain started to diverge between 6 October and 29 October 2021. We estimated that the weekly growth of the ratio of Omicron to Delta is in the range of 7.2–10.2, considerably higher than the growth of the ratio of Delta to Alpha (estimated to be in in the range of 2.5–4.2), and Alpha to pre-existing strains (estimated to be in the range of 1.8–2.7). High relative growth does not necessarily imply higher Omicron infectivity. A two-strain SEIR model suggests that the growth advantage of Omicron may stem from immune evasion, which permits this VOC to infect both recovered and fully vaccinated individuals. As we demonstrated within the model, immune evasion is more concerning than increased transmissibility, because it can facilitate larger epidemic outbreaks. Full article
(This article belongs to the Special Issue Transmission Dynamics of Coronavirus Disease)
►▼ Show Figures

Figure 1

18 pages, 5159 KiB  
Article
Bayesian Inference of State-Level COVID-19 Basic Reproduction Numbers across the United States
by Abhishek Mallela, Jacob Neumann, Ely F. Miller, Ye Chen, Richard G. Posner, Yen Ting Lin and William S. Hlavacek
Viruses 2022, 14(1), 157; https://doi.org/10.3390/v14010157 - 15 Jan 2022
Cited by 12 | Viewed by 3373
Abstract
Although many persons in the United States have acquired immunity to COVID-19, either through vaccination or infection with SARS-CoV-2, COVID-19 will pose an ongoing threat to non-immune persons so long as disease transmission continues. We can estimate when sustained disease transmission will end [...] Read more.
Although many persons in the United States have acquired immunity to COVID-19, either through vaccination or infection with SARS-CoV-2, COVID-19 will pose an ongoing threat to non-immune persons so long as disease transmission continues. We can estimate when sustained disease transmission will end in a population by calculating the population-specific basic reproduction number ℛ0, the expected number of secondary cases generated by an infected person in the absence of any interventions. The value of ℛ0 relates to a herd immunity threshold (HIT), which is given by 1−1/ℛ0. When the immune fraction of a population exceeds this threshold, sustained disease transmission becomes exponentially unlikely (barring mutations allowing SARS-CoV-2 to escape immunity). Here, we report state-level ℛ0 estimates obtained using Bayesian inference. Maximum a posteriori estimates range from 7.1 for New Jersey to 2.3 for Wyoming, indicating that disease transmission varies considerably across states and that reaching herd immunity will be more difficult in some states than others. ℛ0 estimates were obtained from compartmental models via the next-generation matrix approach after each model was parameterized using regional daily confirmed case reports of COVID-19 from 21 January 2020 to 21 June 2020. Our ℛ0 estimates characterize the infectiousness of ancestral strains, but they can be used to determine HITs for a distinct, currently dominant circulating strain, such as SARS-CoV-2 variant Delta (lineage B.1.617.2), if the relative infectiousness of the strain can be ascertained. On the basis of Delta-adjusted HITs, vaccination data, and seroprevalence survey data, we found that no state had achieved herd immunity as of 20 September 2021. Full article
(This article belongs to the Special Issue Transmission Dynamics of Coronavirus Disease)
►▼ Show Figures

Figure 1

Other

Jump to: Research

1 pages, 213 KiB  
Correction
Correction: Kurpas et al. Genomic Analysis of SARS-CoV-2 Alpha, Beta and Delta Variants of Concern Uncovers Signatures of Neutral and Non-Neutral Evolution. Viruses 2022, 14, 2375
by Monika Klara Kurpas, Roman Jaksik, Pawel Kuś and Marek Kimmel
Viruses 2023, 15(5), 1047; https://doi.org/10.3390/v15051047 - 25 Apr 2023
Viewed by 1001
Abstract
Missing Funding [...] Full article
(This article belongs to the Special Issue Transmission Dynamics of Coronavirus Disease)
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop