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Viruses
Special Issues
Infectious Disease Epidemiology and Transmission Dynamics 2.0
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Infectious Disease Epidemiology and Transmission Dynamics 2.0

A special issue of Viruses (ISSN 1999-4915). This special issue belongs to the section "General Virology".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 9408

Special Issue Editors

Dr. Zhanwei Du

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Guest Editor
School of Public Health, University of Hong Kong, Hong Kong Special Administrative Region, China
Interests: computational epidemiology; viral epidemiology; infectious diseases
Special Issues, Collections and Topics in MDPI journals
Dr. Lin Wang

E-Mail Website
Guest Editor
Department of Genetics, University of Cambridge, Cambridge, UK
Interests: infectious disease dynamics; epidemiology; Bayesian modeling; machine learning; immunology; pathogen evolution
Special Issues, Collections and Topics in MDPI journals
Dr. Zeynep Ertem

E-Mail Website
Guest Editor
Systems Science and Industrial Engineering Department, Thomas J. Watson College of Engineering and Applied Science, State University of New York at Binghamton, Binghamton, NY 13902, USA
Interests: infectious disease modeling; healthcare analytics; operations research; medical decision making; outcomes research; computational biology; public health
Dr. Jose Luis Herrera Diestra

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Guest Editor
Department of Integrative Biology. College of Natural Science. University of Texas at Austin, Austin, TX, USA
Interests: mathematical modeling of infectious diseases; contact network epidemiology; network science; computational biology
Dr. Yuan Bai

E-Mail Website
Guest Editor
School of Public Health, University of Hong Kong, Hong Kong Special Administrative Region, China
Interests: computational epidemiology; viral epidemiology; infectious diseases

Special Issue Information

Dear Colleagues,

To understand the epidemiology and transmission dynamics of infectious diseases (e.g., COVID-19, influenza, respiratory syncytial virus, arboviruses, human papillomavirus, and human immunodeficiency virus), epidemiologists and mathematical modelers are continuously developing new methods to characterize transmission patterns and transmission mechanisms, estimate infection and disease burdens, reconstruct transmission history, forecast disease trends and healthcare demands, and evaluate the effectiveness or cost-effectiveness of intervention policies (e.g., mass testing, vaccination champions and stockpiling of antivirals). This Special Issue of Viruses welcomes submissions of epidemiological and infectious disease modeling studies. In particular, research that is relevant to the evaluation of the epidemiological and/or economic impacts of ramping up treatments by mass testing, existing or next-generation antivirals, and vaccinations is welcome.

This Special Issue aims to explore different research areas and to collect articles that focus on infectious disease epidemiology and transmission dynamics. Furthermore, we expect to gain more insight into the applications of such approaches in various areas such as public health, health economics, health informatics, evolution, immunity, and medical affairs.

We encourage the submission of high-quality original research, review, protocol, and perspective articles to this Special Issue. Areas of interest include, but are not limited to, the following topics:

  •     Infectious disease epidemiology and transmission dynamics;
  •     Spatial and temporal transmission patterns of infectious diseases;
  •     Effects of pharmaceutical interventions such as mass testing, vaccines, or antivirals;
  •     Inference of key epidemiological parameters;
  •     Phylogenetics and phylodynamics;
  •     Seroepidemiology.

Dr. Zhanwei Du
Dr. Lin Wang
Dr. Zeynep Ertem
Dr. Jose Luis Herrera Diestra
Dr. Yuan Bai
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

  • infectious disease epidemiology
  • mathematical modeling
  • computational epidemiology
  • pharmaceutical interventions (e.g., mass testing, vaccination and antiviral)
  • infection and fatality burden
  • serology
  • phylogenetics and phylodynamics

Related Special Issue

Published Papers (7 papers)

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Research

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23 pages, 9386 KiB  
Article
A Managerial Approach towards Modeling the Different Strains of the COVID-19 Virus Based on the Spatial GeoCity Model
by Yaroslav Vyklyuk, Denys Nevinskyi, Valentyna Chopyak, Miroslav Škoda, Olga Golubovska and Kateryna Hazdiuk
Viruses 2023, 15(12), 2299; https://doi.org/10.3390/v15122299 - 23 Nov 2023
Viewed by 994
Abstract
This study proposes a modification of the GeoCity model previously developed by the authors, detailing the age structure of the population, personal schedule on weekdays and working days, and individual health characteristics of the agents. This made it possible to build a more [...] Read more.
This study proposes a modification of the GeoCity model previously developed by the authors, detailing the age structure of the population, personal schedule on weekdays and working days, and individual health characteristics of the agents. This made it possible to build a more realistic model of the functioning of the city and its residents. The developed model made it possible to simulate the spread of three types of strain of the COVID-19 virus, and to analyze the adequacy of this model in the case of unhindered spread of the virus among city residents. Calculations based on the proposed model show that SARS-CoV 2 spreads mainly from contacts in workplaces and transport, and schoolchildren and preschool children are the recipients, not the initiators of the epidemic. The simulations showed that fluctuations in the dynamics of various indicators of the spread of SARS-CoV 2 were associated with the difference in the daily schedule on weekdays and weekends. The results of the calculations showed that the daily schedules of people strongly influence the spread of SARS-CoV 2. Under assumptions of the model, the results show that for the more contagious “rapid” strains of SARS-CoV 2 (omicron), immunocompetent people become a significant source of infection. For the less contagious “slow strains” (alpha) of SARS-CoV 2, the most active source of infection is immunocompromised individuals (pregnant women). The more contagious, or “fast” strain of the SARS-CoV 2 virus (omicron), spreads faster in public transport. For less contagious, or “slow” strains of the virus (alpha), the greatest infection occurs due to work and educational contacts. Full article
(This article belongs to the Special Issue Infectious Disease Epidemiology and Transmission Dynamics 2.0)
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17 pages, 2511 KiB  
Article
HantaNet: A New MicrobeTrace Application for Hantavirus Classification, Genomic Surveillance, Epidemiology and Outbreak Investigations
by Roxana Cintron, Shannon L. M. Whitmer, Evan Moscoso, Ellsworth M. Campbell, Reagan Kelly, Emir Talundzic, Melissa Mobley, Kuo Wei Chiu, Elizabeth Shedroff, Anupama Shankar, Joel M. Montgomery, John D. Klena and William M. Switzer
Viruses 2023, 15(11), 2208; https://doi.org/10.3390/v15112208 - 02 Nov 2023
Cited by 2 | Viewed by 1370
Abstract
Hantaviruses zoonotically infect humans worldwide with pathogenic consequences and are mainly spread by rodents that shed aerosolized virus particles in urine and feces. Bioinformatics methods for hantavirus diagnostics, genomic surveillance and epidemiology are currently lacking a comprehensive approach for data sharing, integration, visualization, [...] Read more.
Hantaviruses zoonotically infect humans worldwide with pathogenic consequences and are mainly spread by rodents that shed aerosolized virus particles in urine and feces. Bioinformatics methods for hantavirus diagnostics, genomic surveillance and epidemiology are currently lacking a comprehensive approach for data sharing, integration, visualization, analytics and reporting. With the possibility of hantavirus cases going undetected and spreading over international borders, a significant reporting delay can miss linked transmission events and impedes timely, targeted public health interventions. To overcome these challenges, we built HantaNet, a standalone visualization engine for hantavirus genomes that facilitates viral surveillance and classification for early outbreak detection and response. HantaNet is powered by MicrobeTrace, a browser-based multitool originally developed at the Centers for Disease Control and Prevention (CDC) to visualize HIV clusters and transmission networks. HantaNet integrates coding gene sequences and standardized metadata from hantavirus reference genomes into three separate gene modules for dashboard visualization of phylogenetic trees, viral strain clusters for classification, epidemiological networks and spatiotemporal analysis. We used 85 hantavirus reference datasets from GenBank to validate HantaNet as a classification and enhanced visualization tool, and as a public repository to download standardized sequence data and metadata for building analytic datasets. HantaNet is a model on how to deploy MicrobeTrace-specific tools to advance pathogen surveillance, epidemiology and public health globally. Full article
(This article belongs to the Special Issue Infectious Disease Epidemiology and Transmission Dynamics 2.0)
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12 pages, 2612 KiB  
Article
Prevention and Control Are Not a Regional Matter: A Spatial Correlation and Molecular Linkage Analysis Based on Newly Reported HIV/AIDS Patients in 2021 in Jiangsu, China
by Defu Yuan, Shanshan Liu, Fei Ouyang, Wei Ai, Lingen Shi, Xiaoyan Liu, Tao Qiu, Ying Zhou and Bei Wang
Viruses 2023, 15(10), 2053; https://doi.org/10.3390/v15102053 - 06 Oct 2023
Cited by 1 | Viewed by 776
Abstract
HIV-related spatial analysis studies in China are relatively few, and Jiangsu Province has not reported the relevant data in recent years. To describe the spatial distribution and molecular linkage characteristics of HIV-infected patients, this article combined descriptive epidemiology, spatial analysis, and molecular epidemiology [...] Read more.
HIV-related spatial analysis studies in China are relatively few, and Jiangsu Province has not reported the relevant data in recent years. To describe the spatial distribution and molecular linkage characteristics of HIV-infected patients, this article combined descriptive epidemiology, spatial analysis, and molecular epidemiology methods to analyze patient reporting, patient mobility information, and HIV sequence information simultaneously. The results showed that HIV reporting profiles differed among Jiangsu cities, with the reporting rate in southern Jiangsu being above average. There was a spatial autocorrelation (Global Moran I = 0.5426, p < 0.05), with Chang Zhou showing a High–High aggregation pattern. Chang Zhou and Wu Xi were identified as hotspots for HIV reporting and access to molecular transmission networks. Some infected individuals still showed cross-city or even cross-province mobility after diagnosis, and three were linked with individuals in the destination cities within the largest molecular transmission cluster, involving 196 patients. The cross-city or cross-province mobility of patients may result in a potential HIV transmission risk, suggesting that combining timely social network surveys, building an extensive transmission network across cities and provinces, and taking critical regions and key populations as entry points could contribute to improved prevention and control efficiency and promote achievement of the 95-95-95 target and cascade. Full article
(This article belongs to the Special Issue Infectious Disease Epidemiology and Transmission Dynamics 2.0)
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15 pages, 2338 KiB  
Article
Temporal Analysis of COVID-19 Epidemiological Indicators in a Low-Income Brazilian Context: A Retrospective Analysis in Paraiba State
by Fabiola Ferreira da Silva, Luiz Carlos de Abreu, Blanca Elena Guerrero Daboin, Tassiane Cristina Morais, Matheus Paiva Emidio Cavalcanti, Italla Maria Pinheiro Bezerra, Célia Guarnieri da Silva, Fernando Augusto Marinho dos Santos Figueira, Viviane Valeria de Caldas Guedes and Andres Ricardo Perez Riera
Viruses 2023, 15(10), 2016; https://doi.org/10.3390/v15102016 - 28 Sep 2023
Viewed by 865
Abstract
Northeast Brazil is a region with great international tourist potential. Among the states that make up this region, Paraíba stands out due to the presence of vulnerable groups and factors that contribute to adverse outcomes of COVID-19. Therefore, the aim of this study [...] Read more.
Northeast Brazil is a region with great international tourist potential. Among the states that make up this region, Paraíba stands out due to the presence of vulnerable groups and factors that contribute to adverse outcomes of COVID-19. Therefore, the aim of this study was to analyze the epidemiological data on the incidence, mortality, and case fatality of COVID-19 in Paraíba. An ecological, population-based study was performed, with data extracted from the Brazilian Ministry of Health database. All cases and deaths from COVID-19 from March 2020 to December 2022 were included. The time series was built by applying the Prais–Winsten regression model, and the daily percent change was calculated to analyze the trends. The highest case fatality of the entire period was in April 2020 (7.8%), but in March 2021, the state broke the dismal record of 1248 deaths and the highest mortality rate (30.5 deaths per 100,000 inhabitants). Stationary mortality and case fatality were better in 2022; however, in February 2022, the mortality rate was at levels similar to the same month of the previous year. These results illustrate that COVID-19 is evolving and needs to be constantly monitored. Full article
(This article belongs to the Special Issue Infectious Disease Epidemiology and Transmission Dynamics 2.0)
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17 pages, 2079 KiB  
Article
Continued Circulation of Highly Pathogenic H5 Influenza Viruses in Vietnamese Live Bird Markets in 2018–2021
by Lizheng Guan, Lavanya Babujee, Victoria L. Browning, Robert Presler, David Pattinson, Hang Le Khanh Nguyen, Vu Mai Phuong Hoang, Mai Quynh Le, Harm van Bakel, Gabriele Neumann and Yoshihiro Kawaoka
Viruses 2023, 15(7), 1596; https://doi.org/10.3390/v15071596 - 21 Jul 2023
Cited by 2 | Viewed by 1419
Abstract
We isolated 77 highly pathogenic avian influenza viruses during routine surveillance in live poultry markets in northern provinces of Vietnam from 2018 to 2021. These viruses are of the H5N6 subtype and belong to HA clades 2.3.4.4g and 2.3.4.4h. Interestingly, we did not [...] Read more.
We isolated 77 highly pathogenic avian influenza viruses during routine surveillance in live poultry markets in northern provinces of Vietnam from 2018 to 2021. These viruses are of the H5N6 subtype and belong to HA clades 2.3.4.4g and 2.3.4.4h. Interestingly, we did not detect viruses of clade 2.3.4.4b, which in recent years have dominated in different parts of the world. The viruses isolated in this current study do not encode major determinants of mammalian adaptation (e.g., PB2-E627K or PB1-D701N) but possess amino acid substitutions that may affect viral receptor-binding, replication, or the responses to human antiviral factors. Several of the highly pathogenic H5N6 virus samples contained other influenza viruses, providing an opportunity for reassortment. Collectively, our study demonstrates that the highly pathogenic H5 viruses circulating in Vietnam in 2018–2021 were different from those in other parts of the world, and that the Vietnamese H5 viruses continue to evolve through mutations and reassortment. Full article
(This article belongs to the Special Issue Infectious Disease Epidemiology and Transmission Dynamics 2.0)
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13 pages, 913 KiB  
Article
First Insight into the Seroepidemiology of Hepatitis E Virus (HEV) in Dogs, Cats, Horses, Cattle, Sheep, and Goats from Bulgaria
by Ilia Tsachev, Krasimira Gospodinova, Roman Pepovich, Katerina Takova, Todor Kundurzhiev, Gergana Zahmanova, Kristin Kaneva and Magdalena Baymakova
Viruses 2023, 15(7), 1594; https://doi.org/10.3390/v15071594 - 21 Jul 2023
Cited by 4 | Viewed by 1839
Abstract
In recent years, hepatitis E virus (HEV) infection has been found to be widespread among different animal species worldwide. In Bulgaria, high HEV seropositivity was found among pigs (60.3%), wild boars (40.8%), and East Balkan swine (82.5%). The aim of the present study [...] Read more.
In recent years, hepatitis E virus (HEV) infection has been found to be widespread among different animal species worldwide. In Bulgaria, high HEV seropositivity was found among pigs (60.3%), wild boars (40.8%), and East Balkan swine (82.5%). The aim of the present study was to establish the seroprevalence of HEV among dogs, cats, horses, cattle, sheep, and goats in Bulgaria. In total, 720 serum samples from six animal species were randomly collected: dogs—90 samples; cats—90; horses—180; cattle—180; sheep—90; and goats—90. The serum samples were collected from seven districts of the country: Burgas, Kardzhali, Pazardzhik, Plovdiv, Sliven, Smolyan, and Stara Zagora. The animal serum samples were tested for HEV antibodies using the commercial Wantai HEV-Ab ELISA kit (Beijing, China). The overall HEV seroprevalence among different animal species from Bulgaria was as follows: dogs—21.1%; cats—17.7%; horses—8.3%; cattle—7.7%; sheep—32.2%; and goats—24.4%. We found the lowest overall HEV seropositivity in Plovdiv district (6.2%; 4/64; p = 0.203) and Smolyan district (8.8%; 4/45; p = 0.129), vs. the highest in Pazardzhik district (21.6%; 29/134; p = 0.024) and Burgas district (28.8%; 26/90; p = 0.062). To the best of our knowledge, this is the first serological evidence of HEV infection in dogs, cats, horses, cattle, sheep, and goats from Bulgaria. We found high HEV seropositivity in small ruminants (sheep and goats), moderate seropositivity in pets (dogs and cats), and a low level of seropositivity in large animals (horses and cattle). Previous Bulgarian studies and the results of this research show that HEV infection is widespread among animals in our country. In this regard, the Bulgarian health authorities must carry out increased surveillance and control of HEV infection among animals in Bulgaria. Full article
(This article belongs to the Special Issue Infectious Disease Epidemiology and Transmission Dynamics 2.0)
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Review

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15 pages, 1154 KiB  
Review
Clinical Severity of SARS-CoV-2 Variants during COVID-19 Vaccination: A Systematic Review and Meta-Analysis
by Zhilu Yuan, Zengyang Shao, Lijia Ma and Renzhong Guo
Viruses 2023, 15(10), 1994; https://doi.org/10.3390/v15101994 - 26 Sep 2023
Cited by 4 | Viewed by 1394
Abstract
Due to the variation in the SARS-CoV-2 virus, COVID-19 exhibits significant variability in severity. This presents challenges for governments in managing the allocation of healthcare resources and prioritizing health interventions. Clinical severity is also a critical statistical parameter for researchers to quantify the [...] Read more.
Due to the variation in the SARS-CoV-2 virus, COVID-19 exhibits significant variability in severity. This presents challenges for governments in managing the allocation of healthcare resources and prioritizing health interventions. Clinical severity is also a critical statistical parameter for researchers to quantify the risks of infectious disease, model the transmission of COVID-19, and provide some targeted measures to control the pandemic. To obtain more accurate severity estimates, including confirmed case-hospitalization risk, confirmed case-fatality risk, hospitalization-fatality risk, and hospitalization-ICU risk, we conducted a systematic review and meta-analysis on the clinical severity (including hospitalization, ICU, and fatality risks) of different variants during the period of COVID-19 mass vaccination and provided pooled estimates for each clinical severity metric. All searches were carried out on 1 February 2022 in PubMed for articles published from 1 January 2020 to 1 February 2022. After identifying a total of 3536 studies and excluding 3523 irrelevant studies, 13 studies were included. The severity results show that the Delta and Omicron variants have the highest (6.56%, 0.46%, 19.63%, and 9.06%) and lowest severities (1.51%, 0.04%, 6.01%, and 3.18%), respectively, according to the four clinical severity metrics. Adults over 65 have higher severity levels for all four clinical severity metrics. Full article
(This article belongs to the Special Issue Infectious Disease Epidemiology and Transmission Dynamics 2.0)
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