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Spreading of Infectious Diseases Like COVID-19 and Influenza: Modelling and Propagation Control 2.0

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".

Deadline for manuscript submissions: closed (20 December 2022) | Viewed by 10682
Related Special Issue: Spreading of Infection Diseases like COVID-19 and Influenza: Modelling and Propagation Control

Special Issue Editors

Prof. Dr. Johann Michael Köhler

E-Mail Website
Guest Editor
Institute of Chemistry and Bioengineering, Department of Physical Chemistry and Microreaction Technology, Technische Universität Ilmenau, 98693 Ilmenau, Germany
Interests: microfluidic synthesis of metal nanoparticles; electrical properties of nanoparticles; non-spherical and composite nanoparticles; nanoparticles in sensing and labelling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Stefan Wölfl

E-Mail Website
Guest Editor
Institute of Pharmacy and Molecular Biotechnology, University of Heidelberg, Im Neuenheimer Feld 364, 69120 Heidelberg, Germany
Interests: bioanalytics; cellular biosensors for drug testing and environmental analysis; gene regulation in mammalian cells in disease models; influence of basic biochemical processes on DNA-damage and stress response
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The recent propagation of Covid-19 demands new strategies for the monitoring and control of epidemic diseases. Despite the fact that the understanding of the molecular biology of viruses is much better than decades before, humanity is confronted with the global spreading of a very dangerous viral pathogen. All countries are looking, recently, for suitable strategies for reducing contacts between persons on the one hand and to keep running the everyday life as far as possible on the other hand. The first months of Covid-19 spreading had taught that the mechanisms of virus transfer, infection, and stimulation of immune reactions are not sufficiently understood. Beside experimental biosciences and medicine, the modelling of infection, infectious propagation, individual immune reaction, and herd immunity should be described by suited models.

The Special Issue is dedicated to new approaches of modelling of infection, epidemic propagation, and all aspects of connecting individual response on pathogens with the pandemic developments and their consequences. Contributions from different fields—coming from medical, molecular biological, ecological, kinetical, biophysical and physicochemical as well as mathematical point of views—and interdisciplinary concepts are welcome.

The deadline for submitting of manuscripts is September 10th, 2021. However, authors are encouraged to submit their papers earlier in order to contribute to the recent scientific discussion and to support the right decisions for managing the control of the recent pandemic as soon as possible.

Prof. Dr. Johann Michael Köhler
Prof. Dr. Stefan Wölfl
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. Applied Sciences 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 2400 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.

Published Papers (4 papers)

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Research

10 pages, 1021 KiB  
Article
Method for the Analysis of Health Personnel Availability in a Pandemic Crisis Scenario through Monte Carlo Simulation
by Tamara Pando-Ezcurra, Wilver Auccahuasi, Esther Rosa Saenz Arenas, Emilio Augusto Rosario Pacahuala, Erica Rojana González Ponce de León, Sandro Olaya Cotera, Rosalynn Ornella Flores Castañeda and Lucas Herrera
Appl. Sci. 2022, 12(16), 8299; https://doi.org/10.3390/app12168299 - 19 Aug 2022
Cited by 2 | Viewed by 1932
Abstract
During pandemic times, difficulties and problems related to the health sector are evident as the number of patients coming to health centers is higher compared to normal situations. This increase in the number of patients is typical of the pandemic, due to the [...] Read more.
During pandemic times, difficulties and problems related to the health sector are evident as the number of patients coming to health centers is higher compared to normal situations. This increase in the number of patients is typical of the pandemic, due to the high level of contagion in the population. Health personnel have a higher risk of infection, due to their sharing the work of caring for positive patients, so the infection rate is much higher. Hence, it remains necessary to understand the behavior of infection of health personnel, in order to be prepared to deal with the care of patients. Accordingly, in this research, we present a method to estimate different scenarios of infection and assess the probability of occurrence, so we can estimate the infection rate of health personnel. We present a simulation of 21 possible scenarios with 100 workers and a minimum of 80% needed to guarantee patient care. The results show that it is more likely that a 50% contagion scenario will occur, with an acceptable probability of 20%. Full article
(This article belongs to the Special Issue Spreading of Infectious Diseases Like COVID-19 and Influenza: Modelling and Propagation Control 2.0)
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15 pages, 4451 KiB  
Communication
Vaccination, Immunity and Breakthrough: Quantitative Effects in Individual Immune Responses Illustrated by a Simple Kinetic Model
by Johann Michael Köhler
Appl. Sci. 2022, 12(1), 31; https://doi.org/10.3390/app12010031 - 21 Dec 2021
Cited by 2 | Viewed by 3371
Abstract
The personal risks of infection, as well as the conditions for achieving herd immunity, are strongly dependent on an individual’s response to the infective agents on the one hand, and the individual’s reactions to vaccination on the other hand. The main goal of [...] Read more.
The personal risks of infection, as well as the conditions for achieving herd immunity, are strongly dependent on an individual’s response to the infective agents on the one hand, and the individual’s reactions to vaccination on the other hand. The main goal of this work is to illustrate the importance of quantitative individual effects for disease risk in a simple way. The applied model was able to illustrate the quantitative effects, in the cases of different individual reactions, after exposition to viruses or bacteria and vaccines. The model was based on simple kinetic equations for stimulation of antibody production using different concentrations of the infective agent, vaccine and antibodies. It gave a qualitative explanation for the individual differences in breakthrough risks and different requirements concerning a second, third or further vaccinations, reconsidering different efficiencies of the stimulation of an immune reaction. Full article
(This article belongs to the Special Issue Spreading of Infectious Diseases Like COVID-19 and Influenza: Modelling and Propagation Control 2.0)
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12 pages, 1103 KiB  
Article
Clinical Outcomes in the Second versus First Pandemic Wave in Italy: Impact of Hospital Changes and Reorganization
by Antonio Voza, Antonio Desai, Sabino Luzzi, Alice Giotta Lucifero, Elena Azzolini, Maria Kogan, Giulia Goretti, Daniele Piovani, Stefanos Bonovas, Giovanni Angelotti, Victor Savevski, Alessio Aghemo, Massimiliano Greco, Elena Costantini, Ana Lleo, Claudio Angelini, Mauro Giordano, Salvatore Badalamenti and Maurizio Cecconi
Appl. Sci. 2021, 11(19), 9342; https://doi.org/10.3390/app11199342 - 8 Oct 2021
Cited by 2 | Viewed by 1984
Abstract
The region of Lombardy was the epicenter of the COVID-19 outbreak in Italy. Emergency Hospital 19 (EH19) was built in the Milan metropolitan area during the pandemic’s second wave as a facility of Humanitas Clinical and Research Center (HCRC). The present study aimed [...] Read more.
The region of Lombardy was the epicenter of the COVID-19 outbreak in Italy. Emergency Hospital 19 (EH19) was built in the Milan metropolitan area during the pandemic’s second wave as a facility of Humanitas Clinical and Research Center (HCRC). The present study aimed to assess whether the implementation of EH19 was effective in improving the quality of care of COVID-19 patients during the second wave compared with the first one. The demographics, mortality rate, and in-hospital length of stay (LOS) of two groups of patients were compared: the study group involved patients admitted at HCRC and managed in EH19 during the second pandemic wave, while the control group included patients managed exclusively at HCRC throughout the first wave. The study and control group included 903 (56.7%) and 690 (43.3%) patients, respectively. The study group was six years older on average and had more pre-existing comorbidities. EH19 was associated with a decrease in the intensive care unit admission rate (16.9% vs. 8.75%, p < 0.001), and an equal decrease in invasive oxygen therapy (3.8% vs. 0.23%, p < 0.001). Crude mortality was similar but overlap propensity score weighting revealed a trend toward a potential small decrease. The adjusted difference in LOS was not significant. The implementation of an additional COVID-19 hospital facility was effective in improving the overall quality of care of COVID-19 patients during the first wave of the pandemic when compared with the second. Further studies are necessary to validate the suggested approach. Full article
(This article belongs to the Special Issue Spreading of Infectious Diseases Like COVID-19 and Influenza: Modelling and Propagation Control 2.0)
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15 pages, 655 KiB  
Article
Gaussian Parameters Correlate with the Spread of COVID-19 Pandemic: The Italian Case
by Carmelo Corsaro, Alessandro Sturniolo and Enza Fazio
Appl. Sci. 2021, 11(13), 6119; https://doi.org/10.3390/app11136119 - 30 Jun 2021
Cited by 3 | Viewed by 2488
Abstract
Until today, numerous models have been formulated to predict the spreading of Covid-19. Among them, the actively discussed susceptible-infected-removed (SIR) model is one of the most reliable. Unfortunately, many factors (i.e., social behaviors) can influence the outcomes as well as the occurrence of [...] Read more.
Until today, numerous models have been formulated to predict the spreading of Covid-19. Among them, the actively discussed susceptible-infected-removed (SIR) model is one of the most reliable. Unfortunately, many factors (i.e., social behaviors) can influence the outcomes as well as the occurrence of multiple contributions corresponding to multiple waves. Therefore, for a reliable evaluation of the conversion rates, data need to be continuously updated and analyzed. In this work, we propose a model using Gaussian functions, coming from the solution of an ordinary differential equation representing a logistic model, able to describe the growth rate of infected, deceased and recovered people in Italy. We correlate the Gaussian parameters with the number of people affected by COVID-19 as a function of the large-scale anti-contagion control measures strength, and also of vaccines effects adopted to reach herd immunity. The superposition of gaussian curves allow modeling the growth rate of the total cases, deceased and recovered people and reproducing the corresponding cumulative distribution and probability density functions. Moreover, we try to predict a time interval in which all people will be infected or vaccinated (with at least one dose) and/or the time end of pandemic in Italy when all people have been infected or vaccinated with two doses. Full article
(This article belongs to the Special Issue Spreading of Infectious Diseases Like COVID-19 and Influenza: Modelling and Propagation Control 2.0)
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