Using the recently proposed Susceptible–Asymptomatic–Infected–Vaccinated–Removed (SAIVR) model, we study the impact of key factors affecting COVID-19 vaccine rollout effectiveness and the ...susceptibility to resurgent epidemics. The SAIVR model expands the widely used Susceptible–Infectious–Removed (SIR) model for describing epidemics by adding compartments to include the asymptomatic infected (A) and the vaccinated (V) populations. We solve the model numerically to make predictions on the susceptibility to resurgent COVID-19 epidemics depending on initial vaccination coverage, importation loads, continuing vaccination, and more contagious SARS-CoV-2 variants, under persistent immunity and immunity waning conditions. The parameters of the model represent reported epidemiological characteristics of the SARS-CoV-2 virus such as the disease spread in countries with high levels of vaccination coverage. Our findings help explain how the combined effects of different vaccination coverage levels and waning immunity lead to distinct patterns of resurgent COVID-19 epidemics (either surges or endemic), which are observed in countries that implemented different COVID-19 health policies and achieved different vaccinated population plateaus after the vaccine rollouts in the first half of 2021.
Intervention measures have been implemented around the world to mitigate the spread of the coronavirus disease (COVID-19) pandemic. Understanding the dynamics of the disease spread and the ...effectiveness of the interventions is essential in predicting its future evolution.
The aim of this study is to simulate the effect of different social distancing interventions and investigate whether their timing and stringency can lead to multiple waves (subepidemics), which can provide a better fit to the wavy behavior observed in the infected population curve in the majority of countries.
We have designed and run agent-based simulations and a multiple wave model to fit the infected population data for many countries. We have also developed a novel Pandemic Response Index to provide a quantitative and objective way of ranking countries according to their COVID-19 response performance.
We have analyzed data from 18 countries based on the multiple wave (subepidemics) hypothesis and present the relevant parameters. Multiple waves have been identified and were found to describe the data better. The effectiveness of intervention measures can be inferred by the peak intensities of the waves. Countries imposing fast and stringent interventions exhibit multiple waves with declining peak intensities. This result strongly corroborated with agent-based simulations outcomes. We also provided an estimate of how much lower the number of infections could have been if early and strict intervention measures had been taken to stop the spread at the first wave, as actually happened for a handful of countries. A novel index, the Pandemic Response Index, was constructed, and based on the model's results, an index value was assigned to each country, quantifying in an objective manner the country's response to the pandemic.
Our results support the hypothesis that the COVID-19 pandemic can be successfully modeled as a series of epidemic waves (subepidemics) and that it is possible to infer to what extent the imposition of early intervention measures can slow the spread of the disease.
•A new compartmental model, forced-SIR, quantifies COVID-19 pandemics impact.•Effectiveness of COVID-19 intervention measures is linked to models parameters.•Application of the model to 10 countries ...reveals a wide range of COVID-19 impacts.
A simple analytical model for modeling the evolution of the 2020 COVID-19 pandemic is presented. The model is based on the numerical solution of the widely used Susceptible-Infectious-Removed (SIR) populations model for describing epidemics. We consider an expanded version of the original Kermack-McKendrick model, which includes a decaying value of the parameter β (the effective contact rate), interpreted as an effect of externally imposed conditions, to which we refer as the forced-SIR (FSIR) model. We introduce an approximate analytical solution to the differential equations that represent the FSIR model which gives very reasonable fits to real data for a number of countries over a period of 100 days (from the first onset of exponential increase, in China). The proposed model contains 3 adjustable parameters which are obtained by fitting actual data (up to April 28, 2020). We analyze these results to infer the physical meaning of the parameters involved. We use the model to make predictions about the total expected number of infections in each country as well as the date when the number of infections will have reached 99% of this total. We also compare key findings of the model with recently reported results on the high contagiousness and rapid spread of the disease.
•Introduced a new mathematical model that describes the evolution of the COVID-19 pandemic and how it is affected by the current vaccination effort.•Developed a semi-supervised machine learning ...method to solve the model’s differential equations.•Benchmarked the model on recent epidemic curves of 27 countries.•Made some qualitative assessments on the threat posed by new variants and vaccine hesitancy.•Discussed the concept of herd immunity.
Population-wide vaccination is critical for containing the SARS-CoV-2 (COVID-19) pandemic when combined with restrictive and prevention measures. In this study we introduce SAIVR, a mathematical model able to forecast the COVID-19 epidemic evolution during the vaccination campaign. SAIVR extends the widely used Susceptible-Infectious-Removed (SIR) model by considering the Asymptomatic (A) and Vaccinated (V) compartments. The model contains several parameters and initial conditions that are estimated by employing a semi-supervised machine learning procedure. After training an unsupervised neural network to solve the SAIVR differential equations, a supervised framework then estimates the optimal conditions and parameters that best fit recent infectious curves of 27 countries. Instructed by these results, we performed an extensive study on the temporal evolution of the pandemic under varying values of roll-out daily rates, vaccine efficacy, and a broad range of societal vaccine hesitancy/denial levels. The concept of herd immunity is questioned by studying future scenarios which involve different vaccination efforts and more infectious COVID-19 variants.
Population-wide vaccination is critical for containing the SARS-CoV-2 (Covid-19) pandemic when combined with restrictive and prevention measures. In this study, we introduce SAIVR, a mathematical ...model able to forecast the Covid-19 epidemic evolution during the vaccination campaign. SAIVR extends the widely used Susceptible-Infectious-Removed (SIR) model by considering the Asymptomatic (A) and Vaccinated (V) compartments. The model contains several parameters and initial conditions that are estimated by employing a semi-supervised machine learning procedure. After training an unsupervised neural network to solve the SAIVR differential equations, a supervised framework then estimates the optimal conditions and parameters that best fit recent infectious curves of 27 countries. Instructed by these results, we performed an extensive study on the temporal evolution of the pandemic under varying values of roll-out daily rates, vaccine efficacy, and a broad range of societal vaccine hesitancy/denial levels. The concept of herd immunity is questioned by studying future scenarios which involve different vaccination efforts and more infectious Covid-19 variants.
The Athos peninsula occupies the south-eastern part of the wider Chalkidiki peninsula in Central Macedonia, Greece. It is mainly built up by crystalline rocks belonging to the Serbo-Macedonian ...massif, traditionally constituting, along with the Rhodope massif, the Hellenic hinterland. According to the basic geological map of the peninsula, its northern part is mainly composed of marbles grouped into the Kerdyllion Unit, and biotite gneisses and two-mica gneisses grouped into the Vertiskos Unit of the Serbo-Macedonian massif, whereas the contact between the units is considered as a normal contact, although it has been re-evaluated as tectonic later on. Moreover, amphibolites and ultramafic rocks exist along with the previously mentioned rocks, making the geology and relationship between the two units much more complicated. Two detailed cross-sections and structural analysis permit us to revise the geology of the region concluding that the marbles, the amphibolite gneisses, formerly independent amphibolites, and the biotite gneisses belong to the Kerdyllion Unit that is strongly characterized by migmatization and anatexis, whereas the Vertiskos Unit is represented predominantly by two-mica gneisses that were not extensively, if at all, affected by these phenomena. Isoclinal folding and intense shearing with an overall top-to-the-S sense of shear resulted in the main fabric of the rocks and the mylonitic shear zone between the units. More importantly, the two-mica gneiss of the Vertiskos Unit is sandwiched between the rocks of the Kerdyllion Unit. We attribute both isoclinal folding and shearing to a Mesozoic tectonic event associated with an amphibolite facies metamorphism, leading to an Alpine reworking of the Serbo-Macedonian massif. This Alpine reworking continues during Eocene times with an ENE-WSW compression, giving rise to asymmetric to inverted folds, co-axially refolding pre-existing fabrics and structures. Our work strongly suggests that the overall structure and tectono-stratigraphy concerning the Vertiskos and Kerdyllion Units as well as the contact between them should not be based on the existence of the marbles, as traditionally followed up till now, but on the migmatization and anatexis processes that are almost absent from the rocks of the Vertiskos Unit.
A versatile family of quaternary propargylamines was synthesized employing the KA2 multicomponent reaction, through the single-step coupling of a number of amines, ketones, and terminal alkynes. ...Sustainable synthetic procedures using transition metal catalysts were employed in all cases. The inhibitory activity of these molecules was evaluated against human monoaminoxidase (hMAO)-A and hMAO-B enzymes and was found to be significant. The IC50 values for hMAO-B range from 152.1 to 164.7 nM while the IC50 values for hMAO-A range from 765.6 to 861.6 nM. Furthermore, these compounds comply with Lipinski’s rule of five and exhibit no predicted toxicity. To understand their binding properties with the two target enzymes, key interactions were studied using molecular docking, all-atom molecular dynamics (MD) simulations, and MM/GBSA binding free energy calculations. Overall, herein, the reported family of propargylamines exhibits promise as potential treatments for neurodegenerative disorders, such as Parkinson’s disease. Interestingly, this is the first time a propargylamine scaffold bearing an internal alkyne has been reported to show activity against monoaminoxidases.
Herein, we report a catalytic system based on the earth‐abundant manganese for the ketone, amine, alkyne (KA2) reaction. The efficiency of manganese manifests at relatively high temperatures, ...combined with sustainable reaction conditions, and provides a tool for accessing propargylamines from structurally diverse starting materials, including synthetically relevant and bioactive molecules. Our efforts were also aimed at shedding light on the catalytic mode of action of manganese in this transformation, in order to explain its temperature‐related behavior. The use of computational methods reveals mechanistic aspects of this reaction indicating important points regarding the reactivity of both manganese and ketones.
Tetrasubstituted propargylamines comprise a unique class of highly useful compounds, which can be accessed through the multicomponent coupling between ketones, amines, and alkynes (KA2 coupling), an ...underexplored transformation. Herein, the development of a novel, highly efficient, and user-friendly catalytic system for the KA2 coupling, based on the environmentally benign, inexpensive, and readily available zinc acetate, is described. This system is employed in the multicomponent assembly of unprecedented, tetrasubstituted propargylamines derived from structurally diverse, challenging, and even biorelevant substrates. Notable features of this protocol include the demonstration of the enhancing effect that neat conditions can have on catalytic activity, as well as the expedient functionalization of hindered, prochiral cyclohexanones, linear ketones, and interesting molecular scaffolds such as norcamphor and nornicotine.
Tetrasubstituted propargylamines comprise a unique class of highly useful compounds, which can be accessed through the multicomponent coupling between ketones, amines, and alkynes (KA
coupling), an ...underexplored transformation. Herein, the development of a novel, highly efficient, and user-friendly catalytic system for the KA
coupling, based on the environmentally benign, inexpensive, and readily available zinc acetate, is described. This system is employed in the multicomponent assembly of unprecedented, tetrasubstituted propargylamines derived from structurally diverse, challenging, and even biorelevant substrates. Notable features of this protocol include the demonstration of the enhancing effect that neat conditions can have on catalytic activity, as well as the expedient functionalization of hindered, prochiral cyclohexanones, linear ketones, and interesting molecular scaffolds such as norcamphor and nornicotine.
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