scholarly journals Distribution of Incubation Period of COVID-19 in the Canadian Context: Modeling and Computational Study

2020 ◽  
Author(s):  
Subhendu Paul ◽  
Emmanuel Lorin
Keyword(s):  
Confidence Interval ◽  
Incubation Period ◽  
Delay Differential Equations ◽  
Computational Study ◽  
Original Model ◽  
Context Modeling ◽  
Canadian Context ◽  
Incubation Periods ◽  
Delay Differential ◽  
Good Agreement

We propose an original model based on a set of coupled delay differential equations with fourteen delays in order to accurately estimate the incubation period of COVID-19, employing publicly available data of confirmed corona cases. In this goal, we separate the total cases into fourteen groups for the corresponding fourteen incubation periods. The estimated mean incubation period we obtain is 6.74 days (95% Confidence Interval(CI): 6.35 to 7.13), and the 90th percentile is 11.64 days (95% CI: 11.22 to 12.17), corresponding to a good agreement with statistical supported studies. This model provides an almost zero-cost approach to estimate the incubation period.

scholarly journals Distribution of Incubation Period of COVID-19 in the Canadian Context: Modeling and Computational Study

2020 ◽  
Author(s):  
Subhendu Paul ◽  
Emmanuel Lorin
Keyword(s):  
Confidence Interval ◽  
Incubation Period ◽  
Delay Differential Equations ◽  
Computational Study ◽  
Context Modeling ◽  
Canadian Context ◽  
Incubation Periods ◽  
Delay Differential ◽  
Novel Model ◽  
Good Agreement

Abstract We propose a novel model based on a set of coupled delay differential equations with fourteen delays in order to accurately estimate the incubation period of COVID-19, employing publicly available data of confirmed corona cases. In this goal, we separate the total cases into fourteen groups for the corresponding fourteen incubation periods. The estimated mean incubation period we obtain is 6.74 days (95% Confidence Interval(CI): 6.35 to 7.13), and the 90th percentile is 11.64 days (95% CI: 11.22 to 12.17), corresponding to a good agreement with statistical supported studies. This model provides an almost zero-cost approach to estimate the incubation period.

scholarly journals Distribution of incubation periods of COVID-19 in the Canadian context

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Subhendu Paul ◽  
Emmanuel Lorin
Keyword(s):  
Computational Complexity ◽  
Confidence Interval ◽  
Differential Equations ◽  
Incubation Period ◽  
Delay Differential Equations ◽  
Canadian Context ◽  
Incubation Periods ◽  
Delay Differential ◽  
Novel Model ◽  
Good Agreement

AbstractWe propose a novel model based on a set of coupled delay differential equations with fourteen delays in order to accurately estimate the incubation period of COVID-19, employing publicly available data of confirmed corona cases. In this goal, we separate the total cases into fourteen groups for the corresponding fourteen incubation periods. The estimated mean incubation period we obtain is 6.74 days (95% Confidence Interval(CI): 6.35 to 7.13), and the 90th percentile is 11.64 days (95% CI: 11.22 to 12.17), corresponding to a good agreement with statistical supported studies. This model provides an almost zero-cost computational complexity to estimate the incubation period.

scholarly journals Elementary time-delay dynamics of COVID-19 disease

2020 ◽  
Author(s):  
José Menéndez
Keyword(s):  
Time Delay ◽  
Differential Equations ◽  
South Korea ◽  
Ordinary Differential Equations ◽  
Delay Differential Equations ◽  
Survival Function ◽  
Elementary Model ◽  
Infected People ◽  
Delay Differential ◽  
Good Agreement

An elementary model of COVID-19 dynamics—based on time-delay differential equations with a step-like survival function—is shown to be in good agreement with data from China and South Korea. The time-delal approach overcomes the major limitation of standard Susceptible-Exposed-Infected-Recovered (SEIR) models based on ordinary differential equations, namely their inability to predict the observed curve of infected individuals as a function of time. The model is also applied to countries where the epidemic is in earlier stages, such as Italy and Spain, to obtain estimates of the total number of cases and peak number of infected people that might be observed.

scholarly journals Association of host, agent and environment characteristics and the duration of incubation and symptomatic periods of norovirus gastroenteritis

2014 ◽  
Vol 143 (11) ◽  
pp. 2308-2314 ◽  
Author(s):  
T. DEVASIA ◽  
B. LOPMAN ◽  
J. LEON ◽  
A. HANDEL
Keyword(s):  
Confidence Interval ◽  
Incubation Period ◽  
Environmental Characteristics ◽  
Norovirus Gastroenteritis ◽  
Incubation Periods ◽  
Host Pathogen ◽  
The Mean ◽  
Reported Data

SUMMARYWe analysed the reported duration of incubation and symptomatic periods of norovirus for a dataset of 1022 outbreaks, 64 of which reported data on the average incubation period and 87 on the average symptomatic period. We found the mean and median incubation periods for norovirus to be 32·8 [95% confidence interval (CI) 30·9–34·6] hours and 33·5 (95% CI 32·0–34·0) hours, respectively. For the symptomatic period we found the mean and median to be 44·2 (95% CI 38·9–50·7) hours and 43·0 (95% CI 36·0–48·0) hours, respectively. We further investigated how these average periods were associated with several reported host, agent and environmental characteristics. We did not find any strong, biologically meaningful associations between the duration of incubation or symptomatic periods and the reported host, pathogen and environmental characteristics. Overall, we found that the distributions of incubation and symptomatic periods for norovirus infections are fairly constant and showed little differences with regard to the host, pathogen and environmental characteristics we analysed.

Explaining the magnetism of gold

2017 ◽  
Author(s):  
Robson de Farias
Keyword(s):  
Gas Phase ◽  
Computational Study ◽  
Formation Enthalpy ◽  
Gold Atom ◽  
Orbital Energy ◽  
Knudsen Effusion ◽  
Energy Diagram ◽  
Unpaired Electrons ◽  
The Difference ◽  
Good Agreement

<p>In the present work, a computational study is performed in order to clarify the possible magnetic nature of gold. For such purpose, gas phase Au<sub>2</sub> (zero charge) is modelled, in order to calculate its gas phase formation enthalpy. The calculated values were compared with the experimental value obtained by means of Knudsen effusion mass spectrometric studies [5]. Based on the obtained formation enthalpy values for Au<sub>2</sub>, the compound with two unpaired electrons is the most probable one. The calculated ionization energy of modelled Au<sub>2</sub> with two unpaired electrons is 8.94 eV and with zero unpaired electrons, 11.42 eV. The difference (11.42-8.94 = 2.48 eV = 239.29 kJmol<sup>-1</sup>), is in very good agreement with the experimental value of 226.2 ± 0.5 kJmol<sup>-1</sup> to the Au-Au bond<sup>7</sup>. So, as expected, in the specie with none unpaired electrons, the two 6s<sup>1</sup> (one of each gold atom) are paired, forming a chemical bond with bond order 1. On the other hand, in Au<sub>2</sub> with two unpaired electrons, the s-d hybridization prevails, because the relativistic contributions. A molecular orbital energy diagram for gas phase Au<sub>2</sub> is proposed, explaining its paramagnetism (and, by extension, the paramagnetism of gold clusters and nanoparticles).</p>

Computational Study on the Kinetics and Mechanisms of Unimolecular Reactions of (Z)-(Z)-N-(λ5-phosphanylidene) Formohydrazonic Formic Anhydride: Intramolecular aza-Wittig Reaction in Competition with Mumm Rearrangement

2020 ◽  
Vol 17 (11) ◽  
pp. 884-889
Author(s):  
Somayeh Mirdoraghi ◽  
Hamed Douroudgari ◽  
Farideh Piri ◽  
Morteza Vahedpour
Keyword(s):  
Rate Constants ◽  
Density Functional ◽  
Wittig Reaction ◽  
Computational Study ◽  
Single Step ◽  
Low Energy ◽  
Coupled Cluster ◽  
Unimolecular Reaction ◽  
Single Step Reaction ◽  
Good Agreement

For (Z)-(Z)-N-(λ5-phosphanylidene) formohydrazonic formic anhydride, Aza-Wittig reaction and Mumm rearrangement are studied using both density functional and coupled cluster theories. For this purpose, two different products starting from one substrate are considered that are competing with each other. The obtained products, P1 and P2, are thermodynamically favorable. The product of the aza-Wittig reaction, P1, is more stable than the product of Mumm rearrangement (P2). For the mentioned products, just one reliable pathway is separately proposed based on unimolecular reaction. Therefore, the rate constants based on RRKM theory in 300-600 K temperature range are calculated. Results show that the P1 generation pathway is a suitable path due to low energy barriers than the path P2. The first path has three steps with three transition states, TS1, TS2, and TS3. The P2 production path is a single-step reaction. In CCSD level, the computed barrier energies are 14.55, 2.196, and 10.67 kcal/mol for Aza-Wittig reaction and 42.41 kcal/mol for Mumm rearrangement in comparison with the corresponding complexes or reactants. For final products, the results of the computational study are in a good agreement with experimental predictions.

A new Ф-generalized quasi metric space with some fixed point results and applications

Filomat ◽  
2017 ◽  
Vol 31 (11) ◽  
pp. 3157-3172
Author(s):  
Mujahid Abbas ◽  
Bahru Leyew ◽  
Safeer Khan
Keyword(s):  
Fixed Point ◽  
Differential Equations ◽  
Fixed Points ◽  
Periodic Solutions ◽  
Metric Space ◽  
Delay Differential Equations ◽  
Fixed Point Theorems ◽  
Metric Spaces ◽  
Existence Of Periodic Solutions ◽  
Delay Differential

In this paper, the concept of a new ?-generalized quasi metric space is introduced. A number of well-known quasi metric spaces are retrieved from ?-generalized quasi metric space. Some general fixed point theorems in a ?-generalized quasi metric spaces are proved, which generalize, modify and unify some existing fixed point theorems in the literature. We also give applications of our results to obtain fixed points for contraction mappings in the domain of words and to prove the existence of periodic solutions of delay differential equations.

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