scholarly journals The SIR and SEIR Epidemiological Models Revisited

2020 ◽  
Author(s):  
John P. Maassen
Keyword(s):  
Public Health ◽  
Monte Carlo ◽  
Stochastic Model ◽  
Monte Carlo Simulations ◽  
Sir Model ◽  
Epidemiological Models ◽  
Seir Model ◽  
Social Distancing

We review and assess the classic SIR and SEIR epidemiological models regarding possible applications to the COVID-19 pandemic. In spite of numerous more complicated models, we show how the qualitative features of the solution to the SIR and SEIR models continue to provide valuable public health insights in some scenarios. Using estimated COVID-19 data as of this date, the SEIR model shows that if it were possible to reduce R0 from 2.5 to 1.25 through social distancing and other measures, the maximum fraction of the population that would become infected at any particular time would drop from 17% to 4%, provided that all of the model assumptions are satisfied. Finally, we compare the classic SIR model with a recent stochastic model with favorable results. Since this comparison underscores the importance of underlying connectivity assumptions, we conclude with Monte-Carlo simulations with specific connectivity that reproduce the classical SIR model with standard incidence.

scholarly journals The effect of social distancing on the reach of an epidemic in social networks

2021 ◽  
Author(s):  
Gregory Gutin ◽  
Tomohiro Hirano ◽  
Sung-Ha Hwang ◽  
Philip R. Neary ◽  
Alexis Akira Toda
Keyword(s):  
Public Health ◽  
Infectious Disease ◽  
Social Networks ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Disease Transmission ◽  
Global Level ◽  
Social Distancing ◽  
The Public ◽  
Simulation Results

AbstractHow does social distancing affect the reach of an epidemic in social networks? We present Monte Carlo simulation results of a susceptible–infected–removed with social distancing model. The key feature of the model is that individuals are limited in the number of acquaintances that they can interact with, thereby constraining disease transmission to an infectious subnetwork of the original social network. While increased social distancing typically reduces the spread of an infectious disease, the magnitude varies greatly depending on the topology of the network, indicating the need for policies that are network dependent. Our results also reveal the importance of coordinating policies at the ‘global’ level. In particular, the public health benefits from social distancing to a group (e.g. a country) may be completely undone if that group maintains connections with outside groups that are not following suit.

scholarly journals Contraste de la frecuencia de salida del hogar ante la pandemia por COVID-19

Minerva ◽  
2020 ◽  
Vol 1 (2) ◽  
pp. 40-45
Author(s):  
Andrea Egas ◽  
Carmen Elena Santander ◽  
Marcelo Salazar ◽  
Alejandro Grijalva
Keyword(s):  
Public Health ◽  
Clinical Practice ◽  
Web Of Science ◽  
Sir Model ◽  
Health Policies ◽  
Seir Model ◽  
Public Health Policies ◽  
Palabras Clave ◽  
The Face ◽  
Salud Mental

En el siguiente estudio se evalúa un panorama con respecto al comportamiento sociológico en un preámbulo tanto antes durante y después de esta crisis social que se está viviendo debido a la pandemia de hoy en día. Por ello para sustentar dicha investigación se realizó un censo en el cuál, mediante el uso de herramientas estadísticas, se pudo realizar una comparación entre un antes y un durante de la pandemia, lo cual facilitaría intrínsicamente a la predicción de una denominada post pandemia. En este texto se pretende detallar el proceso y forma de la encuesta, al igual que los resultados obtenidos de la misma. Se proveen, además, posibles explicaciones para estos resultados, guiándose por las restricciones de salud nacionales como posibles razones para el cambio de comportamiento actual. Palabras Clave: coronavirus, pandemia, frecuencia de salida. Referencias [1]P. Byass, «Eco-epidemiological assessment of the COVID-19 epidemic in China, January-February 2020,» Web Of Science, vol. 13, nº 1, 2020. [2]P. Stefanoni, «Brasil: pandemia, guerra cultural y precariedad,» Nueva Sociedad, pp. 49-59, 2020. [3]M. J. Báguena Cervellera, «La pandemia de COVID-19 a la luz de la historia de la medicina,» Investigación y Ciencia , 2020. [4]A. Levy, «La pandemia de COVID-19 podr{ia ayudar a resolver una gran incógnita climática,» Investigación y Ciencia, 2020. [5]T. Marcel Ariel, «Relaciones en tiempos de pandemia: COVID-19 y bienestar animal, ambiental y humano,» Revista Facultad Nacional De Agronomia Medellin, vol. 2, 2020. [6]F. Manrique-Abril, «Modelo SIR de la pandemia de Covid-19 en Colombia/SIR model of the COVID-19 pandemic in Colombia,» Revista De Salúd Publica, vol. 22, pp. 1-6, 2020. [7]D. Arango-Londoño , «Predicciones de un modelo SEIR para casos de COVID-19 en Cali, Colombia/Predictions of a SEIR model for COVID-19 cases in Cali-Colombia,» Revista De Salúd Publica, vol. 22, nº 2, pp. 1-9, 2020. [8]J. Gonzales-Castillo , «Pandemia de la COVID-19 y las Políticas de Salud Pública en el Perú: marzo-mayo 2020/COVID-19 pandemic and Public Health Policies in Peru: March-May 2020,» Revista De Salúd Publica, vol. 22, nº2, pp. 1-9, 2020. [9]A. Valenzuela-Cazés y L. Becerra-Ostos, «Práctica clínica, ámbito laboral y riesgos de la fisioterapia ante el COVID-19/Clinical practice, work and risks of physical therapy in the face of COVID-19,» Revista De Salúd Publica, vol. 22, nº 2, pp. 1-4, 2020. [10]P. Montes-Alarcón y A. Campo-Arias, «Los médicos generales y la salud mental en la pandemia por COVID-19,» Duazary, vol. 17, nº 3, pp. 4-6, 2020.

scholarly journals COVID-19 Case Prediction and Outbreak Control of Navy Cluster in Sri Lanka: Effectiveness of SIR Model

2020 ◽  
Author(s):  
N.W.A.N.Y. Wijesekara ◽  
Nayomi Herath ◽  
K.A.L.C Kodituwakku ◽  
H.D.B. Herath ◽  
Samitha Ginige ◽  
...  
Keyword(s):  
Public Health ◽  
Sri Lanka ◽  
Sir Model ◽  
Epidemiological Surveillance ◽  
Infectious Period ◽  
Base Line ◽  
Ministry Of Health ◽  
Susceptible Population ◽  
Social Distancing ◽  
First Case

Abstract Introduction: Infectious diseases such as coronavirus disease 2019 (COVID-19) can spread dangerously fast in semi-confined places. Nevertheless, it has been found that rapid public health interventions such as isolation and quarantine could successfully curtail such outbreaks. An outbreak of COVID-19 was reported within a cluster of Navy personnel in the Western Province of Sri Lanka commencing from 22nd April 2020. An epidemiological investigation followed by aggressive public health measures were implemented by the Epidemiology Unit of the Ministry of Health with the support of the Sri Lanka Navy in response to the above outbreak. The objective of this research was to predict possible number of cases within the susceptible population in Sri Lanka Navy, to be used primarily for operational planning purpose by the Ministry of Health in control of outbreak in Sri Lanka.Methods: COVID-19 Hospital Impact Model for Epidemics (CHIME) developed by Predictive Health Care Team at Penn Medicine, which was a Susceptibility, Infected and Removed (SIR) model was used. The model was run on 20.05.2020 for a susceptible population of 10400, with number of hospitalized patients on the day of running the model being 357, first case hospitalized on 22.04.2020 and social distancing being implemented on 26.04.2020. Social distancing scenarios of 0, 25, 50 and 74% were run with 10 days of infectious period and 30 days of projection period.Results: With increasing social distancing measures, the peak number of infected persons decreased, as well as the duration of the curve extended. The number of infected cases from the first case ranged from 49th day to 54th day under social distancing scenarios from 0% to 74%. The doubling time increased from 3.1 days to 4.1 days from no social distancing to application of 74% social distancing, with corresponding decrease of Ro from 3.54 to 2.83. Expected daily growth rate of COVID-19 cases has decreased from 25.38 % to 18.53% under aforementioned increasing social distancing scenarios. The observed or actually experienced number of cases were well above the projected number of cases up to 07.05.2020, however, since this date the reported number of cases were lower than the projected number of cases from the model under four social distancing scenarios considered. Similar pattern was noted for the observed or actually experienced number of cases until the 20.05.2020, however, since then it was continuing at a very low intensity until the end of the modelling period. The number of COVID-19 cases prevented as per the model ranged from 2.3 – 21.1 %, compared to the base line prediction of no social distancing. However, based on the observed number of cases and the baseline model with no social distancing, 90.3% reduction was observed by the time of the model application date.Conclusion: The research demonstrated the practical use of a prediction model made readily available through an online open source platform for the operational aspects of controlling a COVID-19 or similar communicable disease outbreaks in a closed community such as armed forces. While comprehensive epidemiological surveillance, contact tracing, case isolation and case management should be the cornerstone of outbreak management, predictive modelling could supplement above efforts.

scholarly journals Evaluating Short-term Forecast among Different Epidemiological Models under a Bayesian Framework

2020 ◽  
Author(s):  
Qiwei Li ◽  
Tejasv Bedi ◽  
Guanghua Xiao ◽  
Yang Xie
Keyword(s):  
Public Health ◽  
Predictive Modeling ◽  
Growth Models ◽  
Sir Model ◽  
Global Scale ◽  
Bayesian Framework ◽  
Epidemiological Models ◽  
Short Term ◽  
Predictive Capacity ◽  
Term Forecast

AbstractForecasting of COVID-19 daily confirmed cases has been one of the several challenges posed on the governments and health sectors on a global scale. To facilitate informed public health decisions, the concerned parties rely on short-term daily projections generated via predictive modeling. We calibrate stochastic variants of growth models and the standard SIR model into one Bayesian framework to evaluate their short-term forecasts. In summary, it was noted that none of the models proved to be golden standards across all the regions in their entirety, while all outperformed ARIMA in a predictive capacity as well as in terms of interpretability.

Low-voltage EDS of magnesium ferrite Dendrites in a FEG-SEM

1996 ◽  
Vol 54 ◽  
pp. 478-479
Author(s):  
Matthew T. Johnson ◽  
Ian M. Anderson ◽  
Jim Bentley ◽  
C. Barry Carter
Keyword(s):  
Monte Carlo ◽  
Quantitative Analysis ◽  
Monte Carlo Simulations ◽  
Cross Section ◽  
Spatial Resolution ◽  
Low Voltage ◽  
Magnesium Ferrite ◽  
X Ray ◽  
Interaction Volume ◽  
Ferrite Spinel

Energy-dispersive X-ray spectrometry (EDS) performed at low (≤ 5 kV) accelerating voltages in the SEM has the potential for providing quantitative microanalytical information with a spatial resolution of ∼100 nm. In the present work, EDS analyses were performed on magnesium ferrite spinel [(MgxFe1−x)Fe2O4] dendrites embedded in a MgO matrix, as shown in Fig. 1. spatial resolution of X-ray microanalysis at conventional accelerating voltages is insufficient for the quantitative analysis of these dendrites, which have widths of the order of a few hundred nanometers, without deconvolution of contributions from the MgO matrix. However, Monte Carlo simulations indicate that the interaction volume for MgFe2O4 is ∼150 nm at 3 kV accelerating voltage and therefore sufficient to analyze the dendrites without matrix contributions.Single-crystal {001}-oriented MgO was reacted with hematite (Fe2O3) powder for 6 h at 1450°C in air and furnace cooled. The specimen was then cleaved to expose a clean cross-section suitable for microanalysis.

MONTE CARLO SIMULATIONS OF ELECTRON DRIFT VELOCITIES IN THE NOBLE GASES AND THEIR MIXTURES

1979 ◽  
Vol 40 (C7) ◽  
pp. C7-63-C7-64
Author(s):  
A. J. Davies ◽  
J. Dutton ◽  
C. J. Evans ◽  
A. Goodings ◽  
P.K. Stewart
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Noble Gases ◽  
Electron Drift
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