scholarly journals New coronavirus outbreak. Lessons learned from the severe acute respiratory syndrome epidemic

2015 ◽  
Vol 143 (13) ◽  
pp. 2882-2893 ◽  
Author(s):  
E. ÁLVAREZ ◽  
J. DONADO-CAMPOS ◽  
F. MORILLA
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
System Dynamics ◽  
Iterative Process ◽  
Emerging Infectious Diseases ◽  
Real Data ◽  
Lessons Learned ◽  
Networked Systems ◽  
Sensitivity Analyses ◽  
Algebraic Equations ◽  
Auxiliary Variables

SUMMARYSystem dynamics approach offers great potential for addressing how intervention policies can affect the spread of emerging infectious diseases in complex and highly networked systems. Here, we develop a model that explains the severe acute respiratory syndrome coronavirus (SARS-CoV) epidemic that occurred in Hong Kong in 2003. The dynamic model developed with system dynamics methodology included 23 variables (five states, four flows, eight auxiliary variables, six parameters), five differential equations and 12 algebraic equations. The parameters were optimized following an iterative process of simulation to fit the real data from the epidemics. Univariate and multivariate sensitivity analyses were performed to determine the reliability of the model. In addition, we discuss how further testing using this model can inform community interventions to reduce the risk in current and future outbreaks, such as the recently Middle East respiratory syndrome coronavirus (MERS-CoV) epidemic.

scholarly journals Innovation and Challenges in Funding Rapid Research Responses to Emerging Infectious Diseases: Lessons Learned from the Outbreak of Severe Acute Respiratory Syndrome

2004 ◽  
Vol 15 (3) ◽  
pp. 167-170 ◽  
Author(s):  
Bhagirath Singh
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Infectious Diseases ◽  
Health Research ◽  
Research Effort ◽  
Rapid Development ◽  
Emerging Infectious Diseases ◽  
Lessons Learned ◽  
Public Health Response ◽  
Local Public Health ◽  
National Network

Although the local public health response to the severe acute respiratory syndrome outbreak in Canada was critical to the diagnosis, management and treatment of patients, such a rapid research response required a national effort to engage the research and stakeholder communities. The Canadian research effort, coordinated through the Institute of Infection and Immunity of the Canadian Institutes of Health Research and the Michael Smith Foundation for Health Research, has provided insight into the mechanisms required to ensure the rapid development of strategical initiatives in response to emerging infectious diseases. It has also provided a rational basis to set up a national network to be engaged if needed in the future.

THE DEVELOPMENT OF THE MATHEMATICAL MODEL OF PREDICTING THE INDICATORS OF ACCREDITATION OF TECHNICAL UNIVERSITIES IN THE RUSSIAN FEDERATION

2017 ◽  
pp. 27-38
Author(s):  
Olga Mikhaylovna Tikhonova ◽  
Alexander Fedorovich Rezchikov ◽  
Vladimir Andreevich Ivashchenko ◽  
Vadim Alekseevich Kushnikov
Keyword(s):  
Mathematical Model ◽  
System Dynamics ◽  
Regression Model ◽  
Oriented Graph ◽  
Real Data ◽  
Educational Process ◽  
Proposed Model ◽  
Linear Differential ◽  
The University ◽  
The Mathematical Model

The paper presents the system of predicting the indicators of accreditation of technical universities based on J. Forrester mechanism of system dynamics. According to analysis of cause-and-effect relationships between selected variables of the system (indicators of accreditation of the university) there was built the oriented graph. The complex of mathematical models developed to control the quality of training engineers in Russian higher educational institutions is based on this graph. The article presents an algorithm for constructing a model using one of the simulated variables as an example. The model is a system of non-linear differential equations, the modelling characteristics of the educational process being determined according to the solution of this system. The proposed algorithm for calculating these indicators is based on the system dynamics model and the regression model. The mathematical model is constructed on the basis of the model of system dynamics, which is further tested for compliance with real data using the regression model. The regression model is built on the available statistical data accumulated during the period of the university's work. The proposed approach is aimed at solving complex problems of managing the educational process in universities. The structure of the proposed model repeats the structure of cause-effect relationships in the system, and also provides the person responsible for managing quality control with the ability to quickly and adequately assess the performance of the system.

Bats as the reservoir for outbreaks of emerging infectious diseases

2005 ◽  
Vol 10 (45) ◽  
Author(s):  
C J Williams
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Infectious Diseases ◽  
Emerging Infectious Diseases ◽  
Natural Reservoir

A study from China has provided evidence that bats may be the natural reservoir for severe acute respiratory syndrome coronavirus (SARS-CoV)

scholarly journals Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations

2021 ◽  
Author(s):  
Fernando Pires Hartwig ◽  
Kate Tilling ◽  
George Davey Smith ◽  
Deborah A Lawlor ◽  
Maria Carolina Borges
Keyword(s):  
Waist Circumference ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Real Data ◽  
Sensitivity Analyses ◽  
Effect Estimate ◽  
Genome Wide Association Studies ◽  
Residual Confounding

Abstract Background Two-sample Mendelian randomization (MR) allows the use of freely accessible summary association results from genome-wide association studies (GWAS) to estimate causal effects of modifiable exposures on outcomes. Some GWAS adjust for heritable covariables in an attempt to estimate direct effects of genetic variants on the trait of interest. One, both or neither of the exposure GWAS and outcome GWAS may have been adjusted for covariables. Methods We performed a simulation study comprising different scenarios that could motivate covariable adjustment in a GWAS and analysed real data to assess the influence of using covariable-adjusted summary association results in two-sample MR. Results In the absence of residual confounding between exposure and covariable, between exposure and outcome, and between covariable and outcome, using covariable-adjusted summary associations for two-sample MR eliminated bias due to horizontal pleiotropy. However, covariable adjustment led to bias in the presence of residual confounding (especially between the covariable and the outcome), even in the absence of horizontal pleiotropy (when the genetic variants would be valid instruments without covariable adjustment). In an analysis using real data from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and UK Biobank, the causal effect estimate of waist circumference on blood pressure changed direction upon adjustment of waist circumference for body mass index. Conclusions Our findings indicate that using covariable-adjusted summary associations in MR should generally be avoided. When that is not possible, careful consideration of the causal relationships underlying the data (including potentially unmeasured confounders) is required to direct sensitivity analyses and interpret results with appropriate caution.

scholarly journals Pandemic Prevention: Lessons from COVID-19

Encyclopedia ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 433-444
Author(s):  
Mario Coccia
Keyword(s):  
Severe Acute Respiratory Syndrome ◽  
Infectious Diseases ◽  
Health System ◽  
Negative Impact ◽  
Lessons Learned ◽  
The Novel ◽  
Policy Responses

Coronavirus disease 2019 (COVID-19) is caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which appeared in late 2019, generating a pandemic crisis with high numbers of COVID-19-related infected individuals and deaths in manifold countries worldwide. Lessons learned from COVID-19 can be used to prevent pandemic threats by designing strategies to support different policy responses, not limited to the health system, directed to reduce the risks of the emergence of novel viral agents, the diffusion of infectious diseases and negative impact in society.

The laminar boundary-layer equation: a method of solution by means of an automatic computer

1955 ◽  
Vol 51 (2) ◽  
pp. 320-332 ◽  
Author(s):  
D. C. F. Leigh
Keyword(s):  
Boundary Layer ◽  
Asymptotic Solution ◽  
Laminar Boundary Layer ◽  
Iterative Process ◽  
Boundary Layer Equation ◽  
Algebraic Equations ◽  
Automatic Computer ◽  
Linear Algebraic Equations ◽  
Method Of Solution ◽  
Incompressible Boundary

ABSTRACTA method, very suitable for use with an automatic computer, of solving the Hartree-Womersley approximation to the incompressible boundary-layer equation is developed. It is based on an iterative process and the Choleski method of solving a simultaneous set of linear algebraic equations. The programming of this method for an automatic computer is discussed. Tables of a solution of the boundary-layer equation in a region upstream of the separation point are given. In the upstream neighbourhood of separation this solution is compared with Goldstein's asymptotic solution and the agreement is good.

scholarly journals A System Dynamics Model of Online Stores’ Sales: Positive and Negative E-WOM and Promotion Perspective

2019 ◽  
Vol 11 (21) ◽  
pp. 6045 ◽  
Author(s):  
Qiang Yan ◽  
Simin Zhou ◽  
Xiaoyan Zhang ◽  
Ye Li
Keyword(s):  
System Dynamics ◽  
Real Data ◽  
System Dynamics Model ◽  
Dynamics Model ◽  
Sustainable Operations ◽  
Main Research ◽  
Interaction Diagram ◽  
Online Stores ◽  
The Impact

In this paper, we build a causal interaction diagram between the factors that may influence the sales and profits of online stores. An online store’s real operation data were used to help determine the causal relationship between variables. Finally, we proposed a system dynamics model and conducted a simulation of the operation of an online store. In this model, we focused on the impact of promotion and positive/negative electronic word of mouth (e-WOM) on the sales and profits of the online stores. The simulation results showed a similar trend to the real data and the main research finding showed that promotion is not a long-term measure for the sustainable development of online stores. Excessive promotion effort may lead to consumers’ dissatisfaction leading the increase of negative e-WOM. The systematic simulation can help us understand better the long-term effect of promotion and e-WOM on the operation of online stores. Finally, we gave some management suggestions for online stores’ sustainable operations.

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