scholarly journals COVID-19 Outbreak: Model-Driven Impact Analysis Comparing Oman and Pakistan

2021 ◽  
pp. 38-54
Author(s):  
Kashif Zia ◽  
Umar Farooq ◽  
Muhammad Shafi
Keyword(s):  
Impact Analysis ◽  
Epidemic Spread ◽  
Real Numbers ◽  
Model Driven ◽  
Mobility Data ◽  
Testing Strategies ◽  
Spread Model ◽  
Rapid Spread ◽  
Simulation Results ◽  
Expected Outcomes

Motivated by the rapid spread of COVID-19 all across the globe, we haveperformed simulations of a system dynamic epidemic spread model in differentpossible situations. The simulation, not only captures the model dynamic of thespread of the virus, but also, takes care of population and mobility data. Themodel is calibrated based on epidemic data and events as they happened. Thesimulation results are quite disturbing, indicating that, during a process of stringent social distancing and testing strategies, a small perturbation can lead toquite undesirable outcomes. The simulation results, although consistent in expected outcomes across changing parameters’ values, also indicate a substantialmismatch with real numbers. An analysis of what can be the reason of this mismatch is also performed. Within these contradictions, a comparative analysisof COVID-19 outbreak between two geographically close but demographicallyvery different countries – that is Oman and Pakistan – is performed.

scholarly journals COVID-19 Outbreak in Oman: Model-Driven Impact Analysis and Challenges

2020 ◽  
Author(s):  
Kashif Zia ◽  
Umar Farooq
Keyword(s):  
Impact Analysis ◽  
Epidemic Spread ◽  
Sultanate Of Oman ◽  
Real Numbers ◽  
Model Driven ◽  
Mobility Data ◽  
Testing Strategies ◽  
Spread Model ◽  
Rapid Spread ◽  
Simulation Results

AbstractMotivated by the rapid spread of COVID-19 all across the globe, we have performed simulations of a system dynamic epidemic spread model in different possible situations. The simulation, not only captures the model dynamic of the spread of the virus, but also, takes care of population and mobility data. The model is calibrated based on epidemic data and events specifically of Sultanate of Oman, which can easily be generalized. The simulation results are quite disturbing, indicating that, during a process of stringent social distancing and testing strategies, a small perturbation can lead to quite undesirable outcomes. The simulation results, although consistent in expected outcomes across changing parameters’ values, also indicate a substantial mismatch with real numbers. An analysis of what can be the reason of this mismatch is also performed. Within these contradictions, for Oman, regarding the eradication of epidemic, the future is not extremely alarming.

scholarly journals Observing the silent world under COVID-19 with a comprehensive impact analysis based on human mobility

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shaobin Wang ◽  
Yun Tong ◽  
Yupeng Fan ◽  
Haimeng Liu ◽  
Jun Wu ◽  
...  
Keyword(s):  
Impact Analysis ◽  
Human Mobility ◽  
Economic Activities ◽  
Underdeveloped Countries ◽  
Mobility Data ◽  
Long Run ◽  
Level Of Economic Development ◽  
Human World ◽  
Dynamic Relationships ◽  
The Impact

AbstractSince spring 2020, the human world seems to be exceptionally silent due to mobility reduction caused by the COVID-19 pandemic. To better measure the real-time decline of human mobility and changes in socio-economic activities in a timely manner, we constructed a silent index (SI) based on Google’s mobility data. We systematically investigated the relations between SI, new COVID-19 cases, government policy, and the level of economic development. Results showed a drastic impact of the COVID-19 pandemic on increasing SI. The impact of COVID-19 on human mobility varied significantly by country and place. Bi-directional dynamic relationships between SI and the new COVID-19 cases were detected, with a lagging period of one to two weeks. The travel restriction and social policies could immediately affect SI in one week; however, could not effectively sustain in the long run. SI may reflect the disturbing impact of disasters or catastrophic events on the activities related to the global or national economy. Underdeveloped countries are more affected by the COVID-19 pandemic.

The Impact Analysis of Revolute Pair Clearance to the End Pose Accuracy of Welding Robot

2015 ◽  
Vol 778 ◽  
pp. 259-263
Author(s):  
Fa Jun Zhang ◽  
Lin Zi Li ◽  
Hui Lin ◽  
Yin Lin Pu ◽  
Zhu Xin
Keyword(s):  
Mathematical Model ◽  
Impact Analysis ◽  
Joint Clearance ◽  
Welding Robot ◽  
Movement Characteristic ◽  
Movement Stability ◽  
Simulation Results ◽  
The Impact ◽  
The Mathematical Model ◽  
Welding Position

Various uncertain factors affect the movement of the welding robot, thus welding gun tend to deviate from the theory of welding position which reduces the welding accuracy, of which the revolute pair clearance have an greater effect on the movement of the welding robot. In order to study the influence of revolute pair clearance to the end pose accuracy of welding robot, the mathematical model of revolute pair clearance was established, and the software SolidWorks was used for establishing the welding robot model, making simulations of the mechanical arm with joint clearance and no joint clearance. At last, the movement characteristic of the hinge shaft is attained. The simulation results showed that the shaft velocity and displacement of mechanical arm with joint clearance has a certain degree of fluctuation, which affecting the end pose accuracy of welding robot , and reducing the movement stability and the welding accuracy of welding robot.

scholarly journals Comparison and analysis of calculation of Bridge backwater based on Mike21 hydrodynamic model

2021 ◽  
Vol 233 ◽  
pp. 03043
Author(s):  
Jiang Chuan Liu ◽  
Zhu Qiu Hu ◽  
Mao Yuan Zhu
Keyword(s):  
Theoretical Basis ◽  
Impact Analysis ◽  
Navier Stokes ◽  
Efficiency Coefficient ◽  
Navier Stokes Equation ◽  
The Real ◽  
Comparison And Analysis ◽  
Simulation Results ◽  
The Difference ◽  
Local Water

The construction of bridges and other structures across the river will affect the flood discharge capacity and local water potential of the river.Based on navier-Stokes equation of MIKE21FM hydrodynamic module, this paper carries out two-dimensional numerical simulation of part of Shixi River. By optimizing the grid near the piers to reduce the difference brought by the terrain generalized grid of the real river, it simulates and analyzes the length of the curve of yong-high and Yong-water under different flood frequencies,the Nash-Sutcliffe efficiency coefficient and relative error analysis are used to verify the rationality of the results. The simulation results can accurately reflect the real changes of river water level, It provides a theoretical basis for flood impact analysis.

scholarly journals Modeling quarantine during epidemics and mass-testing using drones

2020 ◽  
Author(s):  
Leonid Sedov ◽  
Alexander Krasnochub ◽  
Valentin Polishchuk
Keyword(s):  
Differential Equations ◽  
Metropolitan Area ◽  
Extended Model ◽  
Epidemic Spread ◽  
Infected People ◽  
Peak Number ◽  
Infected Population ◽  
Sir Epidemic ◽  
Spread Model ◽  
Over Time

We extend the classical SIR epidemic spread model by introducing the “quarantined” compartment. We solve (numerically) the differential equations that govern the extended model and quantify how quarantining “flattens the curve” for the proportion of infected population over time. Furthermore, we explore the potential of using drones to deliver tests, enabling mass-testing for the infection; we give a method to estimate the drone fleet needed to deliver the tests in a metropolitan area. Application of our models to COVID-19 spread in Sweden shows how the proposed methods could substantially decrease the peak number of infected people, almost without increasing the duration of the epidemic.

MoDSEL

2012 ◽  
pp. 572-594
Author(s):  
Ersin Er ◽  
Bedir Tekinerdogan
Keyword(s):  
Software Development ◽  
Impact Analysis ◽  
Software Evolution ◽  
Academic Research ◽  
Model Driven ◽  
Model Driven Software Development ◽  
Basic Concepts ◽  
The Impact ◽  
Development And Evolution

Model-Driven Software Development (MDSD) aims to support the development and evolution of software intensive systems using the basic concepts of model, metamodel, and model transformation. In parallel with the ongoing academic research, MDSD is more and more applied in industrial practices. Like conventional non-MDSD practices, MDSD systems are also subject to changing requirements and have to cope with evolution. In this chapter, the authors provide a scenario-based approach for documenting and analyzing the impact of changes that apply to model-driven development systems. To model the composition and evolution of an MDSD system, they developed the so-called Model-Driven Software Evolution Language (MoDSEL) which is based on a megamodel for MDSD. MoDSEL includes explicit language abstractions to specify both the model elements of an MDSD system and the evolution scenarios that might apply to model elements. Based on MoDSEL specifications, an impact analysis is performed to assess the impact of evolution scenarios and the sensitivity of model elements. A case study is provided to show different kind of evolution scenarios and the required adaptations to model elements.

scholarly journals Optimal COVID-19 quarantine and testing strategies

2020 ◽  
Author(s):  
Chad R. Wells ◽  
Jeffrey P. Townsend ◽  
Abhishek Pandey ◽  
Seyed M. Moghadas ◽  
Gary Krieger ◽  
...  
Keyword(s):  
Public Health ◽  
Contact Tracing ◽  
Successful Outcome ◽  
Entry And Exit ◽  
Prolonged Stay ◽  
Molecular Tests ◽  
Testing Strategies ◽  
Rapid Spread ◽  
Oil Rig ◽  
Offshore Oil

AbstractAs economic woes of the COVID-19 pandemic deepen, strategies are being formulated to avoid the need for prolonged stay-at-home orders, while implementing risk-based quarantine, testing, contact tracing and surveillance protocols. Given limited resources and the significant economic, public health, and operational challenges of the current 14-day quarantine recommendation, it is vital to understand if shorter but equally effective quarantine and testing strategies can be deployed. To quantify the probability of post-quarantine transmission upon isolation of a positive test, we developed a mathematical model in which we varied quarantine duration and the timing of molecular tests for three scenarios of entry into quarantine. Specifically, we consider travel quarantine, quarantine of traced contacts with an unknown time if infection, and quarantine of cases with a known time of exposure. With a one-day delay between test and result, we found that testing on exit (or entry and exit) can reduce the duration of a 14-day quarantine by 50%, while testing on entry shortened quarantine by at most one day. Testing on exit more effectively reduces post-quarantine transmission than testing upon entry. Furthermore, we identified the optimal testing date within quarantines of varying duration, finding that testing on exit was most effective for quarantines lasting up to seven days. As a real-world validation of these principles, we analyzed the results of 4,040 SARS CoV-2 RT-PCR tests administered to offshore oil rig employees. Among the 47 positives obtained with a testing on entry and exit strategy, 16 cases that previously tested negative at entry were identified, with no further cases detected among employees following quarantine exit. Moreover, this strategy successfully prevented an expected nine offshore transmission events stemming from cases who had tested negative on the entry test, each one a serious concern for initiating rapid spread and a disabling outbreak in the close quarters of an offshore rig. This successful outcome highlights that appropriately timed testing can make shorter quarantines more effective, thereby minimizing economic impacts, disruptions to operational integrity, and COVID-related public health risks.

scholarly journals Disentangling Increased Testing from Covid-19 Epidemic Spread

2020 ◽  
Author(s):  
Benjamin Lengerich ◽  
Willie Neiswanger ◽  
Eugene J. Lengerich ◽  
Eric P. Xing
Keyword(s):  
United States ◽  
Health Risks ◽  
Control Strategies ◽  
The United States ◽  
Test Results ◽  
Epidemic Spread ◽  
Public Health Risks ◽  
Testing Strategies ◽  
Limited Testing ◽  
Virus Testing

AbstractTo design effective disease control strategies, it is critical to understand the incidence of diseases. In the Covid-19 epidemic in the United States (caused by outbreak of the SARS-CoV-2 virus), testing capacity was initially very limited and has been increasing at the same time as the virus has been spreading. When estimating the incidence, it can be difficult to distinguish whether increased numbers of positive tests stem from increases in the spread of the virus or increases in testing. This has made it very difficult to identify locations in which the epidemic poses the largest public health risks. Here, we use a probabilistic model to quantify beliefs about testing strategies and understand implications regarding incidence. We apply this model to estimate the incidence in each state of the United States, and find that: (1) the Covid-19 epidemic is likely to be more widespread than reported by limited testing, (2) the Covid-19 epidemic growth in the summer months is likely smaller than it was during the spring months, and (3) the regions which are at highest risk of Covid-19 epidemic outbreaks are not always those with the largest number of positive test results.

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