scholarly journals Analysis and Prediction of COVID-19 Outbreak by the Numerical Modelling 

2020 ◽  
Author(s):  
Dilshad Azad Mohammed ◽  
Hassan Mohammad Tawfeeq ◽  
Kameran Mohammed Ali ◽  
Hassan Muhammad Rostam
Keyword(s):  
Nonlinear Differential Equations ◽  
Least Square Method ◽  
Analysis Data ◽  
Least Square ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Kurdistan Region ◽  
Runge Kutta Method ◽  
Maximum Value ◽  
Daily Data

Abstract Pandemic COVID-19 is a contagious disease affecting more than 200 countries, territories and regions. Recently, Iraq is one of the countries that has immensely suffered with this outbreak. The Kurdistan Region of Iraq (KRI) is also prone to the disease. Until now more than 23,000 confirmed cases have been recorded in the region. Since the onset of the COVID-19 in Wuhan, based on epidemiological modelling, researchers have used various models to predict the future of the epidemic and the time of peak, yielding a diverse number in different countries. This study aims to estimate the basic reproductive number (R0) for COVID-19 in KRI, using the standard SIR (Susceptible-Infected-Removed) epidemic model. A system of nonlinear differential equations is formulated and solved numerically by the 4th order Runge-Kutta method. Reproductive numbers R0 have been estimated by this method of fitting the curves between the actual daily data and numerical solution by applying the least square method. For the analysis, data were taken for the duration of 165 days from 1st of March to 12th August in a population of 5.2 million. It has been concluded that R0 is fluctuating during the outbreak with an average of 1.33, predicting that infected cases will reach their maximum value of around 540,000 on 5th of November 2020. Then the spread of the disease will die out since the number of susceptible will decrease to about 3.2 million. While the number of removed individuals will reach approximately to 1.5 million.

scholarly journals Analysis and Prediction of COVID-19 Outbreak by the Numerical Modelling 

2020 ◽  
Author(s):  
Dilshad Azad Mohammed ◽  
Hassan Mohammad Tawfeeq ◽  
Kameran Mohammed Ali ◽  
Hassan Muhammad Rostam
Keyword(s):  
Nonlinear Differential Equations ◽  
Least Square Method ◽  
Analysis Data ◽  
Least Square ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Kurdistan Region ◽  
Runge Kutta Method ◽  
Maximum Value ◽  
Daily Data

Abstract Pandemic COVID-19 is a contagious disease affecting more than 200 countries, territories and regions. Recently, Iraq is one of the countries that has immensely suffered with this outbreak. The Kurdistan Region of Iraq (KRI) is also prone to the disease. Until now more than 23,000 confirmed cases have been recorded in the region. Since the onset of the COVID-19 in Wuhan, based on epidemiological modelling, researchers have used various models to predict the future of the epidemic and the time of peak, yielding a diverse number in different countries. This study aims to estimate the basic reproductive number (R0) for COVID-19 in KRI, using the standard SIR (Susceptible-Infected-Removed) epidemic model. A system of nonlinear differential equations is formulated and solved numerically by the 4th order Runge-Kutta method. Reproductive numbers R0 have been estimated by this method of fitting the curves between the actual daily data and numerical solution by applying the least square method. For the analysis, data were taken for the duration of 165 days from 1st of March to 12th August in a population of 5.2 million. It has been concluded that R0 is fluctuating during the outbreak with an average of 1.33, predicting that infected cases will reach their maximum value of around 540,000 on 5th of November 2020. Then the spread of the disease will die out since the number of susceptible will decrease to about 3.2 million. While the number of removed individuals will reach approximately to 1.5 million.

scholarly journals Analysis and Prediction of COVID-19 Outbreak by a Numerical Modelling

2021 ◽  
pp. 1452-1459
Author(s):  
Dilshad Azad Mohammed ◽  
Hassan Mohammad Tawfeeq ◽  
Kameran Mohammed Ali ◽  
Hassan Muhammad Rostam
Keyword(s):  
Nonlinear Differential Equations ◽  
Least Square Method ◽  
Analysis Data ◽  
Least Square ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Kurdistan Region ◽  
Runge Kutta Method ◽  
Maximum Value ◽  
Daily Data

Pandemic COVID-19 is a contagious disease affecting more than 200 countries, territories, and regions. Recently, Iraq is one of the countries that have immensely suffered from this outbreak. The Kurdistan Region of Iraq (KRI) is also prone to the disease. Until now, more than 23,000 confirmed cases have been recorded in the region. Since the onset of the COVID-19 in Wuhan, based on epidemiological modelling, researchers have used various models to predict the future of the epidemic and the time of peak, yielding diverse numbers in different countries. This study aims to estimate the basic reproductive number [R0] for COVID-19 in KRI, using the standard SIR (Susceptible-Infected-Removed) epidemic model. A system of nonlinear differential equations was formulated and solved numerically by the 4th order Runge-Kutta method. The reproductive numbers R0 was estimated by the method of fitting the curves between the actual daily data and numerical solution by applying the least square method. For the analysis, data were taken for the duration of 165 days, from 1st of March to 12th August 2020, in a population of 5.2 million. It is concluded that the R0 value was fluctuating during the outbreak, with an average of 1.33, predicting that infection cases will reach their maximum value of around 540,000 on the 5th of November 2020. Then, the spread of the disease will die out since the number of susceptible people will decrease to about 3.2 million. While the number of removed individuals will reach approximately to 1.5 million.

scholarly journals Impact of Awareness to Control Malaria Disease: A Mathematical Modeling Approach

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Malik Muhammad Ibrahim ◽  
Muhammad Ahmad Kamran ◽  
Malik Muhammad Naeem Mannan ◽  
Sangil Kim ◽  
Il Hyo Jung
Keyword(s):  
Mathematical Modeling ◽  
Numerical Technique ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Awareness Campaign ◽  
Runge Kutta Method ◽  
Proposed Model ◽  
Awareness Programs ◽  
Disease Free ◽  
Differential Process

The mathematical modeling of malaria disease has a crucial role in understanding the insights of the transmission dynamics and corresponding appropriate prevention strategies. In this study, a novel nonlinear mathematical model for malaria disease has been proposed. To prevent the disease, we divided the infected population into two groups, unaware and aware infected individuals. The growth rate of awareness programs impacting the population is assumed to be proportional to the unaware infected individuals. It is further assumed that, due to the effect of awareness campaign, the aware infected individuals avoid contact with mosquitoes. The positivity and the boundedness of solutions have been derived through the completing differential process. Local and global stability analysis of disease-free equilibrium has been investigated via basic reproductive number R0, if R0 < 1, the system is stable otherwise unstable. The existence of the unique endemic equilibrium has been also determined under certain conditions. The solution to the proposed model is derived through an iterative numerical technique, the Runge–Kutta method. The proposed model is simulated for different numeric values of the population of humans and anopheles in each class. The results show that a significant increase in the population of susceptible humans is achieved in addition to the decrease in the population of the infected mosquitoes.

scholarly journals Potential role of particulate matter in the spreading of COVID-19 in Northern Italy: first observational study based on initial epidemic diffusion

BMJ Open ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. e039338 ◽  
Author(s):  
Leonardo Setti ◽  
Fabrizio Passarini ◽  
Gianluigi De Gennaro ◽  
Pierluigi Barbieri ◽  
Sabina Licen ◽  
...  
Keyword(s):  
Close Contact ◽  
Population Data ◽  
Northern Italy ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Average Growth ◽  
Limit Value ◽  
Daily Data ◽  
Italian Provinces ◽  
Lag Period

ObjectivesA number of studies have shown that the airborne transmission route could spread some viruses over a distance of 2 meters from an infected person. An epidemic model based only on respiratory droplets and close contact could not fully explain the regional differences in the spread of COVID-19 in Italy. On March 16th 2020, we presented a position paper proposing a research hypothesis concerning the association between higher mortality rates due to COVID-19 observed in Northern Italy and average concentrations of PM10 exceeding a daily limit of 50 µg/m3.MethodsTo monitor the spreading of COVID-19 in Italy from February 24th to March 13th (the date of the Italian lockdown), official daily data for PM10 levels were collected from all Italian provinces between February 9th and February 29th, taking into account the maximum lag period (14 days) between the infection and diagnosis. In addition to the number of exceedances of the daily limit value of PM10, we also considered population data and daily travelling information for each province.ResultsExceedance of the daily limit value of PM10 appears to be a significant predictor of infection in univariate analyses (p<0.001). Less polluted provinces had a median of 0.03 infections over 1000 residents, while the most polluted provinces showed a median of 0.26 cases. Thirty-nine out of 41 Northern Italian provinces resulted in the category with the highest PM10 levels, while 62 out of 66 Southern provinces presented low PM10 concentrations (p<0.001). In Milan, the average growth rate before the lockdown was significantly higher than in Rome (0.34 vs 0.27 per day, with a doubling time of 2.0 days vs 2.6, respectively), thus suggesting a basic reproductive number R0>6.0, comparable with the highest values estimated for China.ConclusionA significant association has been found between the geographical distribution of daily PM10 exceedances and the initial spreading of COVID-19 in the 110 Italian provinces.

scholarly journals ANALISIS PASANG SURUT MENGGUNAKAN METODE LEAST SQUARE DI WILAYAH PERAIRAN ENDE, NUSA TENGGARA TIMUR

2019 ◽  
Vol 4 (1) ◽  
pp. 1-7
Author(s):  
Celiana F. J. P. Soares ◽  
Abdul Wahid ◽  
Jehunias L. Tanesib
Keyword(s):  
Mixed Type ◽  
Least Square Method ◽  
Analysis Data ◽  
Least Square ◽  
Tidal Component ◽  
Dominant Component ◽  
Tidal Harmonics ◽  
Tidal Harmonic ◽  
Harmonic Components ◽  
Sea Area

Abstrak Telah dilakukan penelitian tentang analisis pasang surut menggunakan metode Least Square di wilayah perairan Ende, Nusa Tenggara Timur. Penelitian ini bertujuan untuk menentukan komponen harmonik pasang surut menggunakan metode Least Square serta menganalisis tipe pasang surut menggunakan bilangan Formzahl. Berdasarkan hasil analisis data, diketahui bahwa komponen pasang surut yaitu M2, S2, N2, K1, O1, Q1 dan tipe pasang surut di perairan Ende termasuk tipe campuran condong keharian ganda (mixed tide prevailing semidiurnal) dengan nilai Formzhal (F) setiap bulannya adalah (0,38), (0,31), (0,25), (0,28), (0,38), (0,44), (0,41), (0,33), (0,25), (0,27) (0,35) dan 0,42. Hasil analisis pasang surut menunjukkan nilai amplitudo harmonik pasang surut ganda utama M2 dan S2 lebih dominan dibandingkan komponen pasang surut tunggal utama K1 dan O1.  Kata Kunci: Least Square, Campuran Condong Harian Ganda, Perairan Ende.  Abstract Research on tidal analysis has been done using the Least Square method in the sea area surrounding Ende, East Nusa Tenggara. This research aims to determine the components of tidal harmonics using the Least Square method and to analyze the type of tides using Formzhal number. Based on the results of analysis data, it is known that tidal harmonic components are M2, S2, N2, K1, O1, Q1 and the type of tides in Ende sea included mixed type of tide prevailing semidiurnal with Formzhal (F) value of (0.38), (0.31), (0.25), (0.28), (0.38), (0.44), (0.41), (0.33), (0.25), (0.27), (0.35), and 0.42. The results show the amplitude of the main tidal component M2 and S2 is the dominant component in the Ende Sea compared to the main single tidal component K1 and O1.  Keywords: Least Square, Mixed Tide Prevailing Semidiurnal, Ende Sea.

Correlation analysis of noise sound pressure and vibration in aluminum alloy milling

2020 ◽  
pp. 107754632097597
Author(s):  
Yuting Hu ◽  
Shuncai Li ◽  
Xing Deng ◽  
Slatin Vadim
Keyword(s):  
Aluminum Alloy ◽  
Regression Models ◽  
Least Square Method ◽  
Least Square ◽  
Noise And Vibration ◽  
Milling Parameters ◽  
Maximum Value ◽  
Multiple Regression Models ◽  
Control Equation ◽  
Milling Vibration

To study the correlation between noise and vibration during dry milling of aluminum alloy, a synchronous acquisition system of noise and vibration was established. Based on the experimental data, the effects of three milling parameters on milling noise and milling vibration were analyzed. Based on the least square method and MATLAB software programming, the multiple regression models of milling noise on milling parameters and milling vibration were established. According to the regression models, it is found that there is a strong correlation between milling noise, milling parameters, and milling vibration. The maximum value of the correlation coefficient R is 0.98. It also shows that the regression models based on milling parameters and milling vibration can well predict the noise of aluminum alloy during milling. In addition, the obtained model can provide a control equation for the future coupling analysis of vibration and noise and for the numerical simulation.

scholarly journals Impact of Intangible Characteristics of Universities on Student Satisfaction

2020 ◽  
Vol 9 (26) ◽  
pp. 105-116
Author(s):  
Noor Us Sabbah Khan ◽  
Yunus Yildiz
Keyword(s):  
Student Satisfaction ◽  
Least Square Method ◽  
Partial Least Square ◽  
Least Square ◽  
Social Activities ◽  
Kurdistan Region ◽  
Public And Private ◽  
Career Opportunities ◽  
Partial Least Square Method ◽  
The Impact

The aim of this research was to investigate the impact of the intangible qualities of the universities on student satisfaction. To do this, we have collected data from 7 different major public and private universities of the Kurdistan Region of Iraq. We have used 170 data to proposed further analysis. The partial least square method (PLS) was used to test the hypothesis. The results reveal that career opportunities and a friendly atmosphere are the main two elements that foster the reputation of the universities. The second interesting result of this research is that social activities impact the reputation of universities but not the friendly atmosphere while social activities impact a friendly atmosphere but not the reputation significantly. Finally, we have suggested the implications to the practitioners in the region.

scholarly journals Nonlinear Finite Element Analysis of Sloshing

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Siva Srinivas Kolukula ◽  
P. Chellapandi
Keyword(s):  
Finite Element ◽  
Free Surface ◽  
External Disturbance ◽  
Least Square Method ◽  
Wave Theory ◽  
Least Square ◽  
Element Analysis ◽  
Runge Kutta Method ◽  
Nonlinear Potential ◽  
Numerical Instabilities

The disturbance on the free surface of the liquid when the liquid-filled tanks are excited is called sloshing. This paper examines the nonlinear sloshing response of the liquid free surface in partially filled two-dimensional rectangular tanks using finite element method. The liquid is assumed to be inviscid, irrotational, and incompressible; fully nonlinear potential wave theory is considered and mixed Eulerian-Lagrangian scheme is adopted. The velocities are obtained from potential using least square method for accurate evaluation. The fourth-order Runge-Kutta method is employed to advance the solution in time. A regridding technique based on cubic spline is employed to avoid numerical instabilities. Regular harmonic excitations and random excitations are used as the external disturbance to the container. The results obtained are compared with published results to validate the numerical method developed.

Direct Assessment of Effective Renal Plasma Flow from Renoscintigraphy with a Gamma Camera and an On-Line Computer

1981 ◽  
Vol 20 (06) ◽  
pp. 274-278
Author(s):  
J. Liniecki ◽  
J. Bialobrzeski ◽  
Ewa Mlodkowska ◽  
M. J. Surma
Keyword(s):  
Count Rate ◽  
Renal Plasma Flow ◽  
Early Period ◽  
Least Square Method ◽  
Least Square ◽  
Uptake Coefficient ◽  
Positive Linear Correlation ◽  
On Line ◽  
Best Fit ◽  
Plasma Activity

A concept of a kidney uptake coefficient (UC) of 131I-o-hippurate was developed by analogy from the corresponding kidney clearance of blood plasma in the early period after injection of the hippurate. The UC for each kidney was defined as the count-rate over its ROI at a time shorter than the peak in the renoscintigraphic curve divided by the integral of the count-rate curve over the "blood"-ROI. A procedure for normalization of both curves against each other was also developed. The total kidney clearance of the hippurate was determined from the function of plasma activity concentration vs. time after a single injection; the determinations were made at 5, 10, 15, 20, 30, 45, 60, 75 and 90 min after intravenous administration of 131I-o-hippurate and the best-fit curve was obtained by means of the least-square method. When the UC was related to the absolute value of the clearance a positive linear correlation was found (r = 0.922, ρ > 0.99). Using this regression equation the clearance could be estimated in reverse from the uptake coefficient calculated solely on the basis of the renoscintigraphic curves without blood sampling. The errors of the estimate are compatible with the requirement of a fast appraisal of renal function for purposes of clinical diagknosis.

Sign in / Sign up

Export Citation Format

Share Document