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Tugas Pemodelan Transportasi Laut

Memodelkan persebaran pandemik covid-19 menggunakan insightmaker

Dosen pembimbing : Dr-Ing Ir. Setyo Nugroho
Pandemic Covid-19 Simulation
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covid 19 in china 1
4 2 weeks ago
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From Yuan Tian's 2024 paper Early COVID-19 Pandemic Preparedness: Informing Public Health Interventions and Hospital Capacity Planning Through Participatory Hybrid Simulation Modeling and  PhD Dissertation 2025 USask Fig 5.1 p96 
Hybrid model of early Covid-19
7 months ago
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COVID-19 Model of Puerto Princesa City as of May 19,2023.
COVID-19 Model of Puerto Princesa City
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2бөлім 1 тапсырма
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A sample model for class discussion modeling COVID-19 outbreaks and responses from government with the effect on the local economy.  Govt policy is dependent on reported COVID-19 cases, which in turn depend on testing rates less those who recover

Assumptions
Govt policy reduces infection and economic growth in the same way.

Govt policy is trigger when reported COVID-19 case are 10 or less.

A greater number of COVID-19 cases has a negative effect on the economy.  This is due to economic signalling that all is not well.

Interesting insights

Higher testing rates seem to trigger more rapid government intervention, which reduces infectious cases.  The impact on the economy though of higher detected cases though is negative. 




Clone of Burnie COVID-19 outbreak demo model version 2
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This stock-flow simulation model is to show Covid-19 virus spread rate, sources of spreading and safety measures followed by all the countries affected around the world.
The simulation also aims at predicting for how much more period of time the virus will persist, how many people could recover at what kind of rate and also about the virus toughness dependence based on its excessive speed, giving rise to bigger numbers day-by-day.
Week-12-Practice
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SEIR Model for COVID-19 in Italy
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Seminární práce
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2 өзіндік жұмыс
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COVID-19 outbreak model brief description

The model stimulated the COVID-19 outbreak at Burnie in Tasmania. The pandemic spread was driven by infection rate, death rate, recovery rate, and government policy.

The government policy reduces the infection in some way, but it also decreases the physical industry. Online industry plays a vital role during the pandemic and brings more opportunities to the world economy. 

The vaccination directly reduces the infection rate. The national border will open as long as residents have been fully vaccinated. 

Assumption: 
The model was created based on different rates, including infection rate, death rate, testing rate and recovered rate. There will be difference between the real cases and the model. 

The model only list five elements of government policies embracing vaccination rate, national border and state border restrictions, public health orders, and business restrictions. Public health order includes social distance and residents should wear masks in high spread regions. 

This model only consider two industries which are physical industry, like manufacturer, retailers, or hospitality industries, and online industry. During the pandemic, employees star to work from home and students can have online class. Therefore, the model consider the COVID-19 has positive impact on online industry. 

Interesting insights:
The susceptible will decrease dramatically in first two weeks due to high infection rate and low recovery rate and government policy. After that, the number of susceptible will have a slight decline. 

The death toll and recovery rate was increased significantly in the first two weeks due to insufficient healthy response. And the trend will become mild as government policy works. 



BMA708_DafeiMeng_567691_Model of COVID-19 Outbreak in Burnie, Tasmania
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Simulasi ini digunakan untuk memodelkan persebaran virus corona di Indonesia untuk kepentingan tugas kuliah
Simulasi Persebaran COVID-19 di Indonesia
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Disease Dynamics
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The Covid-19 pandemic has introduced a variety of novel and intense difficulties, from dealing with the production network for individual defensive gear (PPE) to changing labor force ability to adapting to monetary misfortune. Amidst these difficulties lies a chance for medical services pioneers to more readily position and change their associations for an eventual fate of unusual amazement. To oversee limit, monetary misfortune, and care overhaul, medical services associations have settled on the basic choice to deliver or lessen labor force or to move numerous representatives to far off work, incorporating clinicians working with telehealth advances. (www.catalyst.nejm.org)


Reference:
Begun, J.W. PhD, Jiang, J.H, PhD,. (2020, October 9). NEJM Catalyst/Innovations in Care Delivery. Health Care Management During Covid-19: Insights from Complexity Science. Retrieved from https://catalyst.nejm.org/doi/full/10.1056/CAT.20.0505

Covid-19 Health Care Complexities and Variables
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==edited by Prasiantoro Tusono and Rio Swarawan Putra==

Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.

With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.

We start with an SIR model, such as that featured in the MAA model featured in
https://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model

Without mortality, with time measured in days, with infection rate 1/2, recovery rate 1/3, and initial infectious population I_0=1.27x10-4, we reproduce their figure

With a death rate of .005 (one two-hundredth of the infected per day), an infectivity rate of 0.5, and a recovery rate of .145 or so (takes about a week to recover), we get some pretty significant losses -- about 3.2% of the total population.

Resources:
  1. http://www.nku.edu/~longa/classes/2020spring/mat375/mathematica/SIRModel-MAA.nb
  2. https://www.maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model
Coronavirus: A Simple SIR (Susceptible, Infected, Recovered) with death - based on Andrew E Long
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This model aims to show the outbreak and mitigation approach towards Covid-19  in the Philippines.
Ph_Covid19SDM_Frida Caye B. Taha
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Pada Tugas 3 mata kuliah Pemodelan Transportasi Laut, ditugaskan untuk membuat pemodelan penyebaran COVID-19 di negara yang dipilih, dan pada simulasi ini merupakan negara Indonesia

Dosen Pengampu : Dr.-Ing Ir Setyo Nugroho
Simulasi Pemodelan Penyebaran COVID-19 di Indonesia
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A Susceptible-Infected-Recovered (SIR) disease model with waning immunity

COVID-19 Delta Variant Spread Among Emory Students
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Collapse of the economy, not just recession, is now very likely. To give just one possible cause, in the U.S. the fracking industry is in deep trouble. It is not only that most fracking companies have never achieved a free cash flow (made a profit) since the fracking boom started in 2008, but that  an already very weak  and unprofitable oil industry cannot cope with extremely low oil prices. The result will be the imminent collapse of the industry. However, when the fracking industry collapses in the US, so will the American economy – and by extension, probably, the rest of the world economy. To grasp a second and far more serious threat it is vital to understand the phenomenon of ‘Global Dimming’. Industrial activity not only produces greenhouse gases, but emits also sulphur dioxide which converts to reflective sulphate aerosols in the atmosphere. Sulphate aerosols act like little mirrors that reflect sunlight back into space, cooling the atmosphere. But when economic activity stops, these aerosols (unlike carbon dioxide) drop out of the atmosphere, adding perhaps as much as 1° C to global average temperatures. This can happen in a very short period time, and when it does mankind will be bereft of any means to mitigate the furious onslaught of an out-of-control and merciless climate. The data and the unrelenting dynamic of the viral pandemic paint bleak picture.  As events unfold in the next few months,  we may discover that it is too late to act,  that our reign on this planet has, indeed,  come to an abrupt end?  
Covid 19 - irreversible and catastrophic consequences
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Brief of the model:

The model predicts the outbreak of COVID-19 in the Burnie, Tasmania area. It is imperative to clarify that this model was developed from the SEIR model (Susceptible, Infected, Infected, Recovered). The spread of this pandemic is driven by a combination of infection rates, mortality rates, and recovery rates from the virus itself, as well as government policies.

For COVID-19 itself, vaccination directly reduces the infection rate, thereby reducing the mortality rate of COVID-19 patients and the reduction of confirmed cases. In other words, if the local population is adequately vaccinated, everyday life, shopping, tourism, and even national borders will be open rather than in a closed border situation.

 

Assumption of the model:

The model simulated based on different rates, including Infecting rate, Death Rate, Test Rate, Immunity Loss Rate and Recovery Rate. And, this model lists six elements of government policy, which including border closure, travel ban, social distancing, business restriction, self-quarantine, and vaccination schedule.

Besides, the model considers three economic entities in the Burnie area, one in the brick-and-mortar industry and online business industry. Government policies have somewhat reduced COVID-19 infections. Still, they have also at the same time, online businesses played an essential role in stimulating local economic activity during the pandemic. At the same time, however, online businesses played an indispensable role in promoting regional economic activity during the pandemic.

 

The prediction model is for reference only, and there may be differences between the actual cases and the model.

 

 

Insights of the model:

Due to the high infection and low recovery rates and timely government policy interventions, the number of susceptible individuals changes dramatically in the first four weeks. However, the number of sensitive individuals continues to decline after this period, but the decline is not significant. Secondly, with the implementation of government policies, the number of suspected patients who tested negative for medical follow-up continued to rise, implying that government policy interventions directly affect COVID-19.

BMA708_Model of COVID-19 in Burnie_Yuanyuan Liao