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Индия короновирус, 2021 жыл

Ersultan

8 months ago

This model estimates the deaths due to COVID19 in Bangalore City.

Assumptions:

City has a population = 8 Million

Initial infected population = 10

Probability of infection = 8%

Contact rate in population = 6

Average duration of recovery = 10 days

Death rate = 1%

Quarantine rate = 80%

Delay in quarantine = 5 days

COVID-19_SIR_MODEL_No_Quarantine

Abhijith N

Pemodelan Covid-19 di Indonesia

Jihan Widya Candra

Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus.

We add simple containment meassures that affect two paramenters, the Susceptible population and the rate to become infected.

The initial parametrization is based on the suggested current data. The initial population is set for Catalonia.

The questions that we want to answer in this kind of models are not the shape of the curves, that are almost known from the beginning, but, when this happens, and the amplitude of the shapes. This is crucial, since in the current circumstance implies the collapse of certain resources, not only healthcare.

The validation process hence becomes critical, and allows to estimate the different parameters of the model from the data we obtain. This simulation approach allows to obtain somethings that is crucial to make decisions, the causality. We can infer this from the assumptions that are implicit on the model, and from it we can make decisions to improve the system behavior.

Yes, simulation works with causality and Flows diagrams is one of the techniques we have to draw it graphically, but is not the only one. On https://sdlps.com/projects/documentation/1009 you can review soon the same model but represented in Specification and Description Language.

SEIRD 02: COVID-19 spread with containment measures

Pengcheng Chen

3

Simple epidemiological model for Burnie, Tasmania

SIR: Susceptible to infection - Infected - Recovery, Government responses and Economic impacts

Government policy is activated when there are 10 or fewer reported cases of COVID-19. The more people tested, the fewer people became infected. So the government's policy is to reduce infections by increasing the number of people tested and starting early. At the same time, it has slowed the economic growth (which, according to the model, will stop for next 52 weeks).

Model of Covid-19 Outbreak in Burnie, Tasmania (Yue Xiang 512994)

Yue Xiang

5

Somulacion clase 2, retroalimentación + y - , primer versión

Modelo Covid-19 Co

brow

My Insight

Tomiris Zhalbyrova

Systemigram Model Building Exercise (COVID-19)

Josiah Best

covid 19 in china 1

kusalinadina30@gmail.com

last month

INTRODUCTION

This is a balanced loop model that demonstrates how COVID 19 outbreak in Burnie and the response of the government (e.g. by enforcing health policies: Lockdown; quarantine, non-necessary business closure; border closure) affect the local economy. This model has 13 positive loops and seven negative loops. Government response is dependent on the number of reported COVID-19 cases which in turn thought to be dependent on the testing rates less those who recovered from COVID 19 and dead. Economic activity is dependent on the economic growth rate, increased in online shopping, increased in unemployment, number of people who do not obey the rules, COVID 19 cases and health policies.

ASSUMPTIONS

· Both infection and economic growth is reduced by enforcing government policies

· However, the negative effect of government policies is reduced by the number of people who do not obey government health policies

· Govt policies are enforced when the reported COVID-19 case are 10 or greater.

· Number of COVID cases reported is dependent on the testing rates less those who recovered and dead.

· The higher number of COVID-19 cases have a negative effect on local economy. This phenomena is known as negative signalling.

· Government policies have a negative effect on economic activity because health policies limit both social and economic activities which directly or indirectly affect the economy in Burnie .

· This negative effect is somewhat reduced by the increase in online shopping and the number of people who do not obey heath rules.

INTERESTING INSIGHTS

The test ratings seem to play a vital role in controlling COVID-19 outbreak. Higher Rates of COVID testings decrease the number of COVID 19 deaths and number of infected. This is because higher rates of testing accelerate the government involvement (as the government intervention is triggered earlier, 10 COVID cases mark is reached earlier). Delaying the government intervention by reducing the COVID testing rates increases the death rates and number of infected.

Increased testing rates allow the figures (deaths, susceptible, infected) to reach a plateau quickly.

BMA708- Shakila Bethmage- 548351 - COVID 19 Outbreak in Burnie

Shakila Piyumi Perera Bethmage

өзіндік жұмыс 2 агенттік модель

aidana serzhanovnaa

8 months ago

Demo_Group3_COVID-19

Kathryn Liddle

Introduction:

This simulation model demonstrates the outbreak of Covid-19 in Burnie, Tasmania and how the corresponding government’s responses affect the spreading of Covid-19. Meanwhile, this model also shows how the economy in Burnie is influenced by the impacts of both Covid-19 and government policies.

Variables:

This simulation contains some relevant variables as follow:

Variables in Covid-19 outbreaks: (1) Infection rate, (2) Recovery rate, (3) Death rate, (4) Immunity loss rate

Variables in Government policies: (1) Vaccination rate, (2) Lockdown, (3) Travel ban, (4)Quarantine

Variables in Economy: (1) E-commerce business, (2) Unemployment rate, (3) Economic growth rate.

Assumption:

Government responses would be triggered when reported Covid-19 cases are at least 10.

The government policies reduce the spreading of Covid-19, but they would also limit economic development at the same time due to the negative impact of the policies on the economy is greater than the positive impact.

The increase in reported Covid-19 cases would negatively affect economic growth.

Interesting Insights:

The first finding is that the death number would keep increasing even though the infection rate has decreased, but with stronger government policies (such as implementing a coefficient over 25%), no more death numbers will occur caused by Covid-19.

The second finding is that as government policies limit business activities, with the increasing number of reported Covid-19 cases, economic growth will suffer a severe blow even if e-commerce grows, it can’t make up for this economic loss.

BMA 708 assignment 3 - simulation model of Covid-19 Outbreak in Burnie, Tasmania

Xuanze Liang

System Dynamics Model - Covid-19 (TAYTAY)

AL JOHN D. CENA

S-I-R covid-19 model

KRISTIAN SABATINO

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

Taleisha Y. Alcorn

Modelo epidemiológico simples

SIR: Susceptíveis - Infectados - Recuperados

Clique aqui para ver um vídeo com a apresentação sobre a construção e uso deste modelo. É recomendável ver o vídeo num computador de mesa para se poder ver os detalhes do modelo.

Dados diários sobre infectados, recuperados e óbitos para diversos países (incluindo o Brasil) podem ser obtidos aqui neste site.

Dados diários para o município de Juiz de Fora podem ser obtidos no site da Prefeitura.

Juiz de Fora - Covid-19