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

The model here shows the COVID-19 outbreaks in Burnie Tasmania, which has impacted in the local economy. the relationship between COVID-19 and economic situation has been shown in the graph. Based on the susceptible analysis, people who usual go out are might have chance to meet susceptible people and have a high rate to be infected. The period of spreading can be controlled by keeping social distance and Government lockdown policy. 

Susceptible can be exposed by go out.  resident has a possibility to infect and be infected by others. people who might be die due to the lack of immunity. and others would recover and get the immune. 

Beside, the economy situation is proportionate to the recovery rate. If there are more recovery rate from the pandemic, the employment rate will be increased and the economy situation will recover as well.   

This is an example of a finite state machine (FSM), from Gersting's 7th edition (p. 730, Example 29).

It's the first time I've used vectors (for input); and there are a few interesting twists on models that are different for the Finite State Machine.

So it's been an interesting learning experience for me....

 

It works!

Andy Long

Spring, 2020

Year of Covid-19​

This System Model presents the cases of COVID-19 in Puerto Princesa City as of June 3, 2021

Insight Author: Pia Mae M. Palay

This model is a dynamic model which explains the relationship between the police of the government and the economy situation in Burnie Tasmania after the outbreak of Corona Virus.

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.

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. 

Modelling the demand for health and care resources resulting from the Covid-19 outbreak using an SEIR model.

This model shows the COVID-19 outbreak in Burnie and how the government policy impacts the economy. The possible phases when the infectious disease spreads in Burnie can be labelled as Susceptible, Infection and Recovery, which are main factors in the model. It is concluded that the government policy can reduce the infectious disease and also the impact in the overall economy.

The Government Healthy Policy will affect the decrease in the infection and economy growth rate at the same time.

The Government Health Policy is only triggered when there are more than 10 cases

The increase in number of COVID-19 cases can affect negatively towards the economic growth.