Public Health Models

These models and simulations have been tagged “Public Health”.

Related tagsCVDDisease Prevention

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Introductory overview of Complexity based on Kurt K Workshops on Systems Science for Public Health 2024
Features of Complexity
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Temperature Stress Mortality Simulator: for the older (70+ years) population of West Dorset, UK using the UKCP09 SRES A1B Emission Scenario.
Clone of Temperature Stress Mortality Simulator
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This model was created for ENGR 102 - Studio 2
Infectious Diseases - Sean Cummings
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This model was developed as part of the curriculum development for a short introductory course on systems dynamics modelling for health system analysts
Stage 10 CVD Prevention Model - storytelling
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This model was created to model a disease
Disease Dynamics - Connor Ovenstone
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Modelling prevalence of cardiovascular disease within a population using agent based modelling. The initial population is defined within Tools->Variables and macros.

This is a partial model that is not yet complete.
Cardiovascular Model V1.0
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Temperature Stress Mortality Simulator: for the older (70+ years) population of West Dorset, UK using the UKCP09 SRES A1B Emission Scenario.
Clone of Temperature Stress Mortality Simulator
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ENGR 102 - Studio 2
Infectious Diseases - Madison O
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This is a population model designed for local health and care systems (United Kingdom). This model does not simulation male/female, but rather everyone in 5-year age groups.
Clone of Age-Sex Pop Model
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Infectious Diseases By Team # 1
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Infectious Diseases by Team #!
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This model was created for ENGR 102- Studio 2
Infectious Diseases- Luna Alvarez
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Infectious diseases - Teagan Noel
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Temperature Stress Mortality Simulator: for the older (70+ years) population of West Dorset, UK using the UKCP09 SRES A1B Emission Scenario.
Temperature Stress Mortality Simulator
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This model was created for ENGR 102 - Studio 2
Infectious Disease - Andreu Martin
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Summary of Zimmerman2013 article (paywalled) Habit, custom, and power: A multi-level theory of population health. Also mapped to COM-B. See also Dynamics in action IMPCT Double Loop Learning IM and Structure Agency framework IM
Multilevel theory of behavior
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Infectious diseases by Team ....
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This model was created for ENGR 102 - Studio 2
Infectious Diseases - Hayden A. Forster
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Flujograma: Propuesta de investigación MeCoBi
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This is a model for infectious diseases for ENGR 102
Infectious Diseases - Gervasius Kevin Juanda
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This model was developed as part of the curriculum development for a short introductory course on systems dynamics modelling for health system analysts
Clone of Basic CVD Prevention Model
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This model was developed as part of the curriculum development for a short introductory course on systems dynamics modelling for health system analysts
Stage 8 CVD Prevention Model
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Model description: 

This model is designed to simulate the Covid-19 outbreak in Burnie, Tasmania by estimating several factors such as exposed population, infection rate, testing rate, recovery rate, death rate and immunity loss. The model also simulates the measures implemented by the government which will impact on the local infection and economy. 

 

Assumption:

Government policies will reduce the mobility of the population as well as the infection. In addition, economic activities in the tourism and hospitality industry will suffer negative influences from the government measures. However, essential businesses like supermarkets will benefit from the health policies on the contrary.

 

Variables:

Infection rate, recovery rate, death rate, testing rate are the variables to the cases of Covid-19. On the other hand, the number of cases is also a variable to the government policies, which directly influences the number of exposed. 

 

The GDP is dependent on the variables of economic activities. Nonetheless, the government’s lockdown measure has also become the variable to the economic activities. 

 

Interesting insights:

Government policies are effective to curb infection by reducing the number of exposed when the case number is greater than 10. The economy becomes stagnant when the case spikes up but it climbs up again when the number of cases is under control. 

Sample Model of COVID-19 outbreak in Burnie Tasmania by Yim Fong Ng (544885)
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Infectious Diseases 2.0 Team -3