Comprehensive model for COVID-19 coused by SARS-CoV-2
Version 1

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Model building:

The module was built using modular bottom-up approach where every module describes a certain process and then, when modules are connected together like domino tiles, we can reconstruct the emergent behavior of the whole system.

This is a blueprint model and might be used for various country/data.
If one wans to use it for a particular country/data, we can recommend following steps:

1. Adjust total population by changing initial condition of
A-Initial_population_innocent_non-tested (in species initial concentrations)

2. Start with adjusting the following parameters in “Global Quantities”:

Social_distance -> abstract value referring to the extend of virus exchange in population (very adjustable)

Testing_randome -> shows how widely people without coronavirus symptoms were tested

Testing_for_symtoms -> shows how widely people with coronavirus symptoms were tested

Time-government_action -> this depends on the date when government initiated measures. The earlier is the date , the less is the infection spread

Government_induced_isolation -> this depends on the strength of governmental measures taken to decrease social distance. The higher is the “Time-government_action”, the less is the infection spread

3. If above does not work, you can try to adjust the following parameters in global quantities as well:
Infection-from_non-tested_no-symptom -> shows fraction of the contribution from non-tested yet, and without symptoms yet, but already contagious people, into Total Infection Coefficient
Infection-from_non_no-symptom -> shows fraction of the contribution from non-tested yet, but already with symptoms, and already contagious people, into Total Infection Coefficient
Infection-from_tested_no-symptom -> shows fraction of the contribution from tested, but without symptoms, contagious people, into Total Infection Coefficient
Infection-from_tested_symptom-> shows fraction of the contribution of tested contagious people with symptoms into Total Infection Coefficient

4. If you like, you can also adjust birth and death rates for your country by changing the following parameters in global quantities:
Birth_rate -> computed from newborn per population per time
Normal_death -> death rate constant without taking into account coronavirus
Corona_death -> death rate constant with taking into account coronavirus
Corona_recover -> rate constant representing the fraction and the rate of recovery

5. Get your curve for your time scale and simulate it for longer to see the future!

SEEK ID: https://fairdomhub.org/models/693?version=1

1 item (and an image) are associated with this Model:
  • COVID-19_comprehensive_model_2020-03-24.cps (XML document - 261 KB) Download

Organism: Homo sapiens

Model type: Ordinary differential equations (ODE)

Model format: Copasi

Execution or visualisation environment: Copasi

Model image: (Click on the image to zoom)

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Views: 130   Downloads: 12

Created: 24th Mar 2020 at 15:07

Last updated: 28th Mar 2020 at 18:21

Last used: 29th Mar 2020 at 05:54

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