The Big Data Analytics Center (BIDAC)

COVID-19 Pandemic Simulator For Decision Making

Nazar Zaki, Tetiana Habuza and Stefanache Cornel

Big Data Analytics Center (BIDAC), UAEU

Duration 2 Years
Project Video

Researchers from the Big Data Analytics Center (BIDAC) are working on developing a Pandemic Simulator to provide a better understanding of the effects of social distancing and isolation on the development of the pandemic.



Virus Setup
Population Setup
Actions
Legend

Initially the virus configuration was setup to simulate COVID-19 behavior but it can be configured as follows:

  • Manifestation start (day) - the average start day when the virus manifests - patient taken to hospital
  • Manifestation delay (days) - the maximum amount of days that the manifestation can be delayed
    • Spread Probability - probability to pass the virus to a healthy neighboring person on contact
  • Recovery Time - the average time needed for a patient to recover in hospital
  • Mortality - fatality rate of the virus
  • Reinfect Probability- probability of a person to get reinfectted after getting cured

Environment setup and social interactions:

  • Population Size - number of individuals in the population
  • Worker percent - the number of individuals that are actively working (work day will start at 6:00 +/- 4h and lasts for 8 hours
    • Commercial Areas - number of places for people to work in
  • Social Areas - number of places for people to go and socialize
  • Visit probability - the probability of an individual to go and visit another one in its house
  • Social Probability- the probability of an individual to go and socialize in a public space
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