Selected article for: "infection probability and virus exposure"
Author: Jouni T Tuomisto; Juha Yrjölä; Mikko Kolehmainen; Juhani Bonsdorff; Jami Pekkanen; Tero Tikkanen
Title: An agent-based epidemic model REINA for COVID-19 to identify destructive policies
  • Document date: 2020_4_14
    • ID: 9qdl3jt9_19
    Snippet: This model is based on random interactions between agents, and the interactions lead to outcomes with fixed probability distributions (see Table 1 ). The states are similar to those in SEIR models (e.g. Wilson et al., 2020) , which are typically described by differential equations. Although the individual events and times spent in different states are probabilistic, many key parameters whose real-world values still involve significant uncertainty.....
    Document: This model is based on random interactions between agents, and the interactions lead to outcomes with fixed probability distributions (see Table 1 ). The states are similar to those in SEIR models (e.g. Wilson et al., 2020) , which are typically described by differential equations. Although the individual events and times spent in different states are probabilistic, many key parameters whose real-world values still involve significant uncertainty are assumed as known constants in a simulation. Therefore, sensitivity analyses were done with two key parameters: the fraction of asymptomatic infections and the probability of infection given exposure to the virus. In addition, the five ready-made simulations at the web interface were run for 100 times with different random seeds to investigate their sensitivity to random in-model variation.

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