Epidemic Spread Simulation Pseudo Code

Pseudo Code for Epidemic Spread Simulation

Variables

• attrKey: Attribute key for node status
• new_infected_nodes: Set to store new infected nodes
• new_recovery_nodes: Set to store nodes moving to recovery status

Main Loop for Infection and Recovery

1. Initialize empty sets new_infected_nodes and new_recovery_nodes.
2. For each node in infected_nodes:
   • For each neighbor nbr in the adjacency list of node:
     • If the neighbor's status is Susceptible:
       • If the node's status is Asymptomatic_Infected:
         • With probability p_asymptomatic_infected, add neighbor to new_infected_nodes.
       • Else if the node's status is Symptomatic_Infected:
         • With probability p_symptomatic_infected, add neighbor to new_infected_nodes.
   • With probability p_recovery, add the node to new_recovery_nodes.

Process New Infected Nodes

1. For each node in new_infected_nodes:
   • With probability p_asymptomatic, set node status to Asymptomatic_Infected.
   • Else, set node status to Symptomatic_Infected.
   • Add node to infected_nodes.

Process New Recovery Nodes

1. For each node in new_recovery_nodes:
   • Set node status to Recovery.
   • Remove node from infected_nodes.

Pseudo Code Implementation

DECLARE attrKey AS self.node_attrKey
DECLARE new_infected_nodes AS new empty set
DECLARE new_recovery_nodes AS new empty set

FOR EACH node IN self.infected_nodes:
    FOR EACH nbr IN self.g.adj[node]:
        IF self.g.nodes[nbr][attrKey] == Status.Susceptible:
            IF self.g.nodes[node][attrKey] == Status.Asymptomatic_Infected:
                IF random.random() < self.p_asymptomatic_infected:
                    new_infected_nodes.add(nbr)
            ELSE IF self.g.nodes[node][attrKey] == Status.Symptomatic_Infected:
                IF random.random() < self.p_symptomatic_infected:
                    new_infected_nodes.add(nbr)
                
    IF random.random() < self.p_recovery:
        new_recovery_nodes.add(node)

FOR EACH nin IN new_infected_nodes:
    IF random.random() < self.p_asymptomatic:
        self.g.nodes[nin][attrKey] = Status.Asymptomatic_Infected
    ELSE:
        self.g.nodes[nin][attrKey] = Status.Symptomatic_Infected
    self.infected_nodes.add(nin)

FOR EACH nrn IN new_recovery_nodes:
    self.g.nodes[nrn][attrKey] = Status.Recovery
    self.infected_nodes.discard(nrn)

Explanation

• The pseudo code begins by declaring the necessary variables.
• It then iterates over each infected node to determine if their neighbors get infected or if the node recovers.
• The status of newly infected nodes is updated based on probabilities.
• Nodes recovering are updated to the recovery status and removed from the infected set.

Notes

• This pseudo code focuses on the epidemic spread and recovery logic.
• The use of common programming constructs and clear variable naming should help in understanding the process.
• This serves as a preliminary guide for implementation and further development of the simulation logic.