1. Influenza epidemic spread simulation for Poland – A large scale, individual based model study

2. Very Briefly… Construction, design of an agent based model for studying effects of influenza epidemic in large scale (38 million individuals) stochastic simulations, together with the resulting various scenarios of disease spread in Poland are reported in this paper. aim was to acquire a possible scenario of infectious air- borne disease spread in Poland.

3. State Variables Agent Based stochastic modeling approach Fundamental state variable is the Health Status of each agent Each agent is assigned to a household (primary context); place of work, street are secondary, tertiary contexts. Agents are allowed to travel

6. Process Overview Read in the virtual society data Read in the values of simulation parameters Perform the main loop, that is for each time step: - For each agent: assign the travelling status - For each agent: calculate the probability of infection - Output current epidemic statistics (the total number of ill individuals, newly ill, recovered, etc.).

7. Virtual Society – contact network Virtual Society constructed based on National Census data; population density map used to develop households. Each agent is assigned to a primary household. Secondary context based on age. Tertiary context – streets, to account for misc. activities.

8. Infection spread model Necessary condition for an individual to become infected is contact with an infectious individual. At each time step, probability of infection p(t k ) for all susceptible agents is calculated p(t k ) = 1 – exp( -αn F (t k )) α is transmission probability n F is intensity (number and duration) of all contacts of a given agent with infected agents

9. ..Infection spread model n F.j (t k ) = w j I j (t k ) n F.j (t k ) -- intensity of contacts of a given agent with infected agents in a given context w j -- contacting rate for a given agent I j (t k ) -- fraction of infected agents in jth context at time tk time slot

10. ..Infection spread model Mitigation strategy – using f given by the fraction of infected people who do not change their everyday activities despite the illness Corrected number of infected after considering f, n* inf.j = f. n inf.j

11. Transportation model Stochastic Modeling of travelling Choice of travelers – certain number of agents chosen using Bernoulli trials Choice of start and end points – Start point is home, destinations are randomly chosen from the distribution of all agents' geo-locations. choice of transfer cities – Shortest paths chosen using Dijkstra’s. choice of co-travellers - random number taken from the uniform probability distribution in the range [0, max_bundle_size].

12. Results and Discussion

13. attack rate a cumulative number of individuals who caught the disease during the entire epidemic

14. Conclusion Epidemic duration in Poland, as per this model will not be smaller than 26 days. A small increase of infectivity may lead to a significantly more massive epidemic, revealing the sensitivity of such models to critical values Model sensitive to population density; captures difference between rural and urban scenarios.