Download Influenza epidemic spread simulation for Poland a large

Influenza epidemic spread
simulation for Poland –
A large scale, individual based
model study
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 airborne disease spread in Poland.
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
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.).
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.
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(tk) for all
susceptible agents is calculated
p(tk) = 1 – exp( -αnF (tk))
α is transmission probability
nF is intensity (number and duration) of all contacts of
a given agent with infected agents
..Infection spread model
nF .j(tk) = wjIj(tk)
nF .j(tk) -- intensity of contacts of a given agent with
infected agents in a given context
wj -- contacting rate for a given agent
Ij(tk) -- fraction of infected agents in jth context at
time tk time slot
..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 . ninf .j
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].
Results and Discussion
attack rate a cumulative number of individuals who caught the disease during the
entire epidemic
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.