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ISDS 2012 Conference Abstracts

Multiagent Simulation of the Hepatitis B Epidemic
Process
Tetyana Chumachenko*1, Dmytro Chumachenko2 and Olexandr Sokolov2

1Epidemiology Department, Kharkiv National Medical University, Kharkiv, Ukraine; 2National Aerospace University “Kharkiv Aviation
Institute”, Kharkiv, Ukraine

Objective
To develop multiagent model of hepatitis B (HBV) infection

spreading.

Introduction
The standard approaches to simulation include solving of differ-

ential equation systems. Such approach is good for obtaining general
picture of epidemics (1, 2). When the detailed analysis of epidemics
reasons is needed such model becomes insufficient. To overcome the
limitations of standard approaches a new one has been offered. The
multiagent approach has been offered to be used for representation of
the society. Methods of event-driven programming give essential ben-
efits of the processing time of the events (3).

Methods
For model development C# computing language has been used.

We have used demographical data, the incidence rate of HBV infec-
tion of all population and different population groups (age, profes-
sional and other groups), coverage of hepatitis B vaccination, the
proportion of HBV carriers in population, the prevalence rate of
chronic HBV infection, percent of dominated transmission routes and
factors and other rates in Kharkiv region. All parameters, expressed
in the model were estimated using sero-surveys data and data of epi-
demiological surveillance of Kharkiv region sanitary-epidemiologi-
cal station. Also the theoretical knowledge about HBV infection has
been used. 26 conditions have been derived from the problem do-
main. The transition from one condition to another depends on sto-
chastic value and time of the event change. All events are organized
in priority queue which results in high rate of computation perform-
ance. The dependence on time and random value determines au-
tomata theory conceptions.

Results
The prototype of software system, which includes a subsystem of

the multiagent simulation and specialized statistical and mathemati-
cal sub-system which can process the simulation results and perform
a conditional optimization of the selected objective functions (mor-
bidity, the effectiveness of specific preventive and control activities
and their price, measure of reducing the socio-economic impact of
HBV infection, etc.) have been developed. Screen form is presented
in Figure 1.

Conclusions
The multiagent simulation model of the HBV infection epidemic

situation development, based on data obtained in Kharkiv (Ukraine)
has been created.

The simulation results allow us to: 
1. predict the dynamics of the epidemic process in time in a par-

ticular area, taking into account specific epidemic situation;
2. test the effectiveness of various preventive measures (steriliza-

tion of instruments, coverage of hepatitis B vaccination of certain
groups of people, etc.).

Using the present model in public health system suggests improv-
ment of the epidemiological diagnostics of HBV infection and of the
quality of management decisions about epidemiological surveillance.
The evolution of multiagent simulation in epidemiology will broaden
the possibilities of epidemiological surveillance and control.

Fig. 1. The main panel of simulation management and graphic visualization.

Keywords
Multiagent modeling; Event-driven programming; Predictive disease
modeling; Epidemiological surveillance

References

1. Shoujun Zhao, Zhiyi Xu, Ying Lu.: Mathematical model of hepatitis B
virus transmission and its application for vaccination strategy in
China. International Journal of Epidemiology. 2000;29:744-52.

2. O’Leary, C., Hong, Z., Zhang, F., Dawood, M., Smart, G., Kaita, K.,
Wu, J.: A mathematical model to study the effect of hepatitis B virus
vaccine and antivirus treatment among the Canadian Inuit popula-
tion.Eur J Clin Microbiol Infect Dis. 2010 Jan;29(1):63-72. 

3. Hethcote, H.W.: The mathematics of infectious diseases. SIAM Rev.
2000; 42(4): 599–653.

*Tetyana Chumachenko
E-mail: tatalchum@gmail.com

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * 5(1):e178, 2013