Coordination of Processes as a Starting Point for Simulation-based
Management of Biological Incidents
Tereza Otčenášková
1
, Vladimír Bureš
1
, Pavel Čech
1
and Jana Prattingerová
2
1
Faculty of Informatics and Managmentu, University of Hradec Králové,
Rokitanského 62, Hradec Králové, Czech Republic
2
Regional Public Health Authority, Husova 64, Liberec, Czech Republic
Keywords: Biological Incident, Conceptual Perspective, Coordination, Management, Process, Simulation.
Abstract: Biological incidents nowadays represent more often as well as more serious threat endangering important
assets. Their management requires complex approach including high demands on technological support.
This paper neither contributes with another simulation model or results, nor offers the application of specific
technology. It utilises the literature analysis and interviews with experts to reveal the framework for
potential options and scenarios for simulation employment in the realm of management of biological
incidents. Conceptual issues related to the simulation of biological incidents together with process
perspective are provided and advantages as well as prospective utilisation in modelling and simulation are
discussed.
1 INTRODUCTION AND
PROBLEM FORMULATION
Biological incidents can be defined as events when a
biological agent harms or threatens humans,
livestock or other important assets (UNODA, 2009).
These problems represent a topical issue in several
areas of our society regardless if these are caused by
the biological weapons or if they occur
unintentionally like the leakage of a dangerous
substance from a factory or laboratory, or natural
incidence of a disease. Whereas the former can be
considered as more perilous, the latter is usually
more easily manageable. It is especially because
focal points can be typically identified quickly and
localised more precisely. Therefore, the critical
assets can be recognised faster and adequately
protected. On the other hand, during these incidents
it is hard to react promptly in the initial phase,
because the first phase of the agent identification can
last a significant time. Nevertheless, if appropriately
managed, their consequences can be minimized
(Bureš et al., 2012b). Coping with a biological
incident involving a highly persistent agent (e.g.
anthrax, Brucella, influenza or zoonosis) is a
complex process. It requires extensive information
and both considerable and appropriate resources.
Unfortunately, these are likely to be limited,
particularly if multiple facilities, areas or groups of
people are affected (Krauter et al., 2011). Therefore,
any available tool for decision support and for the
improvement of the effectiveness of the course of
action should be employed. This paper firstly
introduces the current state-of-the-art related to the
modelling and simulation utilisation during the
process of biological incidents. Afterwards, methods
followed by results are discussed. Finally, the
limitations, further research perspectives and
implications of the mentioned research are provided.
2 SIMULATION
AS A RESEARCH METHOD
As discussed above, the biological incident
management should be supported by appropriate and
efficient tools. Therefore, this paper addresses these
issues employing the simulations. The idea to use
modelling and simulations in epidemiology has been
mentioned earlier (Hurd and Kaneene, 1993).
Nevertheless, only particular aspects of the complex
problem predominantly attract researchers’ attention.
For instance, several models such as susceptible-
infected (SI) model (Naji and Mustafa, 2012),
446
Ot
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cenášková T., Bureš V.,
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Cech P. and Prattingerová J..
Coordination of Processes as a Starting Point for Simulation-based Management of Biological Incidents.
DOI: 10.5220/0004478704460452
In Proceedings of the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH-2013),
pages 446-452
ISBN: 978-989-8565-69-3
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
susceptible-infected-recovered (SIR) model (Yusuf
and Benyah, 2012), or susceptible-exposed-infected-
recovered (SEIR) model (Forgoston et al., 2009)
have been already developed. Peculiar feature to
simulation in this realm is the examination of
characteristics and behaviour of a particular system
on the basis of the experiments realised on the
mathematical model of this system. Commonly used
approaches are based on a Liapunov function (Gao
et al., 2013), LaSalle's invariance principle (Xu,
2012), or Bayesian Markov-chain-Monte-Carlo
inference (Filipe et al., 2012). All the
aforementioned models and tools are proved to be
meaningful and applicable. However, their
utilisation is not mostly related to the general
context. Usually, every prospective user selects a
situation or aspect in which various systems, tools,
or methods are applied (e.g. prehospital care
(Junker, 2007) or industrial and agriculture incidents
(Bureš et al., 2012a)), but without broader
perspective, although a few of frameworks or
methodologies have been developed and published
(Nakano et al., 2009; Otčenášková et al., 2011).
Apparently, the successful application of
simulation requires a lot of precedent work prior to
building a computer simulation model. The
simulation itself consists of eight major phases,
which need to be followed for the proper application
of the simulation methodology (Ülgen et al., 1994).
Rarely authors do present in their studies the context
and evidence their awareness of the overall
simulation process. Mostly, the simulation models
are described and results are interpreted. Therefore,
the aim of this paper is to introduce a model of the
epidemiological treatment of a biological incident
that comprise all stages of the process from incident
occurrence to its final termination. This process
view can be successfully applied as a framework for
simulations of biological incidents, which would be
more complex, respect the whole process, and
include more stakeholders.
3 METHODOLOGY
The main research question which determined the
research direction and methods was the following
“Is there a general process that can serve as a
framework for several existing and prospective
simulations in the area of biological incidents?”.
Thus, the discussed research activities were
grounded on the literature review and quantitative
research. The former was based on the analysis of
information resources such as military documents
(McClellan et al., 2010), public institution tools
(NASA, 2010), and approaches incorporated in
procedures of public health institutions. These
include for example State Veterinary Administration
of the Czech Republic, The National Institute of
Public Health in the Czech Republic, or The
National Reference Laboratory of the Czech
Republic. The latter consisted of several iterations of
in-depth un- and semi-structured interviews with
experts in epidemiology and public health realm.
The knowledge revelation, extraction and further
compilation were employed.
4 RESULTS
Three schematic process models of biological
incidents were developed. Based on the consultation
and recommendation of experts, the selected case
studies were anthrax, influenza and diarrhoea. The
complex process from its beginning representing by
the symptoms occurrence to its termination was
modelled. Whereas the full version of the process
description identifies several tasks, steps,
stakeholders or utilisable tools, the Appendix of this
paper comprises the simplified description (due to
space limitations) of the overall process of dealing
with the influenza epidemics. Particular model
elements can be consequently analysed and
appropriate technology can be deployed. Not only
decision support technologies or methods,
professional databases and communication tools can
be used, but also simulations of different biological
or epidemiological aspects can be applied.
4.1 Implications for Epidemiological
Simulations
Typically, simulation models are utilised during the
Scenario development phase (as stated in the
introduction section). Considering the context of the
scheme in the Appendix, it is obvious that various
parts of the incident can be simulated. The most
advantageous is to monitor the consequences of
diverse actions during relevant phase of the incident.
The process indicates that it can be also put in use in
Application of anti-epidemic measures or
Anamnesis trace stages. At the beginning, there are
three options how an incident might occur. The
simulation would provide for example the
comparison of time needed for the whole incident
termination based on differences among the
situations. For instance, there is a significant
difference between two cases. The first one is when
CoordinationofProcessesasaStartingPointforSimulation-basedManagementofBiologicalIncidents
447
the infection is diagnosed at the general practitioner.
This might be compared to the problem on a
particular plane with an infected person. In this
situation, all other people who were on the board
and are suspected from the infection have to be
traced and their condition has to be monitored.
During this phase, the multi-agent based modelling
of the agent spread with integrated geographic
information system can be helpful (Wang et al.,
2010; Laskowski et al., 2011). The duration of the
initial phases of the incident depends also on the
methods employed in the laboratory to analyse the
samples. The three basic methods demonstrate
various demands on people, equipment, necessity of
safety precautions or time for further actions.
Methods potentially employed with their
characteristics follow:
prompt methods: identification if it is influenza
virus or not,
Polymerase Chain Reaction (PCR) method:
identification of influenza type,
virus cultivation: clear specification of the
virus type and its analysis considering the
purposes of future vaccine preparation.
Demands within Application of anti-epidemic
measures in case of serious condition or suspicion of
new virus have the same impact on different
simulation scenarios. The quarantine simulations
might include the following parts:
isolation (relating to infected people), possibly
their treatment,
quarantine of health people suspected from the
infection,
medical control (health condition monitoring).
Apart from these, closure of hospitals,
institutions of social care and places, where
susceptible and endangered population is present, is
necessary. Mostly, the searching for and contacting
of people who were in contact with the affected ones
(especially colleagues, co-passengers, family etc.) is
realised. There are cases when for example police
have to be involved as well to coerce people to stay
in the focus of the infection.
Before the virus is specifically described and
targeted measures are taken, a lot of information
should be gathered dependant on the seriousness of
the whole incident. These factors might also
influence the overall simulation and therefore should
be taken into account. Usually, the following
characteristics should be gathered:
availability of treatment and vaccination,
threat of the transmission,
ways of the spread,
period of infectiousness,
susceptibility,
infectiousness,
or fatality rate.
All the mentioned factors can be considered as
variable inputs in the simulations which influence
the extent of stakeholders to be involved, time,
material, financial and other resources to be utilised
and also the overall effectiveness of required
processes within the incident management.
4.2 Prospective Users
Furthermore, more stakeholders can be included and
simulation results can be more realistic. From the
perspective of involved institutions and individuals,
especially the awareness about the relations and
dependency is supported by the created model as
well as by the simulation process which shows who
interacts with whom and which processes
consequent from the course of action of particular
participant. This opens a new perspective for
simulation with the help of multi-agent models and
techniques, which have already been applied in case
of specific instances (Dion et al., 2011; Linard et al.,
2009). Each participant might moreover choose the
relevant part of simulation which is appropriate for
his or her purposes. Such advantageous approach is
both effective and clearer to the particular
stakeholder. For this reason, participants can try
various situations, get more expertise and experience
without any threats and costs even before an incident
occurs.
4.3 Integration Perspective
The acquired results enable not only putting the
existing simulations and models into context, but
also focusing future results and efforts on better and
meaningful integration of prospective outcomes with
other systems and applications. This is feasible due
to the practical and verified framework. Moreover,
the integration of simulations does not have to
remain at the conceptual level. Since the process
framework determines the context, issues related to
data integration, methodological or application
integration can be considered. The final integration
can contribute to the general scheme of
technological tools utilisable in management of
incidents, as described by Otčenášková et al. (2011).
In business practice every process has its own
owner who is responsible for its execution and
outputs. The process view on biological incidents
reveals that this approach ensures that the ownership
is distributed. This causes issues related to
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responsibilities, budgeting or willingness to
overcome existing barriers related to the
technological automation of particular process
segments. Unless this is solved, the simulations will
remain mostly isolated isles in the world of
technological support of decision-making in the area
of biological incidents management.
As apparent from Figure 1, the determination of
all parts of the simulation processes and all
stakeholders provides with clearer and easier
management of necessary actions. Moreover, the
end users vary significantly and therefore, the
outputs in form of recommendations, decision
support, or scenario creation can be prepared with
the help of plethora of technologies. At the
beginning of the incident management, necessary
data must be collected from several resources (see
bottom boxes in Figure 1). These are afterwards
processes thanks to the employment of techniques
and methods including data transformation,
database, analytical and end user tools. Simulation
belongs to the end users tools and therefore
influences significantly the technological support of
the incident management and consequently both the
chosen measures and actions. Hence, several
technologies can be mutually interrelated with
computer technologies and provide users with the
complex decision support.
Regardless the biological incident, the mentioned
concept ensures better resource planning, easier
identification of stakeholders, clearer and quicker
determination of responsibilities and involved
parties resulting in better crucial assets protection
followed by future prevention and preparedness
improvement.
Figure 1: Technological Context of Simulation in the Biological Incident Domain (Bureš, 2012b).
CoordinationofProcessesasaStartingPointforSimulation-basedManagementofBiologicalIncidents
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5 LIMITATIONS AND FURTHER
RESEARCH
The aforementioned research has particular
limitations. Even though, it was developed in the
Czech Republic, the applicability within different
countries is possible due to the general concepts
which are used. Nevertheless, some changes relating
to the specific institutions involved or the procedural
regulations might be relevant and should be
considered. As discussed above, only a few
scenarios have been simulated so far. Therefore, the
creation of scenarios for the purposes of other
diseases, infections and various threats and incidents
is possible.
There are various approaches and methods
relevant to be considered for the purposes of further
research of the discussed concept. These comprise
exploration of advanced utilisation and development
of gathered information and created models. As
examples, the following can be mentioned:
Markov Chains to monitor the overall system
changes and to evaluate the probable transition
from one state to another,
Net Analysis to represent the relations more
precisely and comprehensibly,
Process Analysis to support the understanding of
chronological changes of the whole system
(model),
Analysis and Forecasting of Time Series to reach
more appropriate system description and to
provide more precise predictions of the following
development,
Causal Loop Diagram to visualise the influence
of one component on another or
RASCI Matrix (responsible, accountable,
support, consulted and informed management of
the particular problem) to determine
responsibilities during the processes.
These methods can be either used separately or
they can be incorporated within already done outputs
to enhance their usability and precision of the
simulations and models.
6 CONCLUSIONS
Currently, the biological incidents require attention
especially because these occur relatively often, the
processes within them demand a lot of resources and
their consequences are more dangerous and
extensive. Nevertheless, simulation exemplifies a
method which can significantly support the
processes necessary for successful and prompt
incident termination. This paper introduces the
process view on incident management which can
consequently represent a framework for the
computer-based decision-making support. It further
highlights the possibilities and the advantages of
simulation method during the biological incident
management. The overall coordination and various
stakeholders are supported and the course of action
is managed more effectively to protect valuable
assets. The simulation is also contextualised and
areas for further research and development of the
mentioned concept are discussed.
ACKNOWLEDGEMENTS
This paper is supported by the project No.
CZ.1.07/2.2.00/28.0327 Innovation and support of
doctoral study program (INDOP), financed from EU
and Czech Republic funds. It is also written with the
support of the specific research project 2/2013
“Cooperation mechanisms of network organisations”
funded by the University of Hradec Králové, Czech
Republic.
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APPENDIX
Process View on the Influenza Incident (Authors’ Research)
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