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particular disease, or role played by NACA to
distribute condom to hotels in Nigeria. Target
participation on the other hand is the minor roles
played by a party in health activity. For example, if a
person identified as a potential carrier of a disease
(which is a target) is unable to speak or express
himself/herself to a physician probably because of
language barrier, or the intensity of the illness or is
an infant, the person that speak for the potential
carrier (may be interpreter, parent or relative) is an
activity target.
Party location participation shows the
relationship between a location and a party. For
example, a hospital may have different health
facilities such as laboratories, consultation room,
female ward, etc. It may also be diseases agency that
have offices in all the states within the country. The
participation role would be that of the disease
agency that have office at a particular location.
Activity relationship is the relationship between
health activities, for example relationship between
observation and diagnosis, relationship between
diagnosis and treatment. Location relationship deals
with the relationship that exists between locations
and this relationship is important in diseases
surveillance. For example, relationship between
ward and operation room, or relationship between X
ray room and consultation room.
In addition, the model makes use of codes in
order to allow extensibility and flexibility. Codes are
alternative to using free text to describe an attribute
or features of a class. The use of code facilitates data
validation by the system when entered by the users.
Codes are used to allow each of the classes to be
more useful by allowing the class to have type codes
instead of defining new class for minor differences
in the properties of party, health activity or location.
4.4 Model Discussion
The purpose of this model is to document the
information needs of an information system for
effective diseases surveillance, monitoring,
management and prediction.
In the location component of this data model of
which we are aware that explicitly supports
geometry which is represented using the widely
accepted, open GML standard. The GML
representation of the hospitals and party features
allows different geometries such as points, curves,
surfaces and geometry collections which provides
flexibility of encoding.
With GML, user can query a point of interest on
a map in order to ascertain the pattern and
distribution of HIV/AIDS in the vicinity of that
location. A Web Feature Server could also be used
query to fetch the name of locations which has more
than certain prevalent rate for a particular disease,
for example, to fetch the name of state(s) with more
than 5% prevalent rate for HIV/AIDS.
This proposed data model will aid in capturing
comprehensive information about diseases, carriers
of the disease and their location. The model will
assist in developing an understanding of the basic
data required within the health care system in order
to build disease surveillance systems to aid effective
management, monitoring and surveillance of
diseases. It will assist the country to have a good and
reliable epidemiological data and increase the
efficiency of health record unit and this will help the
health policy maker in making favourable health
policies and decision. The model in future may give
birth to electronic health record which will
eventually increase the confidentiality and security
of health record.
This data model will be used to develop a
prototype system which aims to allow users to
spatially query and view data on any diseases in
order to ascertain the patterns, distribution and
prevalent rate of any disease such as HIV/AIDS,
malaria, tuberculosis, etc in any location in Nigeria.
When the system is developed, users will be able to
click on particular point or select a polygon on the
map and the features of the point or polygon such as
the name of the state(s), population at risk and
prevalence rates will be displayed. The prototype
will use aggregated data and focus on HIV/AIDS
because it is only aggregated HIV/AIDS data based
on state level that is currently available for this
research.
It is hoped that in the future when the diseases
surveillance system is fully developed, the
physicians in the hospitals will input patient
information such as demographic data, diseases
associated with each patient and information about
geographical location of each patient into the system
so that epidemiologists, disease agents, policy
makers, and any other authorised users will be able
to query, analyse, view, predict and generate
diseases information based on street, town/city, local
government area, year, population at risk, total
number of cases, prevalence rate, sex, marital status,
educational status and age distribution of disease
carriers in the country.
This system will hopefully aid effective and
efficient intervention in outbreaks of any disease,
which eventually will improve the population health
and reduce the expense on health service provision.
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