Geography Reference
In-Depth Information
Case Study
The case study in which the previously presented methods are applied deals with
the spatial distribution of campylobacteriosis in the Czech Republic between the
years 2008 and 2012. There were almost 100 thousand cases of the disease during
that period. Using disease rates calculated for the municipal districts in the Czech
Republic, we tried to identify areas that are possibly more vulnerable to the disease
than their neighbourhood. The 5-year prevalence and the relative risk (SMR) were
used as the main disease rates for this study. Subsequently, Local Moran
s I was
'
used as the statistic of the local clustering.
Campylobacteriosis is caused by bacteria called Campylobacter jejuni, which is
found worldwide in the intestinal tracts of animals. The bacteria are spiral shaped
and can cause disease in animals and humans. Most cases of campylobacteriosis are
associated with handling or eating raw or undercooked poultry meat or fresh milk.
Campylobacteriosis causes gastrointestinal symptoms, such as diarrhoea,
cramping, abdominal pain, and fever in domestic animals and humans. Young
animals and humans are the most severely affected (CFSPH
2013
).
Data
The data set for this study was provided by The National Institute of Public Health
of the Czech Republic. The database contains almost 100,000 records of
campylobacteriosis occurrence in the period 2008-2012. Names, surnames, identity
numbers and sometimes also the full addresses are not included as they are
considered sensitive personal data. The data were firstly cleansed of inconsistencies
and then the geocoding process was run. Furthermore, individual records were
aggregated into municipal districts—administrative units—for clarity of the visu-
alization (Marek et al.
2013
). The problem of converting spatial phenomena between
different areal or administrative units is well known as MAUP—Modifiable Area
Unit Problem (Openshaw
1984
). During the calculation of smoothed rates, the
population data from the Population and Housing Census of the Czech Republic
were used as the main basis for data standardization.
Choropleth Maps of Smoothed Prevalence and Relative Risk
Choropleth maps are probably the most common type of map used to display areal
data. These maps use different colour and pattern combinations to depict different
values of the attribute variable associated with each area, which is coloured
