Jul 16, 2017 Research papers

Are there any areas of Lesvos which are particularly unhealthy in terms of cervical cancer?

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Assessing Spatial Patterns Using GIS


Briefly discuss (no more than one side of A4) the global and local patterns of spatial autocorrelation shown in your results and the results would be sent to u as a file.

Are there any areas of Lesvos which are particularly unhealthy in terms of cervical cancer?

Can you see any potential links between poorer health outcomes(in terms of cervical cancer) and the socioeconomic status in Lesvos (sar9500maN attribute)? You should support your commentary with some links to the academic literature.

The report should have;

1. Introduction 10%

2. Summary of methods 10%

3. Data synthesis, analysis, interpretation and discussion, including evidence of integration with published reports and scientific journal articles 40%

4. Use of supporting figures and tables 30%

5. Brief conclusion 10%


1. Start up ArcMap (ArcGIS) and create a new map file- add the Lesvos shapefile (Lesvos.shp)

2. Using the symbology tab create a graduated colour map display for cl95_00_mN (i.e. number of women with cervical cancer per 1000) using the quantile classification method and five classes

3. Spend a few minutes examining the data closely- can you see any obvious pattern?

4. To test the robustness of any spatial patterning you will calculate the Moran`s I measure of spatial autocorrelation for the cl95_00_mN dataset. First, you must make sure that the ArcToolbox is up and running. Click on the red toolbox icon from the toolbar to install this function within your display. You will find that there are many different functions available- you will be using the Spatial Statistics Tools at the bottom of the list.

5. Double click on Spatial Statistics Tools and do the same for the buttons Analyzing Patterns and Spatial Autocorrelation (Moran`s I). This will bring up a new dialog box.

6. Select lesvos as input feature class and cl95_00_mN as the input field and make sure the Generate Report (optional) is ticked and that you use the Inverse Distance Squared option for determining the spatial relationship then click okay.

7. Assess the results by selecting Geoprocessing and then results.


Assessing Spatial Patterns of Both Disease and Environmental Pollution Using Geographical Information System (GIS) Name Course Instructor Date Introduction Spatial representations of cervical cancer help to visualize the effect of social, economic and environmental determinants of the disease disparity. In many cases, the socioeconomic status of a population in a geographical area is often associated with the extent to which there is accessibility of health services, and economic wealth. Since there is a need to take into account local spatial variation as this avoids bias, when establishing the link between a disease and the explanatory variables (Chang, Atkinson & Shahani, 2011). Disease analysis that relies on Geographical Information System (GIS) helps to identify the local spatial variations, which then makes it easier to identify risk factors. As such, GIS is beneficial in disease analysis since the spatially referenced data represented in mapping focuses on visualizing spatial patterns. This paper will summarize the method used to present data on cervical cancer and socioeconomic status in Lesvos it will also give a description of the interaction as well as provide relevant figure to establish whether there is a relation between socioeconomic indicators and cervical cancer (Cancer Research UK.org, 2015). Summary of methods The incidences of cervical cancer were tracked down, with geocoding helping to provide a general overview of differences in cervical c...

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