Regression modelling of cervical cancer and Chlamydia incidence
in the context of national screening programmes
Regression modelling of cervical cancer and Chlamydia incidence
in the context of national screening programmes
Prevention of cervical cancer development or reduction in undetected Chlamydia
incidence and further onward Chlamydia transmission can be achieved through
regular screening. Early detection through a regular screening programme is
essential to achieve this goal. A well established screening policy is needed to
improve screening efficiency.
This PhD study demonstrated the use of mathematical and spatial modelling to
explore the risk factors through various regression models, to explore the relation
between socio-economic conditions and disease incidence, and also other
techniques including classification analysis, decision models, and simulation to
evaluate screening options. Based on the risk factors and risk grouping, different
groups may have different screening policies. Alternatively, geographical
differences can be taken into account by dividing areas into a few parts; the
population living in each part may be considered to have different risks of
developing cervical cancer or Chlamydia in their life time. Therefore, different
screening programmes and services could be provided to those populations
according their location or the risk groups which they belong to.
Cheng, Man Ying Edith
6e8fc1c1-6355-4998-8875-1a57c833b5f0
February 2009
Cheng, Man Ying Edith
6e8fc1c1-6355-4998-8875-1a57c833b5f0
Atkinson, Peter M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Cheng, Man Ying Edith
(2009)
Regression modelling of cervical cancer and Chlamydia incidence
in the context of national screening programmes.
University of Southampton, School of Geography, Doctoral Thesis, 244pp.
Record type:
Thesis
(Doctoral)
Abstract
Prevention of cervical cancer development or reduction in undetected Chlamydia
incidence and further onward Chlamydia transmission can be achieved through
regular screening. Early detection through a regular screening programme is
essential to achieve this goal. A well established screening policy is needed to
improve screening efficiency.
This PhD study demonstrated the use of mathematical and spatial modelling to
explore the risk factors through various regression models, to explore the relation
between socio-economic conditions and disease incidence, and also other
techniques including classification analysis, decision models, and simulation to
evaluate screening options. Based on the risk factors and risk grouping, different
groups may have different screening policies. Alternatively, geographical
differences can be taken into account by dividing areas into a few parts; the
population living in each part may be considered to have different risks of
developing cervical cancer or Chlamydia in their life time. Therefore, different
screening programmes and services could be provided to those populations
according their location or the risk groups which they belong to.
Text
Cheng_Thesis.pdf
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More information
Published date: February 2009
Organisations:
University of Southampton
Identifiers
Local EPrints ID: 69712
URI: http://eprints.soton.ac.uk/id/eprint/69712
PURE UUID: 288b7a7b-777b-4973-9dfa-c5adf857eb0d
Catalogue record
Date deposited: 27 Nov 2009
Last modified: 14 Mar 2024 02:37
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Contributors
Author:
Man Ying Edith Cheng
Thesis advisor:
Peter M. Atkinson
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