{"id":{"repo_id":"soton","oai_identifier":"oai:eprints.soton.ac.uk:69712"},"canonical_url":"https://search.dev.ndltd.org/etd/soton/oai:eprints.soton.ac.uk:69712","repository":{"repo_id":"soton","name":"University of Southampton","base_url":"https://eprints.soton.ac.uk/cgi/oai2"},"display":{"title":"Regression modelling of cervical cancer and Chlamydia incidence in the context of national screening programmes","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.<br/>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.","abstract_html":"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.&lt;br/&gt;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.","abstract_has_math":false,"creators":["Cheng, Man Ying Edith"],"institution":"University of Southampton","degree_name":"Ph.D.","degree_level":"doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Atkinson, Peter M."],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009-02","date_published":"2009-02","updated_at":"2026-07-24T04:36:06Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Atkinson, Peter M."]},{"key":"dc:creator","label":"Author","values":["Cheng, Man Ying Edith"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2009-02"]},{"key":"dc:date.issued","label":"Date","values":["2009-02"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Geography (pre 2011 reorg)","School of Geography"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Southampton"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://eprints.soton.ac.uk/69712/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Ph.D."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://eprints.soton.ac.uk/69712/1/Cheng_Thesis.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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.<br/>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."]},{"key":"dc:format","label":"Dc Format","values":["text"]},{"key":"dc:title","label":"Title","values":["Regression modelling of cervical cancer and Chlamydia incidence in the context of national screening programmes"]}]}],"canonical_facts":{"dc:contributor.advisor":["Atkinson, Peter M."],"dc:creator":["Cheng, Man Ying Edith"],"dc:date":["2009-02"],"dc:date.issued":["2009-02"],"dc:description.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.<br/>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."],"dc:format":["text"],"dc:identifier.uri":["https://eprints.soton.ac.uk/69712/1/Cheng_Thesis.pdf"],"dc:publisher.department":["Geography (pre 2011 reorg)","School of Geography"],"dc:publisher.institution":["University of Southampton"],"dc:relation.isreferencedby":["https://eprints.soton.ac.uk/69712/"],"dc:title":["Regression modelling of cervical cancer and Chlamydia incidence in the context of national screening programmes"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["Ph.D."]},"updated_at":"2026-07-24T04:36:06Z"}