{"id":{"repo_id":"ku","oai_identifier":"oai:kuscholarworks.ku.edu:1808/37933"},"canonical_url":"https://search.dev.ndltd.org/etd/ku/oai:kuscholarworks.ku.edu:1808/37933","repository":{"repo_id":"ku","name":"University of Kansas","base_url":"https://kuscholarworks.ku.edu/server/oai/request"},"display":{"title":"The Dynamics of the Spread of COVID-19 in Kansas","abstract":"Researchers from various disciplines have studied the factors influencing the rapid spread of COVID-19. Prior studies have reported demographic, socioeconomic, environmental, and health related factors that may influence the diffusion of the virus. Most of these studies, however, used a cross sectional approach at a national scale. Such analysis may hide region specific temporal, spatial, and societal dynamics of the disease that influence its spread. My two part-study investigates the dynamics of the spread of COVID-19 in Kansas by dividing the timeline for the COVID-19 outbreak into phases based on key events, interventions, and policies implemented in Kansas. I used nonparametric tests, spatial, and statistical modeling, to understand the spread of COVID-19. My findings revealed how the pattern and type of diffusion, the relationship between cases and deaths, and the factors that influenced the spread of COVID-19 cases and its associated deaths varied over time. This can be linked to particular human geographic variables such as transportation hubs, age, and occupation of people. Overall, this study has demonstrated how focusing on more localized dynamics across different phases of the pandemic within the state of Kansas provides a more detailed understanding of how a disease like COVID-19 can spread.","abstract_html":"Researchers from various disciplines have studied the factors influencing the rapid spread of COVID-19. Prior studies have reported demographic, socioeconomic, environmental, and health related factors that may influence the diffusion of the virus. Most of these studies, however, used a cross sectional approach at a national scale. Such analysis may hide region specific temporal, spatial, and societal dynamics of the disease that influence its spread. My two part-study investigates the dynamics of the spread of COVID-19 in Kansas by dividing the timeline for the COVID-19 outbreak into phases based on key events, interventions, and policies implemented in Kansas. I used nonparametric tests, spatial, and statistical modeling, to understand the spread of COVID-19. My findings revealed how the pattern and type of diffusion, the relationship between cases and deaths, and the factors that influenced the spread of COVID-19 cases and its associated deaths varied over time. This can be linked to particular human geographic variables such as transportation hubs, age, and occupation of people. Overall, this study has demonstrated how focusing on more localized dynamics across different phases of the pandemic within the state of Kansas provides a more detailed understanding of how a disease like COVID-19 can spread.","abstract_has_math":false,"creators":["Adela, Charity Dzifah"],"institution":"University of Kansas","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Brown, Christopher"],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-05-31","date_published":"2025-05-31","updated_at":"2026-07-24T02:44:44Z","subjects":["Geography","COVID-19","Disease diffusion","Kansas","Non-Parametric test","Spatial analysis","Spatial Durbin Model"],"languages":["en"],"rights":["This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["https://www.proquest.com/LegacyDocView/DISSNUM/32114345"],"render_values":[{"text":"https://www.proquest.com/LegacyDocView/DISSNUM/32114345","href":"https://www.proquest.com/LegacyDocView/DISSNUM/32114345","code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/1808/37933","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Brown, Christopher"]},{"key":"dc:creator","label":"Author","values":["Adela, Charity Dzifah"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-04-21T22:13:58Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-04-21T22:13:58Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-05-31"]},{"key":"dc:publisher","label":"Institution","values":["University of Kansas"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Geography","COVID-19","Disease diffusion","Kansas","Non-Parametric test","Spatial analysis","Spatial Durbin Model"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["https://www.proquest.com/LegacyDocView/DISSNUM/32114345"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1808/37933"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Researchers from various disciplines have studied the factors influencing the rapid spread of COVID-19. Prior studies have reported demographic, socioeconomic, environmental, and health related factors that may influence the diffusion of the virus. Most of these studies, however, used a cross sectional approach at a national scale. Such analysis may hide region specific temporal, spatial, and societal dynamics of the disease that influence its spread. My two part-study investigates the dynamics of the spread of COVID-19 in Kansas by dividing the timeline for the COVID-19 outbreak into phases based on key events, interventions, and policies implemented in Kansas. I used nonparametric tests, spatial, and statistical modeling, to understand the spread of COVID-19. My findings revealed how the pattern and type of diffusion, the relationship between cases and deaths, and the factors that influenced the spread of COVID-19 cases and its associated deaths varied over time. This can be linked to particular human geographic variables such as transportation hubs, age, and occupation of people. Overall, this study has demonstrated how focusing on more localized dynamics across different phases of the pandemic within the state of Kansas provides a more detailed understanding of how a disease like COVID-19 can spread."]},{"key":"dc:title","label":"Title","values":["The Dynamics of the Spread of COVID-19 in Kansas"]}]}],"canonical_facts":{"dc:contributor.advisor":["Brown, Christopher"],"dc:creator":["Adela, Charity Dzifah"],"dc:date.accessioned":["2026-04-21T22:13:58Z"],"dc:date.available":["2026-04-21T22:13:58Z"],"dc:date.issued":["2025-05-31"],"dc:description.abstract":["Researchers from various disciplines have studied the factors influencing the rapid spread of COVID-19. Prior studies have reported demographic, socioeconomic, environmental, and health related factors that may influence the diffusion of the virus. Most of these studies, however, used a cross sectional approach at a national scale. Such analysis may hide region specific temporal, spatial, and societal dynamics of the disease that influence its spread. My two part-study investigates the dynamics of the spread of COVID-19 in Kansas by dividing the timeline for the COVID-19 outbreak into phases based on key events, interventions, and policies implemented in Kansas. I used nonparametric tests, spatial, and statistical modeling, to understand the spread of COVID-19. My findings revealed how the pattern and type of diffusion, the relationship between cases and deaths, and the factors that influenced the spread of COVID-19 cases and its associated deaths varied over time. This can be linked to particular human geographic variables such as transportation hubs, age, and occupation of people. Overall, this study has demonstrated how focusing on more localized dynamics across different phases of the pandemic within the state of Kansas provides a more detailed understanding of how a disease like COVID-19 can spread."],"dc:identifier.other":["https://www.proquest.com/LegacyDocView/DISSNUM/32114345"],"dc:identifier.uri":["https://hdl.handle.net/1808/37933"],"dc:language.iso":["en"],"dc:publisher":["University of Kansas"],"dc:rights":["This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author."],"dc:subject":["Geography","COVID-19","Disease diffusion","Kansas","Non-Parametric test","Spatial analysis","Spatial Durbin Model"],"dc:title":["The Dynamics of the Spread of COVID-19 in Kansas"],"dc:type":["Thesis"]},"updated_at":"2026-07-24T02:44:44Z"}