{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/78596"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/78596","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Simulating the Spatial Spread of an Influenza Epidemic through an Urban Transportation Environment","abstract":"M.S.","abstract_html":"M.S.","abstract_has_math":false,"creators":["Patankar, Aditya Pradeep"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Kang, Jee Eun","Industrial and Systems Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-10-26T02:56:15Z","date_published":"2018-10-26T02:56:15Z","updated_at":"2026-07-27T19:05:12Z","subjects":["operations research","mathematics"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/78596","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kang, Jee Eun","Industrial and Systems Engineering"]},{"key":"dc:creator","label":"Author","values":["Patankar, Aditya Pradeep"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-10-26T02:56:15Z","2018","2018-08-09 16:13:53"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["operations research","mathematics"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/78596"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["M.S.","The spread of infectious diseases in densely populated urban areas and how to curb it is a topic of concern for the policymakers. This paper contributes to the research area of modeling the disease spread by considering one such infectious disease, Influenza. The common occurrence of Influenza and the ease with which it spreads is what attracts attention for this research. To the best of our knowledge, the literature with respect to the infectious disease epidemic modeling does not consider the spread through an urban transportation environment and this paper fills this gap in the research domain. This paper considers the bi-weekly data collected through the passengers using smart cards in buses in Seoul, South Korea and the model presented in this paper generates a list of all the infected individuals within the city. This model starts off with a finite number of infected individuals using buses within the city and then models the probability of infection spread to other susceptible individuals sharing the bus journey with these infected individuals. The unique probability of infection of each of the susceptible individuals obtained by considering their age, the amount of time they spend with the infectious individual and the crowdedness of the bus is compared to a randomly selected cut-off value to decide if the susceptible has been infected or not. The results obtained through this algorithm present the number of people infected on each day during this bi-weekly time period. The location coordinates associated with the journey also present information about the exact metropolitan area of the city to which these infected people belong. This paper presents this visualization through a heat map which helps identify the critical zones in the city having a large number of infectious individuals. This information provided to the policymakers will give them a perspective on where to focus their attention towards vaccine distribution in an attempt to curb the spread of Influenza."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Simulating the Spatial Spread of an Influenza Epidemic through an Urban Transportation Environment"]}]}],"canonical_facts":{"dc:contributor":["Kang, Jee Eun","Industrial and Systems Engineering"],"dc:creator":["Patankar, Aditya Pradeep"],"dc:date":["2018-10-26T02:56:15Z","2018","2018-08-09 16:13:53"],"dc:description":["M.S.","The spread of infectious diseases in densely populated urban areas and how to curb it is a topic of concern for the policymakers. This paper contributes to the research area of modeling the disease spread by considering one such infectious disease, Influenza. The common occurrence of Influenza and the ease with which it spreads is what attracts attention for this research. To the best of our knowledge, the literature with respect to the infectious disease epidemic modeling does not consider the spread through an urban transportation environment and this paper fills this gap in the research domain. This paper considers the bi-weekly data collected through the passengers using smart cards in buses in Seoul, South Korea and the model presented in this paper generates a list of all the infected individuals within the city. This model starts off with a finite number of infected individuals using buses within the city and then models the probability of infection spread to other susceptible individuals sharing the bus journey with these infected individuals. The unique probability of infection of each of the susceptible individuals obtained by considering their age, the amount of time they spend with the infectious individual and the crowdedness of the bus is compared to a randomly selected cut-off value to decide if the susceptible has been infected or not. The results obtained through this algorithm present the number of people infected on each day during this bi-weekly time period. The location coordinates associated with the journey also present information about the exact metropolitan area of the city to which these infected people belong. This paper presents this visualization through a heat map which helps identify the critical zones in the city having a large number of infectious individuals. This information provided to the policymakers will give them a perspective on where to focus their attention towards vaccine distribution in an attempt to curb the spread of Influenza."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/78596"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["operations research","mathematics"],"dc:title":["Simulating the Spatial Spread of an Influenza Epidemic through an Urban Transportation Environment"],"dc:type":["Text","Thesis"]},"updated_at":"2026-07-27T19:05:12Z"}