dc.contributor.advisor | Murray, Megan B. | |
dc.contributor.author | Li, Ruoran | |
dc.date.accessioned | 2020-07-02T12:00:12Z | |
dash.embargo.terms | 2021-05-01 | |
dc.date.created | 2020-05 | |
dc.date.issued | 2020-04-24 | |
dc.date.submitted | 2020 | |
dc.identifier.citation | Li, Ruoran. 2020. Understanding Epidemiologic Risks for Infectious Disease Control. Doctoral dissertation, Harvard T.H. Chan School of Public Health. | |
dc.identifier.uri | http://nrs.harvard.edu/urn-3:HUL.InstRepos:42676030 | * |
dc.description.abstract | As of April 2020, the coronavirus disease 2019 (COVID-19) pandemic has already irreversibly changed our perception of the field of infectious diseases. The first two chapters in this thesis were completed in the pre-2020 era, when we focused on developing tools to inform tuberculosis (TB) control programs in high-burden countries. The last chapter is our quick response to the emerging COVID-19 pandemic, in which we described the disease burden on healthcare resources in cities in China and explored its implication for cities in the United States.
One common theme in all three chapters is our focus on epidemiologic risks. In Lima, Peru, can we predict the risk of disease progression among household contacts of TB patients to better their clinical management (Chapter 1)? In India, how can we use information about the distribution of TB risk factors to identify populations who were missed by disease surveillance systems (Chapter 2)? And finally, how to translate experience from one city to another during a pandemic, when the underlying populations have potentially different risk profiles (Chapter 3)?
While TB continues to plague our most vulnerable population, knowledge about risk and risk factors for the COVID-19 will start to accumulate. The enclosed three chapters are our exploration of how epidemiologic risks could help with infectious disease control programs. | |
dc.description.sponsorship | Epidemiology | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dash.license | LAA | |
dc.subject | tuberuclosis | |
dc.subject | covid-19 | |
dc.subject | epidemiology | |
dc.subject | risk factors | |
dc.subject | prediction models | |
dc.subject | LMICs | |
dc.subject | infectious diseases | |
dc.subject | disease control | |
dc.subject | surveillance | |
dc.subject | critical care | |
dc.subject | healthcare capacity | |
dc.title | Understanding Epidemiologic Risks for Infectious Disease Control | |
dc.type | Thesis or Dissertation | |
dash.depositing.author | Li, Ruoran | |
dash.embargo.until | 2021-05-01 | |
dc.date.available | 2020-07-02T12:00:12Z | |
thesis.degree.date | 2020 | |
thesis.degree.grantor | Harvard T.H. Chan School of Public Health | |
thesis.degree.grantor | Harvard T.H. Chan School of Public Health | |
thesis.degree.level | Doctoral | |
thesis.degree.level | Doctoral | |
thesis.degree.name | Doctor of Science (SD) | |
thesis.degree.name | Doctor of Science (SD) | |
dc.contributor.committeeMember | Lipsitch, Marc | |
dc.contributor.committeeMember | Nordio, Francesco | |
dc.type.material | text | |
thesis.degree.department | Epidemiology | |
thesis.degree.department | Epidemiology | |
dash.identifier.vireo | | |
dc.identifier.orcid | 0000-0001-7575-2758 | |
dash.author.email | liruoran@gmail.com | |