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Modeling Syndromic Surveillance and ...

Pettie, Christa Daniella.

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Modeling Syndromic Surveillance and Outbreaks in Subpopulations.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modeling Syndromic Surveillance and Outbreaks in Subpopulations./
作者:	Pettie, Christa Daniella.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	108 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-01, Section: B.
Contained By:	Dissertations Abstracts International82-01B.
標題:	Public health. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27737948
ISBN:	9798662464889

Modeling Syndromic Surveillance and Outbreaks in Subpopulations.
Pettie, Christa Daniella.

Modeling Syndromic Surveillance and Outbreaks in Subpopulations. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 108 p.

Source: Dissertations Abstracts International, Volume: 82-01, Section: B.

Thesis (Ph.D.)--University of Maryland, College Park, 2020.

This item must not be sold to any third party vendors.

This research is motivated by the need to assist resource limited communities by enhancing the use of syndromic surveillance (SyS) systems and data. Public health agencies and academic researchers have developed and implemented SyS systems as a pattern recognition tool to detect a potential disease outbreak using pre-diagnostic data. SyS systems collect data from multiple types of sources: absenteeism records, over the counter medicine sales, chief complaints, web queries, and more. It could be expensive, however, to gather data from every available source; subsequently, gathering information about only some subpopulations may be a desirable option. This raises questions about the differences between subpopulation behavior and which subpopulations' data would give the earliest, most accurate warning of a disease outbreak. To investigate the feasibility of using subpopulation data, this research will gather and organize SyS data by subpopulation (separated by population characteristics such as age or location) and identify how well the SyS data correlates to the real world disease progression. This research will study SyS how reports of Influenza-like-illness (ILI) in subpopulations represent the disease behavior. The first step of the research process is to understand how SyS is used in environments with varying levels of resources and what gaps are present in SyS modeling techniques. Various modeling techniques and applications are assessed, specifically the Susceptible Infected Recovered "SIR" model and associated modifications of that model. Through data analysis, well correlated subpopulations will be identified and compared to actual disease behavior and SyS data sets. A model referred to as ModSySIR will be presented that uses real world community data ideal for ease of use and implementation in a resource limited community. The highest level research objective is to provide a potential data analysis method and modeling approach to inform decision making for health departments using SyS systems that rely on fewer resources.

ISBN: 9798662464889Subjects--Topical Terms:

534748
Public health.
Subjects--Index Terms:

Influenza

Modeling Syndromic Surveillance and Outbreaks in Subpopulations.
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