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Data-Driven Approaches to Understand the Implications of Social Processes for Infectious Disease Risk.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data-Driven Approaches to Understand the Implications of Social Processes for Infectious Disease Risk./
作者:	Naraharisetti, Ramya.
面頁冊數:	1 online resource (172 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-12, Section: A.
Contained By:	Dissertations Abstracts International84-12A.
標題:	Public health. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30548552click for full text (PQDT)
ISBN:	9798379566609

Data-Driven Approaches to Understand the Implications of Social Processes for Infectious Disease Risk.
Naraharisetti, Ramya.

Data-Driven Approaches to Understand the Implications of Social Processes for Infectious Disease Risk. - 1 online resource (172 pages)

Source: Dissertations Abstracts International, Volume: 84-12, Section: A.

Thesis (Ph.D.)--University of Michigan, 2023.

Includes bibliographical references

Generally, social determinants or social factors have been studied in the context of non-communicable diseases yet there is a critical need to elucidate the mechanisms behind social and environmental factors which affect communicable disease spread in different spatio-temporal and geographic contexts with the explicit purpose of informing policy, intervention and study design. Social determinants of health frameworks are useful for infectious diseases but lack the ability to translate said mechanisms onto processes that are specific to pathogen spread such as environmentally mediated, vector-borne and direct transmission, transmission cycles and exposure routes in a meaningful way. The focus of most transmission models which investigate social factors, have been within long-term infections and far fewer studies exist of social factors which drive acute infections such as influenza and enteric disease. Given the nature of health inequities within the SARS-CoV-2 pandemic recently, there has been a renewed call for social variables to be incorporated into the study of infectious disease to generate a coherent framework. What is lacking then is an overarching framework which can account for the unique ways social and environmental factors impact systems of pathogenic spread across long-term and acute infections. The overarching goal of my research is to elucidate the mechanisms behind social and environmental factors which affect pathogen spread in different spatio-temporal and geographic contexts to inform policy, intervention and study design to inform such a framework. Each aim within this thesis delves into the heterogeneity of social and environmental mechanisms over time and across space. The first paper emphasizes the role of changing social mechanisms over time to examine COVID-19 disparities. The second utilizes space as a dimension of variability and seeks to identify clusters of infectious disease outcomes across two time periods. The third adds more complexity and asks how social context and spatial context interact to increase infectious disease risk. Each of my papers also delves into the heterogeneity of social mechanisms across different geographic contexts. My second paper looks at social mechanisms at the marco level within the low-middle income country of India, my first paper looks at meso-level mechanisms in the state of Michigan within the United States and the last paper looks at micro-level mechanisms within six communities in the northwestern region of Ecuador. Overall, the exploration of social mechanisms over time, spatial mechanisms over time and the interaction of social and spatial mechanisms across different geographic contexts advances the concept of a socially and environmentally informed framework for infectious disease systems.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798379566609Subjects--Topical Terms:

534748
Public health.
Subjects--Index Terms:

Infectious diseaseIndex Terms--Genre/Form:

542853
Electronic books.

Data-Driven Approaches to Understand the Implications of Social Processes for Infectious Disease Risk.
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