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Thesis

Human-environment interactions on infectious disease risk in Brazil

Abstract:

Emerging and re-emerging infectious diseases pose a major threat to global health, yet little is known about their complex socio-ecological pathways that impact population health disproportionately at fine spatial scales. This is common in low-and middle-income countries with stark inequalities such as Brazil, which faces unprecedented changes in land-use and climate, and the burden of several epidemics, including the Zika virus, yellow fever virus, and SARS-CoV-2 responsible for the COVID-19 pandemic. This thesis presents research conducted on these diseases to advance knowledge on the relationships of ecological-epidemiological factors in natural and socio-institutional settings, which shape differential population risk to infectious diseases in Brazil.

Guided by the theoretical frameworks of disease ecology and landscape epidemiology, this thesis uses large open-access datasets, GIS, and statistical modelling to explore the geographic spread of Zika virus, the emergence of yellow fever virus in the natural environment, differential risk to COVID-19 spread in the built environment, and population response to COVID-19 via immunisation. Forest cover and temperature fostered the environmental suitability of yellow fever, while race, income, and healthcare systems contributed to inequalities in access to COVID-19 testing, infection, and death. Mass vaccination campaigns illustrated in the context of COVID-19 showed that vaccine coverage varies by area, age, race, sex, and socioeconomic status. In these settings, population interconnectivity via settlement, mobility, and behaviour significantly influenced disproportionate geographic exposure to disease risk.

Findings and implications from this research can be used to inform public health policies and interventions in Brazil. Future research should continue to explore the integration of large open-access datasets for understanding geographical inequalities in disease risk.

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Division:
SSD
Department:
SOGE
Role:
Author

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Role:
Supervisor
Role:
Supervisor


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Funder identifier:
http://dx.doi.org/10.13039/501100004211
Grant:
Programme on Pandemic Genomics
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Funder identifier:
http://dx.doi.org/10.13039/501100000155
Grant:
752-2019-0224
Oxford Martin School Programme on Pandemic Genomics
Keble College
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Funder identifier:
http://dx.doi.org/10.13039/100010347


Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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