Author ORCID Identifier

https://orcid.org/0000-0002-0917-5064

Date Available

5-15-2025

Year of Publication

2025

Document Type

Doctoral Dissertation

Degree Name

Doctor of Philosophy (PhD)

College

Engineering

Department/School/Program

Biomedical Engineering

Faculty

Scott Berry

Faculty

Sheng Tong

Abstract

Pandemic surveillance is a cornerstone in public health safety, as it enables identification of pathogens circulating within a community before they become widespread outbreaks. Wastewater based epidemiology has blossomed in recent years due to its success in the SARS-CoV-2 pandemic, but this form of public health surveillance has a global equity problem. A large majority of the wastewater-based surveillance work has been done in large metropolitan cities with access to advanced testing infrastructure, which poses a challenge as we consider where pandemics have historically emerged. Therefore, there is a need to identify, adapt, and develop workflows to meet the needs of low- and middle-income-countries for public health surveillance.

Most standard approaches to wastewater-based epidemiology are centralized, which rely on cold-chain shipping (e.g., sample refrigeration is maintained throughout the shipping process) to a large industrial or government laboratory. This poses a major logistical and data ownership issue for scientists in areas of the world, such as Sub-Saharan Africa, where public health surveillance is needed the most. The main objective of this work is to improve wastewater-based epidemiology methods to better serve current and future public health concerns.The main objective of this work is to

Through collaboration with in-country scientists, I developed workflows and cross-training materials to build pandemic surveillance expertise within Sub-Saharan Africa. Single analyte data endpoints, such as PCR or immunoassays, are well understood and sensitive for wastewater-based analysis. However, there is a need for analyte-agnostic endpoints to identify emerging pathogens or circulating drug resistance gene biomarkers in a community. We utilized the long-read sequencing devices from Oxford Nanopore Technologies that can be deployed in-country. This decentralized model favors an equitable international wastewater analysis workflow, where collaborating countries are able to control their data from collection to analysis. The developed decentralized approach presented in this work also reduces the “time-to-answer” drastically, eliminating cold-chain storage requirements or international shipping.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2025.73

Funding Information

This work was funded by National Institutes of Health grants 1U01DA053903-01 and P30 ES026529, Centers for Disease Control and Prevention contract BAA 75D301-20-R-68024 and pilot funding from the UK Center for Clinical and Translational Science. National Science Foundation (No. 21-590), and National Science Foundation grant 2154934.

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