Infectious Disease Surveillance Using Emerging Data Sources: Applications to Antimicrobial Resistance and COVID-19

The COVID-19 pandemic has reawakened public awareness of the deadly threat posed by infectious diseases in our interconnected world. We face mounting challenges in tackling both emerging diseases as well as longstanding threats like the rising tide of antimicrobial resistance. Simultaneously, the digital revolution has unleashed a vast array of data applicable to the critical task of infectious disease surveillance. In this dissertation, I explore the use of emerging data sources to answer questions about two of the most important global health crises of our time: the COVID-19 pandemic and antimicrobial resistance. In the first study, I analyzed human mobility data from a public transit app to estimate the association of mobility reductions with the COVID-19 growth rate and reproduction number during the first wave of the pandemic across 41 global cities. I found that a 10% decline in mobility was associated with a 12.2% reduction in weekly growth rate and a 0.058 decrease in the effective reproduction number. These results persisted, albeit at a smaller magnitude, in a model adjusted for epidemic timing. In the second study, I developed a novel metric to measure the responsiveness of population-level mobility to reported COVID-19 incidence in Canadian provinces and U.S. states from December 2020 to November 2021. Results suggested that responsiveness to rising COVID-19 cases was stronger in Canada compared to the U.S. and revealed a correlation between greater responsiveness and lower reported COVID-19 death rates. In the third study, I evaluated the effectiveness of an automated feedback intervention for antimicrobial stewardship among primary care physicians in Canada and Israel, using concurrent controls drawn from two large primary care databases. The results showed a reduction in the mean duration of prescribing for antibiotics in the intervention group, but no statistically significant decline in overall or indication-specific antibiotic prescribing. This dissertation showcases the potential of human mobility data and large primary care databases for enhancing surveillance of infectious disease outbreaks and shaping interventions in antimicrobial stewardship. Continued research is necessary to effectively harness new and emerging data sources to address both current and future global infectious disease threats.

Department dc:contributor.department

Dalla Lana School of Public Health

Year dc:date.issued

2024

Author dc:creator

• Soucy, Jean-Paul Ryker

Advisors dc:contributor.advisor

• Brown, Kevin A
• Fisman, David N

• Antimicrobial resistance
• Antimicrobial stewardship
• COVID-19
• Human mobility
• Infectious disease surveillance
• SARS-CoV-2

Statement dc:rights

• Attribution 4.0 International

Licence dc:rights.uri

• http://creativecommons.org/licenses/by/4.0/

Handle dc:identifier.uri

http://hdl.handle.net/1807/138074

OAI identifier oai:identifier

oai:utoronto.scholaris.ca:1807/138074