Design and simulation of quarantine policy and wastewater early detection against future pandemics

Abstract

It has been widely debated which policies could have been improved to further mitigate the COVID-19 pandemic. There is a long history of interventions against infectious outbreaks, yet much is not understood about the efficacies of these policies and how to best implement them. This understanding is critical given governmental proposals to make billion-dollar investments in preparedness for future pandemics. In this thesis, we quantitatively studied the design and efficacy of two policies: quarantine and early detection. First, in response to the CDC's November 2020 alternative recommendation of a 7-day test-based quarantine, we used SARS-CoV-2 test data from 301 quarantined university students and staff to quantify transmission risk from quarantines of different durations, leading us to recommend a 10-day quarantine to limit such risk to 5%. As future pathogens emerge, similar analysis can be conducted to guide quarantine policy. Second, looking forward to future pandemics, we developed an infectious disease simulation model to estimate whether hospital, wastewater or air travel early detection systems can provide early warning for a wide variety of pathogens, including COVID-19, monkeypox, polio, flu, and Ebola. We found that the benefits of early detection systems can vary from marginal (0.4 weeks earlier for COVID-19) to significant (110 weeks earlier for HIV/AIDS). These results can help policymakers judiciously design and invest in effective quarantine policies and detection systems for future pandemics.