IEN Seminar Series: Analytical Modeling for Infectious Disease Control Interventions
Friday, November 12, 2021 1:30pm
About this Event
1251 Memorial Dr, Coral Gables, FL 33146
IEN Seminar Series: Analytical Modeling for Infectious Disease Control Interventions
Giovanni Malloy, Stanford University
Date: Friday, Nov. 12, 1:30 pm
Location: McArthur Engineering Building, Room 220
Questions? Contact Murat Erkoc at merkoc@miami.edu
About the Speaker
Giovanni Malloy is a PhD Candidate in Management Science and Engineering at Stanford University. His research focuses on developing computational models and improving analytical methods for guiding health policy decision making. He uses complex networks, machine learning, data analytics, and economic modeling to better understand disease dynamics and intervention effectiveness with applications in preparation and response for infectious disease outbreaks. His work spans COVID-19 mitigation in jails and prisons, structural sensitivity analyses, cost-effectiveness analyses, and developing analytical and metamodel alternatives to traditional model archetypes.
Abstract
In the United States, approximately 2.2 million people are incarcerated on any given day in over 5,000 jails and prisons. The built environment and activities of daily living in correctional facilities make physical distancing exceedingly difficult to implement. In June 2020, correctional facilities accounted for 8 of the 10 largest COVID-19 outbreaks nationally, and one of the largest of those outbreaks was in Cook County jail. To mitigate this outbreak, the jail undertook three major interventions beyond the scope of national guidelines – depopulation, single celling, and asymptomatic testing. After implementation, the question remained: how did these interventions reduce the spread of COVID-19 in the jail? To answer this question, I developed a stochastic dynamic transmission model describing the spread of COVID-19 in Cook County jail and calibrated the model to jail incidence and census data from March to June 2020. Using the model, I quantified the reduction in transmission rate over time as a result of each intervention. In total, the jail’s interventions prevented approximately 83% of projected cases, hospitalizations, and deaths over 83 days. This work shows that depopulation, single celling, and asymptomatic testing within jails can be effective strategies to mitigate COVID-19 transmission and save lives.
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