|Talks|

Optimizing management decisions for control of infectious disease outbreaks

Hybrid
Visiting speaker
Past Talk
Emily Howerton
Ph.D. Candidate, Penn State University
Feb 6, 2023
11:00 am
Feb 6, 2023
11:00 am
In-person
4 Thomas More St
London E1W 1YW, UK
The Roux Institute
Room
100 Fore Street
Portland, ME 04101
Network Science Institute
2nd floor
Network Science Institute
11th floor
177 Huntington Ave
Boston, MA 02115
Network Science Institute
2nd floor
Room
58 St Katharine's Way
London E1W 1LP, UK

Talk recording

Responding to and managing infectious disease outbreaks is a persistent challenge. With limited resources, maximizing efficiency and efficacy of these control efforts is essential. Here, I present three examples across an array of systems to demonstrate how we can make better use of management resources, especially in the face of uncertainty. I show that governance structure (i.e., the allocation of resources across geo-political units) can have a significant effect on the equity of epidemiological outcomes, demonstrate an approach for designing control strategies that leverage multiple interventions, and discuss how we can combine predictions from multiple models to better represent uncertainty for planning.

About the speaker
Emily Howerton is a Ph.D. candidate in the Department of Biology at Penn State University. She uses mathematical models to design strategies for controlling infectious diseases in the face of uncertainty, most recently focusing on the COVID-19 pandemic. For example, Emily has modeled the interaction between diagnostic testing and non-pharmaceutical interventions to identify optimal combination management strategies. Emily is also a member of COVID-19 Scenario Modeling Hub coordination team, where she develops methods to capture uncertainty from multiple models in 6-month projections of COVID-19 outcomes. In particular, she has adapted aggregation and evaluation methods from multiple fields to accommodate the unique needs of infectious disease scenario projections.
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Feb 06, 2023