Presented By: The Center for the Study of Complex Systems
A human-environment systems approach to prioritizing COVID-19 vaccination
Madhur Anand - University of Guelph and Chris Bauch - University of Waterloo
SEMINAR LINK: https://umich.zoom.us/s/96616169868
Madhur Anand - School of Environmental Sciences
Chris Bauch - Department of Math, Applied Math
Join us THURSDAY January 28 at 11:30 am for our first VIRTUAL SEMINAR of 2021.
Abstract:
During the COVID-19 pandemic, authorities must decide which groups to prioritize for vaccination in an evolving landscape where infection dynamics and population mitigating behavior are mutually connected in a feedback loop (i.e., human-environment interactions). Moreover, if we discover that vaccines prevent not only disease but also transmission, authorities must factor vaccine indirect protection (vaccine-generated herd immunity) into their considerations, which sometimes suggest a strategy of targeting groups that cause the most transmission. In this talk we will use a mathematical model to address the question: which age group should be prioritized for COVID-19 vaccination in order to prevent the most deaths? We developed an age-structured human-environment mathematical model for Ontario, Canada, where evolutionary game theory describes how population adherence to non-pharmaceutical interventions (NPIs) responds to case incidence. Schools and workplaces are also closed and re-opened based on reported cases. We compared strategies of vaccinating 60+ year-olds first; <20 year-olds first; uniformly by age; and a novel contact-based strategy. The last three strategies interrupt transmission while the first targets a vulnerable group. The model shows realistic dynamics whereby case notifications, NPI adherence, and lockdown undergo successive waves that interact with timing of the vaccine program to determine the relative effectiveness of the four strategies. We identify a parameter regime where transmission-interrupting strategies are more effective in preventing deaths than prioritizing older age groups. We conclude that using SARS-CoV-2 vaccines to interrupt transmission may prevent more deaths than prioritizing vulnerable age groups, depending on the time course of the pandemic in a given population.
Madhur Anand - School of Environmental Sciences
Chris Bauch - Department of Math, Applied Math
Join us THURSDAY January 28 at 11:30 am for our first VIRTUAL SEMINAR of 2021.
Abstract:
During the COVID-19 pandemic, authorities must decide which groups to prioritize for vaccination in an evolving landscape where infection dynamics and population mitigating behavior are mutually connected in a feedback loop (i.e., human-environment interactions). Moreover, if we discover that vaccines prevent not only disease but also transmission, authorities must factor vaccine indirect protection (vaccine-generated herd immunity) into their considerations, which sometimes suggest a strategy of targeting groups that cause the most transmission. In this talk we will use a mathematical model to address the question: which age group should be prioritized for COVID-19 vaccination in order to prevent the most deaths? We developed an age-structured human-environment mathematical model for Ontario, Canada, where evolutionary game theory describes how population adherence to non-pharmaceutical interventions (NPIs) responds to case incidence. Schools and workplaces are also closed and re-opened based on reported cases. We compared strategies of vaccinating 60+ year-olds first; <20 year-olds first; uniformly by age; and a novel contact-based strategy. The last three strategies interrupt transmission while the first targets a vulnerable group. The model shows realistic dynamics whereby case notifications, NPI adherence, and lockdown undergo successive waves that interact with timing of the vaccine program to determine the relative effectiveness of the four strategies. We identify a parameter regime where transmission-interrupting strategies are more effective in preventing deaths than prioritizing older age groups. We conclude that using SARS-CoV-2 vaccines to interrupt transmission may prevent more deaths than prioritizing vulnerable age groups, depending on the time course of the pandemic in a given population.
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