When will the pandemic end? This is a question that has been asked consistently since COVID-19 emerged. However, end-of-epidemic determination is a difficult issue to tackle, often defaulting to conservative estimates that do not reflect the transmission dynamics of the disease-causing pathogen in question. This seminar will provide an overview of historical methods for determining the end of an epidemic and describe how mathematical modeling methods can be used instead to better optimize end-of-epidemic determination. This optimization is needed because premature declarations that epidemics are over may undermine earlier achievements in disease control and result in a resurgence of cases. However, unnecessary delays in declaring epidemics over can also prolong the use of public health interventions that can induce negative economic and social consequences. Appropriate declarations that balance the benefits of releasing control measures against the risk of a surge in cases thereby allow public health resources to be conserved (and economic and social pressures to be reduced) while limiting the potential for additional transmission.
Natalie Linton graduated from Oregon State University with an MPH in Epidemiology in 2015 and is finishing up a PhD in infectious disease modeling at Hokkaido University in Japan. She previously worked at a local health department in Eastern Oregon and the Washington State Department of Health. Her interests are in global health, infectious disease epidemiology, and mathematical epidemiology. Although born and raised in a beach town, she is a mountain person at heart and can be found in the mountains year-round. You can find her on Twitter at @nlinton_epi or information about her work at nlinton.github.io.
Wednesday, November 17 at 5:00pm to 6:00pmVirtual Event