Biomathematics
Department of Mathematics and Statistics
Texas Tech University
In this work, we revisited the evaluation of the effectiveness of the COVID-19 vaccination campaign in 2021, as measured by the number of deaths averted. The published estimates differ a lot: from one widely referenced paper by Watson et alia (2022) estimating 0.5-0.6% of the USA population being saved, to average-level estimates of 0.15-0.2%, and to some estimates as low as 0.0022%. For other countries, Watson et al. gave much higher estimates than all other works too. We reviewed 30 relevant papers, carried out an in-depth analysis of the model by Watson et al. and of several other studies, and provided our own regression-based analysis of the US county-level data. The model by Watson et al. is very sophisticated and has many features; some of them that make it more realistic (age-structured epidemiology, elderly first vaccination, healthcare overload effects), but others that are likely inaccurate (substantial reinfection rates (i.e., immunity loss) for the Alpha and Delta variants, possible overfitting due to overly flexible time-dependent infection transmission rate) or questionable (45% increase in fatality rate for the Delta variant). Yet, the main argument is that Watson et al.’s model does not reproduce the trends observed in the county-level US data. Eventually, we concluded that Watson et al.'s 0.5-0.6% is an overestimate, and 0.15-0.2% of the US population saved by vaccination — as estimated by regression studies on subnational-level data (e.g., Suthar et al. (2022) and by He et al. (2022)) — is much more plausible value.
In our view, in order to be considered reliable, mathematical models should be tested on more detailed real data that was not used in model fitting. On the other hand, detailed data bring about new challenges in statistical modelling and uncertainties in data reliability.
Zoom link
Meeting ID: 953 8930 8090
Passcode: Biomath
Bring your own lunch and discuss (mostly) biology-related topics in math. Students, postdocs and faculty welcome from any discipline.
See the pdf flyer for this semester's schedule.
Bring your own lunch and discuss (mostly) biology-related topics in math. Students, postdocs and faculty welcome from any discipline.
See the pdf flyer for this semester's schedule.
Bring your own lunch and discuss (mostly) biology-related topics in math. Students, postdocs and faculty welcome from any discipline.
See the pdf flyer for this semester's schedule.
Bring your own lunch and discuss (mostly) biology-related topics in math. Students, postdocs and faculty welcome from any discipline.
See the pdf flyer for this semester's schedule.
We study an ecosystem of three keystone species: salmon, bears, and vegetation. Bears consume salmon and vegetation for energy and nutrient intake but the food quality differs significantly due to the nutritional level difference between salmon and vegetation. We propose a stoichiometric predator-prey model that not only tracks the energy flow from one trophic level to another but also nutrient recycling in the system. Analytical results show that bears may coexist with salmon and vegetation at a steady state but the abundance of salmon may differ under different regimes. Numerical simulations reveal that a smaller vegetation growth rate may drive the vegetation population to extinction whereas a large vegetation growth rate may drive the salmon population to extinction. Moreover, a large vegetation growth rate may stabilize the system where the bear, salmon, and vegetation populations oscillate periodically.
Zoom link
Meeting ID: 564 796 5924
Passcode: Wenjing
Bring your own lunch and discuss (mostly) biology-related topics in math. Students, postdocs and faculty welcome from any discipline.
See the pdf flyer for this semester's schedule.
Bring your own lunch and discuss (mostly) biology-related topics in math. Students, postdocs and faculty welcome from any discipline.
See the pdf flyer for this semester's schedule.