12:00pm - Zoom - Probability and Analysis Webinar Stefanie Petermichl - (Universität Würzburg) TBA |
4:00pm to 5:00pm - Zoom - https://uci.zoom.us/j/97796361534 - Applied and Computational Mathematics Swati Patel - (Oregon State University) Fitting macroparasitic disease transmission models to geostatistical prevalence data In this talk, I will discuss applying a recently developed approach to estimate parameters of a disease transmission model for a group of macroparasites that infect an estimated 1.5 billion people worldwide. While the disease is widespread, its spread occurs on relatively local scales and the vulnerability of populations can vary from region to region. Hence, key epidemiological parameters of mechanistic transmission models vary across regions and understanding these differences is important for developing strategies to mitigate morbidity of the disease. We infer these parameters for 5183 distinct regional units across sub-Saharan Africa. Inferring these parameters is challenging since data is limited to relatively few points in space and time. Previously developed geostatistical maps use this limited data, along with socioeconomic and environmental indicators, to provide broad-scale distributional estimates of disease prevalence. Using a Bayesian statistical framework that employs an adaptive multiple importance sampling algorithm, we fit these geostatistical distributional data to a transmission model. We then use these parameterized transmission models to predict how various mitigation strategies will impact broad-scale disease prevalence. |
4:00pm - NS2 1201 - Differential Geometry Joshua Jordan - (UC Irvine) Pluriclosed flow on Bismut-flat manifolds In this talk, I will present parts of a recent paper written |
2:00pm to 3:00pm - 510R - Combinatorics and Probability Michael Cranston - (UCI) Properties of the Riemann zeta distribution. In this talk we will discuss properties of integers selected according to the Riemann zeta distribution. We will emphasize two aspects of this distribution. The first is its faithful similarity to properties of an integer chosen according to the uniform distribution on a finite interval. The second aspect will be the appearance of Poisson behavior under this distribution. The Riemann zeta function is given for $\mbox{Re} z>1$ by $$\zeta(z)=\sum_{n=1}^\infty \frac{1}{n^z}.$$ An alternative description is given by $$\zeta(z)=\Pi_{p\in\mathcal{P}}\lt(1-\frac{1}{p^z}\rt)^{-1},$$ where $\mathcal{P}$ denotes the set of primes. In our discussions we will replace the complex $z$ by a real number $s>1.$ We will denote by $X_s$ a random variable with the distribution P(X_s=n)=\frac{1}{\zeta(s)n^s},\, n=1,2,3,\cdots. The statistical properties of $X_s$ is the focus of the talk. The talk is based on joint work with Adrien Peltzer. |