Abstract : Pathogen interactions with immune systems are dynamic. Modeling these nonlinear interactions has traditionally been a separate endeavor from modeling disease spread in a population. In
the current environment of accelerating zoonotic spillovers, in which increasing numbers of pathogens are adapting to new hosts, habitats that include within-host innate and adaptive immune
systems, as well as sequence-level data, should not be ignored. We bring together a diverse group of researchers to address the resulting multilevel modeling challenges. The three sessions in this
minisymposium will focus on:
1. vector-borne pathogens
2. Any Pathogen Transmission Mode
3. air- and water-borne pathogens
Organizer(s) : Julie Allison Spencer, Fabio Milner, Joel C. Miller
00955 (1/3) : 3E @A512 [Chair: Julie Allison Spencer]
[04516] Modelling vector-borne disease dynamics and the impact of new interventions
Format : Online Talk on Zoom
Author(s) :
Ilaria Dorigatti (Imperial College London)
Abstract : In this seminar, I will present recent modelling studies developed to analyse the transmission dynamics of vector-borne diseases and to quantify the efficacy of a new dengue antiviral drug (JNJ-1802) from in-vitro and in-vivo experiments and a dengue vaccine candidate (TAK-003) using phase-3 clinical trial data. These models can help assess the population-level impact of novel control interventions across transmission settings. I will discuss current challenges as well as opportunities.
[04353] Hierarchical model of West Nile virus incorporating spatio-temporal environmental effects
Format : Talk at Waseda University
Author(s) :
Laura Albrecht (Colorado School of Mines)
Abstract : West Nile virus is primarily transmitted between mosquitoes and birds, with humans as incidental hosts. Climate change may increase the risk of human infections as climatic variables have been shown to accelerate mosquito development, biting rates, and the incubation period of the disease. We developed a spatio-temporal hierarchical SEIR model that incorporates environmental covariates related to climate change. We use a Bayesian paradigm to fit our model and to predict human cases.
[04123] How genomic data can inform contact patterns in epidemiological models
Format : Talk at Waseda University
Author(s) :
Julie Allison Spencer (Los Alamos National Laboratory)
Emma Goldberg (Los Alamos National Laboratory)
Sara Del Valle (Los Alamos National Laboratory)
Abstract : Infectious diseases threaten global health, as illustrated by the COVID-19 pandemic. Population-level models have been essential for understanding and anticipating impacts, but their ability to forecast outcomes accurately has been limited due to the rapid evolution of viruses and limited availability of parameters. Using sequenced SARS-CoV-2 genomes with associated age metadata, we inferred phylogenetic trees and used a birth-death branching model to understand the role of heterogeneous age structure on transmission pathways.
[05574] Capturing heterogeneity: Differential effects of temperature on Culex mosquito vectors
Format : Talk at Waseda University
Author(s) :
Sarah Moser (Los Alamos National Laboratory)
Abstract : Culex spp. mosquitoes are the primary transmission vectors for West Nile virus (WNV) worldwide. The differential effects of temperature on mosquito range, distribution, and abundance pose challenges for disease forecasting and mitigation. Current models often assume a single vector species; through our scoping review on thermal response for Culex mosquito life history traits, we show the need to implement real-world species heterogeneity and present a useful data resource for modelers.
00955 (2/3) : 4C @A512 [Chair: Fabio Augusto Milner]
[04150] Immunological variables as structure variables of epidemic models
Format : Talk at Waseda University
Author(s) :
Fabio Augusto Milner (Arizona State University)
Abstract : We present some ways to structure epidemic models with infection and immune response as structure variables. The infected class is modeled using a divergence-form partial differential equation with the boundary conditions incorporating the new infections. Some theoretical results are derived, as well as some examples form HIV-infection. Open theoretical and numerical problems will be described.
[01323] Approximations and parameter inference of stochastic models in infectious disease epidemiology
Format : Online Talk on Zoom
Author(s) :
Wasiur KhudaBukhsh (University of Nottingham)
Abstract : In this talk, we will consider stochastic compartmental models in infectious disease epidemiology. We will discuss when the stochastic models agree with their deterministic counterparts in some limiting regimes and when one stochastic model can be approximated in some precise mathematical sense by another. We will also consider the problem of parameter inference of such systems using notions of dynamical survival analysis (DSA).
[04927] Intelligent immunity: wet labs, fat data, and machine learning
Format : Online Talk on Zoom
Author(s) :
Kaitlyn Martinez (Los Alamos National Laboratory)
Abstract : Developing a universal diagnostic is a long standing challenge. However, the human immune system is able to distinguish pathogens and mounts response quickly, perhaps acting as a guide for design of improved, more general diagnostic development. In collaboration with lab scientists, we use data from hundreds of experiments along with both machine learning and mechanistic models to show the potential for determining the presence of bacteria from markers of a human immune response.
[03423] Why do most sexually transmitted infections not produce long-term immunity?
Format : Talk at Waseda University
Author(s) :
Joel C Miller (La Trobe University)
Abstract : Diseases that are classified as "Susceptible-Infected-Recovered" (SIR) are unable to reinfect previously infected individuals. In small communities outbreaks are short-term and the disease is unable to persist. Long-term persistance of an SIR disease requires a large community or many connected small communities, so that new births replenish the susceptible community. The spread of sexually transmitted infections is heavily influenced by the significant heterogeneity of contact rates within the population. We will show that this increases the required "critical community size" for an SIR infection to persist in sexual transmission networks.
[04157] Basic concepts for the Kermack and McKendrick model with individual heterogeneity
Format : Talk at Waseda University
Author(s) :
Hisashi Inaba (Tokyo Gakugei University)
Abstract : The main purpose of my talk is to provide a mathematical basis for the recent arguments and calculations triggered by COVID-19 based on the heterogeneous Kermack-McKendrick model. The basic epidemiological concepts such as basic reproduction number, effective reproduction number, herd immunity threshold and final size are rigorously formulated based on the Kermack-McKendrick model with individual heterogeneity. Furthermore, we discuss a systematic recipe to reduce the infinite-dimensional system to the finite-dimensional ODE system.
[04524] Statistical analysis of global COVID-19 wave dynamics
Format : Talk at Waseda University
Author(s) :
Jessica Stockdale (Simon Fraser University)
Abstract : Different countries around the world experienced vastly different COVID-19 pandemics, and in many cases the complex interplay of driving forces behind this remain unclear. Patterns of hybrid and partial immunity affect the ability of new variants to invade, and therefore must be understood to build insightful predictive models. I will present our work in statistically modelling the relative influence of immunity, demographic, social, and other factors on the size and timing of variant-driven COVID-19 waves.
[03113] Will cross-immunity protect the community from COVID-19 variants?
Format : Online Talk on Zoom
Author(s) :
Marina Mancuso (Arizona State University)
Steffen Eikenberry (Arizona State University)
Abba Gumel (University of Maryland, College Park)
Abstract : The emergence of SARS-COV-2 variants threaten the efficacy of COVID-19 vaccines. Not only can variants be potentially more infectious than the wild-type strain, but they may also partially evade existing vaccines. A two-strain, two-group mechanistic mathematical model is designed to assess the impact of vaccine-induced, cross-protective efficacy of COVID-19 transmission in the United States. We present conditions for achieving vaccine-derived herd immunity and results from global sensitivity analysis under different transmissibility and cross-protection scenarios.
[04936] SARS-CoV-2 variant transition dynamics are associated with vaccination rates, number of co-circulating variants, and convalescent immunity
Format : Talk at Waseda University
Author(s) :
Sara Del Valle (Los Alamos National Laboratory)
Abstract : I will discuss a retrospective analysis that characterized differences in the speed, timing, and magnitude of 16 SARS-CoV-2 variant waves/transitions for 230 regions, between October 2020 and January 2023. Our results show associations between the behavior of an emerging variant and the number of co-circulating variants as well as demographics and vaccination rates. These results suggest the behavior of a variant may be sensitive to the immunologic and demographic context of its location.
