Mathematical and Theoretical Epidemiology and Ecology Models

This paper introduces ABC GP IPM, a flexible IPM framework using Gaussian Processes and Approximate Bayesian Computation to improve demographic modeling across species.

This study shows that increasing intraguild predation (IGP) in food webs leads to greater temporal variability in biomass across all trophic levels, potentially destabilizing ecosystems.

The paper develops a continuous-time microparasite model that incorporates infection intensity and parasite aggregation, showing how these factors influence host-pathogen dynamics.

The paper shows eco-evolutionary feedback can destabilize community dynamics in complex systems, and warming exacerbates this effect.

This study uses an agent-based model to simulate C. elegans populations and finds that chaotic dynamics emerge depending on culling parameters.

The paper introduces a framework to predict species persistence after invasion by analyzing community structure and interaction patterns, demonstrating its application in ecological systems with fluctuating abundances.

The paper extends the Marginal Value Theorem to simple organisms with limited sensory abilities, showing that adjusting feeding speed based on environmental average feeding rates improves foraging efficiency.

The paper develops models predicting the conditions under which aggressive interference optimizes resource gain based on leverage, resource availability, and consumer density.

The paper studies how asymmetric interactions affect mutant survival during population range expansions using simulations and a mathematical model.

This study models Q-fever transmission in Ghanaian cattle using a non-linear differential equation model to show how vaccination and recovery rates influence disease dynamics and control.

This paper evaluates a data-driven method's ability to replicate predator-prey dynamics using SINDy, showing consistency but also parameter sensitivity and the need for extensive data.

This paper introduces BaFOMS, a Bayesian method for selecting fractional order models to analyze eco-epidemiological systems, demonstrating its effectiveness in parameter estimation and forecasting.

This paper introduces a simple population dynamics model that can handle both beneficial and harmful interactions, demonstrating its applicability in data-poor ecological scenarios.

The paper develops a dynamical systems model to study interactions among Mimiviruses, virophages, and transpovirons, finding oscillatory behavior but unclear biological mechanisms for transpoviron persistence.

The paper predicts extinction probabilities in structured populations using branching process models and validates them with experimental data on Folsomia candida.

This study analyzes spatial suppression gene drive dynamics, finding that larger areas and certain life history traits increase vulnerability to chasing, while resistance mechanisms affect drive performance.

This study uses Caenorhabditis elegans to quantify heterogeneity in bacterial transmission by decoupling shedding and susceptibility distributions.

The paper challenges the belief that environmental and individual variabilities drive prey consumption rate variation, showing stochastic foraging paths are the main driver.

The paper develops a spatially explicit predator-prey model to study how climate change affects multispecies interactions and species distribution.

The paper develops a mathematical model to analyze how disturbance enables competitive coexistence by linking within-patch demographic strategies to larger-scale population dynamics.

The paper identifies and corrects a flaw in discrete-time population models where dead individuals are incorrectly revived during dispersal, leading to misleading dynamics.

This paper introduces an integrated integral population model (IIPM) that combines individual and population data to better describe and forecast population dynamics, outperforming existing models in both individual and population levels.

This paper models how migration affects gene drive spread and displacement in populations.

The paper develops a model linking epidemiological and immunological dynamics to show sustained low viral load infections can trigger epidemics even with within-host reproduction numbers below one.

This paper extends an ecological model to predict microbiome dynamics under environmental changes and shows how precise environmental perturbations can improve microbiome control.

This paper introduces a hierarchical mechanistic Bayesian model for epidemiological inference, showing it effectively identifies transmission patterns and hotspots in drug-resistant pathogens.

This study constructs a mathematical model to analyze how protection measures and treatment affect pneumonia transmission dynamics, finding that reducing the effective reproduction number below 1 is not always sufficient to eliminate the disease.

The paper develops a mathematical model to study Sporotrichosis transmission dynamics in domestic cats, finding that mass treatment combined with contact reduction strategies significantly reduces disease prevalence.

This study compares Lotka-Volterra and Multivariate Autoregressive models for ecological interaction systems, finding LV models generally superior for dynamic data with large deviations from steady states.

The paper investigates biophysical models to resolve the Paradox of the Plankton by combining resource competition, metabolic trade-offs, and stochastic assembly, showing simulations align with empirical observations.