Mathematical and Theoretical Epidemiology and Ecology Models

The paper introduces a theoretical framework to calculate ecosystem responses to environmental perturbations using geometric transformations in consumer-resource models.

This study predicts the recoverability of collapsed food webs using dimension reduction and perturbation analysis, showing that topological features like connectance and predator links influence recovery.

The paper models ecological interactions and game dynamics to show how resource flow leads to life-history trade-offs, consistent personalities, and power laws in predator-prey and aggression behaviors.

The paper introduces a Julia package for simulating temporal dynamics of ecological networks with diverse interaction types and environmental drivers.

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

This paper develops methods to detect and optimize sampling for multiphasic virus decay, applying them to show that 94% of phage ΦD9 decays 16-fold faster than the remaining population.

This study investigates when spatial structure should be included in epidemiological models and derives a critical threshold for diffusion coefficient affecting disease spread predictions.

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

The paper derives an analytical distribution of distances to the edge of species coexistence in Lotka-Volterra models, using interaction matrices and applies it to experimental plant community data.

The paper shows that ecosystem stability depends on diversity differences between trophic levels rather than absolute diversity, with stability increasing as diversity differences grow.

The paper clarifies that the sublinear growth model does not resolve the species coexistence paradox because it relies on unrealistic assumptions about growth rates at low abundance.

The paper models biological invasions in IGP communities across homogeneous and heterogeneous landscapes using reaction-diffusion equations, showing how invasion speeds and coexistence depend on habitat structure and species interactions.

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 resource-explicit modeling method for spatial population models that improves computational efficiency while maintaining accuracy.

This study develops a socio-ecological model with social hierarchy and spatial structure to analyze fishery dynamics, finding that fish movement and social influence significantly impact sustainability.

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

This paper develops a framework to predict pathogen mutual invasibility and co-circulation using ecological theory, finding near-universal mutual invasibility across major pathogen systems.

This study introduces a stochastic model of viral-host co-evolution showing that pulse instabilities can lead to extended endemic infection patterns in large host populations with finite immune memory.

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.

The paper experiments with ciliate communities to show that modifier species affect predator-prey interactions, altering trophic interaction strength and dynamics.

This paper develops mathematical models to study how defective interfering particles (DIPs) reduce SARS-CoV-2 replication, showing dose-dependent inhibition in both deterministic and stochastic frameworks.

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 shows that sequential resource use and environmental changes create temporal niches, allowing more species to coexist than resources alone.

DeepDynaForecast uses phylogenetic trees and graph deep learning to predict epidemic transmission dynamics, showing accuracy in simulated and real HIV data.

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