arXiv subjects

Lauren M. Childs

Publications and source records attributed to Lauren M. Childs.

4 recordsLinked to original sources

arXiv2026

A stochastic dose-response framework for environmentally persistent pathogens

Infectious diseases caused by environmentally persistent pathogens can strongly affect host populations as transmission occurs not only through direct host-host contact but also via indirect exposure to contaminated environments. While in some systems environmental reservoirs help sustain exposure even when infected host numbers are low, reliance on environmental transmission pathway may also increase pathogen extinction risk. Infection risk may depend on both pathogen dose and timing of exposure. Thus, understanding how dose-response, stochasticity, and seasonal changes in host susceptibility or contact rates shape pathogen invasion and persistence remains an important challenge for environmentally transmitted disease systems. To address this, we develop a stochastic dose-response framework that integrates host infection dynamics with an explicit environmental pathogen reservoir. Transmission occurs through both direct contact with infectious hosts and indirect environmental exposure, with infection probability governed by dose-response functions. We focus on stochastic continuous-time Markov chain formulation and use branching process approximation to estimate disease extinction probabilities when infected hosts or environmental pathogen loads are low. We extend the framework to include seasonality in host susceptibility, environmental contact, and host-host contact. As a case study, we apply the model to snake fungal disease. Numerical simulations show that dose-response influences epidemic takeoff and infection levels, while seasonality creates windows of high and low extinction risk. These extinction risks depend strongly on the route and timing of introduction within the seasonal cycle. These results, coupled with global sensitivity analysis, illustrate how stochasticity, nonlinear dose-response, and seasonal timing shape outbreak dynamics for environmentally persistent pathogens.

q-bio.PE↗

arXiv2026

The behavioral spillover effect: Modeling behavioral interdependencies in multi-pathogen dynamics

During the recent pandemic, a rise in COVID-19 cases was followed by a decline in influenza. In the absence of cross-immunity, a potential explanation for the observed pattern is behavioral: non-pharmaceutical interventions (NPIs) designed and promoted for one disease also reduce the spread of others. We study short-term and long-term dynamics of two pathogens where NPIs targeting one pathogen indirectly influence the spread of another - a phenomenon we term behavioral spillover. We examine how perceived risk of and response to one disease substantially alters the spread of other pathogens, revealing how waves of different pathogens emerge over time as a result of behavioral interdependencies and human response. Our analysis identifies the parameter space where two diseases simultaneously co-exist, and where shifts in prevalence occur. Our findings are consistent with observations from the COVID-19 pandemic, where NPIs contributed to significant declines in infections such as influenza, pneumonia, and Lyme disease.

math.DS↗

arXiv2025

Once bitten, twice shy: A modeling framework for incorporating heterogeneous mosquito biting into transmission models

The risk of mosquito-borne disease outbreaks is tightly linked to the frequency at which mosquitoes feed on blood, also known as the biting rate. However, standard models of mosquito-borne disease transmission inherently assume that mosquitoes bite only once per reproductive cycle -- an assumption commonly violated in nature. Drivers of multiple biting also affect the mosquito gonotrophic cycle duration (GCD), the quantity customarily used to estimate biting rates. Here, we present a novel framework for incorporating more complex mosquito biting behaviors into transmission models, accounting for heterogeneity and linkages between mosquito biting rates and multiple biting. We provide general formulas for the basic offspring number, $\mathcal{N}_0$, and basic reproduction number, $\mathcal{R}_0$, threshold measures for mosquito population and pathogen transmission persistence, respectively. To exhibit its flexibility, we expand on specific models derived from the framework that arise from empirical, phenomenological, or mechanistic modeling perspectives. Using the gonotrophic cycle duration as a standard quantity to make comparisons among the models, we show that assumptions about the biting process strongly affect the relationship between GCD and $\mathcal{R}_0$. While under the standard assumption of one bite per reproductive cycle, $\mathcal{R}_0$ is an increasing linear function of the inverse of the GCD, alternative models of the biting process can exhibit saturating or concave relationships. Critically, from a mechanistic perspective, decreases in the GCD can lead to substantial decreases in $\mathcal{R}_0$. This work highlights the importance of incorporating the behavioral dynamics of mosquitoes into transmission models and provides a method for evaluating how individual-level interventions against mosquito biting scale up to determine population-level mosquito-borne disease risk.

q-bio.PE↗

arXiv2008

Stability diagram for the forced Kuramoto model

We analyze the periodically forced Kuramoto model. This system consists of an infinite population of phase oscillators with random intrinsic frequencies, global sinusoidal coupling, and external sinusoidal forcing. It represents an idealization of many phenomena in physics, chemistry and biology in which mutual synchronization competes with forced synchronization. In other words, the oscillators in the population try to synchronize with one another while also trying to lock onto an external drive. Previous work on the forced Kuramoto model uncovered two main types of attractors, called forced entrainment and mutual entrainment, but the details of the bifurcations between them were unclear. Here we present a complete bifurcation analysis of the model for a special case in which the infinite-dimensional dynamics collapse to a two-dimensional system. Exact results are obtained for the locations of Hopf, saddle-node, and Takens-Bogdanov bifurcations. The resulting stability diagram bears a striking resemblance to that for the weakly nonlinear forced van der Pol oscillator.

nlin.PS↗