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Shravani Shetgaonkar

Publications and source records attributed to Shravani Shetgaonkar.

2 recordsLinked to original sources

Host diversity and adaptive vector feeding preferences shape disease burden in vector-borne diseases

Vector-borne diseases often involve multiple host species that differ in their ability to sustain transmission. At the same time, vector feeding preferences can change in response to host availability and disease-control interventions, potentially altering disease dynamics in unexpected ways. We develop a two-host vector-borne disease model that links host diversity, adaptive vector feeding preferences, and disease transmission. We demonstrate that the effect of host diversity on disease transmission is mediated by vector feeding behavior and cannot be inferred from host abundance alone. In particular, we identify a critical threshold, $R_{0c}$, that determines whether shifts in vector preference amplify or suppress disease burden in a focal host. This threshold marks a qualitative transition in system behavior and provides a basis for predicting epidemiological responses to changes in host composition and vector behavior. Using adaptive dynamics, we further show that vector populations may evolve toward either specialist or opportunistic feeding strategies depending on host encounter rates and trade-off strength. Finally, we demonstrate that host-targeted interventions can induce adaptive changes in vector feeding behavior that reduce prevalence in the protected host while potentially increasing overall infection burden. Our results highlight how evolutionary responses of vector population can generate unexpected epidemiological outcomes and should be considered when designing disease-control strategies.

q-bio.PE↗

Nonlinear Feedbacks Between Host Behavior and Vector Adaptation in a Multi-Host Vector-Borne Disease Model

Insecticide-treated nets (ITN) are an effective and low-cost intervention for controlling vector-borne disease (VBD), however, their use depends on individual decisions based on perceived cost and risk of infection. This study investigates a nonlinear multi-host model for the transmission of VBD with endogenous strategic control. We assume that hosts' adoption of ITN emerges from the payoff-based decision-making, creating a nonlinear coupling with disease prevalence. We model vector preference as a function of ITN coverage to probe the complex interplay among individual choices, disease prevalence, and its control in a multi-host setting. The qualitative behavior of the system is characterized by the thresholds $R_0$ and $R_c$, which determine the existence and local stability of the disease-free and endemic equilibria. The system exhibits rich dynamical behavior; hence, we provide a bifurcation analysis identifying the conditions for saddle-node and Hopf bifurcations. Our results demonstrate that the interaction between the perceived cost of ITN and the infection risk can induce critical transitions, including regime shift from stable endemic states to sustained periodic oscillations. Furthermore, we identify a counterintuitive effect whereby complete ITN adoption by the primary host can increase the overall prevalence in the secondary host due to adaptive shifts of vector feeding behavior.

q-bio.PE↗