Towards General Principles of Vector-Borne Disease Transmission Across Systems

The proposed research addresses a key limitation in vector-borne disease modelling: the field remains largely driven by case-specific studies of individual outbreaks, with limited understanding of the generalizable processes governing transmission across systems. This project asks: what common mechanisms and critical differences shape transmission dynamics across diverse vector-borne diseases, and how can these insights be used to identify when and where interventions are most effective? To answer this, the project will develop a transferable modeling framework based on network-structured compartmental models (e.g., SIR-type extensions). These models will represent interactions among human populations, animal reservoirs, and vectors as multilayer, dynamic networks, in which transmission pathways are explicitly encoded and modulated by environmental and climatic variability. This approach enables the analysis of spillover dynamics within a unified “zoonotic web,” capturing the interconnected nature of host-vector systems and aligning with the One Health concept. A central challenge lies in the non-linear dynamics and feedback loops inherent to these systems, where interactions between host behavior, vector ecology, and climate drivers produce emergent and often unpredictable epidemic patterns. Methodologically, the project will address this by combining network-based modeling with statistical inference techniques suited to sparse and heterogeneous data, such as hierarchical approaches. This will allow robust parameterization and cross-system comparison despite limited surveillance data. By systematically comparing multiple disease systems within a common modelling framework, the research will identify shared transmission structures, key drivers of spillover, and system-specific deviations. These insights will be used to evaluate intervention strategies as control problems on networks, enabling the identification of critical points in space, time, and transmission pathways where interventions (e.g., vector control or host-targeted measures) are most effective.

Complexity Science Hub Vienna CSH - Verein zur Förderung wissenschaftlicher Forschung im Bereich komplexer Systeme
Funktion: Partner