Planetary health is getting increasingly affected by intersecting global crises, including climate change, biodiversity loss, and the degradation of essential ecosystems. Although significant progress has been made in understanding how climate influences vectors and vector–pathogen dynamics, evidence remains limited and uneven regarding the combined effects of multiple environmental stressors.
These pressures, such as climate change, pollution, and land-use intensification, have already driven significant biodiversity loss, which in turn disrupts natural vector control mechanisms. Reduced biodiversity can weaken natural vector control, alter vector community composition, and eliminate non-competent species that would otherwise buffer pathogen transmission. At the same time, processes such as industrial agriculture, urbanisation, and environmental pollution, including the rapid spread of synthetic chemicals and plastics, are creating new habitats and ecological niches that favour vectors. Further, widespread use of insecticides and antimicrobial treatments is promoting resistance among pathogens, while growing human populations and increasing global mobility expand opportunities for transmission across regions.
Together, these forces shape the traits that influence disease dynamics. In vectors, they can alter life history, behavior, and physiology; in pathogens, they influence replication rates, incubation periods, virulence, and resistance. At a broader level, these pressures reshape vector communities, reservoir competence and biting rates, ultimately affecting transmission pathways and disease risk.
Despite the many known links between vector-borne diseases and individual environmental changes, scientific understanding of how these pressures interact remains fragmented. Addressing this gap requires situating vector–host–pathogen systems within the broader framework of interacting macroecological forces. This challenge calls for interdisciplinary collaboration, integrating expertise from infectious disease biology, entomology, ecology, earth system science, and infection ecology modeling.
Mathematical trait-based models provide a unifying framework for diverse data and for capturing system dynamics. In particular, Bayesian hierarchical trait-based models offer a flexible framework for identifying key uncertainties and highlighting critical data gaps, enabling inference even when there is data scarcity.
Predictive and scenario-based models, built on informed trait-based approaches, can further assess how and which policy interventions may influence the spread of vector-borne diseases most effectively. By comparing different scenarios, they can inform decision-making at multiple scales, from local communities to global governance.
Closer collaboration among researchers conducting experimental research, field-based research, and developing models is central to understanding how multiple environmental pressures act simultaneously on vectors, hosts, and pathogens. Current knowledge remains limited, particularly regarding how major stressors like climate change, plastic pollution, and chemical contamination interact.
Early evidence suggests that these pressures can jointly influence vector reproduction, pathogen development, and transmission dynamics, but available data are often scattered and difficult to integrate into predictive frameworks. To address this, researchers must gather more detailed data under realistic, multi-stressor conditions and integrate these findings into large-scale ecological and earth system models.
Improving models also requires a more accurate representation of ecological complexity. This includes considering interactions among species, such as reservoir hosts and vector communities, as well as variations in biodiversity, habitats, and environmental conditions. Additionally, models should incorporate non-linear responses and feedback loops, recognising that small environmental changes can sometimes trigger disproportionate effects, including tipping points in disease transmission.
Advancing our understanding of vector-pathogen systems amidst a polycrisis world depends on bridging disciplinary boundaries and integrating experimental and observational researchers and modellers. By developing more comprehensive models, scientists can better predict disease risks and support effective responses to the intertwined challenges of environmental change and public health.
Read the article here: https://www.nature.com/articles/s41579-026-01330-x#article-info
Reference: Treskova, M., Rocklöv, J. Coupling experiments and macroecological models to resolve multi-stressor effects in vector–pathogen systems. Nat Rev Microbiol (2026). https://doi.org/10.1038/s41579-026-01330-x
