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Review
. 2023 Aug 7:32:100701.
doi: 10.1016/j.lanepe.2023.100701. eCollection 2023 Sep.

Decision-support tools to build climate resilience against emerging infectious diseases in Europe and beyond

Collaborators, Affiliations
Review

Decision-support tools to build climate resilience against emerging infectious diseases in Europe and beyond

Joacim Rocklöv et al. Lancet Reg Health Eur. .

Abstract

Climate change is one of several drivers of recurrent outbreaks and geographical range expansion of infectious diseases in Europe. We propose a framework for the co-production of policy-relevant indicators and decision-support tools that track past, present, and future climate-induced disease risks across hazard, exposure, and vulnerability domains at the animal, human, and environmental interface. This entails the co-development of early warning and response systems and tools to assess the costs and benefits of climate change adaptation and mitigation measures across sectors, to increase health system resilience at regional and local levels and reveal novel policy entry points and opportunities. Our approach involves multi-level engagement, innovative methodologies, and novel data streams. We take advantage of intelligence generated locally and empirically to quantify effects in areas experiencing rapid urban transformation and heterogeneous climate-induced disease threats. Our goal is to reduce the knowledge-to-action gap by developing an integrated One Health-Climate Risk framework.

Keywords: Adaptation; Climate change; Climate policy; Co-production; Human health; Infectious disease; Mitigation; One Health; Planetary health.

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Conflict of interest statement

All authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Integrated One Health–Climate Risk approach. A.) Illustration of the integration of One Health (i.e., an integrated, unifying approach to animal, human and environmental health) in the IPCC’s framework of risk in terms of hazard (i.e., the occurrence of a climate-related event), exposure (i.e., presence of people, livelihoods, species, ecosystems, resources and infrastructure that can be adversely affected by the hazard), and vulnerability (i.e.,propensity to be adversely affected) to climate change. B.) Nexus of climate hazard, exposure and vulnerability and their associated health risks. Gaps in climate change adaptation and preparedness result in exposure and vulnerability to climate-associated hazards. These gaps constitute a health risk, if they align in time and space. Climate change mitigation can reduce climate hazards, while adaptation and preparedness interventions can reduce exposure and vulnerability to these hazards.
Fig. 2
Fig. 2
Integrated Knowledge-to-Action framework is a proposed approach for generation and transfer of knowledge and research activities on hazards, exposures, vulnerabilities, and risk while integrating environment, animal, and human health to action that creates pathways to a wider societal impact and building-up of health systems’ climate resilience. The framework integrates four major research streams (1–4) and two approaches to research that cut across and are incorporated in all knowledge and evidence generation activities (5–6). A participatory approach is applied to engage knowledge-users and stakeholders into iterative processes of co-design, co-development, and co-dissemination of research. The wheel illustrates the short- and long-term outputs that lead to societal impacts, improve the climate resilience of health systems, and benefit the society at large.
Fig. 3
Fig. 3
Spatio-temporal domains at which the integrated One Health–Climate Risk tools are being developed. Indicators developed using global products can be downscaled using information collected at higher-resolution spatial scales and incorporated into regional or local decision support systems. Meanwhile, locally collected data can inform infectious disease models and improve assessments of disease risk across larger geographic areas (i.e., national, regional, or global). Indicators and models can be formulated and applied to track historical changes (past), predict the probability of emergence and outbreaks from subseasonal to seasonal time scales, and project changing risk patterns in the long-term (e.g., until the end of the century), given different GHG emission pathways, population changes, and levels of adaptation and mitigation.

References

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