Synergising decision making and interventions across human health and environment: concepts for designing a model for infectious diseases
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cross-sectoral model
environmental modelling
infectious disease
environmental health

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Stanhope, J., Mayfield, H. J., Guillaume, J. H. A., Sahin, O., Weinstein, P., & Lau, C. (2022). Synergising decision making and interventions across human health and environment: concepts for designing a model for infectious diseases. Socio-Environmental Systems Modelling, 3, 18126.


The impact of environmental factors on human health outcomes is well established. It is therefore not surprising that interventions aimed at improving human health are often environmental-based, such as restoring riparian vegetation for flood mitigation, with a view to reducing associated infectious disease transmission. Yet the risks and benefits of these interventions on the environment itself are rarely measured, or weighed up against potential health gains. One of the challenges with such an evaluation is the requirement for cross-sectoral support from decision makers in both the health and environmental sectors. To facilitate this support, cross-sectoral models are required that simultaneously estimate the impact of proposed environmental interventions on both sectors. Despite their obvious value, a systematic search of the peer-reviewed literature did not identify any model that concurrently models the impact of environmental intervention on both environmental and human infectious disease related outcomes. In this paper, we conceptually explore potential approaches for designing such a model, using leptospirosis as a case study to highlight the various data sources, spatial scales, temporal scales and required system behaviour that would need to be integrated for a cross-sectoral model of this complexity. By comparing these system requirements against the strengths and limitations of individual modelling techniques, we demonstrate the potential benefits of a hybrid-ensemble approach that uses component models from different frameworks.  By combining the strengths of the different techniques to tackle this wicked problem, such a modelling approach supports the prioritisation of environmental interventions that optimise the overall benefit by considering impacts on both human health and the environment.
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