Both the World Health Organization (WHO) with its 2015 "Climate and Health Country Profile Project" and the Istituto Superiore di Sanità (ISS) with its 2018 "Health and Climate Change", agree on the emergency generated by the climate change and concerning health problems. The mitigation strategy suggested by the Intergovernmental Panel On Climate Change (IPCC) against greenhouse gas emissions and their effects on climate change, has not yet yielded the desired results. It is therefore necessary to focus on adaptation strategies, to immediately counter the effects of climate change (CC) on most vulnerable people and environments, by increasing their resilience through local interventions and targeted resilience actions. Coordinated resilience actions are necessary to combat the effects of CC especially in urban areas. Useful tools to manage and optimize resilience actions are artificial neural networks (ANN) in complex and dynamic domains as cities are. The case of ANN applied to a city is presented as an example to increase the climate resilience of health local systems. In the current state of knowledge, ANN prove to be the most advanced and global solution to coordinate and manage a set of resilience actions in urban areas.

Resilience actions to counteract the effects of climate change and health emergencies in cities: the role of artificial neural networks

Mammarella M. C.;Grandoni G.
2019

Abstract

Both the World Health Organization (WHO) with its 2015 "Climate and Health Country Profile Project" and the Istituto Superiore di Sanità (ISS) with its 2018 "Health and Climate Change", agree on the emergency generated by the climate change and concerning health problems. The mitigation strategy suggested by the Intergovernmental Panel On Climate Change (IPCC) against greenhouse gas emissions and their effects on climate change, has not yet yielded the desired results. It is therefore necessary to focus on adaptation strategies, to immediately counter the effects of climate change (CC) on most vulnerable people and environments, by increasing their resilience through local interventions and targeted resilience actions. Coordinated resilience actions are necessary to combat the effects of CC especially in urban areas. Useful tools to manage and optimize resilience actions are artificial neural networks (ANN) in complex and dynamic domains as cities are. The case of ANN applied to a city is presented as an example to increase the climate resilience of health local systems. In the current state of knowledge, ANN prove to be the most advanced and global solution to coordinate and manage a set of resilience actions in urban areas.
climate change adaptation; climate resilience of health; urban resilience actions; health; artificial neural networks
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12079/53601
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