Shilpa Rao, Prayash Chaudhary, Isabelle Budin-Ljøsne, Susan Sitoula, Kristin Aunan, Matthew Chersich, Francesca De' Donato, Aleksandra Kazmierczak
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引用次数: 0
Abstract
Heat-health early warning systems (HHWS) are an important collaborative activity between the meteorological and health communities. This study aimed to map the evidence on the socioeconomic assessment of HHWS and their effectiveness in terms of averting heat related health outcomes. It also aimed to map the technical, structural, and societal barriers and facilitators to implementation and use of HHWS. We use two methods: (i) a scoping review of literature on the economic assessment and health benefit of climate services for heat-health adaptation (ii) a set of interviews with climate service developers and providers in Europe and Africa to understand further technical and societal aspects as well as evaluation of such services. We find that HHWS can be a cost-effective adaptation option that can reduce heat-related mortality and morbidity, especially in vulnerable groups like the elderly. We find that challenges such as lack of long-term and reliable funding, difficulties in making the climate data relevant, comprehensible, and accessible to different end-users, cultural differences between climate and health professionals, and limited ability to assess the services' real impact need to be accounted for while implementing these services.
期刊介绍:
The European Journal of Public Health (EJPH) is a multidisciplinary journal aimed at attracting contributions from epidemiology, health services research, health economics, social sciences, management sciences, ethics and law, environmental health sciences, and other disciplines of relevance to public health. The journal provides a forum for discussion and debate of current international public health issues, with a focus on the European Region. Bi-monthly issues contain peer-reviewed original articles, editorials, commentaries, book reviews, news, letters to the editor, announcements of events, and various other features.