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Mitigating heat-related mortality risk in Shanghai, China: system dynamics modeling simulations

Numerous studies in epidemiology, meteorology, and climate change research have demonstrated a significant association between abnormal ambient temperature and mortality. However, there is a shortage of research attention to a systematic assessment of potential mitigation measures which could effect...

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Autores principales: Liu, Xiaochen, Tian, Zhan, Sun, Laixiang, Liu, Junguo, Wu, Wei, Xu, Hanqing, Sun, Landong, Wang, Chunfang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518989/
https://www.ncbi.nlm.nih.gov/pubmed/32350804
http://dx.doi.org/10.1007/s10653-020-00556-9
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author Liu, Xiaochen
Tian, Zhan
Sun, Laixiang
Liu, Junguo
Wu, Wei
Xu, Hanqing
Sun, Landong
Wang, Chunfang
author_facet Liu, Xiaochen
Tian, Zhan
Sun, Laixiang
Liu, Junguo
Wu, Wei
Xu, Hanqing
Sun, Landong
Wang, Chunfang
author_sort Liu, Xiaochen
collection PubMed
description Numerous studies in epidemiology, meteorology, and climate change research have demonstrated a significant association between abnormal ambient temperature and mortality. However, there is a shortage of research attention to a systematic assessment of potential mitigation measures which could effectively reduce the heat-related morbidity and mortality risks. This study first illustrates a conceptualization of a systems analysis version of urban framework for climate service (UFCS). It then constructs a system dynamics (SD) model for the UFCS and employs this model to quantify the impacts of heat waves on public health system in Shanghai and to evaluate the performances of two mitigation measures in the context of a real heat wave event in July 2013 in the city. Simulation results show that in comparison with the baseline without mitigation measures, if the hospital system could prepare 20% of beds available for emergency response to heat waves once receiving the warning in advance, the number of daily deaths could be reduced by 40–60 (15.8–19.5%) on the 2 days of day 7 and day 8; if increasing the minimum living allowance of 790 RMB/month in 2013 by 20%, the number of daily deaths could be reduced by 50–70 (17.7–21.9%) on the 2 days of day 8 and day 12. This tool can help policy makers systematically evaluate adaptation and mitigation options based on performance assessment, thus strengthening urban resilience to changing climate.
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spelling pubmed-75189892020-10-13 Mitigating heat-related mortality risk in Shanghai, China: system dynamics modeling simulations Liu, Xiaochen Tian, Zhan Sun, Laixiang Liu, Junguo Wu, Wei Xu, Hanqing Sun, Landong Wang, Chunfang Environ Geochem Health Original Paper Numerous studies in epidemiology, meteorology, and climate change research have demonstrated a significant association between abnormal ambient temperature and mortality. However, there is a shortage of research attention to a systematic assessment of potential mitigation measures which could effectively reduce the heat-related morbidity and mortality risks. This study first illustrates a conceptualization of a systems analysis version of urban framework for climate service (UFCS). It then constructs a system dynamics (SD) model for the UFCS and employs this model to quantify the impacts of heat waves on public health system in Shanghai and to evaluate the performances of two mitigation measures in the context of a real heat wave event in July 2013 in the city. Simulation results show that in comparison with the baseline without mitigation measures, if the hospital system could prepare 20% of beds available for emergency response to heat waves once receiving the warning in advance, the number of daily deaths could be reduced by 40–60 (15.8–19.5%) on the 2 days of day 7 and day 8; if increasing the minimum living allowance of 790 RMB/month in 2013 by 20%, the number of daily deaths could be reduced by 50–70 (17.7–21.9%) on the 2 days of day 8 and day 12. This tool can help policy makers systematically evaluate adaptation and mitigation options based on performance assessment, thus strengthening urban resilience to changing climate. Springer Netherlands 2020-04-29 2020 /pmc/articles/PMC7518989/ /pubmed/32350804 http://dx.doi.org/10.1007/s10653-020-00556-9 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Original Paper
Liu, Xiaochen
Tian, Zhan
Sun, Laixiang
Liu, Junguo
Wu, Wei
Xu, Hanqing
Sun, Landong
Wang, Chunfang
Mitigating heat-related mortality risk in Shanghai, China: system dynamics modeling simulations
title Mitigating heat-related mortality risk in Shanghai, China: system dynamics modeling simulations
title_full Mitigating heat-related mortality risk in Shanghai, China: system dynamics modeling simulations
title_fullStr Mitigating heat-related mortality risk in Shanghai, China: system dynamics modeling simulations
title_full_unstemmed Mitigating heat-related mortality risk in Shanghai, China: system dynamics modeling simulations
title_short Mitigating heat-related mortality risk in Shanghai, China: system dynamics modeling simulations
title_sort mitigating heat-related mortality risk in shanghai, china: system dynamics modeling simulations
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518989/
https://www.ncbi.nlm.nih.gov/pubmed/32350804
http://dx.doi.org/10.1007/s10653-020-00556-9
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