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利用数据科学和机器学习促进两个主要非洲城市的城市气候适应:HEAT 中心研究方案。

Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HEAT Center study protocol.

机构信息

Climate System Analysis Group, University of Cape Town, Rondebosch, Western Cape, South Africa

Wits Planetary Health Research, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.

出版信息

BMJ Open. 2024 Jun 18;14(6):e077529. doi: 10.1136/bmjopen-2023-077529.

DOI:10.1136/bmjopen-2023-077529
PMID:38890141
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11191804/
Abstract

INTRODUCTION

African cities, particularly Abidjan and Johannesburg, face challenges of rapid urban growth, informality and strained health services, compounded by increasing temperatures due to climate change. This study aims to understand the complexities of heat-related health impacts in these cities. The objectives are: (1) mapping intraurban heat risk and exposure using health, socioeconomic, climate and satellite imagery data; (2) creating a stratified heat-health forecast model to predict adverse health outcomes; and (3) establishing an early warning system for timely heatwave alerts. The ultimate goal is to foster climate-resilient African cities, protecting disproportionately affected populations from heat hazards.

METHODS AND ANALYSIS

The research will acquire health-related datasets from eligible adult clinical trials or cohort studies conducted in Johannesburg and Abidjan between 2000 and 2022. Additional data will be collected, including socioeconomic, climate datasets and satellite imagery. These resources will aid in mapping heat hazards and quantifying heat-health exposure, the extent of elevated risk and morbidity. Outcomes will be determined using advanced data analysis methods, including statistical evaluation, machine learning and deep learning techniques.

ETHICS AND DISSEMINATION

The study has been approved by the Wits Human Research Ethics Committee (reference no: 220606). Data management will follow approved procedures. The results will be disseminated through workshops, community forums, conferences and publications. Data deposition and curation plans will be established in line with ethical and safety considerations.

摘要

简介

非洲城市,特别是阿比让和约翰内斯堡,面临着快速城市增长、非正规性和紧张的卫生服务的挑战,加上气候变化导致的气温升高,情况更加复杂。本研究旨在了解这些城市与热相关的健康影响的复杂性。目的是:(1)使用健康、社会经济、气候和卫星图像数据绘制城市内部热风险和暴露图;(2)创建分层的热健康预测模型来预测不良健康结果;(3)建立一个早期预警系统,及时发出热浪警报。最终目标是建设有气候适应能力的非洲城市,保护受热危害影响较大的人群。

方法和分析

该研究将从 2000 年至 2022 年在约翰内斯堡和阿比让进行的符合条件的成人临床试验或队列研究中获取与健康相关的数据集。还将收集其他数据,包括社会经济、气候数据集和卫星图像。这些资源将有助于绘制热危害图和量化热健康暴露、风险升高和发病率的程度。将使用高级数据分析方法,包括统计评估、机器学习和深度学习技术来确定结果。

伦理和传播

该研究已获得威特沃特斯兰德大学人类研究伦理委员会的批准(参考编号:220606)。数据管理将遵循批准的程序。研究结果将通过研讨会、社区论坛、会议和出版物进行传播。将根据伦理和安全考虑制定数据存储和管理计划。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab9/11191804/3cc2d8ab2fad/bmjopen-2023-077529f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab9/11191804/847143fa7b2d/bmjopen-2023-077529f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab9/11191804/3cc2d8ab2fad/bmjopen-2023-077529f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab9/11191804/847143fa7b2d/bmjopen-2023-077529f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ab9/11191804/3cc2d8ab2fad/bmjopen-2023-077529f02.jpg

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