Please use this identifier to cite or link to this item: https://cris.library.msu.ac.zw//handle/11408/6322
Title: Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HE2AT Center study protocol
Authors: Christopher Jack
Craig Parker
Yao Etienne Kouakou
Bonnie Joubert
Kimberly A McAllister
Maliha Ilias
Gloria Maimela
Matthew Chersich
Sibusisiwe Makhanya
Stanley Luchters
Prestige Tatenda Makanga
Etienne Vos
Kristie L Ebi
Brama Koné
Akbar K Waljee
Guéladio Cissé
HE2AT Center Group
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
University Peleforo Gon Coulibaly, Korhogo, Côte d'Ivoire; Centre Suisse de Recherches Scientifiques, Abidjan, Côte d'Ivoire
National Institute of Environmental Health Sciences, Durham, North Carolina, USA
National Institute of Environmental Health Sciences, Durham, North Carolina, USA
National Heart Lung and Blood Institute, Bethesda, Maryland, USA
Climate and Health Directorate, Wits Reproductive Health and HIV Institute, Hillbrow, Gauteng, South Africa
Wits Planetary Health Research, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa; Public Health and Primary Care, School of Medicine, Trinity College Dublin, Dublin, UK
IBM Research-Africa, Johannesburg, South Africa
Centre for Sexual Health and HIV & AIDS Research (CeSHHAR), Harare, Zimbabwe; Liverpool School of Tropical Medicine, Liverpool, UK
Centre for Sexual Health and HIV & AIDS Research (CeSHHAR), Harare, Zimbabwe; Surveying and Geomatics Department, Midlands State University, Gweru, Zimbabwe
IBM Research-Africa, Johannesburg, South Africa
University of Washington, Seattle, Washington, USA
University Peleforo Gon Coulibaly, Korhogo, Côte d'Ivoire; Centre Suisse de Recherches Scientifiques, Abidjan, Côte d'Ivoire
Gastroenterology, University of Michigan, Ann Arbor, Michigan; USA Ann Arbor VA Medical Center, VA Center for Clinical Management Research, Ann Arbor, Michigan, USA
University Peleforo Gon Coulibaly, Korhogo, Côte d'Ivoire; Centre Suisse de Recherches Scientifiques, Abidjan, Côte d'Ivoire
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Keywords: data science
machine learning
urban climate adaptation
Issue Date: 18-Jun-2024
Publisher: BMJ Publishing Group
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 consideration
URI: https://cris.library.msu.ac.zw//handle/11408/6322
Appears in Collections:Research Papers

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