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Identifying globally relevant learnings from Africa's challenges and solutions to climate change and air pollution-related health impacts: a data science scoping review protocol.

Authors :
Wright CY
Jaca A
Kapwata T
Naidoo N
Awokola B
Bainomugisha E
Berhane KT
Blesic S
Kehbila A
Naidoo R
Nemukula B
Nyarko BK
Okekunle AP
Oni T
Quansah R
Thiam S
Zakari IS
Beyene N
Source :
BMJ open [BMJ Open] 2024 May 20; Vol. 14 (5), pp. e076941. Date of Electronic Publication: 2024 May 20.
Publication Year :
2024

Abstract

Introduction: Leveraging data science could significantly advance the understanding of the health impacts of climate change and air pollution to meet health systems' needs and improve public health in Africa. This scoping review will aim to identify and synthesise evidence on the use of data science as an intervention to address climate change and air pollution-related health challenges in Africa.<br />Methods and Analysis: The search strategy will be developed, and the search will be conducted in the Web of Science, Scopus, CAB Abstracts, MEDLINE and EMBASE electronic databases. We will also search the reference lists of eligible articles for additional records. We will screen titles, technical reports, abstracts and full texts and select studies reporting the use of data science in relation to the health effects and interventions associated with climate change and air pollution in Africa.<br />Ethics and Dissemination: There are no formal ethics requirements as we are not collecting primary data. Results, once published, will be disseminated via conferences and shared with policy-makers and public health, air pollution and climate change key stakeholders in Africa.<br />Competing Interests: Competing interests: None declared.<br /> (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Details

Language :
English
ISSN :
2044-6055
Volume :
14
Issue :
5
Database :
MEDLINE
Journal :
BMJ open
Publication Type :
Academic Journal
Accession number :
38772593
Full Text :
https://doi.org/10.1136/bmjopen-2023-076941