Using mobile big data to support emergency preparedness and address economically vulnerable communities during the COVID-19 pandemic in Nigeria

IF 1.8 Q3 PUBLIC ADMINISTRATION
Data & policy Pub Date : 2021-09-15 DOI:10.1017/dap.2021.12
Jean Charles Gilbert, Olubayo Adekanmbi, C. Harrison
{"title":"Using mobile big data to support emergency preparedness and address economically vulnerable communities during the COVID-19 pandemic in Nigeria","authors":"Jean Charles Gilbert, Olubayo Adekanmbi, C. Harrison","doi":"10.1017/dap.2021.12","DOIUrl":null,"url":null,"abstract":"Abstract With the declaration of the coronavirus disease 2019 (COVID-19) pandemic in Nigeria in 2020, the Nigeria Governors’ Forum (NGF) instigated a collaboration with MTN Nigeria to develop data-driven insights, using mobile big data (MBD) and other data sources, to shape the planning and response to the pandemic. First, a model was developed to predict the worst-case scenario for infections in each state. This was used to support state-level health committees to make local resource planning decisions. Next, as containment interventions resulted in subsistence/daily paid workers losing their income and ability to buy essential food supplies, NGF and MTN agreed a second phase of activity, to develop insights to understand the population clusters at greatest socioeconomic risk from the impact of the pandemic. This insight was used to promote available financial relief to the economically vulnerable population clusters in Lagos state via the HelpNow crowdfunding initiative. This article discusses how anonymized and aggregated mobile network data (MBD), combined with other data sources, were used to create valuable insights and inform the government, and private business, response to the pandemic in Nigeria. Finally, we discuss lessons learnt. Firstly, how a collaboration with, and support from, the regulator enabled MTN to deliver critical insights at a national scale. Secondly, how the Nigeria Data Protection Regulation and the GSMA COVID-19 Privacy Guidelines provided an initial framework to open the discussion and define the approach. Thirdly, why stakeholder management is critical to the understanding, and application, of insights. Fourthly, how existing relationships ease new project collaborations. Finally, how MTN is developing future preparedness by creating a team that is focused on developing data-driven insights for social good.","PeriodicalId":93427,"journal":{"name":"Data & policy","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data & policy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1017/dap.2021.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"PUBLIC ADMINISTRATION","Score":null,"Total":0}
引用次数: 1

Abstract

Abstract With the declaration of the coronavirus disease 2019 (COVID-19) pandemic in Nigeria in 2020, the Nigeria Governors’ Forum (NGF) instigated a collaboration with MTN Nigeria to develop data-driven insights, using mobile big data (MBD) and other data sources, to shape the planning and response to the pandemic. First, a model was developed to predict the worst-case scenario for infections in each state. This was used to support state-level health committees to make local resource planning decisions. Next, as containment interventions resulted in subsistence/daily paid workers losing their income and ability to buy essential food supplies, NGF and MTN agreed a second phase of activity, to develop insights to understand the population clusters at greatest socioeconomic risk from the impact of the pandemic. This insight was used to promote available financial relief to the economically vulnerable population clusters in Lagos state via the HelpNow crowdfunding initiative. This article discusses how anonymized and aggregated mobile network data (MBD), combined with other data sources, were used to create valuable insights and inform the government, and private business, response to the pandemic in Nigeria. Finally, we discuss lessons learnt. Firstly, how a collaboration with, and support from, the regulator enabled MTN to deliver critical insights at a national scale. Secondly, how the Nigeria Data Protection Regulation and the GSMA COVID-19 Privacy Guidelines provided an initial framework to open the discussion and define the approach. Thirdly, why stakeholder management is critical to the understanding, and application, of insights. Fourthly, how existing relationships ease new project collaborations. Finally, how MTN is developing future preparedness by creating a team that is focused on developing data-driven insights for social good.
在尼日利亚COVID-19大流行期间,利用移动大数据支持应急准备并解决经济脆弱社区的问题
随着2020年尼日利亚宣布2019冠状病毒病(COVID-19)大流行,尼日利亚州长论坛(NGF)与尼日利亚MTN合作,利用移动大数据(MBD)和其他数据源开发数据驱动的见解,以制定大流行的规划和应对措施。首先,开发了一个模型来预测每个州感染的最坏情况。这笔资金用于支持州级卫生委员会制定地方资源规划决策。其次,由于遏制措施导致领取生计/日薪的工人失去收入和购买基本粮食供应的能力,全球发展基金和MTN同意开展第二阶段活动,以深入了解受大流行影响社会经济风险最大的人群。这一见解被用于通过HelpNow众筹倡议促进对拉各斯州经济弱势群体的可用财政救济。本文讨论了匿名和聚合的移动网络数据(MBD)如何与其他数据源相结合,用于创造有价值的见解,并为尼日利亚政府和私营企业应对疫情提供信息。最后,我们讨论经验教训。首先,与监管机构的合作和支持如何使MTN能够在全国范围内提供关键见解。其次,《尼日利亚数据保护条例》和《GSMA COVID-19隐私指南》如何为展开讨论和确定方法提供了初步框架。第三,为什么利益相关者管理对见解的理解和应用至关重要。第四,现有关系如何促进新项目合作。最后,MTN如何通过创建一个专注于为社会利益开发数据驱动的洞察力的团队来为未来做好准备。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
3.10
自引率
0.00%
发文量
0
审稿时长
12 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信