Social sensing of health and wellbeing impacts from pollen and air pollution

对花粉和空气污染对健康和福祉影响的社会感知

• 批准号: ES/P011489/1
• 负责人: Hywel Williams
• 金额: $ 25.26万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FP011489%2F1
• 关键词: Social; sensing; health; wellbeing; impacts

Air pollution and airborne pollen can have significant impacts on health and wellbeing. Health effects can be severe; for example, people with hayfever may also suffer from asthma, with complications sometimes leading to hospitalisation. However, most cases - while unpleasant and disruptive to the affected individual - are not severe enough to require formal medical treatment. These milder cases are not currently recorded or identified. This masks the true extent of these health conditions and their impacts on quality of life, making them hard to study and to manage. Meanwhile, the digital revolution is creating huge datasets that can provide rich information. We have successfully pioneered a "social sensing" methodology that uses social media data to detect and locate environmental hazards. Social sensing involves several stages: data harvesting, data cleaning (e.g. filtering for relevance and removing spam accounts), event detection, and data visualisation. One of the most exciting opportunities for social sensing is provision of real-time information, allowing accurate monitoring and early warning of emerging hazards.Social sensing has great potential for tracking pollen, air pollution and associated health impacts such as asthma and hayfever. This new source of data can fill an important information gap and bring benefits to public sector organisations and charities working to improve public health. Outputs can be easily provided to the general public through the web, to help asthma and hayfever sufferers manage their conditions more effectively. However, social sensing also raises ethical issues. Collection and analysis of social media data without user consent may be seen as a breach of privacy, especially where the data concern a sensitive topic such as health and/or wellbeing. Furthermore, since social media users are not necessarily representative of wider society, it is possible that decisions or policies based on social media data will unfairly benefit some sections of society at the expense of others.This project at University of Exeter will evaluate a social sensing prototype focused on pollen, air pollution, asthma and hayfever. The prototype will be assessed for use by several partner organisations working on environment and public health issues: Met Office, Public Health England and AsthmaUK. An integrated ethical investigation will directly address the privacy and fairness concerns raised by social sensing. The project has three aims: (1) Create a prototype social sensing platform to track health and wellbeing impacts of pollen and air pollution; (2) Work with partners to evaluate the usefulness of social sensing in a variety of real-world scenarios; and (3) Investigate ethical concerns around social sensing, in particular, fairness and privacy. These aims will be delivered by achieving four specific objectives: (1) Engage end-users and stakeholders to co-design project goals; (2) Develop a prototype social sensing tool focused on pollen, air pollution, asthma and hayfever; (3) Evaluate the prototype in multiple real-world scenarios identified by partner organisations; and (4) Use academic literature, public engagement and surveys to assess ethical concerns around privacy and fairness. The project team brings together an interdisciplinary mix of academics from University of Exeter, policy partners from Public Health England (PHE), Met Office and AsthmaUK, and members of the public from the Health and Environment Public Engagement (HEPE) group. Expertise in computer science, environment and human health will be combined to solve real-world problems. Outputs will include social sensing software (free for anyone to use) and a comprehensive Case Study Report summarising all project findings. Overall this project will create an essential evidence base to guide future use of social sensing in the context of environment and public health.

空气污染和空气中的花粉会对健康和福祉产生重大影响。对健康的影响可能很严重；例如，患有花粉热的人也可能患有哮喘，并发症有时会导致住院治疗。然而，大多数病例——虽然对受影响的个人来说是令人不快和破坏性的——并不严重到需要正式的医疗治疗。这些较轻的病例目前没有记录或查明。这掩盖了这些健康状况的真实程度及其对生活质量的影响，使其难以研究和管理。与此同时，数字革命正在创造能够提供丰富信息的庞大数据集。我们成功地开创了一种“社会感知”方法，利用社交媒体数据来检测和定位环境危害。社会感知涉及几个阶段：数据收集、数据清理（例如过滤相关性和删除垃圾邮件账户）、事件检测和数据可视化。社会感知最令人兴奋的机会之一是提供实时信息，允许对新出现的危险进行准确监测和早期预警。社会感知在追踪花粉、空气污染和相关健康影响（如哮喘和花粉热）方面具有巨大潜力。这种新的数据来源可以填补一个重要的信息缺口，并为致力于改善公共卫生的公共部门组织和慈善机构带来好处。可以很容易地通过网络向公众提供产出，以帮助哮喘和枯草热患者更有效地管理他们的病情。然而，社会感知也引发了伦理问题。未经用户同意收集和分析社交媒体数据可能被视为侵犯隐私，特别是在数据涉及健康和/或福祉等敏感话题时。此外，由于社交媒体用户不一定代表更广泛的社会，基于社交媒体数据的决策或政策可能会不公平地使社会的某些部分受益，而损害其他部分的利益。埃克塞特大学的这个项目将评估一个关注花粉、空气污染、哮喘和花粉热的社会传感原型。该原型将由几个致力于环境和公共卫生问题的合作组织进行评估，包括英国气象局、英国公共卫生部和asthmak。一个完整的伦理调查将直接解决由社会感知引起的隐私和公平问题。该项目有三个目标：(1)创建一个原型社会传感平台，以跟踪花粉和空气污染对健康和福祉的影响；(2)与合作伙伴一起评估社会感知在各种现实场景中的有用性；(3)调查有关社会感知的伦理问题，特别是公平和隐私。这些目标将通过实现四个具体目标来实现：(1)让最终用户和利益相关者参与共同设计项目目标；(2)开发针对花粉、空气污染、哮喘和花粉热的社会传感原型工具；(3)在合作伙伴组织确定的多个真实场景中评估原型；(4)利用学术文献、公众参与和调查来评估有关隐私和公平的道德问题。项目团队汇集了来自埃克塞特大学的跨学科学者，来自英国公共卫生（PHE），气象局和asthmak的政策合作伙伴，以及来自健康与环境公众参与（HEPE）小组的公众成员。计算机科学、环境和人类健康方面的专业知识将结合起来解决现实世界的问题。产出将包括社会传感软件（任何人都可以免费使用）和一份综合案例研究报告，总结所有项目发现。总的来说，这个项目将建立一个重要的证据基础，以指导今后在环境和公共卫生方面使用社会感知。

项目成果

Where health and environment meet: the use of invariant parameters in big data analysis.

• DOI: 10.1007/s11229-018-1844-2
• 发表时间: 2021
• 期刊: Synthese
• 影响因子: 1.5
• 作者: Leonelli S;Tempini N
• 通讯作者: Tempini N

Using social media to measure impacts of named storm events in the United Kingdom and Ireland

• DOI: 10.1002/met.1887
• 发表时间: 2020-01-01
• 期刊: METEOROLOGICAL APPLICATIONS
• 影响因子: 2.7
• 作者: Spruce, M.;Arthur, R.;Williams, H. T. P.
• 通讯作者: Williams, H. T. P.

Social sensing of floods in the UK.

• DOI: 10.1371/journal.pone.0189327
• 发表时间: 2018
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Arthur R;Boulton CA;Shotton H;Williams HTP
• 通讯作者: Williams HTP

From FAIR data to fair data use: Methodological data fairness in health-related social media research

• DOI: 10.1177/20539517211010310
• 发表时间: 2021-01-01
• 期刊: BIG DATA & SOCIETY
• 影响因子: 8.5
• 作者: Leonelli, Sabina;Lovell, Rebecca;Williams, Hywel
• 通讯作者: Williams, Hywel

Crowd-sourced observations for short-range numerical weather prediction: Report from EWGLAM / SRNWP Meeting 2019

短期数值天气预报的众包观测：EWGLAM / SRNWP 2019 年会议报告

• DOI: 10.1002/asl.1031
• 发表时间: 2021
• 期刊: Atmospheric Science Letters
• 影响因子: 3
• 作者: Hintz K