Oldroyd R A, Hobbs M, Campbell M, Jenneson V, Marek L, Morris M A, Pontin F, Sturley C, Tomintz M, Wiki J, Birkin M, Kingham S, Wilson M
Leeds Institute for Data Analytics, University of Leeds, Leeds, UK.
School of Geography, University of Leeds, Leeds, UK.
Appl Spat Anal Policy. 2021;14(4):1025-1040. doi: 10.1007/s12061-021-09381-8. Epub 2021 Apr 29.
Globally, geospatial concepts are becoming increasingly important in epidemiological and public health research. Individual level linked population-based data afford researchers with opportunities to undertake complex analyses unrivalled by other sources. However, there are significant challenges associated with using such data for impactful geohealth research. Issues range from extracting, linking and anonymising data, to the translation of findings into policy whilst working to often conflicting agendas of government and academia. Innovative organisational partnerships are therefore central to effective data use. To extend and develop existing collaborations between the institutions, in June 2019, authors from the Leeds Institute for Data Analytics and the Alan Turing Institute, London, visited the Geohealth Laboratory based at the University of Canterbury, New Zealand. This paper provides an overview of insight shared during a two-day workshop considering aspects of linked population-based data for impactful geohealth research. Specifically, we discuss both the collaborative partnership between New Zealand's Ministry of Health (MoH) and the University of Canterbury's GeoHealth Lab and novel infrastructure, and commercial partnerships enabled through the Leeds Institute for Data Analytics and the Alan Turing Institute in the UK. We consider the New Zealand Integrated Data Infrastructure as a case study approach to population-based linked health data and compare similar approaches taken by the UK towards integrated data infrastructures, including the ESRC Big Data Network centres, the UK Biobank, and longitudinal cohorts. We reflect on and compare the geohealth landscapes in New Zealand and the UK to set out recommendations and considerations for this rapidly evolving discipline.
在全球范围内，地理空间概念在流行病学和公共卫生研究中变得越来越重要。基于人群的个体层面关联数据为研究人员提供了进行其他来源无法比拟的复杂分析的机会。然而，将此类数据用于有影响力的地球健康研究存在重大挑战。问题涵盖从数据提取、关联和匿名化，到将研究结果转化为政策，同时还要应对政府和学术界常常相互冲突的议程。因此，创新的组织伙伴关系对于有效利用数据至关重要。为了扩展和发展各机构之间现有的合作，2019年6月，来自利兹数据分析研究所和伦敦艾伦·图灵研究所的作者访问了位于新西兰坎特伯雷大学的地球健康实验室。本文概述了在为期两天的研讨会上分享的见解，该研讨会探讨了基于人群的关联数据在有影响力的地球健康研究中的各个方面。具体而言，我们讨论了新西兰卫生部（MoH）与坎特伯雷大学地球健康实验室之间的合作伙伴关系以及新型基础设施，以及通过英国利兹数据分析研究所和艾伦·图灵研究所建立的商业伙伴关系。我们将新西兰综合数据基础设施作为基于人群的关联健康数据的案例研究方法，并比较了英国对综合数据基础设施采取的类似方法，包括经济与社会研究委员会（ESRC）大数据网络中心、英国生物银行和纵向队列研究。我们反思并比较了新西兰和英国的地球健康领域情况，为这一快速发展的学科提出建议和注意事项。
