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14th October 2020
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Geospatial Modelling To Predict COVID Prevalence at Community Level

NEW REAL-TIME ANALYSIS DEMONSTRATING THE SPREAD OF COVID-19 IN WALES HAS DIRECTLY INFORMED THE ONE WALES RESPONSE TO COVID-19 IN WALES.

Carried out by the team within Population Data Science at Swansea University, the modelling demonstrates the value of a real-time spatio-temporal inferential mapping platform for public health efforts during the emergence and spread of infectious diseases. The project has prototyped and delivered data infrastructures and analysis pipelines capable of delivering timely and insightful analytics to all levels of government.

The research project is an exemplar of how a combination of skills (Health Informatics, Statistics and Geography) is needed to provide insights to inform local and national government policy throughout the COVID-19 crisis.

This research has been used by devolved administrations for pandemic planning, for example in identifying local hotspots that previous regional-level mapping may have masked. To help understand the localised spread of COVID-19, this project has adapted sophisticated geo-spatial modelling methods to estimate the near-real-time prevalence of infections at community level using COVID-19 testing data. The maps generated provide the first fine-scale, national assessment of the geographical distribution of laboratory-confirmed COVID-19 infections.

Led by the Population Data Science department at Swansea University Medical School, with collaborations across the UK including members from Lancaster University, Health Data Research UK, Administrative Data Research Wales, the National Centre for Population Health and Well-being Research supported by the Medical Research Council, Health and Care Research Wales and Secure E-Research Platform (SeRP).

The project uses pathology data, which confirms a COVID-19 positive result based on testing and the date the test was taken. The data is held anonymously and securely in and extracted from the Secure Anonymised Information Linkage (SAIL) Databank. The SAIL Databank acts as a secure gateway to access sensitive data whilst protecting privacy. Data extracted from the SAIL Databank is then processed to generate suitable inputs for geospatial modelling. The modelled outputs include statistical confidence intervals and probability indicators for the prevalence estimation – for a detailed overview of the outputs please refer to the pre-print paper on the geo-spatial modelling methods.

Further research is underway to refine the modelling and assess the accuracy with updates provided to the Welsh Government’s COVID19 Technical Advisory Cell on a weekly basis.


One Wales is a rapid, intelligence-driven response that brings together partners including HDR UK, ADR Wales, SAIL Databank, ADP, BREATHE, Welsh Government, Public Health Wales and NHS Wales Informatics Service (NWIS), to inform the response to COVID-19 in Wales.

This collaboration has resulted in an agile responsive approach to tackling policy-relevant intelligence generation, based on both the constant and newly developing priorities for tackling COVID-19 in Wales. One Wales has informed Welsh Government’s TAG (Technical Advisory Group) and subsequently the UK’s SAGE (Scientific Advisory Group for Emergencies).

Acknowledgements

This study makes use of anonymised data held in the Secure Anonymised Information Linkage (SAIL) Databank. We would like to acknowledge all the data providers who make anonymised data available for research.

This work was funded by the Medical Research Council (MR/V028367/1) and by Health Data Research UK Ltd (HDR-9006). HDR UK is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation (BHF) and the Wellcome Trust.

Underpinning research was supported by the ADR Wales programme of work and the National Centre for Population Health and Wellbeing Research. The ADR Wales programme of work is aligned to the priority themes as identified in the Welsh Government’s national strategy: Prosperity for All. ADR Wales brings together data science experts at Swansea University Medical School, staff from the Wales Institute of Social and Economic Research, Data and Methods (WISERD) at Cardiff University and specialist teams within the Welsh Government to develop new evidence which supports Prosperity for All by using the SAIL Databank at Swansea University, to link and analyse anonymised data. ADR Wales is part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant ES/S007393/1). The National Centre for Population Health and Wellbeing Research is funded by Health and Care Research Wales.

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