Covid Control Plan: Data Management

Data is crucially important in developing effective outbreak prevention and control arrangements, including:

• Data to prevent and manage local outbreaks
• Data to effectively deploy local testing capacity
• Data to deliver effective contact tracing
• Data to support vulnerable people
• Data to understand vaccination uptake
• Data to monitor local confidence
• Data to make movement restriction decisions
• Data protection protocols
• Understanding of data needs

It is also crucial that we have effective systems and processes around the datasets to ensure an effective outbreak prevention and control response. To achieve this, we have developed an outbreak management system, which includes an outbreak case management system. This system allows us to hold all the relevant information about suspected and confirmed outbreaks that we have been notified of.

Testing data

Positive and negative Pillar 1 and 2 test results are automatically notified to GP systems as part of patient records. These data are also available to the Health Protection Team through the Second Generation Surveillance System (SGSS) database through which lab results are processed.

All PCR-based testing data, both positive and negative is now shared with the Directors of Public Health, including identifiable data which allows more robust surveillance and epidemiological work to take place at a local level. This means we have a much greater understanding of the local spread of the virus and can put in place more effective controls at a local level. These data are shared with the DsPH under strict data protection rules.

We have also been able to develop a number of dashboards - both internal (which is shared with key partners) and public facing, to provide a snapshot of COVID-19 across the city on a daily basis as well as track overall trends. This is updated each weekday at www.newcastle.gov.uk/coronavirus

NHS Test and Trace data

Test and trace datasets are now shared with the Directors of Public Health This provides a level of identifiable data for both contact tracing and ‘contacts’ of those positive cases. Before the establishment of the Local Test and Trace Hub, these data sets we used to carry out some local contact tracing work in response to specific areas of concern such as higher positivity rates in certain geographies and wards in the city, which had been identified through the analysis of the testing data or through the intelligence from the single point of contact and outbreak management process.      

Data sharing and analysis

With the development of the PHE COVID-19 Situational Awareness Explorer Portal, a much wider range of data is now shared and can be used to carry out local analysis. This data is not always timely; therefore, we do not view it in isolation. We also use data and intelligence we receive through our Public Health Single Point of Contact and outbreak management process.

Soft intelligence is defined as non-clinical testing data which may help provide a broader overview of the impact or perceived impact of COVID-19 upon our communities. This is much more ‘live’ which means we can pick up emerging trends or issues at a much quicker pace.

We use other non-clinical data available to us to provide further intelligence on the impact or perceived impact of COVID-19 upon our communities and to inform decision making. This includes, but is not limited to:

• Urban Observatory open data on footfall and social distancing
• Clinically Extremely Vulnerable (CEV) data
• Information from social media
• Mobile phone data
• Press and media coverage
• Symptom data from existing apps
• Historical data
• Data from our COVID-19 CityLife Line service and other council systems

Next steps

Our approach to using and analysing data has evolved and continues to do so. Looking ahead, we will work to:

• Develop the Local Test and Trace Hub data system and analysis so we can identify complex case and take local action.
• Develop and expand further the level of analysis around the COVID Single Point of Contact and outbreak management system so we can identify and react the outbreaks and clusters as quickly as possible as we start to reduce community spread of the virus.    
• Gain access to more granular level vaccination data so we can understand the populations and areas of the city with lower vaccination uptake.
• Use data to support activity to try to address the inequalities in vaccination and future COVID-19 cases.