Community Testing Review

We need to create a framework for data-driven community testing for future pandemics

Large-scale community testing was piloted in Liverpool during the COVID-19 pandemic, with the hope that it would help with the reopening of activities key to society and the economy, while controlling transmission of the virus. It is a massively complex intervention that needs more data, real-time intelligence and background understanding to deploy for maximum value. This review seeks to better understand how we might implement and exit future community testing schemes.

Large-scale testing enabled us to:

  • Protect vulnerable individuals and settings
  • Release people from quarantine or isolation
  • Have a safer return to activities key to society and the economy

Evaluation found that the mass testing was associated with an overall 25% reduction in COVID-19 related hospital admissions.

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Full report

A summary of the findings of the review can be found below, or click the link to be taken to the full review slides.
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About the review

  • Our objectives

    Convene a board of experts involved in the mass community testing to:

    1. Reflect on Covid-19 community testing evaluations / lessons

    2. Identify data and evaluation requirements for intelligence-led (de)escalation of community testing in future scenarios

    3. Publish a framework for programmable risk-mitigation with intelligence-led community testing in pandemics / epidemics

  • What we found

    Areas for further development:

    – Science communications
    – Rapid spread of evidence and best practice
    – Coproduction of tests with users
    – Understanding testing motivation
    – Complex intervention evidence
    – Use of AIs for behavioural insights
    – Access to national data
    – Timely intelligence on viral kinetics
    – Economic models
    – Systems thinking – ‘national grid’ of local public health

  • Our recommendations

    For future community testing schemes we recommend:

    – Prompt, well-governed access to nationwide data
    – Prepare for AIs that can augment complex decision-making and (semi-)automate responses
    – Prepare the policy, political and public health system for distributed resilience to pandemics
    – Define strategies for exiting large-scale/high-cost testing promptly
    – Set proportionate evaluation policies for testing programmes
    – Prepare sleeper protocols now
    – Prepare to work more with security services via DSTL
    – Rehearse different behavioural scenarios around testing uptake/hesitancy and test result reporting
    – Optimise self-test kit usability and reporting functionality now
    – Pre-engineer companion AIs to optimise testing value for individuals and society
    – Prepare antiviral policies linked to testing policies
    – Prepare to link science and industrial supply chains flexibly
    – Incentivise supply chain agility through HealthTech industry growth

Mass community testing evaluation

For an overview of the findings of the mass community testing initiative, click the link.
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