Bridging research and policy

Test, trace and isolate programmes across the UK are under pressure as COVID-19 cases rise in all age groups and demand for tests grows. Further pressure comes from people seeking tests because they have symptoms caused by other respiratory viruses but need a test in order to rule out COVID-19. The Scientific Advisory Group on Emergencies has described the impact of current test and tracing on the transmission of the virus as “marginal”. How does test and trace work and what are the current challenges limiting its effectiveness in reducing COVID-19 cases?

People’s behaviour has a major role in the success of test, trace and isolate programmes. Uncertainty about whether to report symptoms, low perceived risk of COVID-19 disease and concerns about the consequences of self-isolation are among the barriers to adherence. Has the Scientific Advisory Group for Emergencies looked at adherence to TTI? What evidence is there on people’s understanding and willingness to be tested, provide contact details and self-isolate? Is there anything that can be done to improve this?

During the first 6 months of the pandemic, people from ethnic minority groups were more likely to have COVID-19 disease and also more likely to experience severe outcomes from infection, including death. Lockdown measures have also disproportionately affected some communities more than others. What is driving this increased prevalence and death rates in ethnic minority groups? To what extent is it due to biology or pre-existing health? Or does it represent a continuation and exacerbation of social inequalities?

Machine learning (ML, a type of artificial intelligence) is increasingly being used to support decision making in a variety of applications including recruitment and clinical diagnoses. While ML has many advantages, there are concerns that in some cases it may not be possible to explain completely how its outputs have been produced. This POSTnote gives an overview of ML and its role in decision-making. It examines the challenges of understanding how a complex ML system has reached its output, and some of the technical approaches to making ML easier to interpret. It also gives a brief overview of some of the proposed tools for making ML systems more accountable.

A heat network provides heating and hot water to an apartment, commercial site or series of buildings close together. It can also provide cooling. There is interest in using them to help reduce greenhouse gas emissions from UK buildings. This POSTnote looks at the technology of heat networks and their sources of heat. It looks at considerations when building new networks. It also outlines a potential future market framework.

This POSTnote describes edge computing, the use of computing resources in close proximity to the place where data are processed within a network, and some of the opportunities and challenges associated with its use. It supplements POSTnote 629.

The POST Board approved 3 new POSTnotes on 16 September 2020. Topics include childhood obesity, preventing zoonotic diseases, and digital skills for life. Work on these topics will start in January 2021.

A POSTnote on digital skills for life will discuss the digital skills required for everyday life and employment, why parts of the population may lack these skills and which groups are most affected. It will consider the impact of the skills shortage on individuals and the economy as well as strategies to improve the population’s digital skills. Provisional start date: January 2021.

A POSTnote on preventing zoonotic diseases will review the evidence on a One Health approach to zoonoses prevention. It will focus on the animal-environment-human interface in both wild and domestic animals, reviewing national and international policy approaches, and lessons learnt from previous epidemics. It will also summarise opportunities and challenges for the UK’s role in global health and biosecurity policy arenas post COVID-19. Provisional start date: January 2021.