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Perhaps the largest difference between the UK and France has been in the quality of data that is being provided to the public, to the media, and (I suspect) to the politicians making decisions about what to do. National, regional, sub-regional, and demographic breakdowns of deaths, hospital admissions, intensive care capacity and occupancy, excess deaths, and much more are provided regularly by French government bodies. The data.gouv.fr site hosts discussions where data is improved, improvements are requested, and analysis is shared. While The Financial Times has undoubtedly provided the best data analysis to the world, no UK paper has access to the data that would let it provide as good analysis to the country as the French press and French society have been able to provide to the French public and its politicians.

The technology will combine data on journey trends and live updates from station staff, to both inform passengers searching for journeys on the National Rail website and app, and alert those who opt in for updates on specific journeys, using their anonymised data to help predict how busy each train will be.

Data companies are offering to mine troves of personal and public information to help local officials in the UK identify people who are struggling in the aftermath of the coronavirus crisis.

The aim is to move beyond assigning risk just based on an individual’s health and also include those who might be at greater risk of domestic violence, marital breakdown and financial difficulties, said Xantura’s chief executive Wajid Shafiq.

Xantura’s software runs the data against a set of risk factors and demographic data, as well as the NHS’s “shielded list” of individuals believed to be most at risk from Covid-19 complications, scoring households according to their risk profile.

More than 370,000 people in the UK have symptomatic COVID-19, according to an app tracking the virus "in real time".

The figures from the app are more than double the 148,377 who have tested positive, according to the Department of Health's official numbers.

Looking at the news across the UK, there are indications that the easing of lockdown restrictions has led to serious traffic problems. For instance, police were forced to close Falkirk Council’s Roughmute recycling centre two hours after opening it due to traffic building up on roads approaching the site. In Milton Keynes, IKEA was forced to close its car park just two hours after opening due to traffic volumes. Transport Scotland indicated a 60% increase in traffic on Saturday 30th May, compared to the previous Saturday, with traffic at the tourist and leisure hotspot of Loch Lomond up by 200%.

There are various ways to measure traffic volumes. Here, we look at Split Cycle Offset Optimisation Technique (SCOOT) data. The data is gathered from detectors installed at traffic lights. The purpose of the system is to coordinate traffic lights to improve the flow of vehicles. We accessed data on Glasgow’s traffic through an API provided by Glasgow City Council.

The aggregate pattern hides substantial variation at the different locations where the measurements are taken, which could explain why people may have seen large increases in traffic in their local area.

These reports are based on similar analysis carried out on Italian data Pepe E. et al. 2020 and US data Klein B. et al. 2020. We aim to provide and assess the changes in commuting and mobility at local authority level across UK during the COVID-19 health crisis.

One moment the prime minister, Boris Johnson, was asking people with symptoms to stay home for seven days; a few days later, he had ordered a lockdown. What changed was data from Italy’s experience of the pandemic, in which more people were critically ill than anticipated, and from the NHS about its inability to cope if the same should happen in the UK.

“Agent-based models are particularly good in situations where you need to explicitly model the interactions and the behaviour of the individual components of a system,” says Nick Malleson, a professor of spatial science at the University of Leeds, who has worked with Improbable to study crime patterns. “I think the reason that they've become popular for [studying] disease spread is that very often in a disease spread, you might need to look at how people are interacting – when they come into contact in shops, how the social networks affect how people move, how they behave, how they interact, all these kinds of things.”

The crisis more than ever demonstrated there is a very clear need for data in real time (or as near to real time) as possible to help inform decisions. It showed that problems-to-be-solved can’t be solved by the data one organisation holds alone: inevitably joining-up data from other sources is required. It also told us that without greater data collaboration our routes to creative, scalable solutions will remain limited.

The UK’s unusually fragmented approach to public sector data means often we talk more about how data is not shared or is not available than how it is more seamlessly used to understand common needs or meet shared objectives.

For example, City Hall is using aggregated data from Vodafone, O2 and Mastercard payments to add to our view of the observance of lockdown restrictions and add our understanding of the health of local economies.

The idea behind so-called digital “passports” is that they would allow people who have recovered from the coronavirus to signal their immunity and thus move around freely, enabling economies to open up. But there are fears such a system, which is at a preliminary stage of discussion with the developer, could lead to discrimination, create perverse incentives to get infected, and violate privacy.

The scheme also relies on reliable antibody testing and enough kits for large-scale testing — neither of which exist, yet. Not to mention that health experts don’t know whether immunity to the coronavirus even exists and, if it does, how long it lasts. In late April, the World Health Organisation (WHO) warned against a passport scheme on the basis that “there is currently no evidence that people who have recovered from Covid-19 and have antibodies are protected from a second infection.”

Onfido’s technology would work by first verifying someone’s identity — by comparing a picture or video of their face against a picture of their identity card — and then linking that to a coronavirus test result. People would then be able to bring up a QR code on an app or a browser signalling their immunity status just by taking a picture of their face.

A US study suggests Covid-19 death rates rise by about 15% in areas with even a small increase in fine-particle pollution levels in the years before the pandemic."Patterns in Covid-19 death rates generally mimic patterns in both high population density and high [particulate matter] PM2.5 exposure areas," the Harvard University report says.

Health chiefs in the UK have tasked a team of software developers to “investigate” switching its unique contact-tracing app to the global standard proposed by Apple and Google, signalling a potential about-turn just days after the NHS launched its new coronavirus app. 

Purpose should govern the choice of dataset to focus on Standards should be the primary guide to the design of the datasets User engagement should influence engagement activities ‘on top of’ published data to secure prioritised outcomes New user needs should feed into standard extension and development User engagement should shape the initiatives built on top of data

The call for ‘raw data now‘ was not without purpose: but it was about the purpose of particular groups of actors: not least semantic web reseachers looking for a large corpus of data to test their methods on. This call configured open data towards the needs and preferences of a particular set of (technical) actors, based on the theory that they would then act as intermediaries, creating a range of products and platforms that would serve the purpose of other groups. That theory hasn’t delivered in practice

They describe a process that started with a purpose (“get better bids on contract opportunities”), and then engaged with vendors to discuss and test out datasets that were useful to them.

A YouGov poll has found eight out of 10 people would prefer the government to prioritise health and wellbeing over economic growth during the coronavirus crisis, and six in 10 would still want the government to pursue health and wellbeing ahead of growth after the pandemic has subsided, though nearly a third would prioritise the economy instead at that point.

The focus on GDP means economic growth can take place at the expense of the environment, and people’s quality of life, without any of the resulting damages ever being taken into account, the report argues. That in turn encourages ministers and officials to seek ways of raising the GDP figures, even if rising nominal growth is accompanied by environmental degradation, worsening health, poor educational attainment and increasing poverty.

The measures have quite different underlying methodologies. Details are very scant, but it is clear that Apple base their measures on requests for directions while Google base theirs on mobile phone locations.