Can Mathematics Trace a Path for Policymakers through Coronavirus Blockade in the UK?

In her presentation at the Retail Expo virtual conference, associate professor UCL and television presenter Hannah Fry discussed the power of data and how mathematical models can trace pathways through the coronavirus blockade in the UK.

As the daily updates of Covid-19 show, the reproduction number, known as “R”, is one of the key criteria that the government will evaluate before it starts facilitating the blockade. The R figure is directly related to the number of people a coronavirus infected person is infected with.

“It is critical that R be less than one,” said Fry.

Discussing some preliminary results of a new research, he said: “According to our data, returning to normal will not reduce the R. enough. Even if we tested 450,000 people a day, it would not be enough”.

Fry said it would be helpful to manually track all acquaintances that an infected person had been in contact with returns R almost where it should be, but this would not be exactly where the R value falls below one, which is necessary for the infection rate to drop.

Based on the assumption that everyone returns to work, Fry said that R would be less than one if the manual track was combined with people who limit their social interactions to four people a day.

“If we are in a situation where half of the county can work from home, where half of the county has zero business contacts, the number of people we can interact with actually has no effect,” he said.

Discussing the implications of this, he added: “One of the biggest things for me is keeping the number of people working from home as much as possible so that we can go back to seeing our friends and families.”

In 2017, Fry took part in a city science experiment in collaboration with the BBC, observing how an influenza-like pandemic could spread to a community. The results fueled political decisions made by the government to block the United Kingdom and try to ensure that people comply with social exclusion measures.

“When you have good data, good models, you can really make a difference,” he said. “We knew that a pandemic is inevitable. It was truly a case where, not if, and we knew we had to be as prepared as possible.”

In 2017, Fry claimed that the team of researchers from the London School of Hygiene and Tropical Medicine realized that they needed to improve the data they had in order to create a mathematical model to illustrate the effects of a flu-like pandemic.

“Together with the BBC, we did a study with real people, who gave us permission to follow them for 24 hours,” he said. “The data we collected was where people and, above all, how often they come into contact with other people.”

The researchers were able to gather 100,000 days of social interaction, Fry said, which is the fundamental data behind the government’s models. “We started our study in Haslemere in Surrey with me as a zero patient. What we could do with all the data is to simulate different scenarios. “

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