Luke Evans: My Coronavirus report from near the Leicester lockdown front line

1 Jul

Dr Luke Evans is a member of the Health Select Committee, and is MP for Bosworth.

As I sit down to write this week’s column I hope that you will excuse it’s slightly erratic nature and its stream of consciousness tone. Forgive me.

As a Leicestershire MP, the last 48 hours have been taken over by the news of the Government’s local lockdown of Leicester and, at first, considering the approach which should be taken should any of my own Bosworth constituency be included in the lockdown area; and subsequently what steps we may have to take locally now we know that we are not.

Over the weekend, rumours started circulating in the media that ‘Leicester’ might become subject to the first localised lockdown since the imposition of Coronavirus legislation. There is a cluster of outbreaks – which must be taken seriously.

Like many cities, ‘Leicester’ is quite difficult to accurately define. Did rumours relate solely to the local government area that is the ‘City of Leicester’, or could it include the suburbs which stretch out towards the rural areas which are covered by Leicestershire County Council’s jurisdiction, and of course the constituencies of our seven Conservative MPs?

I set out on Monday morning to do my due diligence by speaking with regional public health leads, our chief constable and the chair of our local resilience forum, to get the actual facts on the ground.

During the day, it became increasing clear that a local lockdown would be imposed imminently, and I was invited to a Zoom call with other Leicestershire MPs, the elected Mayor of Leicester, the Leader of the County Council, Dido Harding, senior leaders in Public Health England and Nadine Dorries, the Health Minister.

During the course of that conversation, it became quickly apparent that the data is worrying enough in Leicester to make a local lockdown was inevitable; with an R rate stubbornly stuck at one, it was clear that, unless something was done now, this outbreak could get considerably out of hand…and quickly. To be safe, lockdown would include parts of the county – potentially including my own constituency.

Although incidents of Coronavirus are showing a marked national trend downwards, it is obvious that this isn’t the case in parts of Leicester. Nationally, for every 100 people tested for Covid-19 – that is those displaying symptoms –  two receive positive tests; in Leicester, that figure increases to ten.

Leicester now accounts for 10 per cent of Covid-19 admissions nationally and, crucially, the trend is not downwards.

Clearly, it is important that we understand why the trends in Leicester are so different from the national ones. The health specialists were in agreement that it is not due to the national release of lockdown (otherwise you would expect hot spots popping up all across the country), so something else must be going on.

At this point, the uptick appears multifactorial, and plenty of work is going on to establish categorically what these factors are, but right now our focus is much more about practicalities and what to do.

How do we guarantee health safety, effective enforcement of lockdown, protecting businesses and support for livelihoods? How do we communicate all of this to the public, preventing spread and make best use of shared working?

Questions like these all immediately sprung to mind, and were evidently shared by all fellow MPs on the call.

Post-meeting, it was straight onto a statement from the Health Secretary, and then my first step was to speak with members of my team with a plan, followed by courtesy calls to councillors whose wards and divisions were likely to be affected and local leaders.

I’m very conscious that an MP never works on their own, and I very much rely on my team and local activists. I said in my maiden speech that healthcare taught me that “empowering those who can and helping those who can’t” is critical; this situation ably demonstrated this again.

In the wake of the Secretary of State’s statement, as you might expect, calls continued well into the night.

Yesterday morning started with a very early meeting with the Health Minister and Leicestershire MPs to digest the news, update and then talk about practicalities.

As Tuesday progressed, further questions come to forefront.

With worried residents, particularly those living in the city commuter belt, it would have been preferable if a map of the lockdown area had been produced far quicker than it actually was. There are many questions about how we can prevent those living in the lockdown area from visiting areas, including my own, where restrictions are being lifted this weekend.

Government was clear it was for local decision makers to decide the extent of the boundary, given that they are best placed to know natural geography, and how communities function in real life not just on a map. (The map is not the territory coming through here from last week!)

Ultimately, I see my role as being that of an honest broker in a fluid situation. I’m determined not to put information out because I want to be first with the news, but rather believe it is best to wait until updates are properly verified.

Instead, what are the worries of my constituents both regarding their safety and their livelihoods? My job is to do my best to secure both.

Over the course of yesterday, I had further meetings and calls with officials from the Department of Health, Home Office, Treasury and local leaders from the police, council and LRF, to name but a few.

Like any emergency situation faced, you want to deliver clear, accurate information, even if that maybe no further news, that is an imperative.

The situation reminds me of my early days as an A&E doctor. The relatives of a very sick patient will always want updates quickly, yet medical uncertainty about how the patient will respond is difficult, added to which the demands of my bosses might be altogether different; but at the end of the day you can lay out what you know, what you are doing and why, and how you expect the poorly person to respond.

The outbreak in Leicester city is no different….now we have two weeks to watch for signs of response, and I will continue to be communicating them to my constituents, working with all the teams involved to get the best outcome; a safe time to return the easing of lockdown.

Rob Sutton: Introducing the top 50 Conservative MPs on Twitter

29 Jun

Conservative MP Twitter power rankings: the top 50

Rob Sutton is an incoming junior doctor in Wales and a former Parliamentary staffer. He is a recent graduate of the University of Oxford Medical School.

Amongst the social media giants, Twitter is the primary battleground for political discourse. It’s also one of the key avenues by which MPs convey their message, and has near-universal uptake by members in the current House of Commons.

The effectiveness with which Twitter is utilised varies considerably between MPs, but it is difficult to compare like-for-like. How does one take into account the differences between, for instance, a freshman MP and a veteran Cabinet member? Length of service in Parliament and ministerial rank give a considerable advantage when building a following.

In this article, I have compiled a power ranking of MPs in the current Parliament, with the top 50 shown in the chart above. The MP’s follower count was adjusted by factoring in their previous experience, to better reflect the strength of their following and their success at engagement on the platform.

Being Twitter-savvy is about more than just a high follower count: any Secretary of State can achieve this just by virtue of the media exposure their office brings. Building a Twitter following based on thoughtful commentary and authentic engagement requires skill ,and can be achieved by members across all Parliamentary intakes and ranks of Government.

Though the top 10 is still dominated by MPs holding senior ministerial offices, the composition of the list beyond it is far more variable. A number of prominent backbenchers are in the top 20, and four members from the 2019 intake make the top 50, beating longer-serving and higher-ranked colleagues.

I hope that this list serves as recognition of the skill and contribution by Conservative members to public debate and engagement, beyond ministerial duties which so often dominate any mention in the media.

Building a model of Twitter power rankings

Success is judged by number of followers, with higher follower counts indicating greater influence on Twitter. The follower count was adjusted using three key parameters:

  • The number of years since an MP was first elected to Parliament.
  • The number of years the MP’s Twitter account has been active.
  • Their highest rank within Government achieved since 2010.

Higher values for each of these would be expected to contribute to a higher follower count. I built a model using the open-source Scikit-Learn package, and fitted it to data from the current Parliament.

The model was then used to predict how many followers a given MP might expect to have based on these three factors. The steps taken to produce a final “Twitter power score” were thus as follows:

  • Using these three factors, multiple linear regression was used to calculate the expected number of Twitter followers an MP might have.
  • Their true follower count was divided by the expected follower count to produce a single number which represented the MP’s performance at building a following.
  • Finally, a logarithm was taken of this ratio to make the number more manageable and to produce a final Twitter power score.

The final step of taking a logarithm means it is easier to compare between MPs without those who have very high follower counts (such as Boris Johnson) making the data difficult to compare, but it does not affect the order of the ranking.

Compiling the data

Having decided which factors to correct the model for, I collected the required information. All three factors were easy to find reliable sources for. The Twitter page for each MP displays the date the account was created, and the Parliamentary website provides the date of their first election to Parliament and previous government posts.

Members who are newly returned to the backbenches following governmental duties (such as Sajid Javid and Jeremy Hunt) are scored at their highest government rank since 2010 to recognise this. I was able to find the Twitter accounts and required information for 319 Conservative MPs who were included in this ranking.

To build a model based on this data required incorporating the highest government rank numerically. To do this, I assigned scores according to their rank. These grades recognised their relative seniority and media exposure associated with the office, with higher scores assigned to more senior positions:

  • Prime Ministers, Secretaries of State, Speakers, Leaders of the House and Chief Whips are scored 3.
  • Ministers of State, Deputy Speakers and Deputy Chief Whips are scored 1.
    Parliamentary Under-Secretaries of State, Parliamentary Private Secretaries and Whips are scored 0.5.
  • Backbenchers score 0.

When assigning these values, I considered the typical sizes of follower counts of MPs in each category. When comparing Secretaries of States to Ministers of State, the median follower count is around twice the size, but the mean follower count is around eight times the size, as a handful of very large follower count skews the results upwards.

Deciding on weightings requires a (somewhat arbitrary) decision as to which measures to use when comparing between groups, and the scores I decided on were ultimately chosen as a compromise across these different measures, which produced stable results when used in the model.

It is also worth explaining why Prime Ministers are grouped with Secretaries of State, despite the far higher media exposure and seniority of their post. When deciding on the respective weighting for different levels of government post, a sufficiently large pool of MPs was needed to produce a meaningful comparison. The only data points for comparison of Prime Ministers are Boris Johnson and Theresa May, so it is difficult to give them their own weighting without it being either unreliable or arbitrary.

While grouping them with Secretaries of State and other senior positions might be perceived as giving them an unfair advantage in the weighting, I felt it justified given these challenges in determining the “fair” weight to assign them. With this done, I had three parameters for each MP on which to build a model to calculate the expected number of Twitter followers.

Calculating the number of expected Twitter followers

I built a model to calculate the expected number of Twitter followers using the Scikit-Learn, a popular machine learning package in the Python programming language. The model used multiple linear regression to fit the input parameters to the known follower count.

The input data was prepared by removing extreme high outliers in the data which skewed the fit toward high numbers and away from the vast majority of MPs before fitting. Once fitted, an “expected value” of Twitter followers could be calculated for each MP, based on the year of their first election to parliament, the number of years on Twitter and their highest government rank since 2010.

Including more parameters increases the ability of the model to describe the difference between MPs’ follower counts (the variability). By increasing the number of input variables included in the model, more of the variability is captured:

  • One variable captures between 20.3 per cent and 36.1 per cent of the variability.
  • Two variables capture between 39.1 per cent and 43.1 per cent of the variability.
  • All three variables capture 48.7 per cent of the variability.

These three variables are therefore responsible for almost half of the variation between MPs in their follower counts. The remainder of the variability is likely due to a range of factors which the model does not include, of which the MP’s Twitter-savviness is of particular interest to us. I discuss these factors further below.

Limitations in the model

There are multiple other parameters which could be included in future iterations which I did not include in this model. In particular:

  • Membership or Chairmanship of Select Committees.
  • Previous election to a council, assembly, devolved legislature or the European Parliament.
  • Membership of the Privy Council.
  • Government positions prior to 2010.
  • Prominent positions within the Conservative Party, such as the 1922 Committee or European Research Group.
  • Twitter-savviness and effectiveness of their comms team.

Another limitation was not accounting for the perceived relative importance of various governmental departments: a Great Office of State or Prime Minister is scored the same as any other Secretary of State. The difficulties involved in ranking governmental departments were beyond this first model. The length of service in a given government post was also not considered.

Finally, the choice of model to fit the data may not be the optimal choice. Multiple linear regression assumes, per the name, that the distribution is linear. But the large outliers might be better described by a power law or Pareto distribution, or the non-linearities of a neural network.

During next week, ConservativeHome will produce profiles of six individual MPs who have performed notably well in the power rankings, and who reflect the contributions brought by members beyond their ministerial duties, if they have any.