How did modern London become “the tuberculosis capital of Europe”?

The Royal London Hospital in Whitechapel, in London's East End. Image: Getty.

Poverty, overcrowding, poor housing conditions... All these things, we learnt from a London Assembly report published last week, are contributing to an increase in the incidence of tuberculosis in the city.

The fact this most Victorian of diseases is on the rise is not exactly new information, either. In 2005, the BBC reported that the capital had 20 times the TB rate of the rest of the UK, and in 2010, the Telegraph described the city as “the TB capital of Europe”.

But how bad can it really be? The Tackling TB in London report is fairly explicit:

There were over 2,500 new cases of TB in London in 2014, making up approximately 40 per cent of all cases in the UK. One third of London’s boroughs exceed the World Health Organisation “high incidence” threshold of 40 cases per 100,000 population. And some boroughs have incidence levels as high as 113 per 100,000 people – significantly higher than countries such as Rwanda, Algeria, Iraq and Guatemala.

Ah.

Tuberculosis is caused by the mycobacterium tuberculosis bacteria, and mostly affects the lungs. The symptoms include persistent coughing, fever and tiredness. It's spread by coughing and sneezing, but don't start getting righteous on tube snifflers - you'd need to be in prolonged contact with an infected person to contract the disease.

It's not incurable, but patients can need to take antibiotics for up to six months – more if the strain of TB turns out to be one that’s resistant to drugs. The other danger is from latent TB - where a person is a carrier but doesn't actually have the symptoms.

TB had already been eradicated in the UK – but the disease has made a slow and steady return, thriving on overcrowding in deprived boroughs, poverty and Dickensian housing conditions. As Dr Onkar Sahota, chair of the Greater London Authority’s health committee, explains:

"The causes are complex and far from simply medical. TB affects those who most need our help: migrants, the elderly, prisoners, homeless people and those who are marginalised from society. TB has a relationship with deprivation as well as clinical causes.

“We know TB disproportionately affects prisoners, homeless people and people with substance abuse issues, and high quality TB care services are not universally available to all Londoners."

As to where the disease is on the increase, some boroughs are beset by far more cases than others. Here's a chart showing the 10 boroughs with the highest rates of infection:

Given the unfailing reliability with which some sections of the media crowbar the words “migration” and “ticking time-bomb” into their tuberculosis stories, it's no surprise that a lot of people think migrants are bringing the disease to the UK. But the World Health Organisation (WHO) refutes this, stating that there's “no systematic association” between migration and infectious diseases, adding that “communicable diseases are associated primarily with poverty”.

The writer of the report alluded to by the Telegraph, Professor Alimuddin Zumla of University College London, has made the same point. He noted that, while the increase in TB cases has been mainly among people born outside the UK, they appear to have been infected here rather than in their country of origin. With many migrants to London living in poverty, sleeping rough or in poor quality, overcrowded homes, it's hardly a surprise that they are more at risk.


Crucially, WHO advise against limiting access to medical assistance for immigrants, legal or otherwise. Suddenly, charging migrants to use the NHS doesn't seem like quite such a clever idea.

The homeless, another high risk group, are finding help in Hackney. The council has partnered with Homerton University Hospital to reduce what was once the highest rate of TB infection in London. Any homeless person with TB is given accommodation for the duration of their treatment, even if they're not actually eligible for housing in the first place.

The result? The borough's infection rate has dropped, and in July this year, the Homerton Hospital team won an award for their work.

In Newham, the borough with the current highest rate of infection (and, not coincidentally, one of London's most deprived), the council has partnered with the NHS Newham Clinical Commissioning Group to screen for latent TB when residents register with a GP. Newham was also one of the first councils to introduce a crackdown on “slum” landlords to try and tackle overcrowding.

The London Assembly's recommendations include a city-wide education programme, extending Hackney's housing plan to other boroughs and universal provision of the BCG vaccination. With around 1m people living in poverty, and with housing conditions as poor as they are, Londoners' health is also falling through the inequality gap.

You can read the report here (PDF).

Beth Parnell-Hopkinson is a senior editor at Londonist.

 
 
 
 

Just like teenagers, self-driving cars need practice to really learn to drive

A self-driving car, of unknown level of education. Image: Grendelkhan/Flickr/creative commons.

What do self-driving cars and teenage drivers have in common?

Experience. Or, more accurately, a lack of experience.

Teenage drivers – novice drivers of any age, actually – begin with little knowledge of how to actually operate a car’s controls, and how to handle various quirks of the rules of the road. In North America, their first step in learning typically consists of fundamental instruction conveyed by a teacher. With classroom education, novice drivers are, in effect, programmed with knowledge of traffic laws and other basics. They then learn to operate a motor vehicle by applying that programming and progressively encountering a vast range of possibilities on actual roadways. Along the way, feedback they receive – from others in the vehicle as well as the actual experience of driving – helps them determine how best to react and function safely.

The same is true for autonomous vehicles. They are first programmed with basic knowledge. Red means stop; green means go, and so on. Then, through a form of artificial intelligence known as machine learning, self-driving autos draw from both accumulated experiences and continual feedback to detect patterns, adapt to circumstances, make decisions and improve performance.

For both humans and machines, more driving will ideally lead to better driving. And in each case, establishing mastery takes a long time. Especially as each learns to address the unique situations that are hard to anticipate without experience – a falling tree, a flash flood, a ball bouncing into the street, or some other sudden event. Testing, in both controlled and actual environments, is critical to building know-how. The more miles that driverless cars travel, the more quickly their safety improves. And improved safety performance will influence public acceptance of self-driving car deployment – an area in which I specialise.

Starting with basic skills

Experience, of course, must be built upon a foundation of rudimentary abilities – starting with vision. Meeting that essential requirement is straightforward for most humans, even those who may require the aid of glasses or contact lenses. For driverless cars, however, the ability to see is an immensely complex process involving multiple sensors and other technological elements:

  • radar, which uses radio waves to measure distances between the car and obstacles around it;
  • LIDAR, which uses laser sensors to build a 360-degree image of the car’s surroundings;
  • cameras, to detect people, lights, signs and other objects;
  • satellites, to enable GPS, global positioning systems that can pinpoint locations;
  • digital maps, which help to determine and modify routes the car will take;
  • a computer, which processes all the information, recognising objects, analysing the driving situation and determining actions based on what the car sees.

How a driverless car ‘sees’ the road.

All of these elements work together to help the car know where it is at all times, and where everything else is in relation to it. Despite the precision of these systems, however, they’re not perfect. The computer can know which pictures and sensory inputs deserve its attention, and how to correctly respond, but experience only comes from traveling a lot of miles.

The learning that is occurring by autonomous cars currently being tested on public roads feeds back into central systems that make all of a company’s cars better drivers. But even adding up all the on-road miles currently being driven by all autonomous vehicles in the U.S. doesn’t get close to the number of miles driven by humans every single day.

Dangerous after dark

Seeing at night is more challenging than during the daytime – for self-driving cars as well as for human drivers. Contrast is reduced in dark conditions, and objects – whether animate or inanimate – are more difficult to distinguish from their surroundings. In that regard, a human’s eyes and a driverless car’s cameras suffer the same impairment – unlike radar and LIDAR, which don’t need sunlight, streetlights or other lighting.

This was a factor in March in Arizona, when a pedestrian pushing her bicycle across the street at night was struck and killed by a self-driving Uber vehicle. Emergency braking, disabled at the time of the crash, was one issue. The car’s sensors were another issue, having identified the pedestrian as a vehicle first, and then as a bicycle. That’s an important distinction, because a self-driving car’s judgments and actions rely upon accurate identifications. For instance, it would expect another vehicle to move more quickly out of its path than a person walking.


Try and try again

To become better drivers, self-driving cars need not only more and better technological tools, but also something far more fundamental: practice. Just like human drivers, robot drivers won’t get better at dealing with darkness, fog and slippery road conditions without experience.

Testing on controlled roads is a first step to broad deployment of driverless vehicles on public streets. The Texas Automated Vehicle Proving Grounds Partnership, involving the Texas A&M Transportation Institute, University of Texas at Austin, and Southwest Research Institute in San Antonio, Texas, operates a group of closed-course test sites.

Self-driving cars also need to experience real-world conditions, so the Partnership includes seven urban regions in Texas where equipment can be tested on public roads. And, in a separate venture in July, self-driving startup Drive.ai began testing its own vehicles on limited routes in Frisco, north of Dallas.

These testing efforts are essential to ensuring that self-driving technologies are as foolproof as possible before their widespread introduction on public roadways. In other words, the technology needs time to learn. Think of it as driver education for driverless cars.

People learn by doing, and they learn best by doing repeatedly. Whether the pursuit involves a musical instrument, an athletic activity or operating a motor vehicle, individuals build proficiency through practice.

The ConversationSelf-driving cars, as researchers are finding, are no different from teens who need to build up experience before becoming reliably safe drivers. But at least the cars won’t have to learn every single thing for themselves – instead, they’ll talk to each other and share a pool of experience.

Johanna Zmud, Senior Research Scientist, Texas A&M Transportation Institute, Texas A&M University .

This article was originally published on The Conversation. Read the original article.