̽��ֱ�� of Cambridge - epidemic

Opinion: Patient zero: why it's such a toxic term

fpjl2 — Wed, 01 Apr 2020 15:14:09 +0000

Dr Richard McKay traces the history of the 'patient zero' idea through epidemics such as HIV and typhoid, and the return of this trope with COVID-19.

Opinion: How we lost our collective memory of epidemics

cjb250 — Tue, 31 Mar 2020 07:41:03 +0000

Over the past 70 years richer nations have gradually lost their sense of danger concerning epidemics and serious infections, writes Professor Gordon Dougan. We must now reacquire this instinctive memory.

Half of Ebola outbreaks go undetected, study finds

ta385 — Fri, 14 Jun 2019 09:00:00 +0000

̽��ֱ��research, led by Emma Glennon from Cambridge’s Department of Veterinary Medicine, is the first to estimate the number of undetected Ebola outbreaks. Although these tend to involve clusters of fewer than five people, they could represent well over one hundred patient cases in total.

̽��ֱ��study, published today in PLOS Neglected Tropical Diseases, found that the chance of detecting an isolated case of Ebola was less than 10%.

Glennon, a Gates Cambridge Scholar, says: “Most times that Ebola has jumped from wildlife to people, this spillover event hasn’t been detected. Often these initial cases don’t infect anyone else but being able to find and control them locally is crucial because you never know which of these events will grow into full outbreaks.”

"We rarely find Ebola outbreaks while they are still easy to manage. ̽��ֱ��unfolding epidemic in the DRC demonstrates how difficult it is to stop the disease once it has got out of control, even with international intervention. But if an outbreak is detected early enough, we can prevent it spreading with targeted, low-tech interventions, such as isolating infected people and their contacts.”

̽��ֱ��scientists used three independent datasets from the 2013–16 Ebola epidemic in West Africa to simulate thousands of outbreaks. From these simulations, they worked out how often they would expect a spillover event to fizzle out early versus how often they would expect to see it progress into a true outbreak. This allowed the team to draw comparisons with reported outbreak sizes and estimate detection rates of clusters of different sizes.

Glennon says: “Most doctors and public health workers have never seen a single Ebola case and severe fever can easily be misdiagnosed as the symptom of malaria, typhoid or yellow fever. To limit outbreaks at their source, we need to invest much more to increase local capacity to diagnose and contain Ebola and these more common fevers.

"We must make sure every local clinic has basic public health and infection control resources. International outbreak responses are important but they are often slow, complicated and expensive.”

Reference:

Glennon, E.E., Jephcott, F.L., Restif, O., Wood, J.L.N. ‘Estimating undetected Ebola spillovers’. PLOS Neglected Tropical Diseases (2019). DOI: 10.1371/journal.pntd.0007428

Half of Ebola outbreaks have gone undetected since the virus was discovered in 1976, scientists at the ̽��ֱ�� of Cambridge estimate. ̽��ֱ��new findings come amid rising concern about Ebola in the Democratic Republic of Congo, and highlight the need for improved detection and rapid response to avoid future epidemics.

We rarely find Ebola outbreaks while they are still easy to manage

Emma Glennon

UN Photo/Martine Perret

Burial team in Guinea carry a victim of Ebola, 2015.

Funding

Gates-Cambridge Trust (Bill & Melinda Gates Foundation [OPP1144]), the ALBORADA Trust, the Medical Research Council (MR/P025226/1).

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. Images, including our videos, are Copyright © ̽��ֱ�� of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.

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Target ‘best connected neighbours’ to stop spread of infection in developing countries

fpjl2 — Mon, 24 Jul 2017 19:04:04 +0000

Our lives benefit from social networks: the contact and dialogue between family, friends, colleagues and neighbours. However these networks can also cost lives by transmitting infection or misinformation, particularly in developing nations.

In fact, when there is an outbreak of disease, or of damaging rumour that hinders uptake of vaccination, the network through which it spreads needs to be broken up – and fast.

But who are the people with most connections – the ‘hubs’ in any social network – that should be targeted with inoculating drugs or health education in order to quickly isolate a contagion?

Information about social networks in rural villages in the developing world is costly and time-consuming to collect, and usually unavailable. So current immunisation strategies target people with established community roles: healthcare workers, teachers, and local officials.

Now, Cambridge researchers have for the first time combined networking theories with ‘real world’ data collected from thousands of rural Ugandan households, and shown that a simple algorithm may be significantly more effective at finding the highly connected ‘hubs’ to target for halting disease spread.

̽��ֱ��‘acquaintance algorithm’ employed by researchers is remarkably simple: select village households at random and ask who in their network is most trusted for medical advice.

Researchers were surprised to find that the most influential people in social networks were very often not those with obvious positions in a community. As such, these valuable ‘hubs’ are invisible to drug administration programmes without the algorithmic approach.

“Everyone is a node in a social network. Most nodes have just a few connections. However, a small number of nodes have the majority of connections. These are the hubs we want to uncover and target in order to intentionally cause failure in social networks spreading pathogens or damaging behaviour,” says lead researcher Dr Goylette Chami, from Cambridge’s Department of Pathology.

“It was striking to find that important village positions may be best left untargeted for interventions seeking to stop the spread of pathogens through a rural social network,” says Chami.

In the study, published today in the journal PNAS, the researchers write that this simple strategy could be particularly effective for isolating households that refuse to take medicine, so that they don’t endanger the rest of a community with infection.

To control disease caused by parasitic worm infections, for example, at least three quarters of any given community need to be treated. “ ̽��ֱ��refusal of treatment by a few people can result in the destabilisation of mass drug administration programmes that aim to treat 1.9 billion people worldwide,” says Chami.

An average of just 32% of households (‘nodes’) selected by the acquaintance algorithm need to be provided health education (and ‘removed’ from a network) to reach the disease control threshold for an entire community. Using traditional role-based targeting, the average needed is much larger: some 54%.

“We discovered that acquaintance algorithms outperformed the conventional field-based approaches of targeting well-established community roles for finding individuals with the most connections to sick people, as well as isolating the spread of misinformation,” says Chami

“Importantly, this simple strategy doesn’t require any information on who holds which role and how to reach them. No database is needed. As such, it is easy to deploy in rural, low-income settings.”

“In an ideal world, everyone would be treated,” says Chami. “However, with limited resources, time and information, finding the best connected neighbours, the ‘hubs’, and removing them through treatment, looks to be the quickest way to fragment a network that spreads infections, and to render the most people safe.”

Chami and colleagues from Cambridge and the Ugandan Ministry of Health collected data on social and health advice networks from over 16,000 people in 17 villages across rural Uganda. They also collected data on networks of disease using reports of diarrhoea as a proxy for infection spread – particularly relevant to recent large-scale cholera outbreaks.

To do this, Chami built a survey app from open source code and loaded it on to 76 Google nexus tablets. ̽��ֱ��team then trained a number of individuals from the local villages to help them go door to door.

Adds Chami: “This kind of ‘network theory’ approach to public health in the developing world, and the use of acquaintance algorithms, if tested in randomised controlled trials, may increase compliance to treatments and inform strategies for the distribution of vaccines.”

An innovative new study takes a network theory approach to targeted treatment in rural Africa, and finds that a simple algorithm may be more effective than current policies, as well as easier to deploy, when it comes to preventing disease spread – by finding those with “most connections to sick people”.

Finding the best connected neighbours, the ‘hubs’, and removing them through treatment, looks to be the quickest way to fragment a network that spreads infections

Goylette Chami

A fishing village along Lake Victoria in the Mayuge District of Uganda, close to where researchers gathered data for the latest study.

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. For image use please see separate credits above.

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California’s sudden oak death epidemic now ‘unstoppable’ and new epidemics must be managed earlier

jeh98 — Mon, 02 May 2016 19:02:00 +0000

Sudden oak death – caused by Phytophthora ramorum, a fungus-like pathogen related to potato blight – has killed millions of trees over hundreds of square kilometres of forest in California. First detected near San Francisco in 1995, it spread north through coastal California, devastating the region’s iconic oak and tanoak forests. In 2002 a strain of the pathogen appeared in the south west of England, affecting shrubs but not oaks, since English species of oak are not susceptible. In 2009 the UK strain started killing larch – an important tree crop – and has since spread widely across the UK.

In a study published today in PNAS, researchers from the ̽��ֱ�� of Cambridge have used mathematical modelling to show that stopping or even slowing the spread of P. ramorum in California is now not possible, and indeed has been impossible for a number of years.

Treating trees with chemicals is not practical or cost-effective on the scales that would be necessary for an established forest epidemic. Currently the only option for controlling the disease is to cut down infected trees, together with neighbouring trees that are likely to be infected but may not yet show symptoms. “By comparing the performance of a large number of potential strategies, modelling can tell us where and how to start chopping down trees to manage the disease over very large areas,” explains Dr Nik Cunniffe, lead author from Cambridge’s Department of Plant Sciences.

̽��ֱ��authors say that preventing the disease from spreading to large parts of California could have been possible if management had been started in 2002. Before 2002 not enough was known about the pathogen to begin managing the disease. Their modelling also offers new strategies for more effectively controlling inevitable future epidemics.

In close liaison with colleagues from DEFRA and the Forestry Commission, models developed in Cambridge are already an integral part of the management programme for the P. ramorum epidemic in the UK. ̽��ֱ��models are used to predict where the disease is likely to spread, how it can be effectively detected and how control strategies can be optimised.

Sudden oak death is known to affect over one hundred species of tree and shrub, presenting a significant risk to the biodiversity of many ecosystems. ̽��ֱ��death of large numbers of trees also exacerbates the fire risk in California when fallen trees are left to dry out. There is now concern that the disease may spread to the Appalachian Mountains, putting an even larger area of trees at risk.

“Our study is the first major retrospective analysis of how the sudden oak death epidemic in California could have been managed, and also the first to show how to deal with a forest epidemic of this magnitude,” explains Cunniffe.

“Even if huge amounts of money were to be invested to stop the epidemic starting today, the results of our model show this cannot lead to successful control for any plausible management budget. We therefore wanted to know whether it could have been contained if a carefully-optimised strategy had been introduced sooner. Our model showed that, with a very high level of investment starting in 2002, the disease could not have been eradicated, but its spread could have been slowed and the area affected greatly reduced.”

̽��ֱ��model also indicates how policymakers might better plan and deploy control when future epidemics emerge.

“It is a tool by which we can make a better job next time, because it is inevitable that there will be a next time,” says Professor Chris Gilligan, senior author and also from the Department of Plant Sciences. “With this sort of epidemic there will always be more sites to treat than can be afforded. Our model shows when and where control is most effective at different stages throughout a developing epidemic so that resources can be better targeted.”

“It can be tempting for authorities to start cutting down trees at the core of the infected area, but for this epidemic our research shows that this could be the worst thing to do, because susceptible vegetation will simply grow back and become infected again,” explains Cunniffe.

Cunniffe, Gilligan and colleagues found that instead treating the ‘wave-front’ – on and ahead of the epidemic in the direction that disease is spreading – is a more effective method of control. They also found that ‘front-loading’ the budget to treat very heavily and earlier on in the epidemic would greatly improve the likelihood of success.

“Unlike other epidemic models, ours takes account of the uncertainty in how ecological systems will respond and how the available budget may change, allowing us to investigate the likelihood of success and risks of failure of different strategies at different points after an epidemic emerges,” says Gilligan.

“Whenever a new epidemic emerges, controlling it becomes a question of how long it takes for us to have enough information to recognise that there is a problem and then to make decisions about how to deal with it. In the past we have been starting from scratch with each new pathogen, but the insight generated by this modelling puts us in a better position for dealing with future epidemics,” he adds.

̽��ֱ��researchers say that the next step in dealing with well-established epidemics such as sudden oak death is to investigate how to protect particularly valuable areas within an epidemic that – as they have demonstrated – is already too big to be stopped.

̽��ֱ��methodology is already being applied to create related models for diseases that threaten food security in Africa, such as pathogens that attack wheat and cassava.

This research was enabled by funding from the BBSRC, DEFRA, NSF, USDA and the Gordon and Betty Moore Foundation.

Inset image: Extensive control starting in 2002 could have greatly slowed epidemic spread (map shows risk of infection in 2030 under no control on left; control on and ahead of wave-front on right) (Nik Cunniffe).

New research shows the sudden oak death epidemic in California cannot now be stopped, but that its tremendous ecological and economic impacts could have been greatly reduced if control had been started earlier. ̽��ֱ��research also identifies new strategies to enhance control of future epidemics, including identifying where and how to fell trees, as “there will be a next time”.

It is a tool by which we can make a better job next time, because it is inevitable that there will be a next time

Professor Chris Gilligan

David Rizzo

Large-scale tree mortality in northern Sonoma County, California

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. For image use please see separate credits above.

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Uninfected or asymptomatic? Diagnostic tests key to forecasting major epidemics

cjb250 — Tue, 05 Apr 2016 18:00:00 +0000

Emerging epidemics pose a significant threat to human health worldwide. A principal challenge in infectious disease epidemiology is accurately forecasting the threats posed by diseases early in emerging outbreaks. Accurate real-time forecasts of whether or not initial reports of cases of disease will be followed by a major outbreak – an epidemic in which large numbers of people become infected – are necessary to determine which control measures should be deployed.

For all infectious diseases, there is a delay between infection and the appearance of symptoms, known as the ‘incubation period’, during which infected individuals are classed as ‘presymptomatic’. ̽��ֱ��incubation period, say researchers from the Department of Plant Sciences at Cambridge, can drive significant uncertainty in forecasting during the earliest stages of epidemics.

In research funded by the Biotechnology and Biological Sciences Research Council, the team used mathematical modelling to evaluate the effect of presymptomatic infection on predictions of major epidemics, choosing the Ebola virus as a case study. Their results, published today in the online journal PLOS Computational Biology, show for the first time that precise estimates of the current number of infected individuals – and consequently the chance of a major outbreak in the future – cannot be inferred from data based on symptomatic cases alone. This is the case even if factors such as the average infection rate and the death or recovery rates of individuals in the population can be estimated accurately.

“If we are able to use diagnostic tests to determine whether individuals who do not show symptoms are susceptible or are instead infected but not showing symptoms, we’ll be in a better position to estimate the chance of a major outbreak,” says Dr Nik Cunniffe, who led the study. “Since the reliability of diagnostic tests affects the extent to which forecasting is possible, it’s important not just to develop new diagnostic tests, but also to ensure those we have are continually refined and promptly deployed.”

Although the researchers chose Ebola as a representative case study of a disease for which reports of initial cases are not always followed by a large epidemic, they say their results are applicable to other outbreaks, including not just those that affect humans.

“These findings – that accurate forecasting relies on informing models with data on presymptomatic infections – hold true for anything from the current Zika outbreak through to animal diseases such as bluetongue and even plant pathogens such as Xylella fastidiosa, that is currently causing such devastation to olive groves in southern Italy,” adds first author Robin Thompson, a former PhD student at the Department of Plant Sciences, and now a postdoctoral researcher at the ̽��ֱ�� of Oxford.

̽��ֱ��researchers acknowledge that their models are based on an idealised setting, in which symptomatic cases and deaths were recorded perfectly and in which the values of disease transmission parameters were known exactly. However, they say that additional uncertainty will only make forecasting even more challenging. Presymptomatic infection alone makes prediction imprecise, reinforcing the need to better estimate levels of hidden infection in populations using diagnostic testing.

Reference
Thompson, RN, Gilligan, CA, Cunniffe, NJ. Detecting Presymptomatic Infection Is Necessary to Forecast Major Epidemics in the Earliest Stages of Infectious Disease Outbreaks. PLOS Computational Biology; 5 April 2016; DOI: 10.1371/journal.pcbi.1004836

Major epidemics such as the recent Ebola outbreak or the emerging Zika epidemic may be difficult to forecast because of our inability to determine whether individuals are uninfected or infected but not showing symptoms, according to a new study from the ̽��ֱ�� of Cambridge. ̽��ֱ��finding emphasises the need to develop and deploy reliable diagnostic tests to detect infected individuals whether or not they are showing symptoms, say the researchers.

If we are able to use diagnostic tests to determine whether individuals who do not show symptoms are susceptible or are instead infected but not showing symptoms, we’ll be in a better position to estimate the chance of a major outbreak

Nik Cunniffe

DFID - UK Department for International Development

Ultra-violet screening for potentially Ebola-carrying liquids (cropped)

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A whole host of options

cjb250 — Fri, 09 Oct 2015 08:30:04 +0000

Professor Lalita Ramakrishnan is, it’s fair to say, a world authority on the biology of TB. She studies the disease – one which most people will know of as a disease of the lungs – using what at first sight seems an unusual model: the zebrafish.

“What most people don’t realise is that about 40% of human TB occurs outside the lungs,” explains Ramakrishnan. “It can infect the brain, bone, heart, reproductive organs, skin, even the ear. In fact, TB infection is a basic biology question, and this is the same in zebrafish as it is in humans.”

TB is caused by Mycobacterium tuberculosis, which is generally transmitted from person to person through the air. It has been around since at least the Neolithic period, but its prevalence in 19th-century literature led it to be considered something of a ‘romantic’ disease. ̽��ֱ��truth is a long way from this portrayal. ̽��ֱ��disease can cause breathlessness, wasting and eventual death. And while treatments do exist, the drug regimen is one of the longest for any curable disease: a patient will typically need to take medication for six months.

Ramakrishnan is involved in a new trial due to start soon that might allow doctors to reduce the length of this treatment. She is cautiously optimistic that it can be reduced to four months; if successful, however, it may eventually lead to treatments more on a par with standard antibiotic treatments of a couple of weeks.

̽��ֱ��trial builds on work in zebrafish carried out by Ramakrishnan and colleagues at the ̽��ֱ�� of Washington, Seattle, before she moved to the Department of Medicine in Cambridge in September 2014. These small fish, which grow to the length of a little finger, helped her and collaborator Professor Paul Edelstein from the ̽��ֱ�� of Pennsylvania (currently on sabbatical in Cambridge) to make an important discovery that could explain why it takes a six-month course of antibiotics to rid the body of the disease (rather than seven to ten days that most infections take) and yet in the lab can easily be killed.

Within our bodies, we have a host of specialist immune cells that fight infection. One of these is the macrophage (Greek for ‘big eater’). This cell engulfs the TB bacterium and tries to break it down. This, together with powerful antibiotics, should make eliminating TB from the body a cinch. Ramakrishnan’s breakthrough was to show why this wasn’t the case: once inside the macrophages, TB switches on pumps, known as ‘efflux pumps’. Anything that we throw at it, it just pumps back out again.

“Once we’d identified the pumps, we started to look for drugs that are out there in the market and tested a few of them,” she explains. “We found that verapamil, an old drug, made the bacteria susceptible to two of the antibiotics we use to fight TB.”

̽��ֱ��trial of verapamil, which is commonly used to treat high blood pressure, is due to start soon at the National Institute for Research in Tuberculosis (NIRT) in Chennai, India.

Ramakrishnan is one of a number of brilliant minds working as part of a collaboration between the NIRT and the ̽��ֱ�� of Cambridge to apply the very latest in scientific thinking and technology to the problem of TB.

An expansion of this collaboration has now become possible through the recent award of a £2 million joint grant from the UK Medical Research Council (MRC) and the Department of Biotechnology (DBT) in India, which will enable the exchange of British and Indian researchers. For Professor Sharon Peacock, the UK lead on the proposal, this means an opportunity to train a new cohort of early-career researchers in an environment where they will have access to outstanding scientific facilities and training, at the same time as becoming familiar with the clinical face and consequences of TB for people in India.

“India is home to a large pool of talented young people with the potential to help fight back against this deadly disease,” says Peacock. “Developing a close collaboration between Cambridge and Chennai involving two-way traffic of scientists and ideas is an exciting opportunity to start to tap into this.”

There are few places more suitable for the proposed work than India. According to the World Health Organization, India is home to almost one in four of all worldwide cases of TB, with over two million newly diagnosed cases in 2014.

Not only that, but it is one of the countries that has seen an increase in the number of cases of drug resistance to TB – including ‘multi-drug’-resistant, and even more worrying, ‘extremely’ drug-resistant strains of TB against which none of our first- and second-line drug treatments work. In part, this increase reflects improved access to diagnostic services, but the situation highlights why new approaches to tackling the disease are urgently needed, says Professor Soumya Swaminathan, Director of NIRT and the India lead in the collaboration.

“So far, the treatment of TB has focused almost exclusively on using drugs to try to kill the bacteria directly, but there’s increasing evidence that there may be benefits to targeting the host. TB is very clever and it manipulates the host immune system to its own advantage, so if we could use drugs to help the immune system, then we may be able to make it more effective.”

This is the approach that Professors Ken Smith and Andres Floto from the Department of Medicine at Cambridge, also part of the collaboration, are taking. Smith is looking at the role that specialist immune cells known as T cells play in the persistence of multi-drug-resistant strains of TB. His group has evidence that around two thirds of the population have T cells which have a tendency to become ‘exhausted’ when activated.

“It might be that exhausted T cells can’t fight multi-drug-resistant TB effectively, in which case we need to find a way to overcome this exhaustion and spur the T cells on to rid the body of the disease,” says Smith.

For Floto, the key may lie in the role played by the macrophages and their otherwise voracious appetites. As their Greek name suggests, macrophages ‘eat’ unwanted material (surprisingly similar in action to Pac-Man), effectively chewing it up, breaking it down and spitting it out again.

This process, known as autophagy (‘self-eating’), is a repair mechanism for clearing damaged bits of cells and recycling them for future use, but also works as a defence mechanism against some invading bacteria. So why, when it engulfs TB, does the bacterium manage to avoid being digested?

“Autophagy is partially inhibited by TB itself, but we found that if you overstimulate this mechanism – like flooring the accelerator of a car – you can overcome the bacteria,” explains Floto. “Clearly this will be applicable to normal TB, but we already have drugs that are effective against this. We want to know if this would work against multi-drug-resistant strains.”

Floto and colleagues already have a list of potential drugs that can stimulate autophagy, drugs that have already been licensed and are in use to treat other conditions, such as carbamazepine, which is used to treat epileptic seizures. These drugs are safe to use: the question is, will they work against TB?

“We’ve already shown that carbamazepine stimulates autophagy in cells to kill TB – even multi-drug-resistant TB. We now want to refine it and test it in mice and in fish, alongside a shortlist of around 30 other potential drugs,” he adds.

TB evolves through ‘polymorphisms’ – spontaneous changes in the letters of its DNA to create variants. Because the drug regimen to fight the disease lasts so long, many patients do not take the full course of their medicines. If the TB is allowed to relapse, it can evolve drug resistance.

These patterns of resistance can be detected using genome sequencing – reading the DNA of the bacteria. Peacock believes this technique may be able to help doctors more easily diagnose drug resistance in patients.

“TB is very slow to grow in the laboratory, which means that testing an organism to confirm which antibiotics it is susceptible or resistant to can take several weeks, especially in the case of more resistant strains,” she says. “There is increasing evidence that antibiotic resistance can be predicted from the genome sequence of the organism, and we want to establish and evaluate this technology in India, where it is needed.”

This sequencing data could also then help inform the search for new drugs, explains Professor Sir Tom Blundell from the Department of Biochemistry. He is no stranger to TB: his grandfather died from the disease shortly after the war – though, as Blundell points out, this strain of TB is far less common now, as the organism has evolved in different communities throughout the world.

“We can take the polymorphisms and ask questions such as ‘What does this mean for the use of current drugs?’” says Blundell. “ ̽��ֱ��nature of the polymorphisms in the TB genome sequence of an infected individual can give us information on where that person was infected and what are the drugs that might be most effective. We can then begin to look at new targets for particular polymorphisms.”

Blundell plans to take the information gathered through the Chennai partnership and feed it into his drug discovery work. He takes a structural approach to solving the problem: look at the shape of the polymorphism and its protein products and try to find small molecules that can attach to and manipulate them. In essence, it’s akin to picking a lock by analysing the shape of its mechanism and trying to identify a key that could turn it, thus opening the door.

Yet even if the Chennai venture is successful, and research from the partnership leads to a revolution in how we understand and treat TB, the team recognise that this is unlikely to be enough to eradicate the disease for good.

“TB is as much a public health issue as one of infectious diseases,” says Ramakrishnan, pointing to Europe, where even before the introduction of antibiotics, the disease was already on the decline. “We need better nutrition, better air, less smoking, reductions in diabetes.”

Swaminathan agrees. “TB is very much associated with poverty and all the risk factors that go with it,” she says. “When people are living in very crowded conditions, when they’re malnourished, TB is going to continue to spread. This is happening in the slums of Mumbai, for example, where we’re seeing a mini-epidemic of multi-drug-resistant TB. Unless we see a rapid improvement in the living standards of people we’re not going to see a very major effect. There’s only so much we can do biomedically.”

Inset image: Macrophage engulfing Tuberculosis pathogen (ZEISS Microscopy).

Almost one in four of the world’s cases of tuberculosis (TB) are in India and the disease is constantly adapting itself to outwit our medicines. Could the answer lie in targeting not the bacteria but its host, the patient?

What most people don’t realise is that about 40% of human TB occurs outside the lungs ... It can infect the brain, bone, heart, reproductive organs, skin, even the ear

Lalita Ramakrishnan

Calcutta Rescue

Picture to educate people in villages that have no medical service about the spread of TB

̽��ֱ��Next Generation

If there’s one thing on the side of science v. TB, it’s the wealth of talent available in India.

Professor Sir Tom Blundell is quick to praise the Indian postdocs that come to work in his lab. “They tend to be naturally very inquisitive and interactive, with very enquiring minds,” he says.

This is something with which Professor Ashok Venkitaraman, Director of the Medical Research Council (MRC) Cancer Unit at Cambridge, wholeheartedly agrees. He has helped establish the Center for Chemical Biology and Therapeutics (CCBT) in Bangalore in part, he says, because “the number of really bright, well-trained young scientists in India is huge. ̽��ֱ��level of enthusiasm and commitment is something I find quite exceptional.”

̽��ֱ��CCBT is an inter-institutional centre that links the Institute for Stem Cell Biology and Regenerative Medicine and the National Center for Biological Sciences, both of which are world-class Indian research institutes studying fundamental biology. However, argues Venkitaraman, India needs the capacity to translate fundamental research to clinical application.

It is to help bridge this gap that the CCBT was established, with funding from the Department of Biotechnology (DBT) in India, recently supplemented by a £2 million joint award from the UK MRC and the DBT. ̽��ֱ��idea is to find innovative ways to discover ‘next-generation’ medicines against human diseases, by coupling biological research that reveals novel drug targets with approaches in chemistry and structural biology that create potential drug candidates.

Although Venkitaraman’s interest is in cancer, he predicts the work of the CCBT will be “disease agnostic”, because similar types of novel drug targets have been implicated in infectious diseases, cancer and even developmental defects.

“We desperately need to develop new medicines not just for currently problematic diseases like cancer and TB, but also for the new challenges that are being thrown at us all the time – antibiotic resistance, new infections, metabolic syndromes and diseases of ageing, for example. Nowhere is this need more critical than in emerging nations like India where the spectrum of disease is distinct from countries like the UK.”

̽��ֱ��text in this work is licensed under a Creative Commons Attribution 4.0 International License. For image use please see separate credits above.

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