̽��ֱ�� of Cambridge - epidemiology

̽��ֱ��“zero-chance” doctor who now advises government

cg605 — Wed, 19 Oct 2022 11:47:38 +0000

Growing up on free school meals at one of the lowest performing state schools in the country, Raghib Ali went on to become a leading epidemiologist and OBE awardee. He’s determined to improve the life outcomes of children from poor backgrounds so that they too can reach their full potential.

New national modelling group to provide faster, more rigorous COVID-19 predictions

sc604 — Thu, 18 Feb 2021 16:47:30 +0000

̽��ֱ��JUNIPER consortium (‘Joint UNIversities Pandemic and Epidemiological Research’) brings together leading mathematical and statistical modellers from seven UK universities and has received £3 million in funding from UK Research and Innovation (UKRI).

JUNIPER is developing and using customised models to provide predictions and estimates on key questions about the COVID-19 pandemic. These results feed regularly into SPI-M, the modelling group that provides evidence to the Scientific Advisory Group for Emergencies (SAGE) and the wider UK government.

Examples of modelling JUNIPER provides to government includes:

Understanding how new variants are spreading across the UK and developing statistical models to determine whether new variants are causing more hospitalisations or deaths.
Forecasting and providing real-time estimates of the R-value, using data from sources such as Pillar 1 and 2 testing, hospital data and mobility data. They are currently providing eight of 12 models contributing real-time R estimates that go from SPI-M to SAGE each week.
Modelling the effectiveness of different testing strategies on virus transmission and suppression, and modelling the effect of vaccinations and predicting outcomes from different scenarios of how to ease lockdown restrictions.

Professor Julia Gog, co-lead of the consortium from Cambridge’s Department of Applied Mathematics and Theoretical Physics, said: “By bringing research groups together from our seven universities we can provide predictions and estimates about the pandemic to address questions from the government with unprecedented speed. By combining the right expertise together swiftly across research teams we can now respond to questions in less than 24 hours, which might have taken a week for one team working alone. And further, being able to call upon specialist expertise combinations across multiple research groups means we can provide more robust outputs.

“In this unprecedented pandemic, modelling has been hugely important to provide evidence-based predictions and estimates at great speed. Our insights from transmission modelling are fully integrated with scientific evidence from other disciplines and feed into government decision-making.”

Professor Matt Keeling, co-lead of the consortium from the ̽��ֱ�� of Warwick, said: “We’re generating about half the models for the nowcasting that goes into SPI-M and SAGE every week. This consortium allows us to not only boost our speed and capacity, but also to continue to advance the accuracy of our models using the new data and growing knowledge from the pandemic.

“Standard epidemiological modelling tools have worked well so far, but the future with COVID-19 now demands a suite of new tools to deal with the upcoming complexities of the pandemic, such as localised regional outbreaks, growing understanding of socioeconomic differences with this disease, complexities of imperfect vaccines and the growing problem ahead with new variants. Having several teams using different models working on the same problem helps us to verify our results and makes the consortium much bigger than the sum of its parts.”

̽��ֱ��consortium is funded as part of UKRI’s COVID-19 Agile Call, which has so far invested more than £150M in over 400 projects to address the impacts of the COVID-19 pandemic.

Professor Charlotte Deane, COVID-19 Response Director at UKRI, said: “This consortium enables disease modellers to pool their expertise nationally to increase the scale, speed and quality of their models of policy options and predictions for the pandemic. They’ll provide cutting-edge evidence about the pandemic into the UK government’s decision-making.”

̽��ֱ��consortium will also proactively generate new model-based predictions and develop the necessary methodology as part of a horizon-scanning process.

̽��ֱ��consortium plan to make their models open-source, so scientists worldwide can access them and benefit.

̽��ֱ��seven universities involved in JUNIPER are Cambridge, Warwick, Exeter, Oxford, Bristol, Manchester and Lancaster Universities.

They will work closely with other organisations and research teams active on COVID-19 research including the Alan Turing Institute, the Royal Statistical Society, Health Data Research UK, Public Health England, the Royal Society’s ‘RAMP’ initiative, and the Isaac Newton Institute for Mathematical Sciences.

A new national consortium, co-led by the ̽��ֱ�� of Cambridge, will bring together mathematical modellers to produce faster, more rigorous predictions for the COVID-19 pandemic and advise UK government bodies.

Gordon Johnson from Pixabay

Connections

̽��ֱ��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.

Yes

Researcher profile: Professor Julia Gog

sc604 — Wed, 08 Apr 2020 11:55:40 +0000

In the midst of the pandemic, she has been providing advice to the Government through SPI-M, the specialist pandemic modelling group that feeds into SAGE, the Scientific Advisory Group for Emergencies, as well as through Cambridge’s Centre for Science and Policy (CSaP).

In 2018, she and her team were behind the UK’s largest citizen science experiment in collaboration with the BBC, using location data from mobile phones to map how pandemic influenza might spread across the UK. ̽��ֱ��massive dataset that resulted from the experiment, the largest and most detailed of its kind, has been useful to teams working on the current pandemic.

"Public health experts have been saying for decades that when it comes to pandemic flu, it wasn’t a matter of if, it was a matter of when," Gog said. "And now that this coronavirus pandemic is here and things are changing every day, we’ve got to get information out there quickly, but making sure that it’s useful information that can help inform good policy."

With the earliest cases of COVID-19 in the UK, it was possible to perform contact tracing and shut down early chains of transmission. ̽��ֱ��data suggests that there wasn’t a single case that began the virus’ spread across the UK, but multiple cases, each with their own transmission chains.

It’s likely that cases arrived relatively early London due to its centrality in the nation and as much of the country’s transport infrastructure is built around getting people in and out of London. With many international imports of new cases, eventually the approach of contact tracing is overwhelmed and transmission takes hold within the UK, requiring the introduction of more severe overall social distancing measures to control transmission.

Once cases are rising exponentially, in order to contain the pandemic we must reduce the number of people that each contagious person infects. In disease dynamics, this reproduction ratio is called R. For any epidemic or pandemic to die out, in the absence of a vaccine, the effective R needs to be less than one: that is, if each contagious person infects less than one other person, then the number of new cases will slow and, eventually, stop. Current data suggests that the original reproduction ratio, R0, for coronavirus was between 1.5 and 3.5.

For modellers like Gog, knowing how and when people come into contact with other people helps determine R, and in turn helps develop a model of how a pandemic spreads.

̽��ֱ��data from the BBC Pandemic project provides a highly useful source of data on how we most often come into contact with others. For those of working age, the workplace is the source of much person-to-person contact, so switching to remote working for those who can do so will reduce transmission between workplace colleagues. For those over 65, who are most at risk from severe illness due to COVID-19, most contact occurs outside the home, in places such as shops, restaurants and leisure activities, so shutting down these non-essential activities is also key to reducing R.

Earlier in the pandemic, there was criticism of the Government’s initial reluctance to close schools. However, Gog says that all the evidence suggests that school closures will only reduce transmission rates between 10 and 20 percent. Earlier models of the spread of seasonal ‘flu have looked at schoolchildren as key spreaders, but the behaviour of children, in particular teenagers, has changed a great deal in the past decade: teenagers now do much of their socialising online, and don’t so often gather in large groups as much as older generations did, a point that was confirmed by the BBC Pandemic data. In addition, it is unclear at the moment how much role children play in coronavirus transmission, whether they are as susceptible and infectious as adults.

"We have to adapt our models to account for the way that people are behaving now," said Gog. "Four weeks ago, a transmission reduction of ten or twenty percent might not have seemed like a lot. Additionally, children who were out of school while their parents were continuing to work might have gone to spend the day with their grandparents, putting them at risk. But right now, we’ll take any reduction you can get. ̽��ֱ��key thing now is to keep the number of critical cases as low as you can to reduce burden to a point that health systems can manage."

Every model has a degree of uncertainty, and for Gog, the biggest challenge in mapping how COVID-19 might continue to spread is that there has not been widescale testing in the UK. There is no ‘one true model’, and so epidemiological modellers have been modelling a range of scenarios and adapting as more data becomes available. In addition, there is a lag between the number of reported deaths and when those people became infected, further complicating the work of Gog and her colleagues.

"There are different ways this all plays out based on the information we have right now, and we have to model for different eventualities," said Gog. "It’s likely we won’t see very clearly the full effect of the lockdown measures until they have been in place for a few weeks."

Looking beyond the next few weeks, Gog says the information she and her colleagues around the country are desperate to have is information about what proportion of the population has been infected, via widescale antibody testing.

"Once we have that information, it will help us make better decisions about what to do next," said Gog. "If only a small proportion of the population has contracted the virus, then we could remain in lockdown for quite some time, whereas if a significant part of the population has already had it, then we can start thinking about how we get back to normal."

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Professor Julia Gog is a mathematician who specialises in modelling the spread of infectious diseases, particularly pandemic influenza. For months, she and the other members of her research group in the Department of Applied Mathematics and Theoretical Physics have been modelling and mapping the spread of coronavirus and COVID-19.

Henry Kenyon

Julia Gog

Yes

AstraZeneca/GSK/ ̽��ֱ�� of Cambridge collaborate to support UK national effort to boost COVID-19 testing

plc32 — Tue, 07 Apr 2020 10:46:52 +0000

A new testing laboratory will be set up by AstraZeneca, GSK and Cambridge at the ̽��ֱ��’s Anne McLaren Building. This facility will be used for high throughput screening for COVID-19 testing and to explore the use of alternative chemical reagents for test kits in order to help overcome current supply shortages.

Alongside this new testing facility, AstraZeneca and GSK are working together to provide process optimisation support to the UK national testing centres in Milton Keynes, Alderley Park and Glasgow for COVID-19, providing expertise in automation and robotics to help the national testing system to continue to expand capacity over the coming weeks.

While diagnostic testing is not part of either company’s core business, we are moving as fast as we can to help where possible - with a focus on providing our world class scientific and technical expertise - working both with the Government’s screening programme and alongside the wider life sciences sector and specialist diagnostic companies.

Further updates on progress will be issued on this work in due course.

We continue to pay tribute to those working on the frontlines of this pandemic, in the UK and globally. Defeating COVID-19 requires a collective effort from everyone working in healthcare and we are committed to playing our part.

As part of the UK Government’s announcement of a new five pillar plan to boost testing for COVID-19, AstraZeneca, GSK and the ̽��ֱ�� of Cambridge have formed a joint collaboration to take action to support this national effort.

Everyone in this ̽��ֱ�� and private industry partnership is working hard to help our health service fight COVID-19.

Vice-Chancellor Stephen J Toope

Yes

Women in STEM: Emma Glennon

sc604 — Thu, 17 Oct 2019 06:00:00 +0000

I try to understand how and why new diseases emerge. As cities grow and climates change, new and poorly-understood diseases are causing outbreaks more and more frequently. I build models to help understand how this happens, from how zoonotic diseases – that is, diseases that ‘jump’ from animals to people – circulate in wildlife to how we can detect rare viruses once they make that jump into people. This work is sometimes theoretical but sometimes directly applicable to public health; next month I expect to be deployed to the Democratic Republic of the Congo to work as an epidemiologist on the Ebola outbreak response.

I do primarily computational work, so most days I code and run simulations and write. However, to get to know more of my (very interdisciplinary) team and understand the data I use, I also went to Australia for fieldwork last year. While there, my work looked completely different: I caught bats, collected samples, and climbed a few trees to try to find out what they were eating. Catching bats requires such obscure skills as stringing up flag poles, detangling claws from nets, writing labels in the dark, and feeling vibrations through strings from impacts 20 meters away. I also had a few too many close encounters with spiders the size of my fist.

My hope is that eventually we will understand how to better prevent, detect, and stop outbreaks. Once these sorts of diseases start spreading among people--as we’ve seen in recent years with Ebola--outbreaks can get out of control quickly. Prevention can take a number of forms, including changing how we interact with our environments to protect the health of wildlife and developing health capacity to make sure we notice an outbreak as soon as it starts.

One of my favourite parts of doing a PhD here has been the freedom to do pursue truly interdisciplinary and international work. I’ve learned about my own field in a deep way, but I’ve also been able to learn from collaborators in ecology, virology, computer science, and anthropology, and I think my work is much better for it.

Be stubborn and support other women. There are real frustrations with being a woman in STEM, but in my experience it's easier to get through them if you stand up for what you're passionate about, what you're good at, and where you want to go. And if you are successful, please support other women trying to do the same! Being part of supportive circles of women and LGBTQ+ scientists has been invaluable to me, and I hope one day I get to help make the road a little smoother for others.

Emma Glennon is a PhD candidate in the Department of Veterinary Medicine and a Gates Cambridge Scholar. Here, she tells us about her research on infectious disease and how they emerge, the importance of interdisciplinary work, and learning how to catch bats.

Yes

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.

Yes

Lack of exercise responsible for twice as many deaths as obesity

cjb250 — Wed, 14 Jan 2015 19:00:00 +0000

Physical inactivity has been consistently associated with an increased risk of early death, as well as being associated with a greater risk of diseases such as heart disease and cancer. Although it may also contribute to an increased body mass index (BMI) and obesity, the association with early death is independent of an individual’s BMI.

To measure the link between physical inactivity and premature death, and its interaction with obesity, researchers analysed data from 334,161 men and women across Europe participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) Study. Between 1992 and 2000, the researchers measured height, weight and waist circumference, and used self-assessment to measure levels of physical activity. ̽��ֱ��participants were then followed up over 12 years, during which 21,438 participants died. ̽��ֱ��results are published today in the American Journal of Clinical Exercise.

̽��ֱ��researchers found that the greatest reduction in risk of premature death occurred in the comparison between inactive and moderately inactive groups, judged by combining activity at work with recreational activity; just under a quarter (22.7%) of participants were categorised as inactive, reporting no recreational activity in combination with a sedentary occupation. ̽��ֱ��authors estimate that doing exercise equivalent to just a 20 minute brisk walk each day – burning between 90 and 110 kcal (‘calories’) – would take an individual from the inactive to moderately inactive group and reduce their risk of premature death by between 16-30%. ̽��ֱ��impact was greatest amongst normal weight individuals, but even those with higher BMI saw a benefit.

Using the most recent available data on deaths in Europe the researchers estimate that 337,000 of the 9.2 million deaths amongst European men and women were attributable to obesity (classed as a BMI greater than 30): however, double this number of deaths (676,000) could be attributed to physical inactivity.

Professor Ulf Ekelund from the Medical Research Council (MRC) Epidemiology Unit at the ̽��ֱ�� of Cambridge, who led the study, says: “This is a simple message: just a small amount of physical activity each day could have substantial health benefits for people who are physically inactive. Although we found that just 20 minutes would make a difference, we should really be looking to do more than this – physical activity has many proven health benefits and should be an important part of our daily life.”

Professor Nick Wareham, Director of the MRC Unit, adds: “Helping people to lose weight can be a real challenge, and whilst we should continue to aim at reducing population levels of obesity, public health interventions that encourage people to make small but achievable changes in physical activity can have significant health benefits and may be easier to achieve and maintain.”

Reference
Ekelund, U et al. Activity and all-cause mortality across levels of overall and abdominal adiposity in European men and women: the European Prospective Investigation into Cancer and Nutrition Study (EPIC). American Journal of Clinical Nutrition; 14 Jan 2015

A brisk 20 minute walk each day could be enough to reduce an individual’s risk of early death, according to new research published today. ̽��ֱ��study of over 334,000 European men and women found that twice as many deaths may be attributable to lack of physical activity compared with the number of deaths attributable to obesity, but that just a modest increase in physical activity could have significant health benefits.

This is a simple message: just a small amount of physical activity each day could have substantial health benefits for people who are physically inactive

Ulf Ekelund

Thomas Leuthard

Walk Alone...

̽��ֱ��text in this work is licensed under a Creative Commons Licence. If you use this content on your site please link back to this page. For image rights, please see the credits associated with each individual image.

Yes

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Attribution

Universal approach to tackling lifestyles more appropriate for combating diabetes than focusing on genetic risk

cjb250 — Tue, 20 May 2014 21:00:00 +0000

Over 380 million people worldwide are estimated to be affected by diabetes, with serious consequences for the health and economy of both developed and developing countries. Type 2 diabetes is thought to originate from a complex interplay of a large number of genetic risk variants and lifestyle factors, such as diet and exercise. Lifestyle interventions can reduce the risk of developing diabetes in high-risk individuals by 50%; however, whether there is value in targeted lifestyle interventions according to a person’s genetic susceptibility is unclear.

In an attempt to answer this question, a team of researchers led by the ̽��ֱ�� of Cambridge studied 12,403 middle-aged individuals from the 340,234 person European Prospective Investigation into Cancer and Nutrition (EPIC) cohort who developed type 2 diabetes and a further control subset of 16,154 participants. ̽��ֱ��researchers calculated a genetic risk score for type 2 diabetes for these individuals based on which of 49 known genetic variants for the disease each person carried, and arranged the individuals into four equally-sized groups from lowest to highest genetic risk score. They then examined the combined effects of the genetic score and lifestyle factors on the development of diabetes. ̽��ֱ��results of the study, which was mainly funded by the European Commission under its Framework 6 programme, are published today in the open access journal PLoS Medicine.

̽��ֱ��researchers found that the percentage of people of normal weight who developed type 2 diabetes over a ten-year period varied between 0.25% for those with the lowest genetic risk to 0.89% for those with the greatest genetic risk. In obese people, these figures ranged from 4.22% to 7.99%. In other words, obese individuals had the highest risk of developing type 2 diabetes regardless of their genetic risk score, emphasising the role of lifestyle as being much more important in the development of the disease than genetics.

Professor Nick Wareham, Director of the MRC Epidemiology Unit, says: “We have known for a long time that there is no one cause for type 2 diabetes – it’s a complex interaction of dozens of genes and our lifestyles. Recent genetic breakthroughs have provided the promise of targeted lifestyle interventions based on a person’s genetic make-up. However, genetic risk factors are greatly outweighed by lifestyle factors.

“We need effective strategies in place if we are going to stem the rapid rise in the number of cases of type 2 diabetes and the burden this places on our health systems. Our research suggests that focusing on tackling the lifestyle factors that lead to obesity at a population level will have a much greater impact than tailoring prevention strategies according to an individual’s genetic risk.”

Professor David Lomas, Chair of the MRC’s Population and Systems Medicine Board, adds: “One of the most effective ways to reduce the impact of type 2 diabetes is to stop people developing the condition in the first place, and this large international study reinforces the idea that broad promotion of a healthy diet and lifestyle is the way to go. Genomic information has already given us important insights into the diabetes disease mechanism, and grouping patients based on their genes and other biological factors still holds a great deal of promise for directing more targeted treatments for type 2 diabetes.”

Public health strategies aimed at tackling obesity at a population level through lifestyle changes are more appropriate for preventing type 2 diabetes than targeted interventions based on an individual’s genetic risk, according to a study led by the Medical Research Council Epidemiology Unit at the ̽��ֱ�� of Cambridge.

We need effective strategies in place if we are going to stem the rapid rise in the number of cases of type 2 diabetes

Nick Wareham

Ralph Aichinger

One size fits all

Yes