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World Malaria Day 2019

The 25 of April is World Malaria Day - a good time to take stock of progress towards dealing with one of the great historical global scourges.

Malaria is caused by a tiny parasite transmitted to humans by the bite of certain sorts of (Anopheline) mosquitos. It occurs though the tropics and subtropics. Historically is has caused so many deaths that it has been one of the most powerful selective forces acting on human evolution.

At the turn of this century malaria was rightly described by many as a ‘disaster’: resistance to drugs used in treatment was widespread and estimates of deaths were in millions a year. There was a sense of national and international paralysis. In response to this dire situation came a whole set of initiatives, including declarations by heads of states the initiation of new public private partnerships and the launch of the Global Fund to fight AIDS, TB and malaria. Often such efforts are greeted with a certain amount of scepticism but in this case they marked the beginning of a log order rise in global investment in malaria control and a truly remarkable change in the global malaria situation.

Professor Kevin Marsh

Over the next 15 years malaria reduced dramatically in almost all parts of the world accompanied by an incredible 60% reduction in malaria death rates. In large part this was due to the widespread deployment of effective new drugs, the so called artemisinin combinations and the use of bed nets impregnated with insecticide Encouraged by the possibilities many began to call for a new campaign of global malaria eradication. Others were concerned that this was hubristic, given the biological and social complexity of malaria. The WHO set out in 2015 a Global Technical Strategy, which while disappointing some by not calling for eradication in any short time frame, was in fact very ambitious in aiming at a 90% reduction in malaria deaths by 2030 and at least 35 countries to have achieved elimination.

Over the last few years we have come to a more realistic and nuanced appreciation of the global position. In areas of lower transmission progress toward the elimination targets is on track but at the other end of the spectrum malaria remains a major cause of death in high burden countires. 75% of the worlds estimated 435,000 deaths each year occur in just 11 countries, ten of them in Africa and the eleventh being India. Here progress is in danger of stalling without concerted political and societal action. Against this background there is also concern about emerging drug and insecticide resitance and static levels of international funding. On the more optimistic side there is exciting progress towards potential new tools including drugs, vaccines and ways of genetically modifying mosquito populations.

So on malaria day 2019 we can reflect both on the massive progress over the last 19 years and but also on the considerable challenges ahead. It is a matter of pride that researchers from many parts of Oxford University and especially the major overseas collaborating programmes in south East Asia and Africa have played a central role in the many of the developments that have contributed to the progress described above.

Kevin Marsh is Professor of Tropical Medicine at the Nuffield Department of Medicine.

Solar panels in a field

By Penny Mealey, Thom Wetzer and Matthew Ives

Search online for ‘climate change’ and ‘tipping points’, and you will find some scary results. The possibility for melting ice-sheets, the collapse of the Atlantic thermohaline circulation, the permafrost methane ‘bomb’ and even the dieback of the Amazon to ‘exacerbate the climate crisis’ and cause global warming to ‘spiral out of control’, makes for sobering reading. But what if we could leverage similar tipping-point dynamics to solve the climate problem? Like physical or environmental systems, socio-economic and political systems can – and frequently do – exhibit nonlinear dynamics. Memes on the internet can go viral, loan defaults can cascade into financial crises, and public opinion can shift in rapid and radical ways.

Research into such positive socio-economic tipping points is underway at the Institute for New Economic Thinking for the Oxford Martin School Post-Carbon Transitions Programme, headed up by Professors Doyne Farmer and Cameron Hepburn. In an article just published in Science, the team outline a new approach to climate change that seeks to identify areas in socio-economic and political systems that are ‘sensitive’ - where a modest, but well-timed intervention can generate outsized impacts and accelerate progress towards a post-carbon world. 

Sensitive Intervention Points (SIPs)

These ‘Sensitive Intervention Points’ (SIPs) often take the form of triggering non-linear feedback loops, which can amplify small effects to produce massive change. Take, for example, the case of solar photovoltaics. As more solar panels are produced and deployed, costs fall through learning-by-doing, which in turn leads to further production and more deployment. Our past research has shown such “experience curves” are persistent and can allow us to make predictions. However, the spread of renewables may not only arise from technological cost improvements. Social dynamics can also play a major role: as people observe their neighbours installing rooftop solar or behaving in environmentally-responsible ways, they might be more inclined to do so themselves. This in turn induces other people to act similarly and can potentially lead to a shift in cultural and social norms.

Another example is financial disclosure. Relatively modest changes to financial accounting rules or disclosure guidelines regarding climate risks could have outsized effects. Climate risk can take many forms, from physical risks caused by extreme weather or flooding to the risks associated with the economic transition necessary to limit warming to 1.5 or 2 degrees. Currently, many companies are not adequately disclosing these risks and investors are not pricing them, either.

This means that investors that do not incorporate these risks when allocating capital are implicitly subsidising high-emission industries relative to the clean industries, thereby stalling the post-carbon transition. Better pricing of climate risk will show that climate risk can present material risk to companies’ business models, triggering disclosure obligations and capturing investors’ interest. If such disclosure is consistent and comparable across companies, as championed by the widely-endorsed Task Force on Climate-Related Financial Disclosures, the implicit subsidy enjoyed by high-emission industries will start to disappear, and capital allocation in line with the post-carbon transition becomes more probable. Add to this renewable energy sources approaching parity with fossil fuels and we are starting to see much greater investments in renewables, even by large oil and gas companies.

Windows of Opportunity

Possibilities for triggering SIPs in a given system can also change over time. Sometimes ‘windows of opportunity’ open up, where very unlikely changes become possible. A key example in the United Kingdom was the political climate in 2007-2008, which enabled the 2008 UK Climate Change Act to pass with near unanimous agreement across parties. This national legislation was the first of its kind – committing the UK to reducing greenhouse gas emissions by 80% relative to 1990 levels by 2050, and creating a regular ratcheting cycle to encourage more ambitious future climate action. Since 2008, emissions in the UK have fallen dramatically. Add to this the UK Climate Change Act’s influence moving beyond the UK, influencing similar legislation in other countries, including the Paris Agreement, which contains the same self-reinforcing ratcheting mechanism.

An Agenda for SIPs

Such examples illustrate how adopting the SIP perspective could transform policy and business to accelerate the post-carbon transition. But much work lies ahead. Identifying SIPs can be tricky and requires a systemic identification strategy and a deep understanding of socioeconomic systems and their interaction with the Earth’s climate. What other parts of our socioeconomic system have tipping points, feedback effects, and windows of opportunity? How might we also create such dynamics? And once we have identified SIPs, how do we evaluate and rank them in order of importance? Current economic models designed to evaluate climate policy fall short and must be challenged by new economic thinking that accounts for such feedback effects. We cannot afford to fly blindly into the future.

The window to avert catastrophic climate change is closing fast, but with intelligent interventions at sensitive points in the system, we believe success is still possible. Since the stakes are so high, and the timeframe so limited, it is not possible to chase every seemingly promising idea. But with a smart, strategic approach to unleashing feedback mechanisms and exploiting critical windows of opportunity in systems that are ripe for change, we may just be able to tip the planet onto a post-carbon trajectory.

Do we learn best if we cram or if we plan?

Oxford neuroscientists are marking British Science Week and Brain Awareness Week (11th-17th March 2019) with an interactive experiment to help schoolchildren understand how to improve their revision skills.

Researchers from Oxford Neuroscience have designed a fun game that can be downloaded and played on a phone, which will test whether cramming for exams is successful, or whether learning something over a longer period of time produces a better outcome.

Once downloaded, users will be sorted into two groups: one group will take part in the quick learning, which is done in a single day, and the second group will be selected to take part in a week of learning, where they will play the game every day.

The University of Oxford will be collecting anonymous data about which group of people has most success in the game.

The results from the 'Find the Brain' game will be revealed live on Friday 15 March at 3.00pm, as a volunteer also plays the game while in an MRI scanner to show what’s going on in our brain when we are learning.

Throughout Brain Awareness Week there will also be events to delve into more detail about how the brain learns, how we can re-learn after stroke, how we learn during adolescence, and how sleep and exercise affect our learning.

Through interactive Facebook Lives with researchers, Twitter Takeovers and podcasts, researchers will be working with young people to explore how we can improve the way we learn.
Find out of you are a crammer or a planner by downloading the game from the dedicated microsite that has been created in partnership with British Science Week: www.oxfordsparks.ox.ac.uk/brain-discovery-week

Watch the results of the fun experiment revealed live from the fMRI scanner at the University of Oxford on Friday 15 March, 3.00pm, to find out who learned best: the crammers or the planners! www.facebook.com/OxSparks

Brain - graphical image

By Dr Wahbi El-Bouri

There are over 1.2 million stroke survivors in the UK, with 100,000 strokes happening in the UK each year. That’s the equivalent of one stroke every five minutes. They are also the leading cause of disability in the Western world.

Research underway in the Department of Engineering Science’s Cerebral Haemodynamics Group, headed up by Professor Stephen Payne, is changing our understanding of blood flow around the brain. Here, I explain how this could speed up the arduous process of bringing stroke drugs to market.

Our research has two main questions. Firstly, can we model blood and oxygen transport in the entire human brain, across the billions of blood vessels present? And secondly, can we run in-silico clinical trials (that is, trials performed entirely on a computer) of stroke and stroke treatment?

This is what we are tackling as part of a Horizon 2020 project (In-Silico Trials for Treatment of Acute Ischaemic Stroke) alongside European research collaborators from 10 other institutes, including radiotherapists, clinicians, academics, and industrial partners.

A continuous supply of oxygen and glucose, via the bloodstream, is essential to maintain healthy brain function under all circumstances. Whereas the rest of our body can release stored-up energy when we feel hungry, the brain has no such reserves. As such, any reduction in blood flow to the brain, even if only for a few minutes, can lead to cell death and loss of brain function. A large reduction of blood flow for a prolonged period of time, whether through a blocked or ruptured vessel, is known as a stroke.

In addition, dementia (the leading cause of death in the UK) is increasingly being linked to changes in our smallest blood vessels, or microvasculature, as we age. There is clearly an urgent need to understand the mechanisms of stroke and brain ageing in order to combat these debilitating diseases.

Capiliary velocityCapiliary velocity
Mathematical modelling is ideally positioned to help us understand and simulate these diseases and, more importantly, to run clinical drug trials on a computer. Currently, less than 10% of compounds go from clinical trial to market – with no explanation as to why a product is unsafe or ineffective.

The starting point for these models must be real-life data. Unfortunately, due to the low resolution of current clinical imaging modalities, the only way we can currently ‘see’ the smallest vessels in the brain (which average 1/10th the width of a human hair) is to image slices of dead human brains. Using these, researchers construct networks on a computer and simulate blood and oxygen transport. However, we quickly run into the problem of scaling up these networks to encompass the billions of blood vessels that make up the human brain.

Our team is using mathematical tools developed for use in the oil and gas industry, who have been trying to model water and oil flow through rock for decades. We treat the brain as a chunk of porous rock and hence approximate the flow through our brain, as opposed to modelling the flow in each individual vessel. This allows us to rapidly produce full brain computer models of blood and oxygen transport!

The models that we are developing, along with models of clot formation, clot removal using a stent and thrombolysis (dissolving the clot with drugs), will be used to run clinical trials on computers that can be personalised and help to inform real-life clinical trials. For example, certain geometries of blood vessels or certain clot positions may be more amenable to a certain treatment.

This knowledge, from the in-silico clinical trial, can then inform a real-life trial to target treatment to those people and hence improve the chances of that stroke treatment being brought to market and used to save lives. In the future, these models could be used to simulate a variety of neurological diseases and help us to understand the human brain, in both health and disease.

Read more about the Cerebral Haemodynamics Group’s research.

Find out more about Brain Awareness Week at Oxford.

This article was published to mark Brain Awareness Week, a global campaign running from 11-17 March. 


The concept of equilibrium is one of the most central ideas in economics. It is one of the core assumptions in the vast majority of economic models, including models used by policymakers on issues ranging from monetary policy to climate change, trade policy and the minimum wage. But is it a good assumption? In a recently-published Science Advances paper, Marco Pangallo, Torsten Heinrich and Doyne Farmer from the University of Oxford, investigate this question in the simple framework of games, and show that when the game gets complicated this assumption is problematic. If these results carry over from games to economics, this raises deep questions about when economics models are useful to understand the real world.

Kids love to play tic-tac-toe, aka noughts and crosses, but when they are about 8 years old they learn that there is a strategy for the second player that always results in a draw. This strategy is what is called an equilibrium in economics. If all the players in the game are rational they will play an equilibrium strategy. In economics, the word rational means that the player can evaluate every possible move and explore its consequences to their endpoint and choose the best move. Once kids are old enough to discover the equilibrium of tic-tac-toe they quit playing because the same thing always happens and the game is really boring. One way to view this is that, for the purposes of understanding how children play tic-tac-toe, rationality is a good behavioural model for eight year olds but not for six year olds.

In a more complicated game like chess, rationality is never a good behavioural model. The problem is that chess is a much harder game, hard enough that no one can analyse all the possibilities, and the usefulness of the concept of equilibrium breaks down. In chess no one is smart enough to discover the equilibrium, and so the game never gets boring. This illustrates that whether or not rationality is a sensible model of the behaviour of real people depends on the problem they have to solve. If the problem is simple, it is a good behavioural model, but if the problem is hard, it may break down.

Doyne Farmer, Professor of Mathematics at the University of Oxford, said: ‘Many of the problems encountered by economic actors are too complicated to model easily using a normal form game. Nonetheless, this work suggests a potentially serious problem. Many situations in economics are complicated and competitive. Our research raises the possibility that many important theories in economics may be wrong. If the key behavioural assumption of equilibrium is wrong, then the predictions of the model are likely to be wrong too. In this case new approaches are required that explicitly simulate the behaviour of the players and take into account the fact that real people are not good at solving complicated problems.’

Theories in economics nearly universally assume equilibrium from the outset. But is this always a reasonable thing to do? To get insight into this question, the researchers studied when equilibrium is a good assumption in games. They didn’t just study games like tic-tac-toe or chess, but rather they studied all possible games of a certain type (called normal form games). They made up games at random and had two simulated players play them to see what happens. The simulated players used strategies that do a good job of describing what real people do in psychology experiments. These strategies are simple rules of thumb, like doing what has worked well in the past or picking the move that is most likely to beat the opponent’s recent moves.

The researchers demonstrated that the intuition about tic-tac-toe vs. chess holds up in general, but with a new twist. When the game is simple enough, rationality is a good behavioural model: players easily find the equilibrium strategy and play it. When the game is more complicated, whether or not the strategies will converge to equilibrium depends on whether or not the game is competitive. If the incentives of the players are lined up they are likely to find the equilibrium strategy, even if the game is complicated. But when the incentives of the players are not lined up and the game gets complicated, they are unlikely to find the equilibrium. When this happens their strategies always keep changing in time, usually chaotically, and they never settle down to the equilibrium. In these cases equilibrium is a poor behavioural model.

A key insight from the research is that cycles in the logical structure of the game influence the convergence to equilibrium. The researchers analyse what happens when both players are myopic, and play their best response to the last move of the other player. In some cases this results in convergence to equilibrium, where the two players settle on their best move and play it again and again forever. However, in other cases the sequence of moves never settles down and instead follows a best reply cycle, in which the players’ moves keep changing but periodically repeat – like “ground hog day” over and over again. When a game has best reply cycles convergence to equilibrium becomes less likely.

Using this result the authors have been able to derive quantitative formulas for when the players of the game will converge to equilibrium and when they won’t, and show explicitly that in complicated and competitive games cycles are prevalent and convergence to equilibrium is unlikely.

Read the full paper: 'Best reply structure and equilibrium convergence in generic games' in Science Advances.