COVID-19 has asked a lot of everyone. At the national level, decisions have been taken that affect everything from people’s movements to the running of businesses. For many, there are also individual decisions in which personal risks are weighed: Should I venture to my local grocery store, or should I shop online? Can I eat at the restaurant, or should I buy take out?
In many households, dinner time musings often drifted to something like the following: 'I have barely seen anyone in person for many weeks. I know my neighbours haven’t either. My favourite park is much emptier than usual and the community around me has made many sacrifices. Does this mean COVID-19 is actually decreasing in my area?'
While most people have a UK-wide view and newspapers report national statistics, the decisions that people make to help contain the pandemic are at an individual and personal level. The behaviour of people in Oxford has no sizable effect on COVID-19’s growth or decline in far away Scotland, and these decisions need real-time, local information, an up to date resource that anyone can access to see how their town or county is doing.
View Local Covid UK Map here: https://localcovid.info/
Using historical COVID-19 case counts, the map at localcovid.info shows an estimate for the R number in each local area, along with projections of how the epidemic might develop in the next two weeks
The reproduction number or “R number” tells us about the growth and decline of COVID-19. It is an estimate of the number of people that someone with COVID-19 will pass the virus on to. A reproduction number of R=2 means that an infected person is likely to transmit the virus on to two other people, each of whom then passes it to two more people, and the epidemic grows quickly. On the other hand, if R=1, then on average each infected person only infects one other person and the size of the epidemic remains roughly constant. A reproduction number of R<1 is good news: the number of new infections is reducing and over time the epidemic will shrink.
Yee Whye Teh, Professor of Statistical Machine Learning at the Department of Statistics, University of Oxford, explains how the national “R number” is made up of many local parts: 'The national R number describes an average transmission rate across the nation. It is an aggregate statistic made up of many smaller contributions, and belies significant variations in COVID-19 transmissions rates, both geographically as well as across different sections of society. In order to inform individual decisions, local information relevant to the individual is needed.'
Led by Professor Teh, a team from the Computational Statistics and Machine Learning research group at Oxford’s Department of Statistics has built a model that monitors the daily spread of the virus locally. Their results can be accessed online by anyone at localcovid.info, which gives an informative view of the rate of transmission of COVID-19 in areas such as Oxford, Cherwell, West Oxfordshire, Swindon and more than 300 other local authorities in the UK.
Using historical COVID-19 case counts, the map at localcovid.info shows an estimate for the R number in each local area, along with projections of how the epidemic might develop in the next two weeks. The estimates of R in the map contain what statisticians call “error bars” or “credible intervals”. These are there to say that no one knows the true R number in an area, but we are quite sure that we can pin it down to within a narrow band. For example, in the map snapshot December 14, we are 95% sure that R is currently between 0.7 and 1.4 in Oxford, with a median of 1.0, given the team’s statistical model and the data available.
The real work dynamics of epidemics are incredibly complicated.
Michael Hutchinson, a PhD student in professor Teh’s group, explains how the “R number” is estimated from data: 'This is a difficult task. The real work dynamics of epidemics are incredibly complicated. To begin estimating the R number we start by proposing a simplified statistical model of the real world which captures the most important aspects of the epidemic. We never observe the R number directly, we only observe positive COVID-19 cases. We know that the R number drives new infections however, so using the model and observations of numbers of cases we can infer what R is likely to be. Essentially, using what we see in the world, we reverse engineer what the unobservable R is.'
The statistical model underlying these estimates of R relies on publicly available Pillar 1+2 daily counts of positive PCR swab tests by specimen date, for 312 lower-tier local authorities in England, the 14 NHS Health Boards in Scotland and the 22 unitary local authorities in Wales. The model makes additional use of commuter flow data from the UK 2011 Census and population estimates, as COVID-19 spreads not just among the population of individual areas, but also across areas. As with many aspects of statistical epidemiology, these estimates of R need to be read with care, and in the context of other pieces of data that provide relevant information, e.g. data from the ZOE symptom tracker, seroprevalence studies, test positivity rates, as well as hospitalisation and death rates.
Dr. Ulrich Paquet, a research scientist seconded to the group, noted: 'We are pleasantly surprised to see how the estimates for R have dropped below one for a while in many areas, especially in the North where Tier 3 rules applied since October. We guess that we shouldn’t be surprised to see the result of public behaviour and national action show up so clearly in a model, but we still are! As statisticians, we love it when the data speaks for itself.'
Prof. Teh concluded on a more sombre note: 'We are concerned that since the lockdown was lifted in December, many areas, particularly in the Southeast and London, have seen cases continue to increase. We hope the tool we built at localcovid.info will be helpful to you, in making your decisions to stay safe and to help protect your loved ones.'
Track your local area on the Local Covid UK Map here: https://localcovid.info/.
Social distancing has become one of the key strategies for reducing COVID-19 transmission, together with mask wearing and contact tracing. However, a new study, published in the journal PLOS ONE, maintains it is possible to maximise the impact of social distancing on viral transmission and minimise its impact on the economy and people's well-being - by focusing on the people who are the main drivers of infection.
A new study, published today...maintains it is possible to maximise the impact of social distancing...and minimise its impact on the economy and people's well-being - by focusing on the people who are the main drivers of infection
Lockdowns are a very effective way to reduce transmission and may be necessary, when the infection rate has to be curtailed rapidly, for example because of very high case rates. But lockdowns are disruptive and, in the longer term, more sustainable methods could be adopted.
Today’s study differs in approach from many of the main epidemic models in that it focuses specifically on the role of individuals and, in particular, on the very wide variation seen in the behaviour of different people.
Some individuals interact at a much higher rate than others, because of their work, living conditions or social habits - increasing both their chances of being infected and the probability that they will infect others. The simple theoretical model presented in this paper shows that these people are not only the main drivers of infection, but also the key to controlling the epidemic.
This study shows that social distancing can be highly effective in controlling viral transmission. By reducing the interactions of the most interactive individuals, this can be done while maintaining significant levels of activity in the population as a whole.
Social distancing can be highly effective in controlling viral transmission. By reducing the interactions of the most interactive individuals, this can be done while maintaining significant levels of activity in the population as a whole
Professor Christopher Ramsey, the author of the study and a physicist specialising in interdisciplinary science in the School of Archaeology, says, ‘Until vaccination is widespread, we might have to consider that social interaction time is like exposure to the sun, very beneficial in limited amounts, but harmful in excess.’
Since, in many countries, workplaces have been made relatively COVID-secure, social interaction outside the household has come to play a dominant role in viral transmission. Completely stopping such interactions will work, as in a total lockdown, but is a drastic measure and needs to be time-limited.
Many countries have found that, once socialisation is allowed again, infection rates rise. The model in this paper suggests this is largely because of the high interaction rates of a minority of people, rather than the interaction rates in the population as a whole.
For countries trying to reopen society in a controlled way, a way forward would be to limit interaction rates for individuals. So, rather than simply allowing or forbidding mixing between households in homes and hospitality venues, it would be more effective to say how frequently this can be done safely.
When rates of infection are still moderate, it might be necessary to recommend socialising no more than once a week. As rates improve, this might be relaxed to once every three days, and then unrestricted when the infection rate is very low. This could provide much finer control over the interaction rates than opening and closing bars and restaurants, and it could enable economic activity and some socialisation for everyone most of the time.
This approach should work, if people comply, because someone who socialises every day, rather than just once a week, has seven times the chance of becoming infected and also seven times the probability of infecting someone else
This approach should work, if people comply, because someone who socialises every day, rather than just once a week, has seven times the chance of becoming infected and also seven times the probability of infecting someone else. This person’s potential to spread the virus is nearly 50 times higher!
For this reason, the model suggests, the key aim of social distancing policies should be to avoid a minority of individuals interacting far more than the average. Such an approach would also help contact-tracing, since relevant contacts would be fewer if social interactions were limited to once every few days and so more time could be spent following them up properly.
As widespread mask wearing, improvements in the weather and, ultimately, vaccination help contain the disease, the extent to which socialisation should be possible will gradually increase until we get back to a more normal situation. Ideally, this should be possible without multiple waves of infection and the associated extreme measures that might be needed to bring these under control. However, to do so will need us to focus on individual behaviour and when it comes to social interactions that also implies individual responsibility.
The pandemic is testing our societal structures like never before. To deal with it successfully, we need to think and act collectively, led by our key institutions. But at a time when unity is critical, are we about to see the effects of a long-standing and corrosive drip feed of mistrust?
The rapid development and testing of COVID-19 vaccines has been an extraordinary scientific undertaking. What happens now is arguably even more important: to ensure the vaccines are an effective intervention, people will need to take them. The practical challenges of manufacturing and dispensing millions of doses worldwide are of course immense, but societies also have to deal with the issue of vaccine hesitancy: the belief that a vaccine may be unnecessary, ineffective, or unsafe (and perhaps all three). Unsurprisingly, people who have these concerns may be reluctant to take a vaccine; they may even refuse it outright.
The pandemic has created the ideal conditions for mistrust of a COVID-19 vaccine to thrive. Part of the problem is the complexity and variability of transmission and infection.
Vaccine hesitancy isn’t new. However, the pandemic has created the ideal conditions for mistrust of a COVID-19 vaccine to thrive. Part of the problem is the complexity and variability of transmission and infection. The fact that you may not catch the virus if you break social distancing guidelines and that the illness may be mild if you do get it, has led some to conclude that there isn’t a real problem. The unprecedented speed with which the vaccines have been developed has also provoked worry: there are concerns that safety has been compromised or that the vaccine will be rolled out before we understand the extent and nature of possible side effects. Moreover, the Internet is awash with misinformation -- including conspiracy theories – about the virus, lockdown, and vaccinations.
Finally, it’s worth bearing in mind that this is all taking place after a long period in which trust in science, medicine, and key institutions has been steadily eroded. We can’t overcome the virus if health experts aren’t trusted; yet that’s exactly how many people have been primed to react.
In the Oxford Coronavirus Explanations, Attitudes, and Narratives Survey (OCEANS), we aimed to gauge the extent of COVID-19 vaccine hesitancy: how many people are sceptical about vaccination; whether particular sections of the population are especially reluctant; and, most importantly, why people are hesitant. 5,114 adults took part, representative of the UK population for age, gender, ethnicity, income, and region.
First, the good news: we found a substantial majority in favour of a COVID-19 vaccine, with 72% willing to be vaccinated. But this isn’t enough to be truly considered a consensus. 16% of the population are very unsure about receiving a COVID-19 vaccine, and another 12% are likely to delay or avoid getting the vaccine. One in twenty people describe themselves as anti-vaccination for COVID-19.
Vaccine hesitancy has implications for us all. The fewer the people who are vaccinated, the greater the number of people who will get seriously ill.
The signs are concerning: we may be close to a tipping point, when suspicion of vaccination becomes mainstream. Already we’ve seen conspiracy theories about the virus achieve significant traction. Is COVID-19 vaccine hesitancy about to follow in their wake?
In our survey, one in five people thought vaccine data are fabricated and another one in four people did not know whether such fraud is occurring. Why does this matter? Vaccine hesitancy has implications for us all. The fewer the people who are vaccinated, the greater the number of people who will get seriously ill. Also, we don’t yet know how many people will need to be vaccinated to achieve full herd immunity, but an estimate of 80% has been suggested. As things stand, our survey suggests that figure may not be easy to achieve.
The fear that vaccine hesitancy may be going mainstream is borne out by the fact that, in our survey, mistrust wasn’t confined to particular groups; on the contrary, it was evident across the population. Hesitancy was slightly higher in young people, women, those on lower income, and people of Black ethnicity, but the size of the associations was very small. So we can’t explain COVID-19 vaccine hesitancy by reference to socio-demographic factors.
What, then, lies behind these beliefs? Our survey suggests that what matters most is the way people think about a number of key issues relating to a COVID-19 vaccine, specifically:
• the potential collective benefit
• the likelihood of COVID-19 infection
• the effectiveness of a vaccine
• its side-effects
• the speed of vaccine development
So those who are hesitant about a COVID-19 vaccine tend to be people who may not be so aware of the public health aspects of a vaccine, don’t consider themselves at significant risk of illness, doubt the efficacy of a vaccine, worry about potential side effects, or fear that it’s been developed too quickly.
When I speak to people who are enthusiastic about vaccination the first thing they say is that it helps everyone. In contrast, people wary of a vaccine often focus on their own situation: they’ll tell me that they’re unlikely to fall ill, for example, or worry about what may go wrong if they were to take a vaccine. But this perspective can change: when I’ve asked vaccine-hesitant individuals to imagine that someone close to them is especially vulnerable to COVID-19 they say that they’re more likely to get vaccinated.
Our survey shows people want reassurance that safety hasn’t been sacrificed for speed. They want accurate and comprehensible guidance on effectiveness, potential risks, and how long protection will last. And they’re not scared of detail: messaging should provide us with the full picture.
Vaccine scepticism, it would seem, is linked to a wider crisis of trust. Our data suggest that people who are vaccine hesitant are more likely to be mistrustful of doctors, are more likely to hold conspiracy beliefs, and to have little or no faith in institutions. They can also feel like they are of lower social status compared to others. What we see here is a combination of vulnerability and distrust of those in authority. That manifests itself in defensiveness. Unwilling to be experimented upon by people who don’t care about their well-being, they avoid vaccination.
The next few months are vital. Messaging must be strong and clear: for the benefit of everyone, each of us has a duty to get vaccinated when possible. Most people can see vaccination as the light at the end of the tunnel, but they are also looking – perfectly reasonably – for information they can trust. Our survey shows they want reassurance that safety hasn’t been sacrificed for speed. They want accurate and comprehensible guidance on effectiveness, potential risks, and how long protection will last. And they’re not scared of detail: rather than slogans, soundbites, and selective emphases, messaging should provide us with the full picture.
It must also be energetic, proactive, and open-minded. Make no mistake: people who are vaccine hesitant are thinking long and hard about whether to take a COVID-19 vaccine. Public health professionals need to be out and about across the country, listening to concerns and responding transparently. Presenting accurate information as powerfully as possible is obviously essential, but we also need to counter, and limit the spread of, vaccine misinformation.
Over the longer term, we need to rebuild trust in public institutions and experts – a task that will require society to address the sense of marginalisation that has led many people to question the value and veracity of science and other forms of expert knowledge. As crises like the current pandemic make clear, trust is the foundation stone of our community. Without it, even the most significant medical breakthroughs can seem like cause for suspicion.
Daniel Freeman is Professor of Clinical Psychology in the Department of Psychiatry, University of Oxford.
Read: ‘COVID-19 vaccine hesitancy in the UK: The Oxford Coronavirus Explanations, Attitudes, and Narratives Survey (OCEAN) II’ in Psychological Medicine.
Who would have thought demographic statistics would go viral? Certainly not self-confessed ‘Nerdy Girl’, Oxford Professor Jennifer Dowd, who was stunned when her social media post on excess mortality reached a global audience, as it was reposted and shared around the world.
Twelve women PhDs and clinicians – all experts in public health and related disciplines - were dubbed the ‘Nerdy Girls’ by a follower. Their mission is to curate reliable, accurate and trusted information about the pandemic – and they have gathered tens of thousands of followers across social media
The thing is, the Facebook post in question concerned COVID-19 deaths – and as Professor Dowd and her colleagues have discovered - there is an international appetite for trusted information about the pandemic, amid a torrent of misinformation.
Professor Dowd, the Deputy Director of Oxford’s Leverhulme Centre for Demographic Science, is working with 11 other women PhDs and clinicians – all experts in public health and related disciplines - dubbed the ‘Nerdy Girls’ by a follower. Their mission is to curate reliable, accurate and trusted information about the pandemic – and they have gathered tens of thousands of followers across social media.
Collectively, they are ‘Dear Pandemic’ and have become an online phenomenon, answering questions, providing information and engaging with some of the most common tropes, such as that vaccines alter your DNA (they don’t, insists Professor Dowd).
Dear Pandemic started as a Facebook page last March and quickly added Twitter and Instagram. Now, there is even a Dear Pandemic website which contains a searchable archive of over 600 posts. Aside from Professor Dowd, the women academics are based in her home country of the US, where the concept originated – and where much of the ‘lively’ online debate is taking place around the pandemic.
COVID-19 has become an intensely political subject. Dear Pandemic, however, has cultivated followers across the political spectrum and keeps the focus on data rather than politics. In the beginning, says Professor Dowd, we saw ourselves as ‘a go-to source for friends and family’. But the need for helping people navigate the onslaught of COVID-19 information meant that the group’s reach grew very quickly to many thousands of followers.
‘We wanted to be a relatable and trusted source, the nerdy mom-next-door, who just happens to have a PhD.’
We wanted to be a relatable and trusted source, the nerdy mom-next-door, who just happens to have a PhD
By using the same platforms as the purveyors of misinformation, the nerdy mom’s fact-based insights were being shared far beyond next door. And they did not want just to post science.
According to Professor Dowd, they wanted to ‘help people learn how to vet and interpret information for themselves’. It is something the Nerdy Girls call ‘information hygiene’. An example of this came on Friday, with a Facebook post about detecting misinformation.
The group posts new material on Facebook twice a day, often helping to distil recent news, such as vaccine trial results or debates about herd immunity. Post topics range from practical COVID-19 prevention (Has my COVID bubble gotten out of control?), scientific controversy, and mental health. Professor Dowd says, ‘We try to answer specific follower questions as well as anticipate the hot science topics of the day. It is a constant dialogue with our followers to understand what information people need to make the best decisions for themselves and their families.’
Right now, all eyes are on the vaccines – and with very large numbers of people in the US saying they will not be inoculated, it is not without controversy. The Nerdy Girls include experts in vaccine hesitancy and the team intends to work tirelessly to break down the myths and address concerns to help people feel better about the safety of vaccines.
The Nerdy Girls include experts in vaccine hesitancy and the team intends to work tirelessly to break down the myths and address concerns to help people feel better about the safety of vaccines
With some 50,000 Facebook followers, the group has considerable reach – and some posts, particularly those tackling misinformation can end up with 250k views. Professor Dowd’s posts on excess mortality- normally hard-core demographic interest only – have been among the most widely viewed and shared. The posts help debunk the myth that most COVID-19 deaths are of people who were going to die soon anyway.
‘Having access to reliable information empowers people, she says. ‘The average person can’t devote the time to navigating this overwhelming amount of information themselves and don’t know how to refute friends and relatives who might be sharing misinformation.
‘We see it as our core mission to educate and arm people with the knowledge to make informed decisions and have discussions with their loved ones.
‘Because we are using social media, our posts can be easily shared—a way to turn the weapons of misinformation against themselves.’
The Nerdy Girls have undertaken more than 200 media appearances so far with the goal of helping journalists interpret the science and ensure accurate information is in circulation. Family celebrations have been a recent focus, with the Nerdy Girls strongly urging households to ‘invest in future holidays’ and hold off on gatherings, especially with the promise of vaccines on the horizon.
But why is the group female only?
‘Since the beginning of the pandemic, there has been evidence that women academics were suffering more than men as a result of the pandemic, including family responsibilities and remote schooling....we wanted to amplify the voices of female expertise during the pandemic.’
We’ve all had to find our purpose during this pandemic, and it turns out public communication of demography and epidemiology is having a moment...it keeps me going to believe that we are helping people to make evidence-based decisions about risk and how to best protect their families
Professor Jennifer Dowd
They also hope to inspire and train up the next generation of Nerdy Girls.
A year ago, Professor Dowd - who serves as Dear Pandemic’s chief scientific officer- would never have imagined herself writing for thousands of readers on Facebook, rather than the handful who read a typical academic article. But the urgency of robust science communication during the pandemic has made this a calling she is happy to embrace.
‘We’ve all had to find our purpose during this pandemic, and it turns out public communication of demography and epidemiology is having a moment. While public health efforts are hard, because one never sees the infections that you prevent, it keeps me going to believe that we are helping people to make evidence-based decisions about risk and how to best protect their families.’
We are all familiar now with the use of circuit breakers, lockdowns and other interventions, such as masks and social distancing: these have been policy decisions to restrict the spread of COVID-19 in many places. In the UK, the use of lockdowns aiming to restrict mass movement and gathering have been used to restrict the spread of infection and ensure the capacity of the virus to spread is limited (making that R number fall below 1).
The value of these circuit breakers treads a fine line - while epidemiologically we know that quarantines and restricting movement would break the virus transmission cycle, epidemiology can’t exist in a vacuum and public health policy decisions need to be embedded in a broader social and economic context. Treading the tightrope of limiting infection spread, protecting the health services and maintaining the economy is a complex (nonlinear) problem fraught with scientific and political uncertainties.
Circuit breakers have other consequences than the immediacy of reducing R numbers. This can disrupt transmissions and affect the size and timing of infection peaks. In a recent commentary here we show that lockdowns can push the peak of subsequent waves of infection into the future. As an example, if a hard circuit breaker had been implemented through October, disrupting disease transmission, we have shown that the peak infections of COVID-19 would have been displaced by up to three months from early January to early April.
Provided these circuit breakers are longer than infection incubation periods and infected individuals follow self-isolation guidance, this sort of disruption to the flow of transmission has – in reality - multiple goals; first is the direct effect of reducing immediate transmission, second is shifting the infection peak and third is decoupling COVID-19 from other upper respiratory infections. Put simply, if a shift in the cycle of transmission of COVID-19 shifts an infection peak in January to a peak in April, then health services retain the capacity to offer support to patients with other infections such as seasonal flu.
Seasonal flu is a common upper respiratory infection; it has a lower spread rate than COVID-19 and there is a jab against the most likely common strain in circulation. However, it remains a virus of public health concern: it increases burden at this time of year on the health services and on average, kills 25K people a year in the UK.
Ultimately, circuit breakers can stem the transmission of COVID-19 and disrupt infection peaks, potentially separating peaks in seasonal flu and COVID-19 infections, and allowing critical health services to deal with winter illness.
As vaccine roll out develops at pace, further disrupting the spread of COVID and then using short circuit breakers might be the optimum approach to saving lives.
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