COVID-19: Pandemics and ‘Infodemics’

Posted on September 7, 2021September 6, 2021 by lindsey.pike

Drs Luisa Zuccolo and Cheryl McQuire, Department of Population Health Sciences, Bristol Medical School, University of Bristol.

The problem

Soon after the World Health Organisation (WHO) declared COVID-19 a pandemic on March 11th 2020, the UN declared the start of an infodemic, highlighting the danger posed by the fast spreading of unchecked misinformation. Defined as an overabundance of information, including deliberate efforts to disseminate incorrect information, the COVID-19 infodemic has exacerbated public mistrust and jeopardised public health.

Social media platforms remain a leading contributor to the rapid spread of COVID-19 misinformation. Despite urgent calls from the WHO to combat this, public health responses have been severely limited. In this project, we took steps to begin to understand and address this problem.

We believe that it is imperative that public health researchers evolve and develop the skills and collaborations necessary to combat misinformation in the social media landscape. For this reason, in Autumn 2020 we extended our interest in public health messaging, usually around promoting healthy behaviours during pregnancy, to study COVID-19 misinformation on social media.

We wanted to know:

What is the nature, extent and reach of misinformation about face masks on Twitter during the COVID-19 pandemic?

To answer this question we aimed to:

Upskill public health researchers in the data capture and analysis methods required for social media data research;
Work collaboratively with Research IT and Research Software Engineer colleagues to conduct a pilot study harnessing social media data to explore misinformation.

The team

Dr Cheryl McQuire got the project funded and off the ground. Dr Luisa Zuccolo led it through to completion. Dr Maria Sobczyk checked the data and analysed our preliminary data. Research IT colleagues, led by Mr Mike Jones, helped to develop the search strategy and built a data pipeline to retrieve and store Twitter data using customised application programming interfaces (APIs) accessed through an academic Twitter account. Research Software Engineering colleagues, led by Dr Christopher Woods, provided consultancy services and advised on the analysis plan and technical execution of the project.

Cheryl McQuire, Luisa Zuccolo, Maria Sobcyzk, Mike Jones, Christopher Woods. (Left to Right)

Too much information?!

Initial testing of the Twitter API showed that keywords, such as ‘mask’ and ‘masks’, returned an unmanageable amount of data, and our queries would often crash due to an overload of Twitter servers (503-type errors). To address this, we sought to reduce the number of results, while maintaining a broad coverage of the first year of the pandemic (March 2020-April 2021).

Specifically, we:

I) Searched for hashtags rather than keywords, restricting to English language.

II) Requested original tweets only, omitting replies and retweets.

III) Broke each month down into its individual days in our search queries to minimise the risk of overload.

IV) Developed Python scripts to query the Twitter API and process the results into a series of CSV files containing anonymised tweets, metadata and metrics about the tweets (no. of likes, retweets etc.), and details and metrics about the author (no. of followers etc.).

V) Merged data into a single CSV file with all the tweets for each calendar month after removing duplicates.

What did we find?

Our search strategy delivered over three million tweets. Just under half of these were filtered out by removing commercial URLs and undesired keywords, the remaining 1.7m tweets by ~700k users were analysed using standard and customized R scripts.

First, we used unsupervised methods to describe any and all Twitter activity picked up by our broad searches (whether classified as misinformation or not). The timeline of this activity revealed clear peaks around the UK-enforced mask mandates in June and September 2020.

We further described the entire corpus of tweets on face masks by mapping the network of its most common bigrams and performing sentiment analysis.

We then quantified the nature and extent of misinformation through topic modelling, and used simple counts of likes to estimate the reach of misinformation. We used semi-supervised methods including manual keyword searches to look for established types of misinformation such as face masks restricting oxygen supply. These revealed that the risk of bacterial/fungal infection was the most common type of misinformation, followed by restriction of oxygen supply, although the extent of misinformation on the risks of infection decreased as the pandemic unfolded.

Extent of misinformation (no tweets), according to its nature: 1- gas exchange/oxygen deprivation, 2- risk of bacterial/fungal infection, 3- ineffectiveness in reducing transmission, 4- poor learning outcomes in schools.

Relative to the volume of tweets including the hashtags relevant to face masks (~1.7m), our searches uncovered less than 3.5% unique tweets containing one of the four types of misinformation against mask usage.

A summary of the nature, extent and reach of misinformation on face masks on Twitter – results from manual keywords search (semi-supervised topic modelling).

A more in-depth analysis of the results attributed to the 4 main misinformation topics by the semi-supervised method revealed a number of potentially spurious topics. Refinements of these methods including iterative fine-tuning were beyond the scope of this pilot analysis.

Our initial exploration of Twitter data for public health messaging also revealed common pitfalls of mining Twitter data, including the need for a selective search strategy when using academic Twitter accounts, hashtag ‘hijacking’ meaning most tweets were irrelevant, imperfect Twitter language filters and ads often exploiting user mentions.

Next steps

We hope to secure further funding to follow-up this pilot project. By expanding our collaboration network, we aim to improve the way we tackle misinformation in the public health domain, ultimately increasing the impact of this work. If you’re interested in health messaging, misinformation and social media, we would love to hear from you – @Luisa_Zu and @cheryl_mcquire.

Note:

This blog post was original written for the Jean Golding Institute blog

Can we ever achieve “zero COVID”?

Posted on July 30, 2020August 3, 2020 by relfg

Marcus Munafo and George Davey Smith

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An important ongoing debate is whether the UK’s COVID strategy should focus on suppression (maintaining various restrictions to ensure the reproduction rate of the SARS-CoV-2 virus remains at or below 1), or elimination (reducing the number of infections to a sufficiently low level that restrictions could be removed). Independent SAGE has explicitly called for a “zero COVID UK”.

The latter is attractive, in that it brings the promise of a return to normality, rather than the ongoing maintenance of distancing measures, use of face coverings, etc. Independent SAGE has suggested that “a seven day rolling average of one new case per million per day could represent ‘control’” under a “zero COVID” regime. In other words, around 60 to 70 new cases per day across the UK.

But is “zero COVID”, in the context of ongoing large-scale testing, ever likely to be possible?

It’s unclear how accurate COVID19 tests are – which presents a challenge for the aim of reaching ‘zero COVID’.

Knowing how many cases there are in a population requires testing. But even the best tests are not perfect. Unfortunately, it might be difficult to know exactly how accurate COVID tests are – the RT-PCR (antigen) tests for SARS-CoV-2 are likely to be highly specific, but in the absence of an alternative gold standard to compare these against, calculating the precise specificity is challenging

If we assume excellent specificity (let’s say 99.9%), at current levels of daily testing in the UK (74,783 tests per day processed across pillars 1 and 2, as of the 28^th July update), that would mean around 75 false positive results per day even if there were no true cases of COVID in the UK. A sensitivity of 98% would mean over 1400 false positives *.

Any call for “zero COVID” needs to consider the impact of false positives on the achievability of the criterion that would constitute this, against a background of high levels of testing. Whilst testing is only one source of information that needs to be interpreted in the light of other clinical and epidemiological data, on their own they will be important drivers of any response.

As cases fall to a low level, perhaps we could reduce levels of testing (and therefore the number of false positives). But, given the high potential for substantial undocumented infection and transmission, it is likely that large-scale testing will remain essential for some time, if only to monitor the rise and fall in infections, the causes of which we still don’t fully understand.

The generic Situationist slogan “be realistic, demand the impossible” is one that many political campaigns for equality and freedom can understand.

But in many concrete situations well-meaning phrases can prove to be meaningless when scrutinised. If attempts to achieve zero COVID before relaxing restrictions leads to a delay in the reopening of schools, for example, that will result in vast increases in future levels of inequality in educational outcomes, and the future social trajectories dependent on these.

As with other endemic human coronaviruses, SARS-CoV-2 will likely show high variability and fall to very low levels within any particular population for sustained periods; it will not be permanently eliminated on a continental scale, however. Perhaps a better alternative to the setting of laudable but effectively unachievable targets is to recognise this and plan accordingly.

Marcus Munafò and George Davey Smith

* The importance of the sensitivity (and specificity) of tests for COVID antibodies has been discussed here, and the same logic broadly applies to antigen tests.

Are schools in the COVID-19 era safe?

Posted on July 1, 2020July 1, 2020 by lindsey.pike

Sarah Lewis, Marcus Munafo and George Davey Smith

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The COVID-19 pandemic caused by the SARS-COV2 virus in 2020 has so far resulted in a heavy death toll and caused unprecedented disruption worldwide. Many countries have opted for drastic measures and even full lockdowns of all but essential services to slow the spread of disease and to stop health care systems becoming overwhelmed. However, whilst lockdowns happened fast and were well adhered to in most countries, coming out of lockdown is proving to be more challenging. Policymakers have been trying to balance relaxing restriction measures with keeping virus transmission low. One of the most controversial aspects has been when and how to reopen schools.

Many parents and teachers are asking: Are schools safe?

The answer to this question depends on how much risk an individual is prepared to accept – schools have never been completely “safe”. Also, in the context of this particular pandemic, the risk from COVID-19 to an individual varies substantially by age, sex and underlying health status. However, from a historical context, the risk of death from contracting an infectious disease in UK schools (even in the era of COVD-19) is very low compared to just 40 years ago, when measles, mumps, rubella and whooping cough were endemic in schools. Similarly, from a global perspective UK schools are very safe – in Malawi, for example, the mortality rate for teachers is around five times higher than in the UK, with tuberculosis causing more than 25% of deaths among teachers.

In this blog post we use data on death rates to discuss safety, because there is currently better evidence on death rates by occupational status than, for example, infection rates. This is because death rates related to COVID-19 have been consistently reported by teh Office for National Statistics, whereas data on infection rates depends very much on the level of testing in the community (which has changed over time and differs by region).

Risks to children

Thankfully the risk of serious disease and death to children throughout the pandemic, across the UK and globally, has been low. Children (under 18 years) make up around 20% of the UK population, but account for only around 1.5% of those hospitalised with COVID-19. This age group have had better outcomes according to all measures compared to adults. As of the 12^th June 2020, there have been 6 deaths in those with COVID-19 among those aged under 15 years across England and Wales. Whilst extremely sad, these deaths represent a risk of around 1 death per 2 million children. To place this in some kind of context, the number of deaths expected due to lower respiratory tract infections among this age group in England and Wales over a 3 month period is around 50 and 12 children would normally die due to road traffic accidents in Great Britain over a 3-month period.

Risks to teachers

Our previous blog post concluded that based on available evidence the risk to teachers and childcare workers within the UK from Covid-19 did not appear to be any greater than for any other group of working age individuals. It considered mortality from COVID-19 among teachers and other educational professionals who were exposed to the virus prior to the lockdown period (23^rd March 2020) and had died by the 20^th April 2020 in the UK. This represents the period when infection rates were highest, and when children were attending school in large numbers. There were 2,494 deaths among working-age individuals up to this date, and we found that the 47 deaths among teachers over this period represented a similar risk to all professional occupations – 6.7 (95% CI 4.1 to 10.3) per 100,000 among males and 3.3 (95% CI 2.0 to 4.9) per 100,000 among females.

The Office for National Statistics (ONS) has since updated the information on deaths according to occupation to include all deaths up to the 25^th May 2020. The new dataset includes a further 2,267 deaths among individuals with COVID-19. As the number of deaths had almost doubled during this extended period, so too had the risk. A further 43 deaths had occurred among teaching and education professionals, bringing the total number of deaths involving COVID-19 among this occupational group to 90. It therefore appears that lockdown (during which time many teachers have not been in school) has not had an impact on the rate at which teachers have been dying from COVID-19.

As before, COVID-19 risk does not appear greater for teachers than other working age individuals

The revised risk to teachers of dying from COVID-19 remains very similar to the overall risk for all professionals at 12.9 (95% CI 9.3 to 17.4) per 100,000 among all male teaching and educational professionals and 6.0 (95% CI 4.2 to 8.1) per 100,000 among all females, compared with 11.6 (95%CI 10.2 to 13.0) per 100,000 and 8.0 (95%CI 6.8 to 9.3) per 100,000 among all male and female professionals respectively. It is useful to look at the rate at which we would normally expect teaching and educational professionals to die during this period, as this tells us by how much COVID-19 has increased mortality in this group. The ONS provide this in the form of average mortality rates for each occupational group for same 11 week period over the last 5 years. The mortality due to COVID-19 during this period represents 33% for males and 19% for females of their average mortality over the last 5 years for the same period. For male teaching and educational professionals, the proportion of average mortality due to COVID-19 is very close to the value for all working-aged males (31%) and all male professionals (34%). For females the proportion of average mortality due to COVID-19 is lower than for all working-aged females (25%) and for female professionals (25%). During the pandemic period covered by the ONS, there was little evidence that deaths from all causes among the group of teaching and educational professionals were elevated above the 5-year average for this group.

Teaching is a comparatively safe profession

It is important to note that according to ONS data on adults of working age (20-59 years) between 2001-2011, teachers and other educational professionals have low overall mortality rates compared with other occupations (ranking 3^rd safest occupation for women and 6^th for men). The same study found a 3-fold difference between annual mortality among teachers and among the occupational groups with the highest mortality rates (plant and machine operatives for women and elementary construction occupations among men). These disparities in mortality from all causes also exist in the ONS data covering the COVID-19 pandemic period, but were even more pronounced with a 7-fold difference between males teaching and educational professionals and male elementary construction occupations, and a 16-fold difference between female teachers and female plant and machine operatives.

There is therefore currently no indication that teachers have an elevated risk of dying from COVID-19 relative to other occupations, and despite some teachers having died with COVID19, the mortality rate from all causes (including COVID19) for this occupational group over this pandemic period is not substantially higher than the 5 year average.

Will reopening schools increase risks to teachers?

One could argue that the risk to children and teachers has been low because schools were closed for much of the pandemic, and children have largely been confined to mixing with their own households, so that when schools open fully risk will increase. However, infection rates in the community are now much lower than they were at their peak, when schools were fully open to all pupils without social distancing. Studies which have used contract tracing to determine whether infected children have transmitted the disease to others have consistently shown that they have not, although the number of cases included has been small, and asymptomatic children are often not tested. Modelling studies estimate that even if schools fully reopen without social distancing, this is likely to have only modest effects on virus transmission in the community. If infection levels can be controlled – for example by testing and contact tracing efforts – and cases can be quickly isolated, then we believe that schools pose a minimal risk in terms of the transmission of COVID, and to the health of teachers and children. Furthermore, the risk is likely to be more than offset by the harms caused by ongoing disruption to children’s educational opportunities.

Sarah Lewis is a Senior Lecturer in Genetic Epidemiology in the department of Population Health Sciences, and is an affiliated member of the MRC Integrative Epidemiology Unit (IEU), University of Bristol.

Marcus Munafo is a Professor of Biological Psychology, in the School of Psychology Science and leads the Causes, Consequences and Modification of Health Behaviours programme of research in the IEU, University of Bristol.

George Davey Smith is a Professor of Clinical Epidemiology, and director of the MRC IEU, University of Bristol.

Are teachers at high risk of death from Covid19?

Posted on May 26, 2020 by lindsey.pike

Sarah Lewis, George Davey Smith and Marcus Munafo

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Due to the SARS-CoV-2 pandemic schools across the United Kingdom were closed to all but a small minority of pupils (children of keyworkers and vulnerable children) on the 20^th March 2020, with some schools reporting as few as 5 pupils currently attending. The UK government have now issued guidance that primary schools in England should start to accept pupils back from the 1^st June 2020 with a staggered return, starting with reception, year 1 and year 6.

Concern from teachers’ unions

This has prompted understandable concern from the teachers’ unions, and on the 13^th May, nine unions which represent teachers and education professionals signed a joint statement calling on the government to postpone reopening school on the 1st June, “We all want schools to re-open, but that should only happen when it is safe to do so. The government is showing a lack of understanding about the dangers of the spread of coronavirus within schools, and outwards from schools to parents, sibling and relatives, and to the wider community.” At the same time, others have suggested that the harms to many children due to neglect, abuse and missed educational opportunity arising from school closures outweigh the small increased risk to children, teachers and other adults of catching the virus.

What risk does Covid19 pose to children?

Weighing up the risks to children and teachers

So what do we know about the risk to children and to teachers? We know that children are about half as likely to catch the virus from an infected person as adults, and if they do catch the virus they are likely to have only mild symptoms. The current evidence, although inconclusive, also suggests that they may be less likely to transmit the virus than adults. However, teachers have rightly pointed out that there is a risk of transmission between the teachers themselves and between parents and teachers.

The first death from COVID-19 in England was recorded at the beginning of March 2020 and by the 8^th May 2020 39,071 deaths involving COVID-19 had been reported in England and Wales. Just three of these deaths were among children aged under 15 years and only a small proportion of the deaths (4416 individuals, 11.3%) were among working aged people. Even among this age group risk is not uniform; it increases sharply with age from 2.6 in 100,000 for 25-44 years olds with a ten fold increase to 26 in 100,000 individuals for those aged 45-64.

Risks to teachers compared to other occupations

In addition, each underlying health condition increases the risk of dying from COVID-19, with those having at least 1 underlying health problem making up most cases. The Office for National Statistics in the UK have published age standardised deaths by occupation for all deaths involving COVID-19 up to the 20^th April 2020. Most of the people dying by this date would have been infected at the peak of the pandemic in the UK prior to the lockdown period. They found that during this period there were 2494 deaths involving Covid-19 in the working age population. The mortality rate for Covid-19 during this period was 9.9 (95% confidence intervals 9.4-10.4) per 100,000 males and 5.2 (95%CI 4.9-5.6) per 100,000 females, with Covid-19 involved in around 1 in 4 and 1 in 5 of all deaths among males and females respectively.

Amongst teaching and education professionals (which includes school teachers, university lecturers and other education professionals) a total of 47 deaths (involving Covid-19) were recorded, equating to mortality rates of 6.7 (95%CI 4.1-10.3) per 100,000 among males and 3.3 (95%CI 2.0-4.9) per 100,000 among females, which was very similar to the rates of 5.6 (95%CI 4.6-6.6) per 100,000 among males and 4.2(95%CI 3.3-5.2) per 100,000 females for all professionals. The mortality figures for all education professionals includes 7 out of 437000 (or 1.6 per 100,000 teachers) primary and nursery school teachers and 17 out of 395000 (or 4.3 per 100,000 teachers) secondary school teachers. A further 20 deaths occurred amongst childcare workers giving a mortality rate amongst this group of 3.4 (95%CI=2.0-5.5) per 100,000 females (males were highly underrepresented in this group), this is in contrast to rates of 6.5 (95%CI=4.9-9.1) for female sales assistants and 12.7(95%CI= 9.8-16.2) for female care home workers.

Covid-19 risk does not appear greater for teachers than other working age individuals

In summary, based on current evidence the risk to teachers and childcare workers within the UK from Covid-19 does not appear to be any greater than for any other group of working age individuals. However, perceptions of elevated risk may have occurred, prompting some to ask “Why are so many teachers dying?” due to the way this issue is portrayed in the media with headlines such as “Revealed: At least 26 teachers have died from Covid-19” currently on the https://www.tes.com website. This kind of reporting, along with the inability of the government to communicate the substantial differences in risk between different population groups – in particular according to age – has caused understandable anxiety among teachers. Whilst, some teachers may not be prepared to accept any level of risk of becoming infected with the virus whilst at work, others may be reassured that the risk to them is small, particularly given that we all accept some level of risk in our lives, a value that can never be zero.

Likely impact on transmission in the community is unclear

As the majority of parents or guardians of school aged children will be in the 25-45 age range, the risk to them is also likely to be small. Questions remain however around the effect of school openings on transmission in the community and the associated risk. This will be affected by many factors including the existing infection levels in the community, the extent to which pupils, parents and teachers are mixing outside of school (and at the school gate) and mixing between individuals of different age groups. This is the primary consideration of the government Scientific Advisory Group for Emergencies (SAGE) who are using modelling based on a series of assumptions to determine the effect of school openings on R₀.

George Davey Smith is a Professor of Clinical Epidemiology, and director of the MRC IEU, University of Bristol

Beyond question: a collaboration between EPoCH and artist Olga Trevisan

Posted on January 14, 2020 by lindsey.pike

Back in May, IEU researcher Dr Gemma Sharp took part in Creative Reactions, an initiative that pairs scientists with artists to create artwork based on their academic research. With 50 artists and 50 scientists collaborating on works from sculptures and wood carvings to canvas, digital and performance art, the 2019 exhibition ran across two venues in Bristol.

Gemma was paired with Olga Trevisan, an artist based in Venice, Italy. They had conversations over Skype where they spoke about their work and formed some initial ideas about how they could combine their interests in a new way while remaining coherent to their own practices. Reflecting on the collaboration, Olga said, “I love how curious you can be of a subject you haven’t considered before. I believe collaboration helps to open your own mind.”

Based on some of the work around EPoCH, Olga created a piece called Beyond Question, which comments on the complexities of scientific data collection, bias and interpretation.

It poses questions around the pervasive assumption that pregnant women are more responsible for the (ill) health of their unborn children than their male partners are. Gemma and colleagues have argued that such assumptions drive the research agenda and the public perception of parental roles, by shaping which research questions get asked, which data are collected, and the quality of the scientific ‘answer’.

Beyond Question was presented in two phases at two separate exhibitions: during the first phase, people were invited to answer questions with a simple Yes or No using a stylus; leaving no marks but only invisible, anonymous traces on the surface below. Answers will reflect the real assumptions, beliefs and attitudes of the respondent, but perhaps also, despite anonymity, their eagerness to ‘please’ the questioners, to give the ‘right’ answer, and to mask their true responses to paint themselves in the ‘best’ light.

In the second phase, the questions were removed and the answer traces were left alone to carry their own meaning; free to be combined with the attitudes, beliefs and assumptions of the viewer and to be interpreted and judged in perhaps an entirely different way.

The questions posed were:

“Do you think a mother’s lifestyle around the time of pregnancy could be bad for her baby’s health?”
“Do you think a father’s lifestyle around the time of pregnancy could be bad for his baby’s health?”
“Before her baby is born, a pregnant mother shouldn’t be allowed to do unhealthy things, like smoke or drink alcohol. Do you agree or disagree?”
“Before his baby is born, a father shouldn’t be allowed to do unhealthy things, like smoke or drink alcohol. Do you agree or disagree?”

Find out more

Further info about Creative Reactions Bristol is available on their facebook page, or contact Matthew Lee on matthew.lee@bristol.ac.uk

This blog post was originally posted on the EPOCH blog.

Why haven’t e-cigarettes stubbed out cigarettes?

Posted on May 31, 2019May 31, 2019 by lindsey.pike

On World No Tobacco Day, PhD researcher Jasmine Khouja outlines the evidence around e-cigarettes.

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There are an estimated 3.2 million e-cigarette users in Great Britain, and the majority of users have switched from smoking to vaping in search of a less harmful alternative to help them quit. In a recent study, people who used e-cigarettes to quit smoking were more likely to be smoke-free after one year compared to people who used more traditional methods such as nicotine patches. So, why are some smokers reluctant to try e-cigarettes, and why have some people been unable to quit smoking using them? The media, researchers, public health officials, and the general public have all played a role in discouraging some smokers from vaping.

E-cigarettes in the media

As a researcher in the field of e-cigarette use, I have often looked at news articles about vaping and felt exasperated. We frequently see e-cigarettes portrayed as a harmful option; according to many news articles, e-cigarettes are dangerous, lead to heart attacks and are as bad for your lungs as cigarettes. The same news outlets often report the opposite finding and say e-cigarettes are actually better for you. This flip-flopping leaves smokers confused and could discourage them from trying e-cigarettes for fear that vaping is actually more harmful than smoking.

Science in the media

So, why do the media keep switching their stance on e-cigarettes? They’re getting their information from the research community, and this community is divided. Some researchers claim that the costs of unknown health risks of vaping and the popularity of e-cigarettes among children and adolescents outweigh the potential benefits of helping smokers to quit, and others claim vice versa.

As researchers, we should be impartial and only provide the public with information which we can back up with evidence from our research, but, as we are still human, our opinions tend to seep through into how we report our findings and even what we choose to research. This lack of agreement in the research community is fuelling the media’s flip-flopping , leading to public confusion and reluctance to try e-cigarettes to help them quit smoking.

Public attitudes to vaping

With all of this contrasting information, it’s no wonder the general public’s opinion of vaping seems to be split too. Negative public opinion can have an impact on whether a smoker wants to try an e-cigarette. Quitting smoking isn’t easy; the last thing smokers want is to feel judged when they are trying to quit.

Negative public attitudes to vaping could put smokers off trying vaping but also affects where they can vape. Many businesses include e-cigarettes in their smoke free policies so that vapers have to stand outside with smokers. When trying to quit, it’s not ideal to be surrounded by the very thing you’re trying to wean yourself off. It’s like being on a diet and spending every meal at an all you can eat buffet when all you can eat is a salad; it’s tempting to slip into old habits. So, despite there being no indoor vaping ban (as there is with cigarettes), vapers are forced outside into a situation where they are more likely to start smoking again.

Unintended consequences of policy

It’s not just organisational policies attempting to control e-cigarette use; in 2016, a legislation called the Tobacco Products Directive (TPD) added a section on e-cigarettes in an attempt to regulate the devices. There were a number of unpopular changes to e-cigarette products as a result. Changes to the amount of nicotine allowed in products and restrictions on innovation of new products may have had unintended consequences.

With the introduction of the TPD, a limit was set on how much nicotine a vape product could contain. Nicotine is the key ingredient in cigarettes which keeps people smoking, and although it is highly addictive, nicotine is not the cigarette ingredient which is likely to kill smokers. E-cigarettes help people to quit smoking because they can contain nicotine which satisfies smokers cravings while exposing them to fewer toxins than smoking would. Limiting the amount of nicotine in these products means that heavier smokers don’t receive enough nicotine from an e-cigarette to satisfy their nicotine addiction and this makes them more likely to start smoking again.

The TPD also requires companies to register products in advance of bringing them to market. Where the e-cigarette industry was creating new, more effective devices at a very fast pace, users now can’t buy these products for a substantial amount of time after they have been developed. This restriction on innovation means that while consumers are waiting for these better products to become available, they could be trying products that don’t meet their needs. I often hear tales of “I tried one once and it was just like puffing air, so I kept smoking instead”. They have tried one product, it wasn’t good enough, and they assume all other products will be just as bad. By restricting innovation, we limit the amount of better-quality devices on the market and increase the likelihood that a smoker looking to quit will come across a poor device and turn back to smoking.

Making it easy to stop smoking

Many smokers want to quit and we, as researchers, media representatives, public health officials and even members of the public, need to make it as easy as possible for them to do so. We need to be clearer in the information we provide, be more accepting of vaping and not limit products which could help the most addicted smokers. I still have hope that smoking will be stubbed out in my generation, and that e-cigarettes could be the disruptive technology needed to help us achieve this.