Pandemics, infodemics and the impact on people like you (and me)


By Professor Helen Ward, Patient Experience Research Centre, Abdul Latif Jameel Institute for Disease and Emergency Analytics, School of Public Health, Imperial College London.

Usually busy street in Codogno deserted, 28 Feb 2020
Usually busy street in Codogno deserted, 28 Feb 2020 (credit: Paul O’Brien)

 

“Of all the gin joints in all the towns … of all the one-horse towns … why did this virus have to come to mine?”

The words of my friend Paul who is living in an Italian town under lockdown because of the novel coronavirus epidemic. His frustration is palpable as his plans for travel, work and social life were put on hold for at least two weeks (and subsequently extended for another three). But he reasons, “despite the fact that it’s not a killer disease, we can’t all go around with pneumonia. I don’t want pneumonia myself…and I wouldn’t wish it on any of the local citizens so in a sense, I’m sort of with the authorities, even though it’s against my own personal interests at this moment in time, I think that the lockdown is correct” (interview, 26 Feb 2020).

Public health interventions often raise this dilemma – to protect “the community”, individuals have to take actions for which they may see little or no benefit, and at worst experience, or imagine, damage. And in the case of emergency response, health advice tends towards blanket coverage rather than personalised recommendations. A potential pandemic looks like the other end of the spectrum from personalised medicine. The latter uses genomic and other molecular techniques together with large data sets to promise the right treatment or intervention for the right person at the right time through precision diagnostics and therapeutics. The “one size fits all” approach of epidemic response seems far removed from this, with recommendations for handwashing, social distancing and, as in the case of Wuhan and Lombardy (and now the whole of Italy), mass quarantine.

There is no lack of data on COVID-19. Indeed it is the first pandemic in the era of such widespread and easy access to information from 24-hour news, social media and almost real-time updates of numbers of cases, deaths and responses on websites such as worldometer.  This data sharing is unprecedented, as is the openness of publishing results and sharing information on cases and code. This initial data collection is the first stage of any outbreak investigation, where cases are described by time, person and place. In China, scientists used social media reports to crowdsource a daily line-listing of cases with as much data as possible, and this was then compared with official reports (Sun et al, 2020). Although incomplete, this method had great promise, and teams are now looking to develop methods for more automated approaches, including “developing and validating algorithms for automated bots to search through cyberspace of all sorts, by text mining and natural language processing (in languages not limited to English)” (Leung and Leung, 2020).

But while social media and online publishing is facilitating data access and sharing, it is also leading to what the WHO have termed an infodemic, “an overabundance of information — some accurate and some not — that makes it hard for people to find trustworthy sources and reliable guidance when they need it”. Sylvie Briand, director of Infectious Hazards Management at WHO’s Health Emergencies Programme, explains that this is not new, but different. “We know that every outbreak will be accompanied by a kind of tsunami of information, but also within this information you always have misinformation, rumours, etc. We know that even in the Middle Ages there was this phenomenon…But the difference now with social media is that this phenomenon is amplified, it goes faster and further, like the viruses that travel with people and go faster and further” (Zarocostas 2020).

Conspiracy theories and misinformation about COVID-19 have indeed been spreading widely, from ideas that the disease is caused by radiation from 5G masts, to malicious reports of specific individuals being infected and suggestions of fictitious cures. These can be highly influential in determining people’s response to official advice in an outbreak situation.  Working on the role of misinformation on vaccine uptake, Larson describes resulting emotional contagion and “insidious confusion” which can undermine control efforts (Larson 2018). Health behaviours in relation to infectious disease are complex and shaped by a wide range of factors including beliefs about prognosis and treatment efficacy, symptom severity, social and emotional factors (Brainard et al, 2019). They are also based on the extent to which the source of the advice is trusted and respected. A survey of 1700 people in Hong Kong in the early days of the COVID-19 outbreak showed that doctors were the most trusted source of information, but that most information was actually obtained from social media (Kwok et al. 2020).

Lack of trust was found to have undermined the response to SARS in China in 2003, leading to changes in the way that risks were communicated in the H7N9 influenza in 2013. A qualitative study of both outbreaks concluded, “Trust is the basis for communication. Maintaining an open and honest attitude and actively engaging stakeholders to address their risk information needs will serve to build trust and facilitate multi-sector collaborations in dealing with a public health crisis” (Qiu et al 2018). The focus on engaging stakeholders in the community is a crucial and often neglected part of epidemic response (Gillespie 2016, WHO 2020).

So, can we expect people to respond appropriately to the one-size-fits-all messages to try and reduce the transmission of coronavirus? The response will depend on a number of factors including whether people trust the source of the message, the threat is perceived as real, the interventions are seen as likely to work, and the disruption proportionate. Evidence so far suggests that people are making changes – 30% of 1,400 people who responded to my non-random Twitter survey had already changed their behaviour by 22 February, and the disappearance of soap and hand sanitiser from the shelves indicates intention to adopt hygiene practices. Respondents to a UK survey on 27-29 February reported a range of coronavirus related actions, including more handwashing (62%) and changed travel plans (21%) (Brandwatch, 2020).

Living in Codogno, Italy, my friend has no choice but to change his behaviour, but after initial annoyance he supports the lockdown as a necessary action to protect others. He is not particularly concerned about his own risk, yet in our conversations, and those with many others in person and online, there has been an interesting focus on the differential impact of COVID-19. The severity is clearly greater in older people and in people with some pre-existing conditions. This knowledge can be reassuring for many, if people like them don’t seem to be badly affected but frightening for others. Reports of deaths have often been accompanied by descriptions such as “old” and “with underlying health conditions”. I commented on Twitter that this can create a “disturbing narrative this is acceptable, and can make the young & fit feel reassured”, and had a surprisingly positive response with over 20,000 impressions and 200 likes (many more than usual). One person replied, “I agree, the corollary is… that’s all right then, won’t affect us”.

It is not surprising that people want more precise information on risks, and this will eventually affect the response by identifying those people who should be first to receive vaccines and treatments. But we need to take care that it the information is not used to create complacency in those who do not feel personally vulnerable. In HIV prevention, the concept of high-risk groups was counter-productive in many settings, leading on the one hand to stigma directed at those groups, and on the other to a lack of protective behaviour by people who felt that messages did not apply to them. We need to caution against that response. Even if coronavirus is mild for most people, it has the potential to seriously disrupt healthcare if it spreads quickly. The nature of the illness puts particular demands on critical care. In Italy, they are struggling with lack of critical care beds already, and the UK has far lower capacity (Rhodes, 2012).

In an emergency it is even more important that we take measures that protect others, not just focus on our own personal risks and benefits. So please, wash your hands well, and don’t be offended if I don’t offer to shake your hand when we meet.

Professor Helen Ward


[This blog has been cross-posted on other websites supported by the Patient Experience Research Centre]

To find out more about how you can guide our #COVID19 research and community involvement during this outbreak, please visit our Coronavirus Outbreak Community Involvement page on VOICE-global.org.

 

Acknowledgements

Thanks to Paul O’Brien for sharing his experience and photograph. HW receives funding from Imperial NIHR Biomedical Research Centre and Wellcome Trust.

References

Brandwatch. https://www.brandwatch.com/blog/react-british-uk-public-coronavirus-survey/

Brainard J, Weston D, Leach S, Hunter PR. Factors that influence treatment-seeking expectations in response to infectious intestinal disease: Original survey and multinomial regression [published online ahead of print, 2019 Dec 6]. J Infect Public Health. 2019;S1876-0341(19)30340-5. doi:10.1016/j.jiph.2019.10.007

Gillespie AM, Obregon R, El Asawi R , et al. Social mobilization and community engagement central to the Ebola response in West Africa: lessons for future public health emergencies. Glob Health Sci Pract 2016;4:626–46. doi:10.9745/GHSP-D-16-00226

Kwok KO, Li KK,  Chan HH et al. Community responses during the early phase of the COVID-19 epidemic in Hong Kong: risk perception, information exposure and preventive measures medRxiv 2020.02.26.20028217;  doi:https://doi.org/10.1101/2020.02.26.20028217

Larson H. The biggest pandemic risk? Viral misinformation. Nature 562, 309 (2018) doi: 10.1038/d41586-018-07034-4

Leung GM, Leung K.  Crowdsourcing to mitigate epidemics The Lancet Digital Health, 2020 (February 20) https://doi.org/10.1016/S2589-7500(20)30055-8

Qiu W, Chu C, Hou X, et al. A Comparison of China’s Risk Communication in Response to SARS and H7N9 Using Principles Drawn From International Practice. Disaster Med Public Health Prep. 2018;12(5):587–598. doi:10.1017/dmp.2017.114

Rhodes A, Ferdinande P, Flaatten H, Guidet B, Metnitz PG, Moreno RP. The variability of critical care bed numbers in Europe. Intensive Care Med. 2012;38(10):1647–1653. doi:10.1007/s00134-012-2627-8

Sun K, Chen J, Viboud C. Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: a population-level observational study. Lancet Digital Health. 2020; (published online Feb 20) https://doi.org/10.1016/S2589-7500(20)30026-1

World Health Organisation. Risk communication and community engagement (RCCE) readiness and response to the 2019 novel coronavirus (2019-nCoV). Interim guidance v2, 26 January 2020. WHO/2019-nCoV/RCCE/v2020.2

Zarocostas J. How to fight an infodemic. Lancet. 2020;395(10225):676. doi:10.1016/S0140-6736(20)30461-X

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