Corona science: what does it really say?

Listening today to the sycophantic twaddle coming from government ministers who we’ve been trusting to steer us through the corona emergency, I thought to take a deeper look at the science on which, they told us, policy has been based. We’ve been deprived of our liberty, our families, our jobs and our livelihoods for ten weeks, and we’re now facing the biggest economic recession in history. What if – like their own senior advisor – they’d got it wrong? You may be shocked and outraged at what I’ve found.
The first surprise is how little hard research there seems to be on this the most disruptive event of our lifetime. The world’s governments looked like they were making up policy on the hoof: they were, in spite of multiple warnings going back decades that such a viral pandemic was at some point inevitable.
The World Health Organisation (WHO) said ‘Test, test, test’, advice that South Korea successfully followed. When you think about it, it’s obvious. Find out where the virus is, isolate it and don’t let it spread. It’s what happened with TB, polio, cholera, Ebola, HIV, SARS, MERS.
The UK government preferred rather to follow the advice of Imperial College based on a computer algorithm (Ferguson et al, 2020). This said if you don’t lock people down now, the NHS will be overwhelmed and hundreds of thousands of people will die. We had to ‘flatten the curve’, spread the progress of the disease over months rather than weeks. For the NHS, this has worked. But individuals were never part of the science nor the policy.
The model, sophisticated though it surely is, was based on previous influenza infection patterns in a homogeneous population. It did not take account of care homes nor of the fact that populations are densely packed in some places and not in others. Computer models also need assumptions to be made. It’s hard to build in the vagaries of human behaviour, for example, unproven effects of the weather, or different transmission rates or impacts in different demographic segments. The modellers themselves devised the range of social distancing measures we’ve been obliged to adopt: school closures; shutting down workplaces, shops, bars and restaurants; staying at home, going nowhere, meeting no-one (Lewnard & Lo, 2020). But models look at discrete populations (Chen, 2014), they don’t advise on closing borders and airspace. That was a national panic response by governments all over the world, bolting the door after millions of people had flown around the world taking the virus with them
Both models and governments rule by big picture statistics. They needed 70% of the population to follow the rules for the model’s predictions to come about. By the nature of such things, this doesn’t tell us whether you or I are in the 70% or the 30%. But while statistics like these don’t apply to individuals, real world probability does. If I know that no-one in my village is infected, then there is little risk in meeting them, even at close quarters, even keeping the pub open. If I and my neighbours have self-isolated for a month, there is little risk in getting together. Statistics saved the NHS but not those individuals that have suffered and succumbed.
Modelling doesn’t take account of proven phenomena such as viruses spreading naturally through the upper atmosphere and falling with rain (Reche et al, 2018), that air pollution exacerbates both the spread and the impact of the disease (Qin et al, 2020), and that – as with flu – there are likely to be seasonal fluctuations (Bush, 2020). Neither does it provide any insight into the physiological and psychological damage that the lockdown has caused.
Moving forward, it looks like we’ll be expected to wear masks and maintain a 2m personal separation from others. These too have psychological, social and economic implications. Does the science support them? Not really. The issue is about how droplets may spread when someone coughs or sneezes and the answer is anywhere up to 8m (Bourouiba, 2020). Government advice on physical separation is also variable. The UK says 2m, the USA 6ft, Australia and South Africa 1.5m, Kenya 1m. There is no hard rule. Considering the UK is planning the reopening of public transport, shops, bars and restaurants based on a notional 2m separation, you might reasonably think this matters. For a pub, a train or a bus, the difference between 2m, 1m and just keeping sensibly apart is the difference between bankruptcy and viability.
Masks may change the direction of flow but unless fitted tightly do not stop it. Worse, they may actually harbour viruses, impede the breathing and trigger a build up of carbon dioxide. WHO says that masks are effective only when used in combination with frequent hand-washing. If you wear a mask, you must know how to use it and dispose of it properly. The issue is to avoid coughing or sneezing in public and being around people who do.
I’m left thinking that the hard ‘stay at home’ and rigid distancing rules have been somewhat arbitrary. That a surprising number of people in senior advisory roles have been obliged to resign or defend their own actions may well support this. As the release from lockdown commences, it’s important to understand the risks and, as others have done, exercise our own intelligent judgements. Covid-19 is clearly a nasty disease to be avoided if possible. While many people show few if any symptoms, in a small number of cases it can be a lot worse than ‘just a flu’. But what it has really revealed is just how sick our society has become. People are dying not specifically from the virus but due to their compromised immune systems no longer being able to stave off pre-existing conditions such as dementia and Alzheimers, heart disease, diabetes and other non-covid respiratory diseases (Office for National Statistics, May 2020). What’s really killing us are ‘lifestyle diseases’ caused by over-eating processed foods, lack of exercise, atmospheric pollution, chemicals in the food chain and an out of balance global ecosystem.
In two years, as have other viruses before it, covid-19 will be gone. The question will remain, was all the suffering necessary? We may never know.

Sources:
Bourouiba, ‘Turbulent Gas Clouds and Respiratory Pathogen Emissions: Potential Implications for Reducing Transmission of COVD-19’, MIT/JAMA Insights Clinical Update, 12 May 2020
Bush, Dr Zach, zachbushmd.com 2020
Chen, ‘Modeling the Spread of Infectious Diseases: A Review’, Queens University, Ontario, Canada, Dec 2014
Ferguson et al, ‘Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand’, Imperial College COVID-19 Response Team, 16 March 2020
Lewnard & Lo, ‘Scientific and ethical basis for social distancing interventions against COVID-19’, Division of Epidemiology, University of California, Berkeley, 23 March 2020
Mathani et al, ‘What is the evidence for social distancing during global pandemic? A rapid summary of current knowledge.’ Centre for Evidence-Based Medicine at the University of Oxford: https://www.cebm.net/oxford-covid-19-evidence-service/ 19 March 2020
Qin et al, ‘Longitudinal survey of microbiome associated with particulate matter in a megacity’, Genome Biology, vol 21: 55, 3 March 2020
Reche et al, ‘Deposition rates of viruses and bacteria above the atmospheric boundary layer’, The ISME Journal, vol 12, 1154–1162, 29 January 2018
World Health Organisation, https://www.who.int/emergencies/diseases/novel-coronavirus-2019/advice-for-public 29 April 2020