Prompted by interesting blogs on post-normal science:
Brigitte Nerlich - Public engagement with ‘post-normal science’
Ken Rice - Science in a time of COVID-19
Listening to the modellers instead of public health
From the beginning of news coverage of the pandemic
management in UK, the focus has been on modelling the data, flattening the
curve, ‘squashing the sombrero’ etc. The days of February and March 2020 seemed
to focus on preventing a large second wave, which we heard had been a major
cause of death in the 2018 flu pandemic. We were told that the epidemiologist
had run models that could compare different interventions; closing schools,
airports, etc to tell us which of these could have most effect. Which of these should
be prioritised and which could remain open to ‘save the economy’ – thus the
concept of a dilemma of either saving the economy or the managing the health crisis
was disseminated. The power of these modelling techniques was this apparent
intelligence and targeting of interventions, thus ‘saving’ other populations or
‘markets’ that could continue, because the model indicated that they had little
impact on future spread of the epidemic. The strength of these techniques are
in the raw data available and the weakness in the initial assumptions that make
up the model. These assumptions are things like how transmissible is the virus
by close contact between people, versus passing in a large building such as an
airport, for example.
Modelling was favoured by UK Government, I think, because
this was an opportunity to ‘show off’ our latest development in ‘big data’.
Also mentioned in the news media was behavioural economics and ‘nudge theory’ –
which is another favourite of Government, where the population can be ‘managed’
through friendly nudges rather than draconian legislation. There was talk about
fatigue of the population if Government locked down too soon.
I was pleased, initially, to hear that Government were going
to ‘follow the science’ – it was a relief after the post-expert years – where we
had heard enough from experts. However the science that was chosen to be followed
and the interventions prioritised seemed to be selectively chosen.
What was wrong with public health?
Public health professionals have been managing epidemics
effectively for over 150 years. Arguably one of UK’s best ‘global exports’, but
I guess it was seen as too traditional, or even basic. The strength of the
public health approach is that it is not so reliant on initial assumptions, but
in the basics of cutting transmission links by isolating people who are ill or
may be contagious. Rather than ‘big data’ and ‘smart’ approaches, this requires
local resources and public health experts working with local communities. People
have to forego some rights in exchange for protection from infection; rights
include some elements of privacy, freedom to go to work, to go to the shops. For
me, the key issue to learn from the management of COVID is that rather than predicting
behaviour of the population, we need to build trust, and this needs to be done at
a community level, rather than at a population level. Trust in a local health
protection officer may be more easily obtained rather than trust in an app
which has access to your personal data.
Public health is not a ‘pure science’ – it’s a
multidisciplinary science and also a professional practice. It acknowledges
political and economic pressures and attempts to bring to bear the best science
from different academic disciplines. I don’t think anyone would connect public
health with post-normal science…
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