Epidemiology has been a cornerstone of public health policy in western societies for more than 150 years. It can perhaps be traced back in its modern form to 1850 when the Epidemiology Society of London was created to track and prevent epidemics.
Its members were motivated by a cholera outbreak in the city in 1831. They included John Snow, now recognised as one of the founders of the discipline.
UK Prime Minister Boris Johnson cites epidemiology as the scientific basis for policies which in mid-March included closing schools, bars and restaurants.
On 17 March, UK Chancellor of the Exchequer Rishi Sunak unveiled an unprecedented plan of expanded public spending to counter the impact of Covid on the economy.
He too relies on scientists in the form of highly-qualified economic advisers.
Apart from starting with the same letter of the alphabet and using language and a methodology few comprehend, epidemiologists and economists apparently don’t have much in common.
Or so we thought before the Covid crisis.
It is increasingly evident that models used by epidemiologists are, just like those used by economists, open to challenge.
The human factor is the Achille’s Heel for both disciplines
First, there is the reliability of the data itself, though epidemiologists can claim greater scientific support for the accuracy of its measurement instruments than economists are able to.
For example, what is economics’ definition of capital, precisely? This may come as a shock to non-economists, but there isn’t one.
But after that, there are closer coincidences: random error in the databases used; systematic error and selection and information bias.
It must all sound familiar to economic statisticians.
And then there is the complexity of the models themselves which require a high degree of technical skill both to comprehend and manipulate. UK chief medical officer Dick Whitty, one of the key influencers on Britain’s Covid response, looks like a genius and is a physician with post-graduate qualifications in tropical medicine as well as a master’s in law and an MBA.
He’s just like the economists behind the Bank of England’s latest dynamic stochastic general equilibrium model and their counterparts across the world.
Economics never recovered from failing to forecast the crash of 2008
None of this means that epidemiology or economics should be treated with caution or disrespect.
And the fact that the model being used by the UK this spring has been criticised by other epidemiologists, including former and present employees of the World Health Organisation (WHO), is again no reason to reject it.
It’s evidence that there’s an engaged professional group asking the right questions about Covid policy and its foundations.
But epidemiological models do have a flaw and it’s one that is shared by their counterparts in economics.
The human factor.
You can be define the structure of a virus and how it behaves, which is invariably predictable to the point of being determinate
But people?
This is particularly challenging when you’re dealing with Covid, a new form of the Coronavirus that didn’t exist six months ago. There’s a growing but still limited global Covid database. It will only be complete when the present pandemic has passed.
And then there’s the infection path-way and how that might vary from country to country and culture to culture.
And of course, as the UK is discovering, there is the way people respond to news and fear of Covid.
Initially at least, Britain chose to persuade rather than force its people to stay at home and practice other social distancing measures. As this article was being written, it seems that wasn’t working in the way the British government envisaged.
Doesn’t this all sound very much like economics and its failure to foresee the 2008 great financial crash, an event brought about by unpredictable human behaviour?
Economics has never recovered.
It may be epidemiology’s turn now.