It was practised in 1350 during the Black Death. It was practised during the Great Plague in 1666. And it was still the best advice during the Spanish Flu in 1919. And it is no different today.
In 700 years the advice for the prevention of infection has not changed.
Like any other social “science”, epidemiology is a discipline and a field of study but it is no science.
“COVID-19 is a major acute crisis with unpredictable consequences. Many scientists have struggled to make forecasts about its impact. However, despite involving many excellent modelers, best intentions, and highly sophisticated tools, forecasting efforts have largely failed”.
1997: The Failure of Academic Epidemiology: Witness for the Prosecution, Carl Shy, American Journal of Epidemiology, Volume 145, Issue 6, 15 March 1997, Pages 479– 84.
Academic epidemiology has failed to develop the scientific methods and the knowledge base to support the fundamental public health mission of preventing disease and promoting health through organized community efforts. As a basic science of public health, epidemiology should attempt to understand health and disease from a community and ecologic perspective as a consequence of how society is organized and behaves, what impact social and economic forces have on disease incidence rates, and what community actions will be effective in altering incidence rates. However, as taught in most textbooks and as widely practiced by academicians, epidemiology has become a biomedical discipline focused on the distribution and determinants of disease in groups of individuals who happen to have some common characteristics, exposures, or diseases. The ecology of human health has not been addressed, and the societal context in which disease occurs has been either disregarded or deliberately abstracted from consideration.
And more recently:
2020: Forecasting for COVID-19 has failed, Ioannidis, Cripps and Tanner
Epidemic forecasting has a dubious track-record, and its failures became more prominent with COVID-19. Poor data input, wrong modeling assumptions, high sensitivity of estimates, lack of incorporation of epidemiological features, poor past evidence on effects of available interventions, lack of transparency, errors, lack of determinacy, looking at only one or a few dimensions of the problem at hand, lack of expertise in crucial disciplines, groupthink and bandwagon effects and selective reporting are some of the causes of these failures. Nevertheless, epidemic forecasting is unlikely to be abandoned.
Of course, actual health care and the medications available have advanced immeasurably during this time. Medicine and the development of medicines and vaccines have come a very long way since the Spanish Flu. But the prediction of human behaviour – which is what epidemiology is – is as uncertain now as it was in the Middle Ages. Mathematical forecasts – whether for pandemics or for climate – are only as good as the most inaccurate assumption made. Very often assumptions made are to comply with some other agenda. Sometimes, the assumptions made are just downright stupid.
And so, for over 700 years the advice for the prevention of infection has been and remains “Avoid contact, wear a mask, wash your hands and burn your dead”.
Tags: Epidemiology
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