As the world is beginning to lift the COVID-19 lockdown this week, after months of chaos and suffering, all nations have the same question in mind: When should we lift the lockdown? And how do we do it? The impact of every decision made at the national level is amplified by the hypersensitive conditions of both the reality, and fear of the virus spreading even further. One should look back on history and learn from science – to make informed policy decisions, during these desperately uncertain times of the pandemic.
Sound policy should be based on solid evidence, derived from data, collected through quantitative and qualitative studies. Politicians and policymakers often claim to recall lessons learned from past experience. Yet, historical evidence is rarely used in policy research or design. Like political science, sociology and economics; historical methods are theoretical and interpretative. Therefore, historical evidence is just as valuable in creating policies. The history and the role of the Black Death in the 14th century in civilisational collapse, can teach us about the causes and consequences of COVID-19. Many other infectious diseases like smallpox, measles, influenza, yellow fever, and malaria have led to millions of deaths and the destruction of economic systems of one or more countries. Historical data has been used as valuable evidence to support new health policies. Hence, a history-based approach, often neglected, should complement other methods in designing future pandemic policy. The role of evidence established via rigorous scientific methods are now well accepted and heavily used in policy drafting. In a pandemic like COVID-19; phylogenetic studies, PCR tests and epidemiological data serve as principles to identify new germs and emerging infectious diseases, in establishing strategies to contain the spread of the virus.
William Farr (1807-1883) was trained in medicine, mathematics and medical journalism. He was a pioneer in the development of quantitative studies of morbidity and mortality, thus establishing the foundation of clinical epidemiology. Farr’s Law states that the behaviour of epidemics in terms of evolution over time, can be forecasted by following a bell-shaped curve (Figure 1). Farr made this assumption, based on his observations of past infectious disease outbreaks and epidemics, closely studying the chronological order and occurrences of life and death, during key events. The aforementioned events include the rise, peak, and fall, of both the infection and death statistics, represented by the bell-shaped curve. Farr famously stated: “The death rate is a fact, anything beyond this is an inference.” This emphasized that in uncertain times filled with alternative explanations based on weak evidence – leading to rumors, fake news and conspiracy theories – scientific facts such as death statistics are the only numbers we should trust. Once we take this statistic one step further in making assumptions, we are at the stage of inference.
These historical statistics modeled the overall pattern of the rise and fall of an epidemic, leading to the establishment of Farr’s Law. This followed the “Scientific Method”, starting from the observation of factual events at different stages of an epidemic, forming a hypothesis on its pattern, highlighting recurring patterns between different epidemics, and finally – making a scientific claim and establishing a law that could predict the general pattern of future epidemics. One shall note here the remarkable ingenuity of Farr in establishing his law on infection spread, even before the “Germ Theory” was established 20 years later. Careful statistical observation of diseases can be remarkably accurate without any use of biological laws!
Now that Farr’s law has been established, how do we apply it in today’s pandemic, without distorting its fundamental basis? The COVID-19 outbreak has rejuvenated Farr’s law. Post-Normal Science (PNS) allows us contextualise scientific claims and laws, as we evolve our understanding of a contemporary issue in society and policy, which may be labeled as non-scientific. The concept of PNS analysis was developed in the 1990s by Silvio Funtowicz and Jerome R. Ravetz. PNS is the application of scientific facts in interpreting a complex event that affects society. It is best used to tackle societal issues where “facts are uncertain, values in dispute, stakes high and decisions urgent”. Pandemics, climate change, and nuclear accidents are situations that fall into the PNS paradigm. While scientific consensus can be achieved among scientists, there is a dire need for dialogue in the PNS context between scientists, policymakers, and the public, in order to establish an effective shared narrative. Yet, the fundamentals of science are still implemented; by means of critical and reflective thinking, peer-review, and the consensus of a community of qualified experts. Science is necessary, but not sufficient in the PNS paradigm. One striking example is the impossible debate between those who wish for an early lift of the COVID-19 lockdown, against those who think otherwise. This fundamental decision considers the risk and benefit, between life and livelihood.
This article uncovers the importance of historical evidence in establishing various pandemic policies. Farr’s law offers a combination of scientific and historical evidence to explain the rise and fall of a pandemic that follows a bell-shaped curve. Sound policy shall be designed according to the stage of the pandemic and its trends. Farr’s law may inform policymakers at key important stages – when to decide a lockdown order and when to lift it up. Science is uncertain, despite the use of sophisticated statistical methods and increasingly complex pandemic modelling softwares – policies should be created in light of the history and cultural values of a particular country, within the PNS paradigm. Therefore, the limitation of science in society should be acknowledged, especially when one seeks to accurately forecast the behaviour of both viruses and people, in deciding when to lift a lockdown.
CHHEM Siriwat, Master in Digital Technology Management (MDTM), Director of the Centre for Inclusive Digital Economy (CIDE), Asian Vision Institute (AVI) & CHHEM Rethy, MD, PhD (Edu), PhD (His), Honourary Distinguished Fellow, AVI. This article was originally published via the Centre for Inclusive Digital Economy (CIDE) of the Asian Vision Institute (AVI).
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