Well-formulated scientific tools exist for tackling complex problems such as the Covid-19 pandemic that include all role players in society. However, rather than a holistic, scientifically based, inclusive plan for the pandemic, the government focused on models that gave uncertain and alarmist projections of loss of life and attached too little weight to the certain loss of jobs, tax revenue and government services.
The notion of science and the awe in which society holds the scientific method is rooted mainly in what science has achieved in the fields of physics and engineering, and how these achievements have driven technological innovation to the benefit of mankind. Science has been less helpful in the fields of human behaviour, such as economics, politics (forecasting election outcomes) and the study of disease transmission. When applied to Covid-19, scientific models could tell us very little about how it would unfold.
In the case of Covid, statisticians have devoted considerable time to building a “model” of the infection path associated with the disease, as well as the impact interventions might have. Such models of the spread of a viral disease in effect try to mimic the path of the virus’s past behaviour, or the past behaviour of what is believed may be a similar virus. In the case of Covid-19 very little past data was available, so statisticians had to not only guess which model might be most appropriate but were unable to test the reliability of any model against actual data. Hence, on the basis of an uncertain model, and with effectively no historical data, it was always going to be challenging to use this approach to estimate the progress of the virus into the future.
In the case of the liquor-trade ban the estimates of the apparent positive spin-offs of the regulations have tended to imply that they are scientific truths, whereas in fact the reverse is probably true
Statisticians must always give model estimates that include the uncertainty of their estimates. If the uncertainty associated with model estimates is not made explicit, the government and the public may be given the impression that the model estimates have a weight of scientific knowledge behind them that they do not have. In the same way that forecasts of the spread of Covid are uncertain, the efficacy of the lockdown measures to counter the pandemic that are based on the model estimates are equally uncertain.
One of the most controversial restrictions imposed on SA has been on the sale of liquor and cigarettes. In the case of liquor, the ban has been supported by the contention that there is a need to take pressure off hospitals, which normally deal with many alcohol-related problems. However, scientific modelling and forecasting of Covid-related phenomena are challenging at best, and even with good data there is considerable uncertainty associated with such contentions.
In the case of the liquor-trade, ban the estimates of the apparent positive spin-offs of the regulations have tended to imply that they are scientific truths, whereas in fact the reverse is probably true. Estimates produced by the Medical Research Council that purportedly measured the positive effects an alcohol ban would have on societal health overall did not recognise the uncertainty underlying them. While trauma cases will be reduced to some extent, the negative effects resulting from the cancellation of elective surgery, for instance, and the reconfiguration of the health system to focus on Covid-19 cases, which has pushed aside HIV and TB cases, should also be considered.
Poorly based
The loss of tax receipts from the alcohol and tobacco ban have directly affected the provision of government services such as education and social grants, and indeed health services themselves.
The alcohol case is one example of several that pose many questions about the lockdown regulations and instances in which the government has taken an extremely restrictive position with little regard for how tenuous and poorly based this position is.
In reality, good scientific tools do already exist to approach such problems and have a widely recognised success record. There is a branch of the statistical sciences known as “operation research” specifically for the kind of problems considered above. It provides a methodological structure for determining what sort of intervention is appropriate when society is threatened by say a pandemic.
In a “cost-benefit” type approach, the methodology is known in the scientific community as “multicriteria decision analysis (MCDA)”. It weighs the overall benefits of a set of regulations (lives saved) against the overall costs to society of any imposed raft of lockdown regulations. The estimated benefits and costs are then assessed by the different groups and stakeholders in society. With this method, any given set of lockdown regulations could be more objectively assessed in terms of its overall net effect on society by the affected parties in society.
Though the government clearly needed to move quickly initially to protect the vulnerable, it also needed to consider a sensible structure, such as MCDA, within which stakeholders could assess the overall impact on society.
From the outset we needed to use the expertise of all stakeholders in the economy. Such stakeholders would include those who on ideological, religious or even aesthetic grounds favour the prohibition of tobacco and alcohol.
Society should not simply accept a set of seemingly arbitrary regulations imposed by politicians on the basis of questionable scientific recommendation — without consultation with the very people those regulations will affect.
• Barr is an emeritus professor in the department of statistical sciences at the University of Cape Town.
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