Flattening the Curve, Flooring the Poor

The coronavirus (Covid-19) pandemic now has infections doubling every 3-5 days in some countries, raising fears that the exponential growth could soon infect most of their populations. Although Covid-19 is an “equal opportunity infector”, the poor are more susceptible and suffer disproportionately from curtailment measures. Therefore, informed policy making is critical especially when safety nets are weak.

The two countries with the highest infection and mortality rates – China and Italy – have introduced shutdowns. Infection rates have stabilized in China but not yet in Italy. Other countries with high infection rates like Iran, Spain, Germany and France are following suit. These community isolation measures are intended to “flatten the curve”; to slow the spread so that medical providers, supplies and infrastructure can cope with the increase.

These increases combined with fear driven by uncertainty is pushing other countries to implement increasingly draconian measures. Governments that have underestimated initial risks may over-react in an attempt to compensate for initial failings. The compulsion not to appear complacent relative to others, especially when lives are at stake, is leading countries to err on the side of caution. But errors and such caution come at a price.

If there is uncertainty over the effectiveness of these measures, there is less so about the costs. The measures are having major, wide-ranging economic and social consequences, although the discussion has focussed on the macroeconomic impacts. What is missing is a contextual analysis which considers initial conditions and ground realities in assessing whether the measures are justified in cost-benefit terms.

The first of these initial conditions is the data itself- reported infection and mortality rates. When the Philippines imposed its shutdown, to last a month, infections were below 100, with 3 deaths. When Malaysia did the same from mid-March for 2 weeks, its reported rates were only slightly higher. While these numbers were admittedly underestimations due to limited testing, there was no basis to suspect significant community transmission. Rates have since increased sharply with increased testing, but remain relatively low. Indeed, there is no country with an equatorial climate that exhibits rampant community transmission (including Singapore, with reliable data).

Are these extreme measures warranted? Shutdowns will reduce the spread, but at what cost?

In developing countries, there are more effective ways to reduce death from disease. Up to 40 per cent of often deadly diseases could be prevented by proper hand washing, if the poor had access to clean water.

In the Philippines, the limited testing was not due to complacency alone. There were limited test kits, and little personal interest in being tested if healthcare was unaffordable anyway. If the curve is being flattened, it is not for the poor, although they will bear most of the unintended consequences. The poor live day-to-day, and any prolonged shutdown could prevent the poorest from scavenging for food, or the millions in the informal sector from earning a subsistence income. For the poor, it is quickly becoming a question of survival, in the absence of adequate safety nets.

In developing countries, there are more effective ways to reduce death from disease. Up to 40 per cent of often deadly diseases could be prevented by proper hand washing, if the poor had access to clean water. But with a third of urban populations living in slums, and 1 in 5 people under 17 years being excluded from education, the poor lack access to clean water and the requisite knowledge to practice even proper hand washing. And the list goes on.

Admittedly, these issues are long term challenges, while the pandemic is an immediate concern. But they highlight how governments consistently ignore the poor, reaffirmed in the response to Covid-19. It also demonstrates how susceptible the poor are, and how the shutdown increases that vulnerability. These ground realities require the response to include mitigation measures that protect the vulnerable against adverse consequences.

But decisions are being made not based on data but on the lack of it, guided by the false presumption that over-reacting is justifiable. If the decision to shutdown was based on fear that community spread was rampant, then it may already be too late. Trying to slow it further may not justify the high cost of shutdowns. If there was no rampant community spread, then a shutdown is simply an over-reaction.

Therefore, when there is no evidence of rapid community transmission, a gradual approach is probably best. Start with a combination of international controls and domestic social distancing measures stopping mass gatherings but not threatening livelihoods. Review as data becomes available. An unsustainable shutdown should be the last resort, and data should support it.

The importance of data in developing an effective response is evidenced by the experience of Korea with mass testing, and Singapore with contact tracing (when community transmission is low). Data from mass testing and contact tracing will enable the evaluation of mitigation measures. This would help facilitate timely adjustments that limit harmful, sometimes deadly, over-reactions. Even with limited resources, poor countries could do more in testing and tracing; an immediate rethink of priorities is required.

There is a long way to go in the war against Covid-19. But policy needs to be responsive not just to trends overseas, but to how response and mitigation measures are working domestically. This should be based on data rather than fear. Over-reacting without adequate mitigation measures can be as bad as complacency if it leads to vulnerable groups suffering irreversible harm.

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