Part 2: Physical distancing saves more than hospital beds, it saves lives. Considerations for Africa.

Should countries in Sub-Saharan Africa consider physical distancing?

Many African countries have already imposed physical-distancing measures. The Government of Malawi, which we are supporting with predictive modeling, recently announced a three-week partial lockdown. (That order is tied up in court.)

Some commentators argue that physical distancing measures are useless or impractical in low-resource settings. They raise two basic objections:

1. The point of physical distancing, they argue, is to keep the number of severe cases within the health system’s capacity to treat them. (This is the horizontal line on the ubiquitous “flatten the curve” chart.) There’s no hope of achieving that in countries where ICU capacity is minimal and the health care system is overstretched to begin with.

2. Countries with many people on the edge of subsistence can’t afford to constrain mobility drastically enough to make a difference.

For those of us with deep experience in sub-Saharan Africa (SSA), these theories resonate and follow conventional wisdom. However, a deeper look into the data and epidemiology of COVID-19 suggest these hypotheses are short-sighted and lack the nuance needed to design optimal policies and strategies in local context.

The first objection rests on the flawed premise that flattening the curve is only about protecting healthcare capacity, by spreading out the same number of infections over a longer time.

Protecting the health system is important, of course, but it’s not the whole story.

Flattening the curve also reduces the number of people who ever become infected. We explain why below.

The second objection overlooks that even a modest intervention — far less drastic (and thus less effective) than those imposed in the U.S. and Europe — still saves many lives. Short-term physical distancing can’t suppress the virus altogether, but it can save lives at an economic cost that may be more bearable for low-resource countries. (It’s also important not to forget the economic and social costs of allowing a frightening epidemic to run uncontrolled through society.)

In this post, we explain why, using modeling we’ve conducted for the Government of Malawi.

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How does physical distancing reduce the total number of infections (rather than just spreading the same number of cases out over a longer time)?

The key factor is how fast the population reaches herd immunity.

Herd immunity occurs when enough people have been infected and recovered and thus achieved some degree of immunity. As the remaining infectious carriers encounter fewer and fewer vulnerable people, the virus runs out of new hosts and reaches a dead end.

Herd immunity eventually ends the epidemic (after many deaths), but — counterintuitively — we don’t want to get there too fast.

(To be clear: this is not an argument for choosing a “herd immunity” approach over suppressing the epidemic, in any situation where suppression is possible. Our point is that even if long-term lockdowns are taken off the table because of resource constraints, short-term physical distancing measures are still much better than doing nothing.)

Left unchecked, the new coronavirus can tear through a population at incredible speed — apparently much faster than its well-known relatives, SARS and MERS. People can be highly contagious but have few or no symptoms. “Stealth transmission” by outwardly normal people makes the spread much harder to stop.

This virus moves fast, and — if R0 is above 2 — it expands exponentially. A fast-growing epidemic does not simply stop at the theoretical herd-immunity threshold — that is, the level of immunity in a population that would prevent a new outbreak from taking root. The reason is that the huge group of people carrying the virus at the peak of the epidemic continues to infect many others, even if the overall number of infections begins to decline.

The result is that the overall infection rate in a raging epidemic can land far above the theoretical herd-immunity threshold. Modelers call that extra portion of the population that gets infected “overshoot.”

With no mitigation, our model predicts that the virus would infect 85% of Malawi’s population before herd immunity kicks in. That is far more than the 55% that we predict would provide herd immunity against a new outbreak (assuming that R0 is 2.2).

With distancing, the virus moves through the population more slowly. With three weeks of modest physical distancing[1], only 60% of the population eventually becomes infected. This is shown in the chart below by the green line, labeled “additional restrictions”:

The “Current Policies” include installing hand-washing stations at markets and water pumps; early closures of bars; prohibitions on wedding parties, sporting events, and church gatherings larger than 100 attendees; and guidance on maintaining 1-meter distance in social interactions. (Additional details on the categories is in the table below.)

Across a population of more than 18 million, that means millions of fewer infections.

And as you would expect, preventing millions of infections prevents thousands of deaths (10% of deaths averted):

Note that this reduction in deaths has nothing to do with reducing strain on health-system capacity, the most commonly cited reason for physical distancing.

We also found that this effect is durable — these deaths never occur, as long as governments maintain less-invasive mitigation measures (see “Current Policies” category above) once additional restrictions end.

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What does this mean for Sub-Saharan Africa?

The bottom line is that even a short period of physical distancing can save many lives.

Governments in low-resource countries, like their counterparts in wealthy countries, must weigh the benefits of various interventions against their economic and social costs. As we will explain in our next post, granular, localized data on economic and social vulnerability can help governments mitigate the consequences of targeted lockdowns and other distancing measures.

Local experts, armed with this data, are best placed to judge what measures are sustainable and appropriate for their own people. Many African governments, including the Government of Malawi, are using predictive modeling and other advanced techniques to develop COVID-19 plans that reflect local conditions.

African governments need more resources to fight COVID, but they also bring their own strengths to this challenge. Past epidemics, including HIV and Ebola, have left many countries with hard-won experience in testing, contract-tracing, and explaining public-health measures to their people. Some of their approaches could be models for state and local governments in the United States, which face significant resource constraints of their own.

More information about our team and our work can be found here.

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[1] These additional restrictions would entail rotational work schedules, capping the number of passengers in public-transit vehicles, and requiring self-quarantine for those returning from overseas, and restricting gatherings to fewer than 100.