Category Archives: Epidemiology

The study of the causes and distribution of disease. A methodological branch of health sciences

The Great Trade Experiment

Last month I wrote about The Great Foreign Aid Experiment of the Trump administration. Foreign aid has not been without its critics because it is inefficient, promotes corruption, or is a part of an insidious program of neo-colonialism. The decision, however, by the US Government to put foreign aid “through the wood chipper” sets up a natural experiment to test whether aid save lives—more precisely, whether the sudden removal of aid ends lives. Most people in global health believe that it will result in significant suffering, although some see a silver lining: deaths among the poor and vulnerable will mark the emergence of independent health systems in low-income countries that are more resilient and finally free of external interference.

Not content with one natural experiment at the expense of the global poor, on the 2^nd of April 2025, Donald Trump announced the imposition of the highest rate of tariffs on US imports in almost 100 years. In effect, the government is dismantling the free-trade mechanism that has been operating since the mid-1990s, and adopting a more isolationist market posture. Under this new theory of trade, wealth is not created, it is finite and accrued by one country to dominate another.

The evidence has been pretty clear about the effects of poverty on health. Poor people are more likely to die than rich ones. Infant, child, and maternal mortality rates are significantly higher among the poor. Preventable and treatable diseases such as HIV, tuberculosis, and malaria also disproportionately infect and kill the poor. These poverty effects occur both within and between countries. Furthermore, they are not just biological outcomes—they are deeply social, economic, and political in nature. The conditions of poverty limit access to healthcare, nutrition, education, and safe living environments.

Over the last 75 years, in parallel with increasing life expectancy across the globe, wealth has also increased. The proportion of people living in extreme poverty today is much lower than it was 50, 20, or even 10 years ago. In fact, historically the sharpest global decline in extreme poverty occurred between 1995 and 2019—2020 was, of course the COVID pandemic, which reversed a wide rage of health and economic indicators.

Bill Clinton assumed the presidency of the United States in January 1993. He was supportive of free trade and the Uruguay Round of of the General Agreement on Tariffs and Trade (GATT), which was completed in 1994. The successful conclusion of GATT led to the creation of the World Trade Organization (WTO) in January 1995.

Following the liberalisation of trade, global extreme poverty rates fell from 36% to 10% between 1995 and 2018. In South and South-East Asia the extreme poverty rates fell from 41% to 10%. In Sub-Saharan Africa, the extreme poverty rates fell substantially, but without the same speed or depth as elsewhere: 60% to 37%. The gains of trade liberalisation were also more advantageous to some markets than others, and it particularly benefited countries with cheap manufacturing capacity such as Bangladesh and Cambodia.

The sudden US reversal on tariffs will be punishing for those poor countries that have developed a manufacturing sector—particularly in shoes and garments—to provide cheap, volume goods based on low labour costs. Of course, the goods in the US need not be cheap, because there is considerable profit in branding.

If exports drop significantly, factories will want to cut staff numbers swiftly to retain their commercial viability. Poor households, particularly those reliant on a single income manufacturing jobs, will likely be thrown backwards into extreme poverty. The global economic gains of the last 30 years could begin to reverse. A major drop in exports will have an immediate impact on the factories’ labour force but there will be flow on effects to the entire economy of poor countries. In Bangladesh, for example, garment manufacturing is the single biggest source of export revenue, and reductions here will mean reductions in national tax revenue which supports health, education and welfare services.

In other LMICs that are less reliant on a global export market, shifts in tariffs will have a concomitantly smaller impact. Thus, the two natural experiments will intersect. The impact of foreign aid on health and the impact of foreign trade on health will play out with interacting effects.

Needless to say, none of this was ever framed as an experiment. Cutting aid and raising tariffs was all to “Make America Great Again”. It is a cruel, indifferent approach to trade and foreign policy. There will be no one in the Situation Room plotting a Kaplan-Meier survival curve. No policymaker will announce that the hypothesis has been confirmed/rejected: that wealth, when withdrawn or walled off, leaves people dead. Nonetheless, the data will tell its own story.

And when it does, it won’t speak in dollars or trade deficits. It will speak in the numbers of anaemic mothers, closed clinics, empty pharmacies, and missed meals. It will speak in children pulled from school to help at home. It will speak in lives shortened not by biology, but by policy

The Great Trade Experiment, like the Great Aid Experiment, won’t just test theories in global health and economics. It will test people—millions of them. And the results, while statistically significant, will not be ethically neutral. Some experiments happen by accident. Others, by design.

This one was designed—by the President of the United States.

Pandemic schmandemic

I was disconcerted to read that the last of the formal Pandemic Accord meetings for 2024 closed tonight (6 December 2024) without reaching an agreement. My colleague, Professor Nina Schwalbe, summed it up perfectly in her bluesky post. “Member States have missed a once-in-a-generation opportunity to make a difference because national interests prevailed over global solidarity”.

The World Health Assembly established the Intergovernmental Negotiating Body (INB) almost three years ago to “draft and negotiate a convention, agreement or other international instrument under the Constitution of the World Health Organization to strengthen pandemic prevention, preparedness and response”. When the WHA established the INB, we were in the middle of the COVID-19 pandemic. There was a visceral urgency to figure out better ways to work together globally to prevent and manage the next pandemic. Now, it’s all a bit “meh“.

In the last month, we have been gifted non-ignorable data points by the fates, which should have focused the mind. We did not need special skills to read the tea leaves at the bottom of the cup or divine the future from goat entrails.

The American people re-elected Donald Trump as President of the United States and handed him a clear mandate. He campaigned on a populist America First policy and has declared (and demonstrated) an antipathy towards global treaties and accords that threaten global health.
Trump also announced that Robert F. Kennedy Jr. (RFK Jr), a vaccine denier, would be the Health Secretary. RFK Jr is also on record that there is too much focus on infectious diseases.

Together, these will create geopolitical friction in negotiating a pandemic accord that may be impossible to overcome. Fate has also been teasing us with news of infectious diseases among those geopolitical tea leaves.

A mystery infectious disease has appeared in a remote area of the Democratic Republic of Congo. According to the Ministry of Public Health, there have been 394 cases and 30 deaths.
Influenza A subtype H5N1 is the stuff of infectious disease specialists’ nightmares. It has a very high case fatality rate–typical ‘flu’ has a fatality rate of <1%. H5N1 has a case fatality rate of around 50%. The saving grace has been that it had not adapted to human-to-human transmission. Human transmission might be about to change. It has swept through U.S. dairy herds and is found in raw milk. Did I mention that RFK Jr. is a fan of raw milk?

This failure is particularly bitter because they’re walking away from the negotiating table when the stars are aligning for potential future crises. We have a new U.S. administration openly sceptical of global health cooperation, an increasingly complex geopolitical landscape, and emerging pathogens testing our surveillance and response capabilities. The window of opportunity that opened during COVID-19–when the world’s attention was focused on pandemic preparedness–appears to be rapidly closing.

Local causation and implementation science

If you want to move a successful intervention from here (where it was first identified) to there (a plurality of new settings), spend your time understanding the context of the intervention. Understand the context of success. Implementation Science—the science of moving successful interventions from here to there—assumes a real (in the world effect) that can be generalised to new settings. In our latest (open access) article, recently published in Social Science and Medicine, we re-imagine that presumption.

As researchers and development specialists, we are taught to focus on causes as singular things: A causes B. Intervention A reduces infant mortality (B1), increases crop yields (B2), keeps girls in school longer (B3), or…. When we discover the new intervention that will improve the lives of the many, we naturally get excited. We want to implement it everywhere. And yet, the new intervention so often fails in new settings. It isn’t as effective as advertised and/or it’s more expensive. The intervention simply does not scale-up and potentially results in harm. Effort and resources are diverted from those things that already work better there to implement the new intervention, which showed so much promise in the original setting, here.

The intervention does not fail in new settings because the cause-effect never existed. It fails in new settings because causes are local. The effect that was observed here was not caused by A alone. The intervention was not a singular cause. A causes B within a context that allows the relationship between cause and effect to be manifest. The original research in which A was identified had social, economic, cultural, political, environmental, and physical properties. Some of those properties are required for the realisation of the cause-effect. This means that generalisation is really about re-engineeering context. We need to make sure the target settings have the the right contextual factors in place for the intervention to work. We are re-creating local contexts. The implementation problem is one of understanding the re-engineering that is required.

What is the optimal number of broken jaws?

I was chatting with a friend recently about the COVID-19 response in different countries. Reflecting on her own country, she said, “It is so hard to know what is right!”; that is, it is so hard to know what the right response to COVID-19 should be.

The variation, for instance, in countries’ lockdown responses is substantial, but which country is doing the right thing? In some countries, there has been no lockdown. The government asked the people to be sensible. In other countries, the government legally confined people to their homes — only one person was allowed out at very specific (restricted) times to buy essentials. Given these two policy extremes (be sensible and house arrest), which one is the right one, and how do you know?

An economist, I have forgotten who once asked tongue-in-cheek, what is the optimal number of dead babies? The very purpose of such a crass question is to make you stop and think. What tradeoffs are you prepared to make to save the lives of babies? Sure, you could be lazy, condemn the questioner as immoral (for even asking you to think), and declare zero dead babies to be the right number. As a simple policy proposition, if zero dead babies is the right number, then all the resources of society should be aimed at preventing neonatal deaths. ALL RESOURCES! Until the policy goal has been achieved, there is more work to be done to reduce the number. One dead baby is too many!!! Farmers may farm, but only to produce the food that supports the workforce that is striving to reduce baby deaths to zero. Teachers may teach, but only to educate the people to fill the jobs to support the policy goal to reduce baby deaths to zero. There is very limited use for art, music, cinema, sport, fashion, restaurants, etc. They will all have to go! If five-year-old deaths increase, that is something to live with, just as long as we can save another baby.

At this point, you’re probably thinking, well that’s stupid. That’s not what I meant when I said the optimal number of dead babies is zero. What I meant was something more along the lines of, “In an ideal world there would be zero dead babies”. Equally, if you were asked about poverty or crime, or amazing works of art, you presumably would have stated the ideals in terms of zero poverty, zero crime, and lots more wonderful art. And this is quite a different proposition. An ideal world is not ideal in virtue of its achievement of a single goal. It is ideal in having achieved all sorts of different outcomes. And that is why the real and the ideal do not intersect. In the real world, we do not achieve the ideal anything. We seek to achieve many ideals, and realistically, we hope to make progress against them, knowing that there is always more to be done. In striving to improve the societal position against a basket of goals, we allocate limited resources and make trade-offs.

This is one part of the COVID-19 problem, and, as my friend observed, why it is so hard to know what is right. What is the right number of COVID-19 deaths? There are lots of important, rational debates to be had around this topic because it is about the tradeoffs we are prepared to make against a basket of societal goals against the myopic achievement of one. Muscular public health responses — effective house arrest — are very good at reducing the number of new COVID-19 cases. They are also very effective at increasing domestic violence, increasing depression, lowering child immunisation rates, degrading child education, increasing poverty and increasing unemployment. If the societal goal should be zero COVID-19 deaths, what is the optimal number of broken jaws, suicide attempts, measles encephalitis cases, illiterate and enumerate children, beggars, and soup kitchens?

All these issues, under normal circumstances, are things of concern to Public Health and maybe, one day, they will be again.

Another part of the COVID-19 problem is that, whether a government “did the right thing” will be determined in hindsight, and by making (inadequate) historical comparisons between the outcomes across countries’. In democracies, at least in the short-term, “did the government do the right thing?” will often be decided at the ballot box. This will surely get the answer wrong. In less-than-democracies, astute rulers will write the history books themselves ensuring that, without regard to the outcome, the government did the right thing.

One of the main reasons that “it is so hard to know what is right!” is that we rarely have a societal view about the long term goals we wish to achieve and the tradeoffs we are prepared to make. Furthermore, we are reluctant to accept the fact that one can do the right thing and still fail. We assume that the right course of action will, by definition, result in success. We are prospective Kantians and retrospective Utilitarians.