Big if true
Three health interventions that deserve a closer look
Some health interventions are no-brainers. We have plenty of evidence to support them— randomized trials, meta-analyses, large-scale replications. They’re the closest thing global health has to sure bets—proven, cost-effective, relatively low-risk. And yet, many of these still go underfunded or poorly implemented. We “EA-adjacent” types spend a lot of time at parties lamenting how global health isn’t short on well-supported ideas we underuse.
But this piece isn’t about those.
It’s about weird ideas—edge cases and overlooked risks where the research is far from settled, but might be doing way more harm (or good) than we think. Each of the examples that follows is grounded in data, but not enough to be conclusive. They're strange, they're striking, and they’re still uncertain.
What they have in common is this:
Surprising upside: The impact, if real, could be much bigger than anyone expects.
Not easily dismissed: The evidence is credible enough to take seriously.
Still an open question: We don’t know yet whether it’s true—but it’s worth asking.
These are the kinds of ideas I think we should poke at. If they turn out to be real, it could reshape how we think about improving health.
Biodiversity conservation
Diclofenac is a common painkiller, used in humans and animals alike. After its patent expired in 1993, cheap generics flooded the market and became widely used in Indian cattle.
That turned out to be a disaster for vultures.
When vultures fed on livestock treated with diclofenac, they died—usually within two weeks. India’s vulture population crashed. One species, the Indian white-rumped vulture, declined by over 97%.
This matters more than it might seem to. Vultures perform a public service by eating the bodies of animals. When they vanish, carcasses pile up, polluting water and attracting rats and wild dogs. The pollution leads to diseases like gastroenteritis, cholera, typhoid fever, hepatitis A and E, leptospirosis, and cryptosporidiosis; the rats and stray dogs spread diseases like rabies. One study, Frank et. al in the American Economic Review, estimated that in parts of India where vultures once thrived, the die-off led to a 4% rise in human mortality. The authors attribute 500,000 excess deaths over five years to the crash.
If true, given most of those deaths would have been from rabies or enteric infections, it would mean around 3.8 million disability-adjusted life years (DALYs) lost per year over those five years. That’s about half the global burden of cervical cancer during that time period.
Luckily, this is a problem with some obvious fixes. Diclofenac has been banned for veterinary use in India since 2006, but enforcement is patchy. Cracking down on illegal sales, promoting meloxicam (a vulture-safe, cheaper alternative), and supporting captive breeding and release programs could help reverse the decline. In the meantime, stopgaps like carcass incinerators can reduce the risk of disease spillover while populations recover.
Frank also published another striking finding—this time in the U.S., and this time about bats. White-nose syndrome, a fast-spreading fungal disease, has decimated North American bat populations. Some bat species eat up to half their body weight in insects each night. When they disappeared, farmers responded by spraying more pesticides—about 31% more, on average, in affected counties.
Pesticides come with health risks, especially for children. Frank’s study finds that infant mortality from internal causes rose by about 8% after the bat die-off. Another unbelievably large figure.
Both studies suggest that protecting certain animal populations might have large, direct effects on human health that we’re overlooking. But there are good reasons to be cautious. These are outlier results; there isn’t much else in the way of evidence for estimates of this magnitude for the impact of biodiversity loss on human mortality. There’s also the possibility of publication bias. In particular, since both papers come from the same author, this may be driven by a file drawer effect, where a researcher looks at many potential similar cases but the null findings are less likely to see the light of day.
Still, if these effects are real, they could change how we think about conservation. Saving vultures or bats wouldn’t just be about biodiversity—it could also be a form of public health policy.
Replacing dirt flooring
Dirt floors are breeding grounds for disease. Diarrhea, parasitic infections, and respiratory illness are all more common in homes without finished flooring. And downstream of those health problems come others: poor cognitive development, higher mortality, and lower income over time. Roughly a billion people still live in homes with dirt floors today.
In 2000, a program in Mexico tried something simple: it gave households up to 430 square feet of concrete—about $150 worth—to replace their dirt floors. A follow-up World Bank evaluation found that doing so led to a 78% drop in parasitic infestations, 49% less diarrhea, 81% less anemia, and up to 96% improvement across early childhood cognitive tests. Adults reported feeling less depressed and more satisfied with life, even 15-18 months later.
There’s an important catch: the study wasn’t randomized. Families weren’t selected by lottery or assigned randomly, but rather chosen based on their poverty status and household characteristics, so it’s possible the households that received cement floors were already different in ways that mattered. To adjust for this, researchers used a matched cohort design, comparing each treatment household to one that looked similar on observable traits. But unobserved differences—like motivation, or local infrastructure—could still explain part of the effect.
A replication team led by Basurto et al. reanalyzed the study. They dug into the sampling strategy, cleaned up some coding errors, and tested alternative assumptions and analytical methods. Despite all that, their results closely matched the original and were robust to different analytical decisions: flooring really did seem to improve health and cognition.
Still, the effect sizes are so big that I feel like this story is likely missing important context. The authors found a: 49% reduction in diarrhea, 81% in anemia. But from what baseline? If anemia was 10% prevalent, an 81% decrease is meaningful but modest in absolute terms; about eight fewer cases per hundred people. If it was 70%, that’s a very different story. Without clear baseline rates, durations, or age-specific disability weights, it’s hard to translate these results into a comparable metric.
That said, let’s play it out. If these numbers are even half right, this is a wild finding. A one-time $150 slab of concrete seems to outperform daily iron pills (which reduce anemia by ~39%) and nearly match handwashing campaigns for diarrhea prevention (estimated at ~40%). And unlike those interventions, it requires no behavior change and lasts for decades.
That’s a remarkable return for a humble flooring upgrade. If this replicated elsewhere, replacing dirt floors might be one of the highest-return infrastructure investments for child health.
Which is also why it’s hard to swallow. Can concrete really beat decades of targeted public health programming? Maybe this context was uniquely favorable. Maybe the design exaggerated the effects. Or maybe there’s something deeper going on—like flooring acting as a proxy for stability, security, or perceived agency. Either way, if it’s real, even a little, it’s too big to ignore.
There are a few more reasons for caution. The method for measuring parasitic infection wasn’t clearly stated, raising the possibility that the data came from self-reports (which are more vulnerable to bias). People who got the concrete may have genuinely felt better and more optimistic, and that could shape how they remembered or reported their health. And this was early 2000s Mexico. Many regions today may have lower baseline disease risk due to deworming or sanitation improvements.
Still, the possibility that something so basic could drive these kinds of outcomes on health, cognitive development, and subjective well-being is worth a closer look. I haven’t come across any completed randomized trials that could triangulate these findings, but I’m aware of at least one large RCT underway, with results expected in a few years.
Reducing environmental noise exposure
We know that extremely loud noise—like standing next to a jackhammer—can damage hearing. But a growing body of evidence suggests that much lower levels, when experienced constantly, may also pose serious health risks. Chronic environmental noise, like from traffic, trains, or construction, has been linked to heart disease, cognitive decline, and even early death.
Noise is measured in decibels (dB). A whisper is about 30 dB, typical conversation clocks in at 60, a vacuum cleaner hits 75, and a train can reach 100. The scale is logarithmic—each 10 dB increase doubles how loud a sound feels.
At high volumes—above 85 dB—noise can damage your hearing. But for more subtle health effects, the thresholds are lower. The World Health Organization considers average noise levels above 40 dB to be harmful. At night, that drops to 30 dB, due to noise’s impact on sleep. That’s about the volume of a quiet suburban street or a humming fridge—background noise you'd barely register.
Unlike many public health risks, noise often flies under the radar. But it’s everywhere. Nearly a third of Americans live in areas where environmental noise exceeds 45 decibels, according to U.S. Department of Transportation models.
And like air pollution, it’s not distributed evenly. Lower-income communities are often hit hardest. This makes noise a surprisingly plausible candidate for a major, under-appreciated health risk. But the evidence is still emerging, and most studies are observational.
The health links are worrying:
A study near Heathrow Airport found that people living in the noisiest areas had a 10–25% higher risk of stroke or coronary heart disease. The study adjusted for area-level deprivation and air pollution, but not for individual income or housing value. This means the observed association could partly reflect socioeconomic differences, since quieter homes near airports tend to be more expensive and house wealthier, healthier residents.
A 15-year cohort study in Switzerland found that each 10 dB increase in road traffic noise raised the risk of heart attack mortality by 4.3%. Compared to the earlier study near Heathrow, the Swiss cohort used individual-level data, tracked address histories, and adjusted for air pollution and spatial factors. But the study didn’t control for income or housing value directly, so some of the observed risk likely still reflects underlying socioeconomic differences.
A meta-analysis of 14 studies reported an 8% increase in heart attack risk for every 10 dB increase in road traffic noise (within the 53–77 dB range).
Another review, covering 24 studies on hypertension, found that every 5 dB increase in noise exposure raised the odds of high blood pressure by about 3.4%.
These are modest effect sizes. But given how common cardiovascular disease is, and how many people are exposed, the total burden could be significant.
The risks don’t stop at the heart. A 2021 study of 2 million Danish residents found that long-term road noise above 65 dB was associated with a 16% higher risk of Alzheimer’s compared to levels under 45 dB. A study in China found that factory workers exposed to occupational noise scored lower on standard cognitive tests. In animals, chronic noise exposure disrupts sleep, activates stress hormones, and damages brain regions involved in memory, and prenatal exposure seems to make the effects worse.
The WHO now ranks traffic noise as the second most harmful environmental factor in Western Europe, after fine particulate air pollution.
Still, these are all correlational findings. Researchers try to control for confounders like air pollution or smoking, but it’s hard to isolate the specific effect of noise. The mechanisms are plausible—stress, sleep disruption—but still speculative. Since noise often co-occurs with poverty and pollution, there’s a real risk the effect sizes are inflated.
Beyond health, noise may also affect learning and productivity. A 2015 review found that chronic noise from traffic and aircraft impairs children’s memory and reading comprehension. A more recent study in Kenyan factories showed that persistent workplace noise reduced workers’ cognitive performance—even after adjusting for other variables. If these effects generalize, cutting noise could improve not just health but also income.
And noise isn’t random. It maps onto inequality. A global study using “hearing age gaps”—the difference between someone’s hearing age and their actual age—found that people in cities with lower average incomes often had hearing ages 15–20 years older than expected.
In New York City, exposure varies dramatically from block to block. Highways, flight paths, and industrial zones concentrate noise in places like the Bronx, Queens, and parts of Brooklyn.
This all makes noise especially hard to study, but potentially high-leverage. The concentration of exposure in certain areas means targeted reductions could have outsized impacts. But it also means that many studies are observational and vulnerable to confounding.
Still, if chronic environmental noise really does affect cardiovascular health, cognition, and learning—even modestly—it could be a bigger deal than we’ve realized. Like air pollution, it may be a slow, invisible driver of poor health outcomes.
And if that’s the case, we’re not helpless. There are already tools: subsidies for urban soundproofing or insulation, quieter road surfaces, better vehicle design, and “Buy Quiet” procurement policies (used by NASA and NIOSH) to encourage low-noise tools and machines.
Curious about your own noise exposure? If you’re in the U.S., you can search your ZIP code in the Department of Transportation’s noise map. Or download the NIOSH Sound Level Meter app to measure it directly. If you’re feeling generous, you can even contribute your readings to the Noise Across America dataset.