u/Lonely_Lemur

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Chryses attempts to ransom Chryseis from Agamemnon, Apulian red-figure volute-krater, ca. 360–350 BCE, Louvre K 1. Photograph by Jastrow, public domain via Wikimedia Commons.

Christopher Nolan’s The Odyssey is sending a lot of people to read translations of the Homeric epic poems set in the Late Bronze Age. Follow the story backward and you get to The Iliad, set in the final weeks of the tenth year of the Trojan War. It opens with Chryses, an old priest of Apollo, who has come to try to ransom back his daughter Chryseis. Earlier in the war, Achaean troops took her captive and gave her to their commander, Agamemnon. Other Greek leaders in the story urge him to accept the ransom, however he refuses and drives Chryses away:

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He asks Apollo to avenge this insult, with the god responding by going to the Achaeans with his quiver and bow, sending disease through their camp. It first struck the mules and dogs, then the men. It lasted nine days, with the dead being burnt on funerary pyres. On the tenth day, Achilles, the Greeks’ greatest fighter brings together the leaders for an assembly noting the army would likely not survive the looming combination of war and disease.

It’s an episode that made my ears perk up as an epidemiologist. What kind of illness could’ve killed the working animals, dogs, and people that made up a crowded army camp? Could there have been some real outbreak at a real siege that ended up remembered as being the result of a god, angry on behalf of one of his loyal priests? They’re sensible questions, but mythology of The Iliad’s type can’t answer them. It provides no symptom history, duration of illness, or transmission route, and we’re without any archeological or biological evidence for such an event. The poem was composed in the late eighth century BCE from a much older oral tradition, centuries after the Late Bronze Age setting it was placed in.

The work attributed to Homer lets us see how this kind of catastrophe was understood by those alive at the time. A king’s bad decision followed by animal and human deaths and subsequent impacts to army logistics could be seen as divine anger. This wasn’t unique to the Greeks of the time, as a Hittite source from Anatolia shows us how a real Late Bronze Age king tried to confront an epidemic through similar political and religious actions.

What Disease Did Apollo Send?

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Chryses Praying to Apollo to Send the Plague upon the Greeks, attributed to Jacopo Alessandro Calvi, before 1815. Hinton Ampner, National Trust. Public-domain reproduction via Wikimedia Commons.

In the poem, the cause of death is clearly the response of Apollo to Agamemnon’s dishonoring of Chryses. The deaths only stop when Chryseis is returned and Apollo is appeased. We’re left without any symptoms to try and speculate based on, with even the original Greek words not fixing the problem. A study of plague-related language in Homer, Sophocles, and Thucydides notes that the Iliad first called the outbreak a nosos, a ‘disease,’ and later a loimos, usually translated into plague or pestilence. Neither gives any hint as to the pathogen itself and the surrounding language is the hostility of arrows, darkness, and destruction as a result of a god’s anger as it moves unrelentingly through the army.

But people love to speculate, so the facts at hand haven’t stopped some from trying to retrospectively diagnose the outbreak. In 1978 Frederick Berneim and Ann Adams Zener proposed equine encephalomyelitis as a candidate for the Achaean outbreak at the beginning of The Iliad. Their short article accepts the narrative as a disease chronology, inferring mosquitos to have been meant by Apollo’s arrow, while eventually acknowledging their theory would require an ancient viral variant that behaved vastly different from any known strains. They accept that this disease may not have existed in the ancient world and I see their work as an instance of responsible speculation. There’s nothing inherently wrong with asking whether some literary plague could’ve been based on real observations from the past, but without the information needed to distinguish one disease from another, the illness gets no modern name.

Apollo at Wilusa

The broader setting of The Iliad matters here, as the archeological site widely accepted as Troy is in northwestern Anatolia on the coast of modern Turkey. In the Late Bronze Age, it was on the western edge of a political world where Hittite kings who were based much further east made treaties with the local rulers, sometimes even intervening in local issues.

Sometime around 1275 BCE, the Hittite king Muwatalli II signed a treaty with Wilusa’s ruler Alaksandu. Wilusa is the city widely identified with the names Ilios or Troy. Interestingly, the treaty names one Appaliuna among the gods guaranteeing it. Appaliuna is often connected to Apollo, though the origin of the name and direction of cultural transmission are unclear. The recent review by Mary Bachvarova also mentions Appaluwa, a West Anatolian bow-wielding god invoked in two surviving plague-ritual texts from around 1200 BCE; the rituals concern sickness in a town or at an army encampment and would’ve been performed alongside the interpretation of omens. Bachvarova makes the argument that Appaluwa, Appaliuna, and Apollo are preserving closely related forms of the same underlying name within a greater Greco-Anatolian religious history. She also notes one version, a-pe-re-u, may be an early form of Apollo’s name on Crete.

The Hittite Plague

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Tablet of Muršili II’s prayer concerning the plague, from Hattusa. Istanbul Archaeological Museums. Photograph by Osama Shukir Muhammed Amin, CC BY-SA 4.0.

The Late Bronze Age leaves us with a somewhat more concrete record of an instance of prolonged mortality attributed to epidemic in Anatolia. Hatti, the Hittite empire that was centered on Hattusa in modern day Turkey, was a major power of the eastern Mediterranean at the time. Its king Mursili II, ruler from 1321 to 1295 BCE, left a series of prayers concerning a crisis that started under his father, Suppiluliuma I. He notes that people had been dying from plague under his father’s, brother’s, and his own rule and that more than twenty years into the crisis, the dying had not relented. When historians refer to the Hittite plague, this is usually the sustained mortality crisis being referred to. But like The Iliad, the prayers of Mursili don’t give us any type of symptom list or information that can give us a better idea of the pathogen in question either. He mentions Egyptian prisoners taken during the war, though he doesn’t go so far as to establish them as bringers of the disease. He asks the diviners and oracles to look for any offense that may have provoked the gods. They remind him of a broken oath by his father to the Storm God, with Mursili responding with confession, offerings, prayer, and requests for further divination services from the diviners and oracles.

Now, Homer and Mursili are incredibly unlikely to be describing the same event, as Mursili’s prayers are historical documents and Homer’s epics are myth possibly based on some past reality blended with myth. But both make widespread death into a question of authority with Agamemnon’s treatment of a priest putting his army at risk and Mursili’s father’s own conduct risking his. A third text brings the phrase “The Hand of Nergal” into relevance as well. The text, designated ‘Amarna Letter EA 35,’ is a diplomatic letter from the ruler of Alashiya, usually identified with Cyprus, to the Egyptian king, who at the time would have been either Amenhotep III or his son Akhenaten, and it notes that Nergal’s hand is in his country and has killed “all the men” of the land. The letter tends to be folded into the Hittite plague narrative because it belongs to the same fourteenth-century eastern Mediterranean infectious disease ecosystem.

Whether it describes the same outbreak will likely stay unresolved except in light of truly extraordinary evidence being uncovered. The comparison still matters though, as disease could have reached connected societies and received vastly different divine explanations, this hypothetical scenario being a plague attributed to Nergal among the Akkadians, the result of a broken oath to a storm god among the Hittites, and to Apollo among the Greeks. It’s what I might expect to see if we did uncover some wide reaching eastern Mediterranean plague. Communities have long made mass death more intelligible through those kinds of connections to the gods.

The Cost of Divine Anger

Hands down, the most elaborate attempt to name Mursili’s devastating plague is Siro Trevisanato’s 2007 proposal of tularemia, AKA rabbit fever, a bacterial infection often maintained in animal reservoirs and one capable of infecting people through multiple routes. His hypothesis paper also makes the claim that it was the first instance of biological warfare. That claim should be taken with a heaping helping of salt, with a later historical review stating there was no evidence of the Hittites deliberately spreading disease. He links Hittite prayers, Egyptian material from Amarna, military movements, animal transport, and later Greek traditions to claim there was one epidemic that crossed the eastern Mediterranean for some three or four decades.

While Trevisanato’s reconstruction is possible, in the sense that none of the individual links is too absurd to be possible, it is far from established orthodoxy among Late Bronze Age scholars. Gretchen Dabbs and Anna Stevens stress-tested one part of that wider story in 2025 by examining whether Akhetaten, later called Amarna, seems to have been through a high-mortality epidemic based on the archeological patterns. Their conclusion was one of restraint, noting that the cemeteries and settlement evidence don’t support such an event. Tularemia is still a possibility for what infected Mursili’s people, though it’s unlikely to be the same illness Apollo sent the Achaeans. The narrative of animals dying before people could preserve some memory of a long-lost event, but the poems can’t establish what that was. Within the story, I think it functions as a tell to the listener that no part of the camp was safe from the danger created by angering the gods. Apollo shows what can come of this through his bringing of disease to the Achaeans in the opening of The Iliad. The same moral logic shows up in the Odyssey. After Odysseus blinds Polyphemus, the Cyclops asks his father Poseidon to make sure Odysseus returns home late, without his companions, and finds further troubles in his kingdom of Ithaca. Mursili’s prayers give us a historical example of one comparable idea, that a ruler’s offense, divine anger, and the collective danger of a disaster belong to one larger explanation.

“Dark Ages” is still a bad label when it turns early medieval Europe into one long civilizational coma. It’s also too easy to answer that caricature by pretending that the western Roman collapse didn’t make some people’s lives harder. The useful question is what stopped working, where, and when. In Britain, the end of the coin supply and changes in town layers make Roman-style circulation, repair, and administration far harder to see after the early fifth century. Gaul wasn’t Britain: Marseille kept Mediterranean connections and urban importance. Italy, North Africa, and Iberia each followed different paths. Rural production and exchange didn’t vanish; they were reorganized into smaller, uneven networks.

Inscriptions, pottery, and burials can’t serve as a crude mortality ledger. They do show that, in many places, the ability to coordinate food, money, labor, taxation, and repairs across distance had contracted. Empires create risks, but they also provide buffers. Once that capacity weakened, a bad harvest or raid couldn’t always be absorbed as it had been.

That’s the more narrow sense in which parts of the post-Roman West got “darker”: people and institutions became harder to count, supply, and mobilize. This claim’s limited in that it doesn't cover anything like cover intellectual capacity or cultural production, while also not applying uniformly across the former empire.

I'm an outsider to the area of research as an epidemiologist, but I've been doing historical epi writing for a little while now. I'd appreciate any feedback from those with a background in the area, especially criticism as someone stepping into areas I don't always know about going in.

Sources:

- Bryan Ward-Perkins, *The Fall of Rome and the End of Civilization* (Oxford University Press, 2005): https://global.oup.com/academic/product/the-fall-of-rome-and-the-end-of-civilization-9780192807281

- Chris Wickham, *Framing the Early Middle Ages* (Oxford University Press, 2005): https://global.oup.com/academic/product/framing-the-early-middle-ages-9780199212965

- Ramsay MacMullen, “The Epigraphic Habit in the Roman Empire,” *American Journal of Philology* 103, no. 3 (1982): https://doi.org/10.2307/294470

- Richard Reece, “Town and Country: The End of Roman Britain,” *World Archaeology* 12, no. 1 (1980): https://doi.org/10.1080/00438243.1980.9979782

- Tamara Lewit, “Vanishing villas: what happened to elite rural habitation in the West in the 5th–6th c.?” *Journal of Roman Archaeology* 16 (2003): https://doi.org/10.1017/S104775940001309Xdoesn’t

The loudest public debates over ‘policing’ treat the position like a monolith, with homicide investigation, traffic enforcement, crisis response, hot-spot patrol, stop-and-frisk, and jail booking all being looked at as one ‘exposure’ in epidemiological terms. That couldn’t be further from the truth. Some police activities plausibly prevent death while others produce it, injury, fear, and distrust from the community they’re supposed to be policing. The task of public health individuals examining the impacts on society is to stop treating these as effects that can be averaged into one metric and acknowledging and embracing the heterogeneity of exposures.

One caveat before getting into this piece: policing in its various forms is something that is unusually hard to measure, and the data-oriented readers out there have good reason to distrust some of the official record regarding police violence specifically. Official use-of-force and death records are often incomplete, with some of the best mortality data coming from journalistic or open-source databases like The Washington Post’s Fatal Force archive data from 2015-2024, Fatal Encounters, and Mapping Police Violence. The evidence is still usually messier than one would hope for when looking to see how different aspects of policing act as a public health exposure. This is my best attempt to square that messy evidence with the epidemiological question I’ve had for a while now: what functions of the police protect health and lives, and which cause damage while purporting to help?

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Asking the Wrong Question

Like I said earlier, my prior here is that the loudest public conversations around policing have become almost useless. One side often talks as if the police are uniformly near flawless or at least doing such a good job that any criticism hits a brick wall. The other talks as if the police are so ineffective, violent, and rotten-to-the-core that reducing their funding and function becomes their obvious public health answer. I find it hard to trust either of those overly clean narratives because I’ve found truth on contentious topics often lives in the gray middle that people aiming for clicks typically avoid. The mistake I think is being made is treating policing as a singular intervention and then asking if its good or bad. That’s the wrong question because policing isn’t a singular exposure that can be generalized in that way. The same word covers violence prevention/responses, traffic enforcement, street level stops, homicide detectives, and crisis response. All different interventions that have vastly different mechanisms, target populations, counterfactuals, and health effects. Those health effects depend on which function we’re talking about.

How Police Became the Overflow System

That variability is also present in the history of policing in the United States as it lacks a singular origin story and is more one of an accumulation of new roles. In 19^(th) century cities in the North, full time police departments took on the roles of earlier watch systems and local volunteer services. The growth of large, commercial cities meant growth of the police departments as well as they tried to protect property, manage the newly crowded streets, and control conflicts that came with multi-origin immigration and industrial labor said immigrants often ended up working in. When it comes to the South, you can’t do an honest history of policing that skips over slave patrols and the armed patrol systems used to regulate the movement of slaves and protect the racial status quo.

I’ve seen the claim that the modern police department is just an evolution of those slave patrols but that’s too clean of a narrative of an institution with such variable history. The more narrow and stronger point to make is that American policing was multifaceted from the beginning as it covered ordinary public order and emergency response as well as property protection and control over who could move freely and where that freedom stopped. The same set of powers can be seen as protective or coercive depending on one’s standing. The 1988 National Institute of Justice essay by George Kelling and Mark Moore divides policing into three eras: the political era, the reform era, and an (at the time) emerging community problem-solving era.

The political era ranged roughly from the 1840s to the early 20^(th) century when police departments were most closely tied to their local political machines and the demands of specific neighborhoods. Police enforced the law while also involved in informal forms of urban management. They turned into the municipal instrument the area could call on to handle whatever was wanted or needed of them. Then came the reform era, which tried to solve one problem through the creation of another. Reformers wanted a bit of distance from the partisan politics of the time as well as a clearer, more professional chain of command with civil-service rules, radio communications, patrol cars, and bureaucratic standards to make things more modern and easier to administer. That era also narrowed the official story of what police before, with the official, respectable answer of the time being ‘crime control.’

That’s difficult to make a reality when the city itself doesn’t simultaneously reduce the problems it has need for responses to. Calls still came in from all corners of the urban centers including problems that were clearly terrifying or urgent, but not always criminal. Patrol cars with radios could hear about and then reach those calls quicker than other public agencies at the time which made them especially useful in emergencies. It also had the effect of deepening the habit of routing those sometimes difficult to deal with social problems through the one agency that was always readily dispatchable. Reform made the police departments more professional but that doesn’t make the problems they deal with more coherent for them to be dealing with.

That model had come under pressure by the 60s and 70s, as rising crime had made the reactive model look inadequate to respond to new challenges. Civil unrest and police violence had questioned the legitimacy and rendered that reputation fragile. A 2018 National Academies’ report on what became known as proactive policing describes it as a strategic approach that grew out of that crisis of confidence and from the crime-control innovations that arose in the 80s and 90s. The historical epidemiology is clear here with that preventive approach having some clearly defined strategies and theories of how police might prevent harm. A hot-spots strategy focuses energy where crime is most heavily clustered. Problem-oriented policing asks what specifically is producing a recurring problem and tries to change those specific conditions. Focused deterrence methods aim at people or groups who are at an unusually high risk of violence. Community-oriented and procedural-justice strategies focus most heavily on the legitimacy issue and cooperation of society and lawmakers with policing to better outcomes for all involved.

Some older strategies like order-maintenance and broken-windows followed a related pattern where, theoretically, they treated disorder as the signal informing them that the informal social controls are breaking down. Practically, they often meant more low-level enforcement in places with already high levels of poverty, violence, and police attention. Historically, that explains why the public debate can contain some truths that seem to contradict each other. Proactive policing can include both a focused violence-prevention strategy and increased street stops, even though those are different exposures for the residents.

By the time we get to the present day, police departments are doing so many jobs it becomes difficult to analyze as a public health exposure. The average day for a police officer where I grew up could consist of showing up to my house when one of my seizures lasted too long, a homicide call, and everything in between. Cities send the cops when someone’s been shot or just when someone is sleeping outside where they “shouldn’t be,” or when a family can’t manage a psychiatric crisis. That’s the historical reason why the evidence points in different directions. Modern policing is a heavily layered institution, with layers added in response to different political problems, gaps in service, and theories of the social order. It’s difficult to imagine them having all of the roles they have outside of blanket necessity or lack of other options.

Homicide Prevention

Homicide prevention is a public health good, as homicides contribute to premature mortality in the US compared to other nations, especially since the majority of homicide victims are young. There’s also the grief, trauma, retaliation, and sometimes reorganization of one’s daily life around possible dangers. The cleanest source on the topic I could find is a 2022 paper in AER paper called Police Force Size and Civilian Race by the criminology/economics/public affairs team of Aaron Chalfin, Benjamin Hansen, Emily Weisburst, and Morgan Williams Jr., where they estimate race-specific effects of police force size in 242 large US cities from 1981 to 2018. They use two strategies to get around the basic problem that cities often change police staffing in response to a crime, making a simple comparison of officer counts and homicide rates biased. Instead, the authors compare two independently reported officer counts, one from FBI law-enforcement employment data and one from the Census Annual Survey of Governments. This was done to correct for any measurement error in police staffing counts. Second, they used federal COPS (Community Oriented Policing Services) hiring grants as a source of outside variability, as those grants give cities money to hire additional officers.

The study found that each additional officer was estimated to stop 0.06-0.1 homicides, corresponding to roughly one life per 10-17 officers hired. In per-capita terms, these effects were roughly twice as large for Black victims as it was for Whites. This is because homicide is heavily spatially clustered, with Black Americans overrepresented among homicide victims and perpetrators in many large cities due to homicide being a local and intraracial phenomenon. This is what one expects in a heavily residentially segregated country where neighborhood conflict and social networks aren’t randomly distributed variables in the populous. The 1980-2008 homicide data from the Bureau of Justics confirms this, with 84% of White victims were killed by White offenders and 93% of Black victims were killed by Black offenders. The AER study also estimate that larger police forces tend to make more low-level “quality-of-life” arrests at about 7.1 per marginal officer in the measurement error model and 22 in the COPS model, all while simultaneously reducing arrests for more serious crimes by 1 to 1.6 per officer, again with larger impacts on Black suspects per-capita. For things like liquor-law and drug-possession, per-capita increases are about 2.5 to 3 times larger for the Black population. That tradeoff is uncomfortable. The same staffing margin can be associated with fewer homicides but also fewer serious arrests and more low-level coercive contact. This is where the clean anti-policing version breaks down. A public-health account that treats policing only as violence or social control has to explain why some staffing margins appear to reduce homicide, especially in the same communities most exposed to both violence and coercive policing.

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Estimated homicide reduction and added low-level arrests at the police-staffing margin. Source: Chalfin et al., American Economic Review: Insights, 2022.

These estimates are narrower than people might be tempted to take them as though. The paper doesn’t make the claim that police overall save lives or that any specific tactic can claim credit for the homicide reduction. The first strategy is excellent for dealing with bad officer-count data, but it doesn’t consider why those counts differ from place to place. The grants-based method isn’t totally random either though. Departments had to apply and grants were awarded through a federal program that may have had its own biasing priorities. The authors try to handle that by controlling for grant applications, non-hiring grants, city-level traits, budgets, and demographics to make the estimate more credible than some crude comparison of cities with more vs less officers. The paper also doesn’t quite find evidence that bigger forces improve the homicide clearance rate, so those estimates of lives-saved shouldn’t be immediately put on detectives, patrol, deterrence, or any singular mechanism with many things likely playing a part.

The fact that homicide prevention is inherently counterfactual makes this point difficult for some to see as equally important to the visible, frequent low-level arrests that sometimes end up in injury or death. The authors note that when one applies the estimate from Emily Weisburst’s AER paper of roughly 2.5% of arrests involving non-shooting physical force from the police, the police expansion needed to stop just one homicide would also be expected to lead to 7-10 use-of-force incidents with 4-5 of those involving a Black suspect. While a rough translation, it makes the tradeoff more tangible. The question becomes whether cities can preserve, improve, or replace serious-violence prevention and simultaneously reduce the low-level enforcement and coercive contact that come with it. These aren’t the same public-health interventions.

Contact isn’t Nothing

Before getting to fatal use-of-force, we should cover general police contact as a broader exposure. It’s not rare to be stopped, searched, ticketed, arrested, or threatened with 49.2 million US residents aged 16 and up having had contact with police in the prior 12 months according to the BJS. That’s about 19% of the population. Roughly 8% had police-initiated contact, 11% was resident-initiated, and 3% were related to a traffic accident. 2.1% of residents reported that their most recent contact involved the threat or use of nonfatal force in that same 2022 dataset. Among tens of millions of contacts, that small percentage becomes a nontrivial sum of people.

The pro-policing accounting of these often ends up selective, counting the prevented homicides while treating the rest of the causal chain of events as unimportant. But coercive contact can lead to lost work, jail bookings, and familial disruption. For those outside of the system, it’s a constant reminder that every day could be interrupted in the blink of an eye. And while the contact literature isn’t perfect, it’s strong enough to firmly reject the idea that contact is a non-event. In a 2014 study of over 1200 surveyed young men from New York, 85% reported at least one police stop in their live with 46% reporting being stopped the year of the survey. The distribution of contacts was skewed in the expected way, with more than 5% reporting over 25 lifetime stops and 1% reporting more than 100. Those reporting more lifetime stops were also reporting higher levels of trauma and anxiety. And while cross-sectional and not a causally informed study design that can determine direction of effect, the pattern here still matters. How often police stop someone likely matters, as does how the stop is conducted.

Traffic stops make a similar point. In an analysis of nearly 100 million traffic stops by 21 different state patrol agencies and 35 municipal police departments across nearly a decade, Pierson and colleagues found evidence of racial disparity at the stop and search stages of traffic stops. Their veil-of-darkness analysis found that Black drivers became a smaller percentage of drivers stopped after sunset, when it’s more difficult to see who one is pulling over, which is indicative of discrimination in stop decisions. In the subset of agencies where data include enough search and contraband data, Black and Hispanic drivers were searched about twice as often as white drivers, with state patrol data suggesting search rates of 4.3%, 4.1%, and 1.9% for Black, Hispanic, and White drivers, respectively. Municipal data had those rates at 9.5%, 7.2%, and 3.9%. The authors also did a “threshold test” which indicated that Black and Hispanic drivers were searched on thinner evidentiary lines than white drivers were.

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Veil-of-darkness odds ratios and search-rate differences from Pierson et al. Source: Nature Human Behaviour, 2020.

Death by Cop

The team of Frank Edwards, Hedwig Lee, and Michael Esposito published their estimates of lifetime and age-specific risk of being killed by police use-of-force. Some of the numbers traveled well due to their stark implications. Black men had about a 1 in 1,000 lifetime risk at current risk levels. That lifetime risk was roughly 1 in 2,000 for all men and 1 in 33,000 for women. Annual risk was much smaller, with men ages 25-29 having an estimated use-of-force mortality rate of 1.8 per 100,000. Black men in the same age range had a higher annual risk estimate of 2.8-4.1 per 100,000. The paper also estimated the share of all deaths in a group that involved use of force. That statistic can sound larger than it is when not explained carefully. Among Black men ages 20-24, use-of-force accounted for 1.6% of deaths- far from a trivial amount.

That last statistic is proportionate mortality, not annual risk, which is why it can sound a bit strange next to those per-100k estimates. It says that in an age group where death is relatively uncommon on the whole, police use-of-force is problem enough to take up a slice of the deaths. Another problem is that even the deaths aren’t always counted well. A study published in The Lancet estimated some 30,800 deaths due to police violence in the US between 1980-2018. That was over 17,000 more than the National Vital Statistics System had recorded in that same timeframe, meaning some 55.5% of deaths attributable to police violence were not recorded as such. Measurement problems like that are antithetical to solving the problem of police violence, as it obscures the true numbers. This is where the clean pro-policing version breaks down. A public-health account that counts only prevented homicides while treating stops, searches, force, jail exposure, and miscounted deaths as background noise is not doing accounting. It is doing advocacy.

The Average is the Error

This piece could easily go on to be some 10,000 words if I decided to touch everything relevant to what I see as the epidemiology of policing. How policing relates to homelessness, addiction, psychiatric crisis response, traffic injury, etc. could all be their own essays (and some might be if some readers show interest). But that’s part of the problem. When someone complains about policing in generalities or vagueries it’s difficult to know which aspect they’re referring to specifically. The same goes for generic ‘Back the Blue’ praise. The word policing covers so many different exposures today that the loudest public arguments end up turning a bundle of vastly different exposures into some singular, morally linked variable.

I find the more useful question to be much more narrow: which functions, when aimed at which populations, through what specific mechanisms, and with what outcome being counted? That is the epidemiological reality of looking at policing as it currently exists. The vastly different contexts that make up police contact are shaped by their histories with the area, its politics, local levels of violence, prior neglect, and simple bureaucratic convenience. The error is averaging things that can’t be averaged.

The loudest public debates over ‘policing’ treat the position like a monolith, with homicide investigation, traffic enforcement, crisis response, hot-spot patrol, stop-and-frisk, and jail booking all being looked at as one ‘exposure’ in epidemiological terms. That couldn’t be further from the truth. Some police activities plausibly prevent death while others produce it, injury, fear, and distrust from the community they’re supposed to be policing. The task of public health individuals examining the impacts on society is to stop treating these as effects that can be averaged into one metric and acknowledging and embracing the heterogeneity of exposures.

One caveat before getting into this piece: policing in its various forms is something that is unusually hard to measure, and the data-oriented readers out there have good reason to distrust some of the official record regarding police violence specifically. Official use-of-force and death records are often incomplete, with some of the best mortality data coming from journalistic or open-source databases like The Washington Post’s Fatal Force archive data from 2015-2024, Fatal Encounters, and Mapping Police Violence. The evidence is still usually messier than one would hope for when looking to see how different aspects of policing act as a public health exposure. This is my best attempt to square that messy evidence with the epidemiological question I’ve had for a while now: what functions of the police protect health and lives, and which cause damage while purporting to help?

https://preview.redd.it/t01kn49wv0ah1.png?width=1024&format=png&auto=webp&s=e7833d16c27064178509aa75a22a996cdcc8dbd3

Asking the Wrong Question

Like I said earlier, my prior here is that the loudest public conversations around policing have become almost useless. One side often talks as if the police are uniformly near flawless or at least doing such a good job that any criticism hits a brick wall. The other talks as if the police are so ineffective, violent, and rotten-to-the-core that reducing their funding and function becomes their obvious public health answer. I find it hard to trust either of those overly clean narratives because I’ve found truth on contentious topics often lives in the gray middle that people aiming for clicks typically avoid. The mistake I think is being made is treating policing as a singular intervention and then asking if its good or bad. That’s the wrong question because policing isn’t a singular exposure that can be generalized in that way. The same word covers violence prevention/responses, traffic enforcement, street level stops, homicide detectives, and crisis response. All different interventions that have vastly different mechanisms, target populations, counterfactuals, and health effects. Those health effects depend on which function we’re talking about.

How Police Became the Overflow System

That variability is also present in the history of policing in the United States as it lacks a singular origin story and is more one of an accumulation of new roles. In 19^(th) century cities in the North, full time police departments took on the roles of earlier watch systems and local volunteer services. The growth of large, commercial cities meant growth of the police departments as well as they tried to protect property, manage the newly crowded streets, and control conflicts that came with multi-origin immigration and industrial labor said immigrants often ended up working in. When it comes to the South, you can’t do an honest history of policing that skips over slave patrols and the armed patrol systems used to regulate the movement of slaves and protect the racial status quo.

I’ve seen the claim that the modern police department is just an evolution of those slave patrols but that’s too clean of a narrative of an institution with such variable history. The more narrow and stronger point to make is that American policing was multifaceted from the beginning as it covered ordinary public order and emergency response as well as property protection and control over who could move freely and where that freedom stopped. The same set of powers can be seen as protective or coercive depending on one’s standing. The 1988 National Institute of Justice essay by George Kelling and Mark Moore divides policing into three eras: the political era, the reform era, and an (at the time) emerging community problem-solving era.

The political era ranged roughly from the 1840s to the early 20^(th) century when police departments were most closely tied to their local political machines and the demands of specific neighborhoods. Police enforced the law while also involved in informal forms of urban management. They turned into the municipal instrument the area could call on to handle whatever was wanted or needed of them. Then came the reform era, which tried to solve one problem through the creation of another. Reformers wanted a bit of distance from the partisan politics of the time as well as a clearer, more professional chain of command with civil-service rules, radio communications, patrol cars, and bureaucratic standards to make things more modern and easier to administer. That era also narrowed the official story of what police before, with the official, respectable answer of the time being ‘crime control.’

That’s difficult to make a reality when the city itself doesn’t simultaneously reduce the problems it has need for responses to. Calls still came in from all corners of the urban centers including problems that were clearly terrifying or urgent, but not always criminal. Patrol cars with radios could hear about and then reach those calls quicker than other public agencies at the time which made them especially useful in emergencies. It also had the effect of deepening the habit of routing those sometimes difficult to deal with social problems through the one agency that was always readily dispatchable. Reform made the police departments more professional but that doesn’t make the problems they deal with more coherent for them to be dealing with.

That model had come under pressure by the 60s and 70s, as rising crime had made the reactive model look inadequate to respond to new challenges. Civil unrest and police violence had questioned the legitimacy and rendered that reputation fragile. A 2018 National Academies’ report on what became known as proactive policing describes it as a strategic approach that grew out of that crisis of confidence and from the crime-control innovations that arose in the 80s and 90s. The historical epidemiology is clear here with that preventive approach having some clearly defined strategies and theories of how police might prevent harm. A hot-spots strategy focuses energy where crime is most heavily clustered. Problem-oriented policing asks what specifically is producing a recurring problem and tries to change those specific conditions. Focused deterrence methods aim at people or groups who are at an unusually high risk of violence. Community-oriented and procedural-justice strategies focus most heavily on the legitimacy issue and cooperation of society and lawmakers with policing to better outcomes for all involved.

Some older strategies like order-maintenance and broken-windows followed a related pattern where, theoretically, they treated disorder as the signal informing them that the informal social controls are breaking down. Practically, they often meant more low-level enforcement in places with already high levels of poverty, violence, and police attention. Historically, that explains why the public debate can contain some truths that seem to contradict each other. Proactive policing can include both a focused violence-prevention strategy and increased street stops, even though those are different exposures for the residents.

By the time we get to the present day, police departments are doing so many jobs it becomes difficult to analyze as a public health exposure. The average day for a police officer where I grew up could consist of showing up to my house when one of my seizures lasted too long, a homicide call, and everything in between. Cities send the cops when someone’s been shot or just when someone is sleeping outside where they “shouldn’t be,” or when a family can’t manage a psychiatric crisis. That’s the historical reason why the evidence points in different directions. Modern policing is a heavily layered institution, with layers added in response to different political problems, gaps in service, and theories of the social order. It’s difficult to imagine them having all of the roles they have outside of blanket necessity or lack of other options.

Homicide Prevention

Homicide prevention is a public health good, as homicides contribute to premature mortality in the US compared to other nations, especially since the majority of homicide victims are young. There’s also the grief, trauma, retaliation, and sometimes reorganization of one’s daily life around possible dangers. The cleanest source on the topic I could find is a 2022 paper in AER paper called Police Force Size and Civilian Race by the criminology/economics/public affairs team of Aaron Chalfin, Benjamin Hansen, Emily Weisburst, and Morgan Williams Jr., where they estimate race-specific effects of police force size in 242 large US cities from 1981 to 2018. They use two strategies to get around the basic problem that cities often change police staffing in response to a crime, making a simple comparison of officer counts and homicide rates biased. Instead, the authors compare two independently reported officer counts, one from FBI law-enforcement employment data and one from the Census Annual Survey of Governments. This was done to correct for any measurement error in police staffing counts. Second, they used federal COPS (Community Oriented Policing Services) hiring grants as a source of outside variability, as those grants give cities money to hire additional officers.

The study found that each additional officer was estimated to stop 0.06-0.1 homicides, corresponding to roughly one life per 10-17 officers hired. In per-capita terms, these effects were roughly twice as large for Black victims as it was for Whites. This is because homicide is heavily spatially clustered, with Black Americans overrepresented among homicide victims and perpetrators in many large cities due to homicide being a local and intraracial phenomenon. This is what one expects in a heavily residentially segregated country where neighborhood conflict and social networks aren’t randomly distributed variables in the populous. The 1980-2008 homicide data from the Bureau of Justics confirms this, with 84% of White victims were killed by White offenders and 93% of Black victims were killed by Black offenders. The AER study also estimate that larger police forces tend to make more low-level “quality-of-life” arrests at about 7.1 per marginal officer in the measurement error model and 22 in the COPS model, all while simultaneously reducing arrests for more serious crimes by 1 to 1.6 per officer, again with larger impacts on Black suspects per-capita. For things like liquor-law and drug-possession, per-capita increases are about 2.5 to 3 times larger for the Black population. That tradeoff is uncomfortable. The same staffing margin can be associated with fewer homicides but also fewer serious arrests and more low-level coercive contact. This is where the clean anti-policing version breaks down. A public-health account that treats policing only as violence or social control has to explain why some staffing margins appear to reduce homicide, especially in the same communities most exposed to both violence and coercive policing.

https://preview.redd.it/al7dp3xxv0ah1.png?width=936&format=png&auto=webp&s=af97838f543e627ca0d7b2dcd9a88ea5450bf85a

Estimated homicide reduction and added low-level arrests at the police-staffing margin. Source: Chalfin et al., American Economic Review: Insights, 2022.

These estimates are narrower than people might be tempted to take them as though. The paper doesn’t make the claim that police overall save lives or that any specific tactic can claim credit for the homicide reduction. The first strategy is excellent for dealing with bad officer-count data, but it doesn’t consider why those counts differ from place to place. The grants-based method isn’t totally random either though. Departments had to apply and grants were awarded through a federal program that may have had its own biasing priorities. The authors try to handle that by controlling for grant applications, non-hiring grants, city-level traits, budgets, and demographics to make the estimate more credible than some crude comparison of cities with more vs less officers. The paper also doesn’t quite find evidence that bigger forces improve the homicide clearance rate, so those estimates of lives-saved shouldn’t be immediately put on detectives, patrol, deterrence, or any singular mechanism with many things likely playing a part.

The fact that homicide prevention is inherently counterfactual makes this point difficult for some to see as equally important to the visible, frequent low-level arrests that sometimes end up in injury or death. The authors note that when one applies the estimate from Emily Weisburst’s AER paper of roughly 2.5% of arrests involving non-shooting physical force from the police, the police expansion needed to stop just one homicide would also be expected to lead to 7-10 use-of-force incidents with 4-5 of those involving a Black suspect. While a rough translation, it makes the tradeoff more tangible. The question becomes whether cities can preserve, improve, or replace serious-violence prevention and simultaneously reduce the low-level enforcement and coercive contact that come with it. These aren’t the same public-health interventions.

Contact isn’t Nothing

Before getting to fatal use-of-force, we should cover general police contact as a broader exposure. It’s not rare to be stopped, searched, ticketed, arrested, or threatened with 49.2 million US residents aged 16 and up having had contact with police in the prior 12 months according to the BJS. That’s about 19% of the population. Roughly 8% had police-initiated contact, 11% was resident-initiated, and 3% were related to a traffic accident. 2.1% of residents reported that their most recent contact involved the threat or use of nonfatal force in that same 2022 dataset. Among tens of millions of contacts, that small percentage becomes a nontrivial sum of people.

The pro-policing accounting of these often ends up selective, counting the prevented homicides while treating the rest of the causal chain of events as unimportant. But coercive contact can lead to lost work, jail bookings, and familial disruption. For those outside of the system, it’s a constant reminder that every day could be interrupted in the blink of an eye. And while the contact literature isn’t perfect, it’s strong enough to firmly reject the idea that contact is a non-event. In a 2014 study of over 1200 surveyed young men from New York, 85% reported at least one police stop in their live with 46% reporting being stopped the year of the survey. The distribution of contacts was skewed in the expected way, with more than 5% reporting over 25 lifetime stops and 1% reporting more than 100. Those reporting more lifetime stops were also reporting higher levels of trauma and anxiety. And while cross-sectional and not a causally informed study design that can determine direction of effect, the pattern here still matters. How often police stop someone likely matters, as does how the stop is conducted.

Traffic stops make a similar point. In an analysis of nearly 100 million traffic stops by 21 different state patrol agencies and 35 municipal police departments across nearly a decade, Pierson and colleagues found evidence of racial disparity at the stop and search stages of traffic stops. Their veil-of-darkness analysis found that Black drivers became a smaller percentage of drivers stopped after sunset, when it’s more difficult to see who one is pulling over, which is indicative of discrimination in stop decisions. In the subset of agencies where data include enough search and contraband data, Black and Hispanic drivers were searched about twice as often as white drivers, with state patrol data suggesting search rates of 4.3%, 4.1%, and 1.9% for Black, Hispanic, and White drivers, respectively. Municipal data had those rates at 9.5%, 7.2%, and 3.9%. The authors also did a “threshold test” which indicated that Black and Hispanic drivers were searched on thinner evidentiary lines than white drivers were.

https://preview.redd.it/h7xh5k3zv0ah1.png?width=936&format=png&auto=webp&s=565127bdf20e11222265551fbd213558036d8b20

Veil-of-darkness odds ratios and search-rate differences from Pierson et al. Source: Nature Human Behaviour, 2020.

Death by Cop

The team of Frank Edwards, Hedwig Lee, and Michael Esposito published their estimates of lifetime and age-specific risk of being killed by police use-of-force. Some of the numbers traveled well due to their stark implications. Black men had about a 1 in 1,000 lifetime risk at current risk levels. That lifetime risk was roughly 1 in 2,000 for all men and 1 in 33,000 for women. Annual risk was much smaller, with men ages 25-29 having an estimated use-of-force mortality rate of 1.8 per 100,000. Black men in the same age range had a higher annual risk estimate of 2.8-4.1 per 100,000. The paper also estimated the share of all deaths in a group that involved use of force. That statistic can sound larger than it is when not explained carefully. Among Black men ages 20-24, use-of-force accounted for 1.6% of deaths- far from a trivial amount.

That last statistic is proportionate mortality, not annual risk, which is why it can sound a bit strange next to those per-100k estimates. It says that in an age group where death is relatively uncommon on the whole, police use-of-force is problem enough to take up a slice of the deaths. Another problem is that even the deaths aren’t always counted well. A study published in The Lancet estimated some 30,800 deaths due to police violence in the US between 1980-2018. That was over 17,000 more than the National Vital Statistics System had recorded in that same timeframe, meaning some 55.5% of deaths attributable to police violence were not recorded as such. Measurement problems like that are antithetical to solving the problem of police violence, as it obscures the true numbers. This is where the clean pro-policing version breaks down. A public-health account that counts only prevented homicides while treating stops, searches, force, jail exposure, and miscounted deaths as background noise is not doing accounting. It is doing advocacy.

The Average is the Error

This piece could easily go on to be some 10,000 words if I decided to touch everything relevant to what I see as the epidemiology of policing. How policing relates to homelessness, addiction, psychiatric crisis response, traffic injury, etc. could all be their own essays (and some might be if some readers show interest). But that’s part of the problem. When someone complains about policing in generalities or vagueries it’s difficult to know which aspect they’re referring to specifically. The same goes for generic ‘Back the Blue’ praise. The word policing covers so many different exposures today that the loudest public arguments end up turning a bundle of vastly different exposures into some singular, morally linked variable.

I find the more useful question to be much more narrow: which functions, when aimed at which populations, through what specific mechanisms, and with what outcome being counted? That is the epidemiological reality of looking at policing as it currently exists. The vastly different contexts that make up police contact are shaped by their histories with the area, its politics, local levels of violence, prior neglect, and simple bureaucratic convenience. The error is averaging things that can’t be averaged.

The work of an occupational epidemiologist starts with the boring question of “what do you do all day?” Your doctor asking about what you do, who you do it for, how long you do it, what materials you work with, what exposures you’re under, whether you come home covered in something dusty, or whether anyone else doing the same job has the same problem can sound like irrelevant questions when you’re there for a specific ailment.

The biographical fact that is one’s occupation can also contain relevant details regarding why someone has a specific disease or disorder. Relevant details can be exposures to dust, fumes, metals, fibers, solvents, heat, noise, poor posture, repetitive movement, nigh-shift work, or anything else with a negative impact on the body. A job title alone is also rarely enough due to the variability within jobs. A person who lists their occupation as a painter could be rolling latex paint onto brand new drywall, or they could be sanding old lead paint in a closed room. “Stone fabricator” might mean wet-cutting under decent personal protection protocols, or dry cutting in a small, poorly ventilated shop heavy with dust in the air. A good occupational history needs to ask what exposures came with the job.

Ramazzini’s Question

https://preview.redd.it/s10auico3u8h1.jpg?width=960&format=pjpg&auto=webp&s=70944c294cef9df16b794c4722d481beefd1be31

There’s a reason history has been kind to Bernardino Ramazzini. When he published De Morbis Artificum Diatriba (Diseases of Workers) in 1700, and the update in 1713, he was working without germ theory, any kind of disease registry, biomarkers, or the language of modern-day cohort studies. He had a collection of trades, patients, repeated observations, and a sneaking suspicion that the cause of some illnesses were on-the-job exposures. Asking patients about what they do for a living feels so obvious in the modern medical office that it almost sounds like it’s asked as a formality. Back then, the question was nowhere near obvious enough to have been routinely asked. While his work was foundational, Ramazzini was not the first to notice that work had been damaging bodies.

The oldest written implications of the harms of work on the body come from the Egyptian text the Edwin Smith Surgical Papyrus from roughly 1700 BC which is thought to detail the neurosurgical and orthopedic diseases resulting from construction of the pyramids. The intellectual trail then gets traced through the likes of Hippocrates, Lucretius, Pliny the Elder, Galen, and Middle Eastern scholar Abu Bakr, Muhammad ibn Zakariya al-Razi, all of whom wrote on the impacts of occupation on health in one way or another. It was never difficult to notice the dangers that came with work, especially when some jobs were so obviously brutal like mining or metallurgy. What Ramazzini really deserves his flowers for is bringing that observation into regular medical practice by asking what work they do, how it is done, and by considering if the disease itself could be because of the job.

Jobs As Exposure Systems

Job titles aren’t the best exposure measure to use since there can be variability in what individuals with the same job title do in terms of their tasks, tools used, materials exposed to, specific rooms they’re in, different shifts, and stupid little habits of the shop that can make all the difference. That hidden variation is one of the reasons occupational diseases can be difficult to see in real time. An industrial accident of sufficient size announces itself in a way that daily hazards don’t. Those can just become part of the day-to-day of the job where dust exposure is the norm or solvent exposure is brushed off as just a smell in the warehouse. Symptoms arrive years later most of the time, with the original exposure looking like irrelevant history until people ask the right question.

That gap is also key because the longer the space between exposure and a diagnosis, the easier it is for people to just say the disease is related to aging, weakness, bad luck, smoking, or some other combination of individual-level traits leaving job exposures off to the side, not taken into consideration. Occupational epidemiology steps in when too many individuals start looking the same and a pattern emerges. One worker developing a rare disorder is obviously a sad event but once ten who were assigned the same task end up with the same exact rare disease, it’s time for a deeper look at things.

That’s a hard kind of evidence to obtain though. Outside of specific industries and companies, workplaces aren’t treated like laboratories and exposures aren’t tracked with the rigor one would hope for. People can change jobs, sick individuals might leave, records are often missing, exposure measurements come too late, and we get healthy worker bias with the healthiest people often being the ones employed long enough to be counted in a table. But the work has to be done to reconstruct their tasks, estimate doses of exposures, compare workers in similar (and vastly different) jobs, check for dose-response, see if any known biological mechanisms make this make sense, see if the timing would fit that mechanism, and then the hardest part of all, quantifying the uncertainty and whether it is of an acceptable level to label this cause-and-effect while people are still showing up to the same job. The last part is hard on everyone involved. False alarms can cost money and resources while disrupting the workplace to redirect attention to the “problem.” Missed hazards, on the other hand, can maim and kill.

Seeing Patterns Before Knowing Mechanisms

https://preview.redd.it/ma13mjco3u8h1.jpg?width=960&format=pjpg&auto=webp&s=e50397eba6110fcb050c26e033bec464adf5a02a

Percival Pott’s chimney sweeps are well-known example that many reach for when looking for a clear example of occupational hazards. His Chirugical Observations from 1775 described a type of scrotum cancer common in chimney sweeps. Now, polycyclic aromatic hydrocarbons weren’t some known part of his world nor was any part of the modern theory of carcinogenesis. The mechanisms came to be known far later than the pattern did. This is still often the case because our biology is still being uncovered, now at faster rates than ever. Beyond the occupational epidemiology, Pott’s work also brought to light some of the horrors that came with the job. Chimney sweeps tended to be young boys as they were small enough to climb into the chimneys and do the job. That came with burns, bruises, chronic soot exposure, and sometimes suffocation.

Exposure Changing Personality

https://preview.redd.it/dr6q7lco3u8h1.jpg?width=500&format=pjpg&auto=webp&s=a2a7ab97facdbcc607a1fcfa051b9028b9c09c4b

Hat makers got turned into a bit of a joke since the late 1800s. The phrase “mad as a hatter” has become so well known that this story one that a lot of people know a bit about. Mercury exposure in the making of felt hats can and did produce neurological and psychiatric symptoms that would often be lumped in with character and morality. Richard Weeden’s 1989 paper Were the hatters of New Jersey ‘mad’? does some great work separating the real occupational mechanism of mercury exposure from some of the sloppier folklore that arose from Lewis Carroll’s Mad Hatter.  In a Victorian world where everything becomes heavily moralized, mercury exposure was a problem. Trembling workers were seen as unreliable while the anxieties it brought on made people think the hatters were strange. The symptoms were outwardly noticeable in everyday life, so the workers got stuck with the stigma.

Countertop Hazards

https://preview.redd.it/fsxyazco3u8h1.png?width=1431&format=png&auto=webp&s=7c3f6eb62e61ed4f2856a7e7b7e8f8e6e0fe99a9

Silica is one of the everyday materials we’re all exposed to that seems innocuous, but the work that can turn stone, sand, concrete, granite, minerals, or artificial stone into a dust fine enough to get deep into the lungs is far from it. NIOSH describes ‘respirable crystalline silica’ as tiny particles that end up airborne when people work with those materials in a way that agitates them enough for particles to form. Deep in the lungs they can cause silicosis, an irreversible, but totally preventable disease, as well as lung cancer and some other serious health issues. The commonly cited disaster here is the Hawk’s Nest of 1930, where workers were drilling a tunnel through Gauley Mountain in West Virginia. Workers were dry drilling through rock with high silica levels which released massive amounts of dust into a poorly ventilated area with little dust control or PPE. Workers, many of them Black migrant laborers, came out of the tunnel covered in a fine white dust. Many of the exposed got sick, left, or died without being counted, so the death toll is still a debated topic. We do know that of the 5,000 or so workers, some 2,900 worked in the tunnel and, of those, 764 died of silicosis. Today’s engineered-stone countertops come with some of the same risk for those working on them because before that glossy tabletop becomes part of someone’s home, it had to be cut, ground, and polished in a shop. A 2019 report described cases of severe silicosis in engineered-stone fabricators in California, Colorado, Texas, and Washington, noting that the silica content of engineered stone can be up to 90% compared to less than 45% in granite.

 Asking About the Work

In the post-Ramazzini world, occupational disease and asking about workplace exposure is obvious. The cough, tremor, rash, cancer, or breathing problem might have something to do with the different exposures that shaped that individual’s working life. The harder part is moving beyond the field filled out on a form and into the exposures the job came with. Exposure reconstruction forces the person to examine the task they performed, how they performed it, how often, and whether they were protected from exposure during their work. Those questions inherently can bring about recall bias, but they’re the best we have in retrospective studies without on-the-job measurement being taken. Treatment often arrives too late in these cases with the exposure often having had its chance to inflict its damage by then. This is especially true when novel diseases come with the exposure like silicosis or asbestosis. So, when a doctor asks, “what do you do all day?” it’s far from small talk (no patient-respecting doctor would go into small talk when they have 15 minutes on average per appointment). They’re seeing if any symptoms being discussed can be traced to the things you do almost every day.

The work of an occupational epidemiologist starts with the boring question of “what do you do all day?” Your doctor asking about what you do, who you do it for, how long you do it, what materials you work with, what exposures you’re under, whether you come home covered in something dusty, or whether anyone else doing the same job has the same problem can sound like irrelevant questions when you’re there for a specific ailment.

The biographical fact that is one’s occupation can also contain relevant details regarding why someone has a specific disease or disorder. Relevant details can be exposures to dust, fumes, metals, fibers, solvents, heat, noise, poor posture, repetitive movement, nigh-shift work, or anything else with a negative impact on the body. A job title alone is also rarely enough due to the variability within jobs. A person who lists their occupation as a painter could be rolling latex paint onto brand new drywall, or they could be sanding old lead paint in a closed room. “Stone fabricator” might mean wet-cutting under decent personal protection protocols, or dry cutting in a small, poorly ventilated shop heavy with dust in the air. A good occupational history needs to ask what exposures came with the job.

Ramazzini’s Question

https://preview.redd.it/21y24os84o8h1.jpg?width=960&format=pjpg&auto=webp&s=e7740443e784db574c2bfcb90c327a711722b3a2

There’s a reason history has been kind to Bernardino Ramazzini. When he published De Morbis Artificum Diatriba (Diseases of Workers) in 1700, and the update in 1713, he was working without germ theory, any kind of disease registry, biomarkers, or the language of modern-day cohort studies. He had a collection of trades, patients, repeated observations, and a sneaking suspicion that the cause of some illnesses were on-the-job exposures. Asking patients about what they do for a living feels so obvious in the modern medical office that it almost sounds like it’s asked as a formality. Back then, the question was nowhere near obvious enough to have been routinely asked. While his work was foundational, Ramazzini was not the first to notice that work had been damaging bodies.

The oldest written implications of the harms of work on the body come from the Egyptian text the Edwin Smith Surgical Papyrus from roughly 1700 BC which is thought to detail the neurosurgical and orthopedic diseases resulting from construction of the pyramids. The intellectual trail then gets traced through the likes of Hippocrates, Lucretius, Pliny the Elder, Galen, and Middle Eastern scholar Abu Bakr, Muhammad ibn Zakariya al-Razi, all of whom wrote on the impacts of occupation on health in one way or another. It was never difficult to notice the dangers that came with work, especially when some jobs were so obviously brutal like mining or metallurgy. What Ramazzini really deserves his flowers for is bringing that observation into regular medical practice by asking what work they do, how it is done, and by considering if the disease itself could be because of the job.

Jobs As Exposure Systems

Job titles aren’t the best exposure measure to use since there can be variability in what individuals with the same job title do in terms of their tasks, tools used, materials exposed to, specific rooms they’re in, different shifts, and stupid little habits of the shop that can make all the difference. That hidden variation is one of the reasons occupational diseases can be difficult to see in real time. An industrial accident of sufficient size announces itself in a way that daily hazards don’t. Those can just become part of the day-to-day of the job where dust exposure is the norm or solvent exposure is brushed off as just a smell in the warehouse. Symptoms arrive years later most of the time, with the original exposure looking like irrelevant history until people ask the right question.

That gap is also key because the longer the space between exposure and a diagnosis, the easier it is for people to just say the disease is related to aging, weakness, bad luck, smoking, or some other combination of individual-level traits leaving job exposures off to the side, not taken into consideration. Occupational epidemiology steps in when too many individuals start looking the same and a pattern emerges. One worker developing a rare disorder is obviously a sad event but once ten who were assigned the same task end up with the same exact rare disease, it’s time for a deeper look at things.

That’s a hard kind of evidence to obtain though. Outside of specific industries and companies, workplaces aren’t treated like laboratories and exposures aren’t tracked with the rigor one would hope for. People can change jobs, sick individuals might leave, records are often missing, exposure measurements come too late, and we get healthy worker bias with the healthiest people often being the ones employed long enough to be counted in a table. But the work has to be done to reconstruct their tasks, estimate doses of exposures, compare workers in similar (and vastly different) jobs, check for dose-response, see if any known biological mechanisms make this make sense, see if the timing would fit that mechanism, and then the hardest part of all, quantifying the uncertainty and whether it is of an acceptable level to label this cause-and-effect while people are still showing up to the same job. The last part is hard on everyone involved. False alarms can cost money and resources while disrupting the workplace to redirect attention to the “problem.” Missed hazards, on the other hand, can maim and kill.

Seeing Patterns Before Knowing Mechanisms

https://preview.redd.it/sfx6cfu84o8h1.jpg?width=960&format=pjpg&auto=webp&s=2d839a1a0df4ceba67a40f667411f1ed01554e74

Percival Pott’s chimney sweeps are well-known example that many reach for when looking for a clear example of occupational hazards. His Chirugical Observations from 1775 described a type of scrotum cancer common in chimney sweeps. Now, polycyclic aromatic hydrocarbons weren’t some known part of his world nor was any part of the modern theory of carcinogenesis. The mechanisms came to be known far later than the pattern did. This is still often the case because our biology is still being uncovered, now at faster rates than ever. Beyond the occupational epidemiology, Pott’s work also brought to light some of the horrors that came with the job. Chimney sweeps tended to be young boys as they were small enough to climb into the chimneys and do the job. That came with burns, bruises, chronic soot exposure, and sometimes suffocation.

Exposure Changing Personality

https://preview.redd.it/p9806ps84o8h1.jpg?width=500&format=pjpg&auto=webp&s=7ea131800d3f40e161780b1cbedb10ebe2539ef7

Hat makers got turned into a bit of a joke since the late 1800s. The phrase “mad as a hatter” has become so well known that this story one that a lot of people know a bit about. Mercury exposure in the making of felt hats can and did produce neurological and psychiatric symptoms that would often be lumped in with character and morality. Richard Weeden’s 1989 paper Were the hatters of New Jersey ‘mad’? does some great work separating the real occupational mechanism of mercury exposure from some of the sloppier folklore that arose from Lewis Carroll’s Mad Hatter.  In a Victorian world where everything becomes heavily moralized, mercury exposure was a problem. Trembling workers were seen as unreliable while the anxieties it brought on made people think the hatters were strange. The symptoms were outwardly noticeable in everyday life, so the workers got stuck with the stigma.

Countertop Hazards

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Silica is one of the everyday materials we’re all exposed to that seems innocuous, but the work that can turn stone, sand, concrete, granite, minerals, or artificial stone into a dust fine enough to get deep into the lungs is far from it. NIOSH describes ‘respirable crystalline silica’ as tiny particles that end up airborne when people work with those materials in a way that agitates them enough for particles to form. Deep in the lungs they can cause silicosis, an irreversible, but totally preventable disease, as well as lung cancer and some other serious health issues. The commonly cited disaster here is the Hawk’s Nest of 1930, where workers were drilling a tunnel through Gauley Mountain in West Virginia. Workers were dry drilling through rock with high silica levels which released massive amounts of dust into a poorly ventilated area with little dust control or PPE. Workers, many of them Black migrant laborers, came out of the tunnel covered in a fine white dust. Many of the exposed got sick, left, or died without being counted, so the death toll is still a debated topic. We do know that of the 5,000 or so workers, some 2,900 worked in the tunnel and, of those, 764 died of silicosis. Today’s engineered-stone countertops come with some of the same risk for those working on them because before that glossy tabletop becomes part of someone’s home, it had to be cut, ground, and polished in a shop. A 2019 report described cases of severe silicosis in engineered-stone fabricators in California, Colorado, Texas, and Washington, noting that the silica content of engineered stone can be up to 90% compared to less than 45% in granite.

 Asking About the Work

In the post-Ramazzini world, occupational disease and asking about workplace exposure is obvious. The cough, tremor, rash, cancer, or breathing problem might have something to do with the different exposures that shaped that individual’s working life. The harder part is moving beyond the field filled out on a form and into the exposures the job came with. Exposure reconstruction forces the person to examine the task they performed, how they performed it, how often, and whether they were protected from exposure during their work. Those questions inherently can bring about recall bias, but they’re the best we have in retrospective studies without on-the-job measurement being taken. Treatment often arrives too late in these cases with the exposure often having had its chance to inflict its damage by then. This is especially true when novel diseases come with the exposure like silicosis or asbestosis. So, when a doctor asks, “what do you do all day?” it’s far from small talk (no patient-respecting doctor would go into small talk when they have 15 minutes on average per appointment). They’re seeing if any symptoms being discussed can be traced to the things you do almost every day.

The ongoing Ebola outbreak in Central Africa had me asking a question I hadn’t really considered beyond surface level curiosity. That question was “how in the hell do researchers get anything resembling accurate data in a war-zone?” How do they get an estimate of mortality when nobody is counting carefully?

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This is a major difference that exposes one of the hidden inequalities of the modern world, one in which the rich’s dead are mourned by families and then get processed by the institutions in charge of keeping count of lives, deaths, and their trends. These are registered, certified, coded, aggregated, analysed, compared, revised, and put out by the state. Compare that to the poor’s dead, who are often just reconstructed later by demographers and epidemiologists looking to make as strong of an inference as possible from very little professionally gathered data. Because of that, the death certificate is one of the most important, but least glamorous public health technologies to have been invented, despite its lack of any charismatic efforts like vaccination campaigns or vector control programs. 
As a population level field, public health relies heavily on bureaucracy to function at its highest level. In the case of building population and mortality tables, we rely on the birth having been recorded, the death having been recorded (and a cause being assigned), as well as place, date, sex, age, and identify all being attached. Populations have to be legible for us to make any inferences or calculations about them (thus us having next to no knowledge of the North Sentinelese). Infant mortality, life expectancy, cardiovascular death, maternal mortality, cancer survival, and excess mortality all rely on the unsexy but crucial premise that somebody has to know who died. That’s often left to civil registration and vital statistics (CRVS), the population level data that lets us ask and answer questions. The World Health Organization defines a well-functioning CRVS system as one that registers births and death certificates while compiling vital statistics information like cause-of-death information. CRVS turns those vital statistics into the legal and statistical facts that nations, states, counties, and cities rely on to support identification, inheritance, school enrollment, social protections, health planning, and more. They tell us who was born, who died, where, when, at what age, and if the systems are good enough, what the person died from. 
Some History of Population Level Statistics
John Graunt’s 17th century work on the London Bills of Mortality is one of the most discussed early efforts in the space of population health and statistics. He’s particularly remembered for being one of the first to look at the records of births and burials and see the hidden population level patterns inside of them. He noted the sex ratio at birth leaning slightly toward excess males, and theorized the surplus was a natural “insurance policy” due to boys and men facing higher mortality rates, that those living in the countryside tended to be healthier on average due to the hazards of city life, and constructed the first rudimentary mortality table, noting that out of 100 people born in London, only 64 made it to age 6, 25 to age 26, and just 1 in 100 surviving to 76. His records were crude and the causes of death would seem strange to a modern observer, but he had tabulated death and used it to make important comparisons which was lightyears beyond what was being done previously. 
William Farr of the 19th century British General Register Office furthered the development through the development of cause-of-death registration, occupational mortality comparisons, epidemic curves, and better life tables as part of the national administrative apparatus where causes could be classified, different places could be compared. Occupations, ages, seasons, neighborhoods, epidemics, and samples could all be turned into arguments in favor of improving public health. And while over time our systems had to become less biased, better categorized, and more statistically sound, the underlying shift toward quantifying population health was a massive boon for civilization. That kind of history also makes the inequalities of today easier to see, as countries with strong mortality stats are those that built, funded, repaired, and normalized the institutions responsible for making these vital events visible to the public. Legal obligations were created, physicians and coders were trained, and local events made their way into national level files and helped to make death certification so ordinary in the developed world that a family still in the earliest stages of grief have to go straight into administrative paperwork. 
These infrastructural changes result in a powerful system where once death is recorded, it can make accusations, or show that heat waves killed more than officials had admitted, or maternal mortality is on the rise/mend, or that opioid deaths are clustering among certain populations, or that homicide is falling, or that tuberculosis is back, or… you get the point, it can do a lot! 

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The gap in record keeping between the countries who have the best infrastructures and, for example, those in the throes of a civil war is massive. WHO estimates that something like 40% of the world’s deaths are not recorded with birth registration not doing much better with an estimated 36 million babies born each year not having a birth certificate. That can be mended later on through going to school, a clinic, getting employed, or a census taker coming by, but an unregistered death is something that can disappear from the administrative record and not end up recovered via census. The regional differences are severe, with 98% of deaths registered in the European Region, 91% in the Region of the Americas, 82% in the Western Pacific, 61% in South East Asia, 55% in the Eastern Mediterranean, and just 10% in the African Region, a number that honestly stopped me dead in my tracks. It’s a number that should be handled with caution though, as the Africa Region is not some monolithic thing. It’s got many countries, with vastly different cultures and populations, and lacks a single administrative system to link all of these together. The WHO also reports that only 8% of reported deaths in low-income countries have a documented cause. The result is that only about 25% of the world is regularly putting out population level health statistics of a quality that can be used to guide policy level decision making, with almost all of that coming from Europe, the Americas, and nations like Japan, South Korea, Australia, and New Zealand.  
Because of how much global health information is simply never collected, any global-health dashboard is telling white lies by looking cleaner than the data that went into its development. It all looks nice but may be built from unlike datasets. One number might be coming from a national civil registration system that has high levels of completeness, medically certified deaths, matching birth certificates, and decades of comparable coding. Another might be the result of a partial registration that researchers have attempted to adjust for undercounting, or it may be assembled from an amalgamation of data from household surveys, sample registration, verbal autopsy, hospital records, regional patterns, and statistical priors gathered from observations of similar groups. The WHO developed an entire scoring system (called Survey Count Optimize Review Enable or SCORE) to get around this systemic problem in how countries count, optimize, review, enable, and use health data and information. And even while the certainty of the evidence is lacking, these are often the best available estimates.
As a result, some of the more skeptically minded people who see those numbers might shout fraud but I’d argue they’re throwing the baby out with the bathwater. There are many cases in which an infant or child dies in a rural district without any medical certification confirming what had happened, but that death doesn’t all of the sudden become imaginary because we needed modeling to help place it correctly in mortality estimates. If a pandemic races through a country that doesn’t have timely mortality reporting, excess deaths still occur whether they were recorded or not. That’s why models are published alongside the uncertainty they inherently come with to show the range of plausible effects and to make clear how much of the data is observed, adjusted, inferred, or reconstructed based on prior estimates. 
Counting deaths sounds simple but it requires a state that can reach people and a population with reason to let themselves be reached by said state. It needs laws, registers, clinics, trained certifiers, roads, and some sort of paper or digital system to record everything. It needs to work within the existing infrastructure, levels of trust, monetary constraints, burial rules, and local customs. WHO’s CRVS strategic plan makes the point bluntly: health systems are close to births and deaths but registration still requires law, workflow, institutional roles, and sustained coordination between everyone involved. In war-torn regions or ones where the state is distant, predatory, underfunded, or fragmented you end up with death registration being nearly impossible in some cases. There may be no registrar nearby or the clinic doesn’t have an available physician to certify a cause of death. We end up with a statistical gap as a result of laws, geography, money, fear, trust, and a lack of administrative reach.
That’s also why registration isn’t something that can just be reduced to a phone app or some sort of donation-funded dashboard. Not to say things like mobile reporting or electronic medical records and automated coding can’t help, but without building up the institutional framework to measure what is needed to be measured, including the legal framework, trained individuals, ensuring families there is good reason to report, and a system to incorporate all of that, the mobile reporting or EMR would be next to useless. That conforms well to the UN Legal Identity Agenda since it keeps identity, civil registration, vital statistics, and state capacity all under one roof. 
As mentioned, the cause-of-death side of things is in even worse shape. Death certificates are statements that a life has ended and are meant to have an argument about why said life came to an end. That often requires a physician, medical record, diagnostic test, capacity to perform autopsy, and an understanding about underlying vs contributing causes. In many places that’s not available as deaths often occur outside of a facility, in a situation where a certifier never saw the patient, and relying on familial descriptions of symptoms in the days leading up to the death. The verbal autopsy at least gives us something even if it is ambiguous. Trained interviewers ask the relatives about symptoms before death and then physicians (or algorithms) give an idea of the probable cause of death if medical certification is absent or hasn’t been well established. The WHO describes the primary goal of verbal autopsy as describing community or population level causes of death where medical certification is still absent or hasn’t been established. It’s a great invention that is much better than no information at all, but comes with its own weak spots like when there is symptom overlap between multiple conditions. 
Each method used has its own failure modes. Surveys can miss households that fled the area, disbanded, or were never reachable in the first place. Censuses come too rarely for them to be useful in monitoring a pandemic, famine, disaster, or conflict in real time. Sample registration systems are able to generate nationally representative mortality data but require a sample that stays representative over time. Health care facilities miss the deaths that never made it to be cared for in the first place. Burial records are useful but still incomplete. And verbal autopsy has issues beyond what was mentioned earlier like recall bias. We interpret millions of deaths per year based on these kinds of fragments and it’s exactly why the phrase “the cause-of-death data are weak” exists in the first place in global health fields. 
The Modeling Part

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This also means countries with poor mortality data can understate a crisis without ever issuing a knowingly false statement (see the ongoing Ebola outbreak for evidence of that; it’s likely much larger than we know). Governments, maliciously or not, can also avoid being held accountable when deaths never become legible enough to direct policy. Journalists need to be careful when comparing countries in a table because some data may be mostly observed and the other reconstructed or purely simulated. It’s a bit of a comforting fiction that global health issues become visible when every country is listed in the mortality table, but those entries are often unequal in quality. Countries with more reliable registrars, more doctors, local officials, tailored laws, roads, and better health coding will always have more reliable entries than those lacking in any or all of those areas. 
The issues with modeling are why global and population health workers and researchers are calling for higher-capacity systems to be developed in areas that currently lack them. This would allow for more deaths to be observed vs estimated, more cause-of-death patterns to discern, better excess mortality calculations, and better societal outcomes. CRVS should always be brought up in the same conversation as building labs, hospitals, surveillance systems, improving supply chains, and building emergency stockpiles of medications and vaccines. Families also get to establish inheritance claims, pensions, and legal identities important for establishing certain freedoms when seeking asylum. 
CRVS is one way for a country to put the reality of the lives and deaths of their citizens out in the world. Better infrastructure means those become more honest and accurate. But until then, it’s not like the world is unknowable. Demographers, global/population health researchers, and epidemiologists are clever enough to use surveys, burial records, health facility records, sibling histories, verbal autopsies, and satellite covariates to build models that can help reconstruct a better picture of the world. They’d still like there to be fewer places where that modeling is needed in place of simple records saying someone was born, they later died, and a specific thing killed them. The goal for any developing country should be to be able to do that continuously, almost universally in their population, and with enough precision to make actions based on the numbers. 

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On June 3^(rd), 2026, the USDA confirmed that Cochliomyia hominivorax, indigenous New World screwworm (NWS) fly, was detected on American soil for the first time in 60 years in a three-week-old calf in Zavala County, Texas (roughly 90 miles southwest of San Antonio and about 50 miles north of the border with Mexico). The National Veterinary Services Laboratory in Ames, Iowa confirmed the positive after being sent samples from the calf taken from the umbilical area. This was followed by a second case in a one-month old calk found some 5.6 miles from the first case being confirmed two days later on the 5^(th.).

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I won’t say this is definitive proof that the New World screwworm has reestablished itself in Texas, although I see it as more likely than when I started writing this given the second case was found after just two days. Two nearby detections in very young calves with umbilical lesions mean the state and federal officials working on this now have to treat the area as one with a local reproductive focus until surveillance tells us otherwise. In line with this, the USDA and the Texas Animal Health Commission established a 20-kilometer infested zone with imposed movement controls on warm-blooded animals leaving the zone, increased trapping, instituting wildlife surveillance, and started new targeted sterile-fly releases (more on those later).

First, a small clarifying point: USDA declared the United States free of indigenous screwworms in 1966, but the border is not some impermeable force. That’s what the “first time in 60 years” refers to. The Southwestern United States had serious post-eradication incursions in the 1970s, and Florida had a contained outbreak in 2016-2017. So the June 2026 cases are not the first screwworms ever found on American soil since 1966. They are the first confirmed U.S. animal detections of what has been seen as a northward resurgence, and the first Texas detections in this new phase of the problem. Screwworm was never defeated completely, we had just pushed it south with labs, planes, quarantines, reporting by ranchers, wound treatment, fly factories, international agreements, and mountainous amounts of public health work.

What is New World Screwworm?

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Many people in the US may not have ever heard of NWS with it having been eradicated in 1966, but it is a type of fly whose larvae eat living flesh (compared to other blowfly species whose larvae feed on dead tissue). To complete their lifecycle, they have to parasitize the living tissue of an animal, requiring a wound of some sort on a warm-blooded animal such as a cow, deer, dog, horse, human, etc. The female flies are attracted by the odor put off from the wound/bodily opening and will then deposit some 200-300 eggs at the edge of the wound/mucous membrane/orifice such as the nose, mouth, ears, eyes, umbilical area of newborns, or genitalia. Something as small as a tick bite could attract the female. Then, some 12-24 hours later the eggs hatch into larvae that burrow, quite literally screwing their way into the living tissue, tearing the flesh with their sharp mouth hooks as they feed. Over about seven days they cycle through three larval stages, dropping to the ground, burrowing into the soil, and pupating. Adult flies emerge anywhere from seven to 50+ days later depending on things like temperature and humidity.

The biological aspect most important to their eradication though is the fact that the female flies only mate once in their lifetime, with the ability to lay some 3,000 eggs across multiple clutches during the 10-30 day life as an adult. Untreated, the infestation can kill a full-grown steer in as little as a week or two, with wounds expanding and deepening as the hundreds of larvae feed. This can lead to secondary bacterial infections and septic shock. When humans get infected, its called myiasis, though this is rare in the United States. It’s a pretty simple biological cycle in the end though. Female finds a wound, lays some eggs, those become larvae, and those deepen the wound. That attracts even more females and the cycle continues until treatment or death stops it in its tracks.

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Before the mid-twentieth century, screwworm was one of the American South and Southwest’s greatest agricultural pests, as the nuisance fly species was in effect a tax on animal births, a risk post-branding, castration, or dehorning, made barbed wire more of a liability, and turned ordinary scrapes into infestation risks. The USDA’s historical collections describe it as a parasite of warm-blooded animals and as obligate living flesh eaters. In the 1935 outbreak, an estimated 180,000 livestock were killed in Texas counties despite the constant work on the part of ranchers to treat wounds and segregate the infested from the healthy. The earliest efforts to combat screwworm were relatively simple, with ranchers being taught things like shifting calving, branding, castration, and dehorning away from fly season, treating fresh wounds immediately, isolating infested animals, the burning of carcasses, and attempting to get rid of the flies with things like pine tar oil, benzol, and later larvicides. These were taught in demonstrations and in state fair exhibits to get the word out.

Understanding the taxonomy was the first necessary discovery made. In 1933 Emory Cushing and Walter Patton showed that NWS was a different species from the other ordinary blowfly that ranchers knew. The second discovery was more practical when a method of breeding them with non-living tissue was discovered using a medium of ground meat, beef blood, water, and preservatives. This allowed for laboratory work to be done and led to the work of Edward Knipling who developed his theory of autocide: with the release of enough sterile males into the wild population, fertile females who mate with them would lay eggs that wouldn’t hatch. With each passing generation the reproductive rate would fall further and further and, with enough sterile pressure for long enough, completely crash. Knipling began looking for ways to create sterile, but otherwise healthy flies when Hermann Muller’s work on radiation in fruit flies suggested a route to him. Radiation would be tested and found to sterilize screwworms without ruining any ability to compete for mates and a new public health weapon was created.

The first tests were done at Sanibel Island off the western coast of Florida. In 1951 scientists started their program with sterilized males being dropped into the island. Wounded goats were placed around the island and researchers would track the infestation as fly traps helped to get an idea of the ratio of sterile to fertile flies. The population was pushed down enough to call the trial a success, but reinfestation kept the authors humble with the realization that screwworm could make its way back to where it once was even after an eradication event. Further proof came from Curacao when in 1953 veterinary officer B.A. Bitter wrote the USDA to ask advice on getting rid of livestock infestation. At 40 miles off the coast of Venezuela and with plenty of livestock, this was the first opportunity for a real-world test to see if his method would work. The USDA team started in 1954 with sterile flies being supplied from Orlando with round-the-clock operations producing millions of flies. Researchers worked to make the flies hardier, bigger, and more sexually competitive through the manipulation of their larval diets. From there the effort just became more industrial, working on infestations in Florida at the Sebring plant, facilities related to the screwworm effort popping up elsewhere in the Southeast and the Southwest, better rancher reporting and quarantining, and aerial releases finally leading to the 1966 declaration of the US being screwworm free.

Why We Were Still Left Vulnerable

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The 1970s made it clear that, despite our gains, we were still vulnerable to screwworm infestation with heavy screwworm activity in northern Mexico resulting in some of the worst US outbreaks since 1966’s eradication declaration. The year 1971 saw some 444 cases. Compare that to 1972 when there were over 125,000 cases across California, Arizona, New Mexico, Texas, Oklahoma, Arkansas, and northern Mexico, with 90k being in Texas alone and 30k in Mexico (likely an underestimate due to lesser testing capabilities compared to Texas at the time). That outbreak led to the 1972 agreement between the US and Mexico creating the Mexico-United States Screwworm Eradication Commission. As eradication moved south, they targeted the Isthmus of Tehuantepec in Mexico as a target to push beyond. Once that had been done, they moved their target to the Darien Gap between Panama and Colombia.

That much progress had required massive amounts of infrastructural investment and setup. It only worked because sterile flies were being produced in enormous numbers and were being released in the right places to be followed up with surveillance, reporting, quarantine, and further international cooperation. That would be tested in the 2016-2017 outbreak in the Florida Keys, largely among Key deer. While the origin couldn’t be definitively tracked down, it’s thought to have been a possible importation via cargo ship or accidental drift from the Caribbean or Central America. So, while the current outbreak is worrisome, it’s not unprecedented.

We had roughly two decades with the front line in eastern Panama, with the Panama-United States Commission for the Eradication and Prevention of Screwworm (COPEG) maintaining the biological barrier near the Darien Gap, consistently releasing sterile flies to prevent the fertile ones from moving north into Central America. The USDA’s own budget documents describe it as a 102-mile jungle barrier along the Panama-Colombia border and a s a hub for field operations and sterile insect techniques. While the system held together, it looked almost miraculous in its effectiveness. But that all came crashing down under a mix of factors including migration of people and cattle through the Darien Gap, COVID’s impact on everything that took joint efforts between the involved countries and the economy, and funding cuts. In 2021 there were 78 positive cases in the barrier zone, a bit higher than normal after some field activity was suspended during COVID.

The situation just deteriorated further from there. The CDC noted that in 2023 Panama and Costa Rica had identified an outbreak, with all of the other countries in Central America and Mexico soon following suit, accumulating over 170,000 animal and over 2,000 human cases since. The Darien Gap itself was also changing as the corridor, long seen as incredibly difficult to trek through, ended up with an estimated 520,000 people crossing in 2023 alone. This likely complicated surveillance, animal inspection, land use, field access, and possibly introduced unregulated animal movement including cattle. Once screwworm had made it past that barrier, the geography played into their favor as the continent widened from the incredibly narrow straight, allowing for flies to spread out (they can travel some 180 miles). By November 2024 Mexico had reported a case in Chiapas. The next year the USDA was closing and reopening imports of cattle, bison, and horses from Mexico. You already know what happened this week with the two cases in Texas.

The Stakes are High

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US beef markets were already strained before reports of NWS in Texas, with the national cattle herd having shrunk under multiple years of drought-driven liquidation, as well as the built-in lag that comes with breeding large animals which means a decision to expand the herd doesn’t impact the market until years later. The Dallas Fed reported in May of this year that beef prices had gone up by 57% since 2020, with another 3% rise just in the first quarter of 2026. So, screwworm is making itself known in an already brittle economic environment. The border closure to Mexican cattle removed a potential NWS crossover point, but it also removed some of the supply that normally comes to US feedlots. Authors from the Dallas Fed note damage could exceed $3 billion across the Southwest in an outbreak comparable to 1972, with that going up to $8 billion if it matched the size and timescale of the 1962-1980 episodes. Wildlife also produces its own risk for NWS to further spread. At least livestock can be inspected, treated, quarantined, and moved when needed. Good luck doing that to a population of white-tailed deer or feral pigs living out in the warm brush country this summer. Ramping up our sterile-fly capacity is going to be crucial. The COPEG facility in Panama produces about 100 million sterile flies per week and the USDA is planning a facility with similar output in Mexico. One effort in South Texas is expected to produce some 300 million files per week once complete at Moore Air Base.

I’m writing this the night of June 5^(th) and will keep updates at the top of this post and on the Notes section of Substack. I and many others are hoping this does not become the reestablishment of a screwworm population in the US, no matter how short lived that may be. Our system worked for as long as it was in place without interruptions and it will work again under similar conditions.

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On June 3^(rd), 2026, the USDA confirmed that Cochliomyia hominivorax, indigenous New World screwworm (NWS) fly, was detected on American soil for the first time in 60 years in a three-week-old calf in Zavala County, Texas (roughly 90 miles southwest of San Antonio and about 50 miles north of the border with Mexico). The National Veterinary Services Laboratory in Ames, Iowa confirmed the positive after being sent samples from the calf taken from the umbilical area. This was followed by a second case in a one-month old calk found some 5.6 miles from the first case being confirmed two days later on the 5^(th.).

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I won’t say this is definitive proof that the New World screwworm has reestablished itself in Texas, although I see it as more likely than when I started writing this given the second case was found after just two days. Two nearby detections in very young calves with umbilical lesions mean the state and federal officials working on this now have to treat the area as one with a local reproductive focus until surveillance tells us otherwise. In line with this, the USDA and the Texas Animal Health Commission established a 20-kilometer infested zone with imposed movement controls on warm-blooded animals leaving the zone, increased trapping, instituting wildlife surveillance, and started new targeted sterile-fly releases (more on those later).

First, a small clarifying point: USDA declared the United States free of indigenous screwworms in 1966, but the border is not some impermeable force. That’s what the “first time in 60 years” refers to. The Southwestern United States had serious post-eradication incursions in the 1970s, and Florida had a contained outbreak in 2016-2017. So the June 2026 cases are not the first screwworms ever found on American soil since 1966. They are the first confirmed U.S. animal detections of what has been seen as a northward resurgence, and the first Texas detections in this new phase of the problem. Screwworm was never defeated completely, we had just pushed it south with labs, planes, quarantines, reporting by ranchers, wound treatment, fly factories, international agreements, and mountainous amounts of public health work.

What is New World Screwworm?

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Many people in the US may not have ever heard of NWS with it having been eradicated in 1966, but it is a type of fly whose larvae eat living flesh (compared to other blowfly species whose larvae feed on dead tissue). To complete their lifecycle, they have to parasitize the living tissue of an animal, requiring a wound of some sort on a warm-blooded animal such as a cow, deer, dog, horse, human, etc. The female flies are attracted by the odor put off from the wound/bodily opening and will then deposit some 200-300 eggs at the edge of the wound/mucous membrane/orifice such as the nose, mouth, ears, eyes, umbilical area of newborns, or genitalia. Something as small as a tick bite could attract the female. Then, some 12-24 hours later the eggs hatch into larvae that burrow, quite literally screwing their way into the living tissue, tearing the flesh with their sharp mouth hooks as they feed. Over about seven days they cycle through three larval stages, dropping to the ground, burrowing into the soil, and pupating. Adult flies emerge anywhere from seven to 50+ days later depending on things like temperature and humidity.

The biological aspect most important to their eradication though is the fact that the female flies only mate once in their lifetime, with the ability to lay some 3,000 eggs across multiple clutches during the 10-30 day life as an adult. Untreated, the infestation can kill a full-grown steer in as little as a week or two, with wounds expanding and deepening as the hundreds of larvae feed. This can lead to secondary bacterial infections and septic shock. When humans get infected, its called myiasis, though this is rare in the United States. It’s a pretty simple biological cycle in the end though. Female finds a wound, lays some eggs, those become larvae, and those deepen the wound. That attracts even more females and the cycle continues until treatment or death stops it in its tracks.

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Before the mid-twentieth century, screwworm was one of the American South and Southwest’s greatest agricultural pests, as the nuisance fly species was in effect a tax on animal births, a risk post-branding, castration, or dehorning, made barbed wire more of a liability, and turned ordinary scrapes into infestation risks. The USDA’s historical collections describe it as a parasite of warm-blooded animals and as obligate living flesh eaters. In the 1935 outbreak, an estimated 180,000 livestock were killed in Texas counties despite the constant work on the part of ranchers to treat wounds and segregate the infested from the healthy. The earliest efforts to combat screwworm were relatively simple, with ranchers being taught things like shifting calving, branding, castration, and dehorning away from fly season, treating fresh wounds immediately, isolating infested animals, the burning of carcasses, and attempting to get rid of the flies with things like pine tar oil, benzol, and later larvicides. These were taught in demonstrations and in state fair exhibits to get the word out.

Understanding the taxonomy was the first necessary discovery made. In 1933 Emory Cushing and Walter Patton showed that NWS was a different species from the other ordinary blowfly that ranchers knew. The second discovery was more practical when a method of breeding them with non-living tissue was discovered using a medium of ground meat, beef blood, water, and preservatives. This allowed for laboratory work to be done and led to the work of Edward Knipling who developed his theory of autocide: with the release of enough sterile males into the wild population, fertile females who mate with them would lay eggs that wouldn’t hatch. With each passing generation the reproductive rate would fall further and further and, with enough sterile pressure for long enough, completely crash. Knipling began looking for ways to create sterile, but otherwise healthy flies when Hermann Muller’s work on radiation in fruit flies suggested a route to him. Radiation would be tested and found to sterilize screwworms without ruining any ability to compete for mates and a new public health weapon was created.

The first tests were done at Sanibel Island off the western coast of Florida. In 1951 scientists started their program with sterilized males being dropped into the island. Wounded goats were placed around the island and researchers would track the infestation as fly traps helped to get an idea of the ratio of sterile to fertile flies. The population was pushed down enough to call the trial a success, but reinfestation kept the authors humble with the realization that screwworm could make its way back to where it once was even after an eradication event. Further proof came from Curacao when in 1953 veterinary officer B.A. Bitter wrote the USDA to ask advice on getting rid of livestock infestation. At 40 miles off the coast of Venezuela and with plenty of livestock, this was the first opportunity for a real-world test to see if his method would work. The USDA team started in 1954 with sterile flies being supplied from Orlando with round-the-clock operations producing millions of flies. Researchers worked to make the flies hardier, bigger, and more sexually competitive through the manipulation of their larval diets. From there the effort just became more industrial, working on infestations in Florida at the Sebring plant, facilities related to the screwworm effort popping up elsewhere in the Southeast and the Southwest, better rancher reporting and quarantining, and aerial releases finally leading to the 1966 declaration of the US being screwworm free.

Why We Were Still Left Vulnerable

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The 1970s made it clear that, despite our gains, we were still vulnerable to screwworm infestation with heavy screwworm activity in northern Mexico resulting in some of the worst US outbreaks since 1966’s eradication declaration. The year 1971 saw some 444 cases. Compare that to 1972 when there were over 125,000 cases across California, Arizona, New Mexico, Texas, Oklahoma, Arkansas, and northern Mexico, with 90k being in Texas alone and 30k in Mexico (likely an underestimate due to lesser testing capabilities compared to Texas at the time). That outbreak led to the 1972 agreement between the US and Mexico creating the Mexico-United States Screwworm Eradication Commission. As eradication moved south, they targeted the Isthmus of Tehuantepec in Mexico as a target to push beyond. Once that had been done, they moved their target to the Darien Gap between Panama and Colombia.

That much progress had required massive amounts of infrastructural investment and setup. It only worked because sterile flies were being produced in enormous numbers and were being released in the right places to be followed up with surveillance, reporting, quarantine, and further international cooperation. That would be tested in the 2016-2017 outbreak in the Florida Keys, largely among Key deer. While the origin couldn’t be definitively tracked down, it’s thought to have been a possible importation via cargo ship or accidental drift from the Caribbean or Central America. So, while the current outbreak is worrisome, it’s not unprecedented.

We had roughly two decades with the front line in eastern Panama, with the Panama-United States Commission for the Eradication and Prevention of Screwworm (COPEG) maintaining the biological barrier near the Darien Gap, consistently releasing sterile flies to prevent the fertile ones from moving north into Central America. The USDA’s own budget documents describe it as a 102-mile jungle barrier along the Panama-Colombia border and a s a hub for field operations and sterile insect techniques. While the system held together, it looked almost miraculous in its effectiveness. But that all came crashing down under a mix of factors including migration of people and cattle through the Darien Gap, COVID’s impact on everything that took joint efforts between the involved countries and the economy, and funding cuts. In 2021 there were 78 positive cases in the barrier zone, a bit higher than normal after some field activity was suspended during COVID.

The situation just deteriorated further from there. The CDC noted that in 2023 Panama and Costa Rica had identified an outbreak, with all of the other countries in Central America and Mexico soon following suit, accumulating over 170,000 animal and over 2,000 human cases since. The Darien Gap itself was also changing as the corridor, long seen as incredibly difficult to trek through, ended up with an estimated 520,000 people crossing in 2023 alone. This likely complicated surveillance, animal inspection, land use, field access, and possibly introduced unregulated animal movement including cattle. Once screwworm had made it past that barrier, the geography played into their favor as the continent widened from the incredibly narrow straight, allowing for flies to spread out (they can travel some 180 miles). By November 2024 Mexico had reported a case in Chiapas. The next year the USDA was closing and reopening imports of cattle, bison, and horses from Mexico. You already know what happened this week with the two cases in Texas.

The Stakes are High

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US beef markets were already strained before reports of NWS in Texas, with the national cattle herd having shrunk under multiple years of drought-driven liquidation, as well as the built-in lag that comes with breeding large animals which means a decision to expand the herd doesn’t impact the market until years later. The Dallas Fed reported in May of this year that beef prices had gone up by 57% since 2020, with another 3% rise just in the first quarter of 2026. So, screwworm is making itself known in an already brittle economic environment. The border closure to Mexican cattle removed a potential NWS crossover point, but it also removed some of the supply that normally comes to US feedlots. Authors from the Dallas Fed note damage could exceed $3 billion across the Southwest in an outbreak comparable to 1972, with that going up to $8 billion if it matched the size and timescale of the 1962-1980 episodes. Wildlife also produces its own risk for NWS to further spread. At least livestock can be inspected, treated, quarantined, and moved when needed. Good luck doing that to a population of white-tailed deer or feral pigs living out in the warm brush country this summer. Ramping up our sterile-fly capacity is going to be crucial. The COPEG facility in Panama produces about 100 million sterile flies per week and the USDA is planning a facility with similar output in Mexico. One effort in South Texas is expected to produce some 300 million files per week once complete at Moore Air Base.

I’m writing this the night of June 5^(th) and will keep updates at the top of this post and on the Notes section of Substack. I and many others are hoping this does not become the reestablishment of a screwworm population in the US, no matter how short lived that may be. Our system worked for as long as it was in place without interruptions and it will work again under similar conditions.

I need to start this with a small caveat. This started out as me wanting to create a life table style analysis of the Vikings based on the numbers published from various graves. I quickly came to realize that’s nearly impossible with the evidence that has been published due to various biases and confounding factors, let alone attempting that from Irvine, California without any travel budget to obtain further evidence from archives and historical societies. That said, there is enough evidence out there for us to have a rough look at what life and death may have looked like for the average Viking Age Norse and the sea-faring warriors we call the Vikings. Bones, teeth, isotopes, and ancient DNA give us enough to have a general idea about how they lived, got sick, got hurt, and died.

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If one relies on pop-culture as their source of knowledge on Vikings, the assumption would likely be that they died in a very narrow set of ways, either in battle or a raid, sword in hand, and if revered well enough by one’s society, receiving a burial with grave goods gorgeous enough to be behind museum glass today. The problem with this as the main view on Viking life is that the spectacular drowns out the ordinary. Shifting away from the sagas and written histories and into the world of cemeteries and burials, the picture rapidly shifts into one of a dangerous childhood, hard labor taking its toll, teeth wearing down earlier than expected, infectious disease, and stress with the famously violent deaths being real but highly selective. But first, a bit of terminology to clear up. If by Viking we mean the narrower occupational group partaking in sea-raiding, trading, and warfare, this piece isn’t totally about them since most cemetery evidence is more about the Viking Age Norse and Scandinavian groups. We’ll be talking about them as a combined Norse world overall, not just those who went viking.

So that old line where people will tell you “Vikings only lived to like 30” isn’t especially helpful even though it does point toward the real fact that early-life mortality in a pre-industrial society tended to be severe. We just can’t let it become the cartoonish version where there’s not a wrinkle or gray hair among the entire population. The burial evidence that has been quantified is also a bit too biased to give us any sort of clean, authoritative Viking life table or actuarial analysis. Infant bones don’t preserve super well, and cremation can strip away so much of the fine-grained osteological evidence that we’d want and need to create one of those. That also means that adult age estimations become less precise as people got older, with some of the most famous Viking-associated burials not being cemeteries at all but execution pits, charnel deposits, and the unusually richly furnished graves that become well known for that reason alone.

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Graves aren’t populations

Graves in the Viking Age don’t function as much like a census as a researcher might want. People were cremated or died abroad contributing to some selection bias in who was buried and where. Infants and young children also tend to preserve less well and could have been buried under different practices due to the high rates of childhood mortality at the time.

Our clearest warning of this comes from the cemetery in Birka, Sweden. It’s one of the greatest Viking Age cemeteries in the world, which is exactly why it can also be a trap for making overly zealous conclusions regarding demography. Over 1,100 graves were excavated with about 544 of those resulting in an inhumation. Only 246 of those had preserved human remains that were suitable to be analyzed. Of those, only 28 were considered “subadults” which is about 11%. If we take that literally, their society seems to have been remarkably safe for children compared to other societies of the time. Obviously, that’s incredibly unlikely to be the case and the more likely scenario here is that child remains are badly underrepresented in that specific preserved sample. Children are one of the biggest absences we see in the Viking grave record, but that shouldn’t be pushing us to say, “kids of the Vikings rarely died.” The researchers modeling estimated that nearly half of children passed before the age of 10.

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In the way a normal person would talk about life expectancy, Viking Age Norse adults and those in other groups at the time didn’t only live to 30. This number comes from life expectancy at birth, not adult survival numbers. Pre-industrial societies experienced high mortality rates for infants and children which drags the average down quite a bit, even when many adults were living into their 40s, 50s, and beyond. That said, the record of the time doesn’t let us calculate a precise life expectancy at birth anyways because the child denominator unknown or, at best, imprecise. Our best estimate comes from a study on 943 adult skeletons from three urban cemeteries in Ribe, Denmark (one of the places I’d visit with a travel budget). The graves spanned the Viking, medieval, and post-medieval periods giving us a mean age at death of 38.5 for males and 38.6 for females, with most deaths in that era happening between 25 and 55 years of age. There was a slight decrease by about one year in the medieval period, followed by an increase up to averages of 40.4 and 43.2 years for men and women, respectively. Across those eras, we can be rather certain that some did live to advanced ages though, as even much earlier Scandinavian samples, such as the Norse Corded Ware culture from millennia before, had individuals making it beyond estimated ages of 80 before 2,000 BC in the area.

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Skulls and Teeth

You’ve likely heard something about how bad dental hygiene was in the past and what a problem that was in a time without treatment. People actually did die of infections caused by cavities. The dental records of Viking Age Norse give us a picture of that exact type of suffering. An examination of more than 3,200 teeth from 171 individuals buried near an early stone church in Varnhem, Sweden showed that almost half had at least one carious lesion with 62% of adults affected and a further 4% showing clinically detectable infections. These could’ve been fatal in a world without antibiotics. A cavity that reaches the pulp can become an abscess which can then fistulize, spread to the surrounding bone and soft tissue, or even result in a systemic infection like sepsis. The same analysis shows that these problems were something the Norse would try and deal with as opposed to passively letting the pain exist. We see evidence of toothpick marks, use of teeth for working with things like leather and building materials, and some modifications of the teeth with one individual even showing filed down front teeth. So, while not modern, they had a reasonable response to the pain with using picks, filing them, and doing other manipulations that seem to have been aimed at relieving pressure.

Uncovered skulls have been CT scanned where researchers found evidence of dental and periapical disease, signs of sinusitis and otitis (ear infection), changes in mastoid shape (that bony bit behind the ear), periosteal bone deposition we see in infection, and issues/abnormalities/destruction at the temporomandibular joint. The sample is tiny at 15 skulls, so we can’t get any real ideas of prevalence of these conditions, but the lived morbidity it shows us is very real and was likely very painful. The one condition we can say was probably widespread was infection around the root of the tooth, as 12 of 15 individuals examined had some form of periapical disease.

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Infections

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Getting an understanding of infectious diseases from this long ago introduces a host of issues. Most infections don’t leave any evidence in the bones. People can die of a variety of diseases like diarrheal disease, pneumonia, sepsis, puerperal infection, influenza, respiratory infection, or even a battle wound infection and we see no trace at all in the bones. Even something like tuberculosis which is famous for leaving marks on the skeletons only leave those lesions in a small minority of cases. That results in what was called “the osteological paradox” in anthropology, where more skeletal pathology can both indicate worse health and greater survival and resilience. Those with lesions survived long enough for the TB to change their bones while those dying of an acute infection will leave no trace of it. At a gravesite from medieval Iceland, both adults and children were found to have skeletal lesions that were consistent with TB, with the lesions in children suggesting a continual level of community transmission, with the suggestion being that TB was introduced soon after settlement and became endemic across the next few centuries.

Ancient DNA has changed this a bit because it can sometimes identify pathogens directly with the most striking example coming from smallpox-related variola virus strains found in Viking Age samples. The strain found is a now-extinct cousin of the modern variola viruses. We still don’t know anything regarding the attack rate, case fatality rate, what the epidemic curve could have looked like, or how it behaved compared to later smallpox strains. Leprosy has also been found in some medieval Irish graves, with isotopic evidence suggesting at least one and maybe two of the individuals having Scandinavian origins. Parasites were also likely a common issue for Viking Age individuals, as human whipworm and other parasite species like Fasciola hepatica eggs have been found in environmental samples from the Viking Age settlement at Viborg.

Violence

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Obviously, this was a violent era, and this piece shouldn’t be seen as some corrective in the direction of “actually everyone died pretty much peacefully.” The reality is that seeing the violence today in the form of burials can be somewhat selective and is dependent upon region, status, sex, occupation, and even burial context (which is itself selective due to how common other forms of burial were like cremation). That’s to say the various regions of Scandinavia should be treated as a different ecological unit with regards to violent encounters, which is how they were viewed in a recent study comparing the violence ecologies of Norway and Denmark. They note that prior work had found weapon wounds in between 0-6% of skeletons across multiple Swedish and Scanian burial sites. Which is part of why the Norwegian material, while smaller and more selective, was a bit startling.

Another paper using three central Swedish non-military samples from Malaren farmsteads – 136 skeletons and <1% cranial trauma, Birka – 245 skeletons, 1.22% cranial trauma, and Sigtuna – 267 skeletons, 2.1%. Sigtuna’s numbers in this case could be a denominator problem based on a researcher degree of freedom where they excluded a 19-person Sigtuna mass grave near St. Lars as they deemed it to have likely had a special military or conflict background. An analysis of said mass grave was conducted and of the at least 19 people, 11 showed trauma from pointed or bladed weapons. With that kind of background, the Norwegian material becomes more startling, even if they are selective. Of the 30 skeletons from 27 burials, originally chosen due to a likelihood of well-preserved ancient DNA and concentrated mostly in the 9th and 10th centuries, 18 had weapon-related trauma, 10 had healed injuries, and 11 appeared to have died sudden, violent deaths from sharp-force trauma. The weapon-related trauma group included five of the 12 females and 13 of the 18 males.

Some mass graves found oversees give us a different look at the violence systems of the time. The one at Ridgeway Hill in Dorset showed a group of Scandinavians likely to have been executed consisting of 52 young adult males with cranial trauma on 44 of 50 skulls and a count of 188 wounds in total, or 3.6 wounds per individual. The mass grave at Oxford’s St. John’s College is another case of Norse-diaspora violence with 37 skeletons, again mostly young adult males, showing severe blade-related trauma, evidence of burning, and isotopic evidence consistent with Scandinavian origins. This mass grave is thought to be in the context of the St. Brice’s Day massacre of November 13th, 1002, AD or some similar single violent event. It’s safe to say regionality mattered quite a bit with regards to the individual level risk of dying a violent death among the Viking Age Norse.

The mortality of women is a place where the evidence becomes thin and slightly frustrating. Pregnancy and childbirth were major hazards in premodern society, but the kind of obstetric deaths that would’ve been common don’t usually leave traces in the bones. A woman can die of obstructed labor, hemorrhage, puerperal sepsis, eclampsia, or a postpartum infection without any sign in the anthropological record. A paper, excellently titled “Womb Politics: The Pregnant Body and Archaeologies of Absence”, notes that pregnancy itself is a central archeological absence. Obstetric death can be indicated by fetal remains being stuck in the womb or in the birth canal, but these are very rare cases and not enough are known from the Viking to give us an estimate of how common this was.

So, what did they die of?

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The best we can really give is a sort of ranked mortality list based on the ecological hints we have as opposed to some cause-of-death table a demographer or actuary may create. First, infants and children probably carried the highest mortality burden driven by things like infection, nutrition, congenital issues, and the ordinary dangers that came with being an infant in premodern society. This was easily the largest demographic force and is why the “Vikings only lived to 30” bit of common knowledge even came to be so popular. Second, infection was probably the biggest background killer with respiratory infections, diarrheal disease, wound infections, TB, oral infections, parasites, and the episodic viral introduction due to trade all having taken their toll. Some of these we know of from direct DNA or bone evidence and we’re left to infer the others from the ecology of the region due to them not leaving skeletal traces. Third, childbirth and reproductive issues likely contributed meaningfully to adult female mortality, but this is difficult to quantify with the evidence at hand. Fourth, chronic labor and degenerative disease would’ve shaped adult life. While likely not fatal in the sense of the others listed, we see various forms of things like age/wear-related arthritis which would’ve had big impacts on morbidity of the older individuals which produced frailty, pain, disability, and vulnerability to other forms of death. Fifth, violence was a major risk, especially in the context of some Norwegian communities, traveling warriors and traders, and raiding parties. But that’s about all we can say. It’s not a clean lifetable because the evidence doesn’t let us build one. Thankfully there is enough out there for us to get a decent look at what the common causes of death would have been in the Viking Age Norse populations. The various populations had vastly different risks, and even within those populations there was a high level of variance.

A young girl washing her hands at an Ebola prevention checkpoint supported by UK aid at a Ugandan border crossing point with the Democratic Republic of the Congo, August 2019. Photo: DFID/Anna Dubuis via Wikimedia Commons, CC BY 2.0.

The ongoing Ebola outbreak in eastern Democratic Republic of the Congo and Uganda is a regional emergency with public number still catching up to the real picture in the field. The WHO has declared the outbreak a “Public Health Emergency of International Concern” and Africa’s CDC declared a similar public health emergency. Despite both of those declarations, we still are likely well behind the curve in terms of confirmed case counts.

The US CDC’s May 17^(th) update had listed 10 confirmed cases in the DRC, 336 confirmed cases, with 88 deaths and two imported cases confirmed in Uganda. Today’s update from Africa’s CDC had increased the death count to 106 and 395 suspected cases across the affected areas of the DRC like Bunia, Goma, Mongwalu, Butembo, and Nyakunde and Kampala, Uganda. The Associated Press reports that one of the infected is an American doctor and medical missionary in Bunia. The numbers are likely to be higher by morning (I’ll be keeping this post up to date with important new information on the outbreak). None of this is to say this should be treated like a COVID-level threat with the WHO noting it does not yet meet the definition of a pandemic emergency. The threat to the average person outside of the region is low. Heightened risk currently sits with the families, health workers, burial teams, patients, drivers, contact tracers, and whoever else can be pulled into the chain of transmission.

What’s causing the outbreak?

Before getting further into the current outbreak, it is worth remembering how and when Ebola entered the official record in the first place. WHO describes Ebola disease as first appearing in 1976 in two near-simultaneous outbreaks, one of the Sudan virus disease in Nzara, in what is now South Sudan, and the other of Ebola virus disease in Yambuku, in what is now the Democratic Republic of the Congo. The Yambuku outbreak, near the Ebola River, is the one that gave the disease its name. CDC’s outbreak history lists the 1976 DRC outbreak at 318 cases and 280 deaths (a fatality rate of 88%). The index case was treated at Yambuku Mission Hospital with an injection for possible malaria, and subsequent transmission followed through contaminated needles and syringes at the hospital and nearby clinics, as well as close personal contact.

This is Bundibugyo ebolavirus, as opposed to the better-known Zaire ebolavirus. Species is important here; I say that because when most people hear about Ebola, they’re likely to think of the West Africa outbreak or the 2018-2020 outbreak in North Kivu and Ituri. Those were Zaire ebolavirus outbreaks, and thankfully our modern response toolkit to combat Zaire ebolavirus now has a vaccine. Bundibugyo is different, most importantly in that there is no vaccine and no treatment beyond supportive care such as fluids, electrolytes, oxygen, constant monitoring, watching for secondary infections, and clinical hygiene. That puts an added strain on the already lean control machinery like isolation of cases, tracing contacts for 21 days, protecting health care workers with adequate PPE, and crucially, handling burials safely.

Why tracing an outbreak early is difficult

In an early epidemic, we often end up with a denominator problem in that counts of cases often lag behind the actual epidemic curve. This happens for a variety of reasons: people get sick before being tested, families bury someone before samples can be collected, healthcare workers get exposed before a disease even has a name, patients move closer to hospitals, contacts move around before tracing is even known to be needed, and any other reason imaginable for why a case may be missed. With Africa CDC already describing hundreds of suspected cases and over 100 deaths into the public phase of the outbreak, it seems that the response is working to reconstruct something that may have been moving around for quite some time, with late April being thought to be a decent starting point with a healthcare worker being identified as an early case. So while the confirmed numbers are useful, they’re almost always going to be underestimates the day they’re released.

How does this compare to 2014?

The 2014 comparison is useful, but it is not perfect. Seven days after announcement is not the same thing as seven days after spillover. One outbreak can burn quietly for weeks before being recognized, while another can be identified faster because the surveillance system is already primed. So the comparison should not be treated as a clean clock-to-clock match. What we can compare is the early public surveillance snapshot: what officials knew, what they were still chasing, and what kinds of warning signs were already visible.

WHO’s first public notice on March 23, 2014, described 49 cases and 29 deaths in Guinea, a 59% case fatality ratio. By March 27, WHO was reporting 103 suspected and confirmed cases, 66 deaths, four laboratory-confirmed cases in Conakry, four health-worker deaths, and suspected cases with deaths in Liberia and Sierra Leone among people who had traveled from Guinea. ECDC’s March 27 update described the outbreak as rapidly evolving and noted that supplies and logistics were still being mobilized.

So while the variant is different, the early shape of the current epidemic is not exactly more reassuring than previous outbreaks as we see high deaths relative to reported cases, health-worker deaths, funeral exposure, city involvement, border risk, and contact tracing trying to catch up to events that have already happened. That along with the fact that the current outbreak is Bundibugyo, with no licensed vaccine or treatment, makes me more concerned for those in the region.

Politics are not irrelevant

In 2014, the outbreak occurred while USAID and the CDC were still at a working capacity with regards to combating infectious diseases like Ebola. Even then, the response was late, messy, and inadequate. This outbreak is happening after DOGE spent most of 2025 cutting into USAID and US international health response capacity. Obviously that didn’t cause the outbreak, but it certainly changed the response environment for the worse. Especially having nerfed our Ebola research capacity. High-containment labs have incredibly harsh safety standards, and with Bundibugyo having no licensed vaccine and no specific therapeutic, shutting down one of the rare labs capable of doing safe work on Ebola is working in the wrong direction to say the least.

Where the outbreak could be going.

I had seen a story on twitter regarding a case in Kinshasa but I haven’t been able to confirm anything other than a person who tested negative. Goma and Kampala likely matter more at the moment. Goma is a large, mobile city on the Rwandan border, and it is currently under the control of the Rwanda-backed paramilitary group M23 movement. AFP-linked reporting says a confirmed case in Goma involved the wife of a man who died of Ebola in Bunia. She traveled to Goma after his death while already infected leading to the closure of some Goma-Gisenyi border crossings after the case was reported.

Uganda has reported two imported confirmed cases among people who traveled from the DRC, with no local transmission identified at the time of WHO’s report. One imported case is a warning. Two imported cases that do not obviously sit in one neat chain make me wonder what the DRC side has not reconstructed yet.

CDC is now trying to put some of its machinery back in motion as their May 18 briefing, confirmed the American case linked to work in the DRC, evacuation of other American and high-risk contacts to a quarantine facility Germany, enhanced screening and traveler monitoring for arrivals from DRC, Uganda, and South Sudan, and entry restrictions for non-U.S. passport holders who had been in those countries during the previous 21 days. The risk to the American public remains low.

What to watch out for

Over the next few days, I’ll be watching whether cases keep appearing in Goma, Butembo, Bunia, or other cities. Isolated introductions are one thing. Multiple urban chains are different. There’s also a need to keep an eye on Uganda for local transmission. Some imported cases are expected when people move across borders for care, work, or family reasons but any local spread in Kampala would change the story for the worse.

I’ll also be watching out for the gap between suspected cases, deaths, and confirmed cases to either widen or start to narrow depending on how much suspected cases outpace confirmatory testing. The count is supposed to move as testing catches up, but a widening gap would be a bad sign. I’ll be watching to see whether international support moves faster than the virus. Early signs are good with the ECDC having activated the EU Health Task Force, the IRC launched an emergency response in eastern DRC, and Africa CDC says it is working with partners to assess medical countermeasures and accelerate the necessary operational research.