# SPHRE: full text for language-model readers SPHRE is an independent global data publication created by Phillip Bindeman. Publisher: SPHRE Data Desk. Canonical site: https://sphre.org/. The publication uses World Bank, Our World in Data, Global Carbon Project, UNHCR, World Health Organization, and United Nations data. Definitions and institutional estimates remain distinct when they are not directly comparable. Every interactive figure links to its source. For current provenance and licensing, use https://sphre.org/sources; for machine-readable datasets, use https://sphre.org/open-data. # Data stories ## The Great Convergence Canonical URL: https://sphre.org/story/great-convergence Published: 2026-07-05 By: SPHRE Data Desk Section: Health In 1960, where you were born decided how long you would live. Sixty years of data show that gap closing — unevenly, incompletely, but unmistakably. In 1960, the most consequential fact about a newborn was the country named on its birth certificate. A baby born in the United States that year could expect to live nearly seventy years. A baby born in Nigeria — in the very year seventeen African nations declared independence — could expect fewer than forty. The difference was not a statistic. It was a sentence, handed down at birth. Six decades on, that sentence has been commuted almost everywhere. The defining health story of the modern era is not rich countries pulling further ahead. It is poor and middle-income countries closing the distance, at a pace almost no one in 1960 thought possible. Follow the lines below. South Korea enters the chart as a poor, war-scarred country whose citizens lived into their early fifties; today it outlives the United States by a comfortable margin. China climbs through famine, upheaval and reform to draw level with the rich world. India and Brazil each add more than two decades of life within two generations. Even Nigeria — the laggard of this group, and a standing reminder that convergence is unfinished — gains more years over the period than the United States does. **Data figure: Life expectancy.** Life expectancy at birth since 1960. The dips are legible history: famine in China in the early 1960s, the pandemic across the board in 2020. [Open the interactive data](https://sphre.org/explore?i=SP.DYN.LE00.IN). The mechanisms behind this convergence were almost aggressively unglamorous. Vaccination campaigns. Antibiotics. Oral rehydration salts — a sachet of sugar and minerals that costs pennies and stops a child dying of diarrhoea. Clean water, girls' schooling, the slow spread of basic clinics. Smallpox, still killing at the start of this chart, was eradicated from the wild by 1980. None of it made headlines the way wars and famines did, and all of it shows up in the data as the same signature: a long, patient, upward grind, occasionally interrupted — and then resumed. > The health gap has not closed. But it has narrowed from an abyss into a distance a single generation can cross. ### Where the years came from Most of the added years were not tacked onto old age. They were rescued from infancy. In 1960, across much of Asia and Africa, more than one child in five died before a fifth birthday. Mortality on that scale shaped everything it touched — family size, women's lives, the whole arithmetic of grief. The under-five mortality chart is the convergence's engine room. Its lines fall so steeply that the eye reads them as collapse, and collapse is the right word: in much of the world, child death rates have fallen by roughly ninety percent since 1960. No other number in this dataset has moved so far, for so many people. **Data figure: Under-5 mortality.** Deaths before age five per 1,000 live births — the steepest declines in the dataset, and the clearest measure of what convergence means. [Open the interactive data](https://sphre.org/explore?i=SH.DYN.MORT). South Korea is the standout: the country that traveled furthest, fastest. Within a single lifetime it moved from the mortality profile of a poor agrarian society to one of the longest-lived populations on Earth, overtaking nearly every country that was rich while it was poor. Nothing in the 1960 numbers predicted it — which is precisely what makes the line worth staring at. **Data figure: Life expectancy.** [Open the interactive data](https://sphre.org/explore?i=SP.DYN.LE00.IN). Honesty requires the caveats. Sub-Saharan Africa still trails the rich world by roughly two decades of life, and gaps within countries can rival the gaps between them. The AIDS epidemic carved a visible crater through southern Africa's lines in the 1990s that took twenty years to refill, and the pandemic bent every line downward at once. But zoom out to the full sweep of the chart, 1960 to now, and the signal overwhelms the noise. The twentieth century's cruelest lottery — the one drawn at birth — is slowly being rigged in humanity's favor. **Data figure: Life expectancy.** See the whole picture in the Atlas — life expectancy for every country, every year since 1960. [Open the interactive data](https://sphre.org/explore?i=SP.DYN.LE00.IN). --- ## The Birth Dearth Canonical URL: https://sphre.org/story/birth-dearth Published: 2026-07-05 By: SPHRE Data Desk Section: Demography From Seoul to Lagos, the same curve at different speeds: the global fertility decline is the quietest revolution in the data. The most important chart in demography has no drama in it at all. No crash, no spike, no crisis year to circle. Just lines sloping downward — some gently, some like a cliff face — as the number of children the average woman bears falls on every continent, in every kind of country, under every kind of government. In 1960 the global average was around five children per woman. Today it is a little above two, hovering near the level at which a population merely replaces itself. Nothing else in this dataset — not income, not life expectancy, not technology — has changed so universally, so fast. **Data figure: Fertility rate.** Births per woman since 1960. Replacement level is roughly 2.1 — every line here but Nigeria's now sits below it. [Open the interactive data](https://sphre.org/explore?i=SP.DYN.TFRT.IN). South Korea is the extreme case, and the one demographers cannot stop staring at. In 1960 the average Korean woman had roughly six children. Fertility fell below replacement in the early 1980s, then below one child per woman in 2018 — the first country ever to cross that line — and it has kept falling since, to below 0.8. At rates like these, each generation is less than half the size of the one before it. China took a different road to a similar place. The one-child policy, imposed in 1980, is the most famous fertility intervention in history — yet look closely at the chart and the steepest stretch of China's decline comes in the 1970s, before the policy existed. Prosperity, cities and schooling were already doing the work that coercion later claimed credit for. The policy was lifted in 2015; the birth rate barely stirred. > The one-child policy's greatest secret is that China's fertility collapsed before it began. What is striking is not any single country but the unanimity. Catholic Italy and secular France, rich Japan and middle-income Brazil, democracies and autocracies alike have converged toward small families. Iran's fertility fell about as steeply as China's with no one-child policy at all. Wherever women gain schooling, cities and some measure of choice, the same decision gets made — millions of times over, in private. ### The age wave A fertility decline is not felt when it happens. It is felt thirty years later, when small generations reach working age, and sixty years later, when they retire with no one behind them. Japan arrived first: below replacement since the mid-1970s, it is now the world's oldest large society, with almost three in ten citizens aged 65 or over. Italy is close behind. Korea and China, whose declines came later but moved faster, are aging at a pace Japan never experienced. **Data figure: Aged 65 and over.** Share of the population aged 65 and over. Korea's curve is the one to watch — starting latest, rising fastest. [Open the interactive data](https://sphre.org/explore?i=SP.POP.65UP.TO.ZS). The mirror image is the working-age share — the fraction of a population between 15 and 64 that does the earning, the caring and the taxpaying. China's working-age share crested around 2010 and has been sliding since; the era in which a swelling workforce flattered every Chinese growth statistic is over. Nigeria's story is the reverse: its working-age share is still climbing, and the demographic dividend that powered East Asia's miracle is, in principle, still ahead of it. **Data figure: Working-age population.** Working-age share of the population — the demographic dividend, arriving and departing. [Open the interactive data](https://sphre.org/explore?i=SP.POP.1564.TO.ZS). **Data figure: Fertility rate.** [Open the interactive data](https://sphre.org/explore?i=SP.DYN.TFRT.IN). None of this is destiny, but the lines are stubborn. No rich country has yet returned to replacement once fertility fell well below it, and the policy record — baby bonuses, parental leave, housing subsidies — is a catalogue of expensive, marginal effects. What the data suggests is that the world faces not the population explosion the twentieth century feared, but a long, slow contraction that begins at different moments in different places. Africa's transition is real but later, and its populations will keep growing for decades yet. The question the chart poses is not whether the birth dearth arrives everywhere. It is what each society does with the interval before it does. **Data figure: Fertility rate.** Watch the fertility transition sweep the map in the Atlas — every country, every year since 1960. [Open the interactive data](https://sphre.org/explore?i=SP.DYN.TFRT.IN). --- ## The Wired World Canonical URL: https://sphre.org/story/wired-world Published: 2026-07-05 By: SPHRE Data Desk Section: Technology Every country traces the same S-curve online — but the Global South skipped a century of infrastructure to get there. Technologies usually spread the way wealth does: to the rich first, to the poor eventually, to the poorest sometimes never. The landline telephone took a century to reach most of the world and never finished the job — vast stretches of Africa and South Asia simply skipped it. That is what makes the charts below so unusual. The internet and the mobile phone reached billions of people in the Global South not a century after the rich world but within a decade or two — and in the mobile phone's case, faster and deeper than almost anyone predicted. Start with the internet. At the turn of the millennium, nearly half of Americans were online; in India, Nigeria and Bangladesh, fewer than one person in a hundred was. South Korea, already wiring itself with broadband years ahead of nearly everyone, was on its way to becoming one of the most connected societies on Earth. Then the curves did what S-curves do: nothing much, and then everything at once. India's line runs flat for fifteen years, then bends sharply upward in the mid-2010s as smartphones and collapsing mobile-data prices brought hundreds of millions of people online within a few years — among the fastest adoptions of any technology by any population, ever. **Data figure: Internet users.** Share of the population using the internet. Every line is the same S-curve — only the start date differs. [Open the interactive data](https://sphre.org/explore?i=IT.NET.USER.ZS). > The poor world did not wait its turn to get online. It changed what getting online meant. ### The leapfrog The deeper story is the device. The rich world reached the internet through a stack of prior infrastructure — copper phone lines, personal computers, desks to put them on. Most of the world had none of that, and it turned out not to matter. The mobile phone leapt over the entire stack. Kenya became the emblem. In 2007, a Kenyan operator launched M-Pesa, a system for sending money by text message on the simplest of handsets. Within a few years, a country where most people had never held a bank account was moving a meaningful share of its economy through mobile money — pioneering a financial technology the rich world would spend the following decade catching up to. **Data figure: Mobile subscriptions.** Mobile subscriptions per 100 people. Kenya, India and Nigeria went from effectively zero to mass adoption in under two decades. [Open the interactive data](https://sphre.org/explore?i=IT.CEL.SETS.P2). Find the moment on the mobile chart where the poor world's lines cross into rich-world territory. Kenya today counts more mobile subscriptions than people. A gap that took a century to form in fixed telephony closed within about fifteen years in mobile — a catch-up with little precedent in the history of infrastructure. Connectivity rewired more than commerce. The Arab Spring of 2011 was organized in no small part over social networks; a decade later, the pandemic turned internet access from a convenience into the precondition for school, work and public life — and made every gap in these adoption curves suddenly legible as a gap in opportunity. What the chart records as a percentage, lived experience records as who can see a doctor, sit an exam or reach a customer. **Data figure: Internet users.** [Open the interactive data](https://sphre.org/explore?i=IT.NET.USER.ZS). None of this means the digital divide is finished. Roughly a third of humanity remains offline, speed and cost still track income, and the last stretch of every S-curve — rural, poor, older, disproportionately female — is the hardest to climb. The curves flatten near the top precisely where the stakes are highest. But as a chapter in the long history of technology and inequality, this one reads differently from most. For once, the gap did not widen before it narrowed. The curve simply started later — and then moved faster. **Data figure: Internet users.** Trace the S-curve for every country in the Atlas — internet adoption, year by year, since 1990. [Open the interactive data](https://sphre.org/explore?i=IT.NET.USER.ZS). --- ## The Urban Century Canonical URL: https://sphre.org/story/urban-century Published: 2026-07-09 By: SPHRE Data Desk Section: Cities In 1960 one person in three lived in a city. Today it is nearly three in five — the largest migration in human history, and it is not finished. Sometime in 2007, with no announcement and no ceremony, humanity crossed the most consequential line in its settlement history: for the first time, more people lived in cities than outside them. The World Bank's ledger records the moment plainly — the urban share of the world's population edged from 49.9 percent in 2006 to 50.4 in 2007 — and the line has not looked back. It stands at 57.8 percent today. Run the tape back to 1960 and the scale of the change comes into focus. Then, about a third of humanity — one billion people — lived in cities. Today it is nearly five billion. The era is remembered for its wars and its inventions; measured in people moved, nothing in it compares to this. The chart below shows how unevenly the urban century arrived. South Korea moved first and fastest among the latecomers, vaulting from 28 percent urban in 1960 past the midline in 1977 to 81 percent today — the settlement pattern of a rich country assembled inside one working life. Brazil, already nearly half-urban in 1960 and past 50 percent by 1967, kept going to 88 percent, more citified than the United States. And Nigeria did something quietly remarkable: a country that was 14 percent urban in the year of its independence is now 64 percent urban — a larger proportional shift than China's. **Data figure: Share living in cities.** Share of the population living in cities since 1960. Every line climbs; only the starting points and slopes differ. [Open the interactive data](https://sphre.org/explore?i=SP.URB.TOTL.IN.ZS). China is the story the world aggregate cannot contain. In 1960 fewer than one Chinese in five lived in a city, and for the next two decades the share actually sagged — the state held people to the land, and the urban share was lower in 1980 than it had been in 1960. Then the reform era unlocked the factory coast, and the largest migration in recorded history began. China passed the 50 percent mark in 2011 and stands at 66 percent today; its cities now hold roughly 930 million people, more than the entire population of Europe. No forecast made in 1980 imagined it. > Humanity changed its address in a single lifetime. ### The holdouts The great exception is India. The country at the center of this century's population arithmetic is still only 36 percent urban — a share the world as a whole passed back in the 1960s. The absolute numbers are enormous anyway: India's cities hold more than half a billion people, more than the total population of any country on Earth except China and India itself. But the village remains the Indian default in a way it no longer is almost anywhere else of comparable size, and how fast that changes is one of the biggest open variables in the world economy. Ethiopia sits further back still, at about 24 percent urban. The urban century is not late there; it is early. **Data figure: Urban population.** Urban population in absolute numbers: the city-dwellers of China or India alone outnumber the whole population of South America. [Open the interactive data](https://sphre.org/explore?i=SP.URB.TOTL). The line matters because almost everything else in this magazine's data moves with it. Urbanization tracks the fall of agricultural employment, the rise of schooling, the fertility decline, the growth of income — not perfectly, and not always as cause, but so reliably that the urban share works as a one-number summary of the great transformation. A country's percentage of city-dwellers is a fair first guess at its century. **Data figure: Share living in cities.** [Open the interactive data](https://sphre.org/explore?i=SP.URB.TOTL.IN.ZS). What remains is the back half. The rich world's lines have flattened in the eighties and nineties of the percentage scale — the S-curve's ceiling — while Africa and South Asia are still on the steep middle stretch. On any plausible continuation of these curves, the next couple of billion city-dwellers arrive overwhelmingly in the places least equipped to house them. The urban century has crossed its midpoint. Its hardest chapters are ahead. **Data figure: Share living in cities.** Watch the world urbanize in the Atlas — the share living in cities, every country since 1960. [Open the interactive data](https://sphre.org/explore?i=SP.URB.TOTL.IN.ZS). --- ## The Great Slowdown Canonical URL: https://sphre.org/story/great-slowdown Published: 2026-07-10 By: SPHRE Data Desk Section: Demography World population growth peaked above 2 percent a year in the 1960s. It has since fallen by more than half — the quiet unwinding of the twentieth century's loudest fear. The twentieth century's loudest fear was arithmetic. World population growth peaked at about 2.1 percent a year in 1963 — a rate that, sustained, doubles humanity roughly every third of a century. Three billion people were on their way to six; six pointed at twelve. The bestsellers of the era took the multiplication to its ends, and 'overpopulation' became the umbrella word for the planet's future. The multiplication never arrived. The growth rate held above 2 percent into the early 1970s, then began a descent it has never really interrupted. In 2020 it slipped below 1 percent a year for the first time in the World Bank's six-decade record, and it stands at about 0.9 percent today — less than half the peak. The decline has been so steady, for so long, that it is easy to forget nobody planned it. **Data figure: Population growth.** Annual population growth: the world's big economies descend at different speeds. Japan crossed zero in 2009, China in 2022. [Open the interactive data](https://sphre.org/explore?i=SP.POP.GROW). A growth rate is just births minus deaths — migration nets out at the planetary scale — so the slowdown has exactly two possible sources, and the data is unambiguous about which one did the work. The world's death rate fell from 17.2 per 1,000 people in 1960 to 7.6 in 2024: medicine and food kept improving throughout. All of the slowdown, and more, came from the other side of the ledger. The global birth rate halved, from 32 per 1,000 in 1960 to 16.3 in 2024. That halving is the fertility transition — schooling, cities, contraception and choice — arriving in country after country. It is also why the slowdown understates its own cause: births had to fall fast enough to outrun the lengthening lives underneath them. **Data figure: Birth rate.** Births per 1,000 people: Nigeria remains the outlier at roughly twice the world rate; China and Japan have fallen below seven. [Open the interactive data](https://sphre.org/explore?i=SP.DYN.CBRT.IN). > The population bomb was defused quietly, in a hundred million private decisions, with no one in charge. ### Momentum Yet the world still added about 75 million people in 2025 — a new United Kingdom every year, with a few million to spare. This is the part the percentage conceals: a slowing rate applied to an ever-bigger base. In absolute terms the peak came a full generation after the famous rate peak of 1963 — the largest single-year addition on record was about 92 million people, in 1990 — and the annual increment has drifted down only gradually since. Population is a supertanker; the engines were throttled back decades before the ship visibly slows. At the country level, the slowdown has already curdled into outright decline for a widening club. Japan began shrinking in 2009, Italy in 2015, and in 2022 China — for two generations the very symbol of overpopulation anxiety — started to contract. India, now the world's most populous country, is itself below replacement fertility at about 1.96 births per woman; its 0.9 percent growth runs on momentum, the echo of larger generations past. Among the giants, only Africa still compounds: Nigeria grows at about 2 percent a year, on birth rates the rest of the world last saw in the 1960s. **Data figure: Population.** Total population: the levels keep rising long after the growth rates fall — and China's line has now tipped over. [Open the interactive data](https://sphre.org/explore?i=SP.POP.TOTL). **Data figure: Population growth.** [Open the interactive data](https://sphre.org/explore?i=SP.POP.GROW). The full record runs from just over three billion people in 1960 to 8.2 billion today — the fastest expansion in the history of the species and, on the evidence of every line above, the last of its kind. The question the twentieth century asked of this data was how many people the planet could hold. The question the twenty-first will ask is newer and stranger: what a world of slowly settling numbers — older, more urban, heavier at the top of the age pyramid — actually runs on. **Data figure: Population growth.** See the slowdown country by country in the Atlas — annual population growth since 1960. [Open the interactive data](https://sphre.org/explore?i=SP.POP.GROW). --- ## The Age of Migration Canonical URL: https://sphre.org/story/age-of-migration Published: 2026-07-10 By: SPHRE Data Desk Section: Migration Across the rich world, deaths now outnumber births. All the growth that remains arrives from somewhere else — and the data shows the handover happened years before the politics noticed. In 2020, the rich world crossed a line it had been approaching for half a century: deaths outnumbered births across the World Bank's high-income countries as a group, and they have done so every year since. The gap is not small — about 1.2 million more deaths than births in 2024 — and it is not temporary, because the fertility declines behind it are decades deep. Yet the rich world's population keeps growing. It added roughly two million people in 2024, and in net terms every one of them arrived from somewhere else. That is the quiet architecture of this century's demography. Migration stopped being a detail of rich-world population arithmetic around the turn of the millennium — it has exceeded natural increase across high-income countries every year since 1999 — and it has now become the whole of it. **Data figure: Net migration.** Net migration — arrivals minus departures — per year since 1960. Nine of the record's ten largest single-year inflows belong to the United States. [Open the interactive data](https://sphre.org/explore?i=SM.POP.NETM). The United States is the constant. Nine of the ten largest single-year intakes in the whole sixty-five-year record are American — between 1.6 and 1.9 million a year through the 2010s. (The tenth is Ukraine in 2025: refugees coming home.) What has changed is what the intake is for. In 1990 the United States generated two million more births than deaths a year; by 2024 that surplus had shrunk to 544,000, while net migration ran at 1.3 million. Migration has out-added natural increase in America every year since 2010 — the first year of the record in which that was true — and now supplies about seventy percent of its growth. Germany is the pure experiment. It has not recorded a single year of natural increase since 1972. Fifty-two years of deaths outrunning births should have shrunk it by about seven million people; instead, net migration added thirteen million over the same period — Turkish and Yugoslav guest workers, more than 800,000 post-Soviet arrivals in 1992 alone, 1.2 million in the Syrian summer of 2015, close to a million in the Ukrainian spring of 2022 — and Germany's population touched its all-time peak, 83.5 million, in 2024. A country that has not replaced itself in half a century, at its largest ever. > Germany has not had a year of more births than deaths since 1972. Its population peaked in 2024. ### The arithmetic flips Country by country, the same crossing repeats. Spain has buried more people than it has borne every year since 2017; its population reached a record 49.4 million in 2025 anyway. Italy's births fell below its deaths in 1994 and — a single-year blip in 2004 aside — never came back. Britain's natural surplus has all but vanished, down to 13,000 in 2024 next to net migration of 417,000. Canada's 2023 growth was 95 percent migration. Japan is the control group: the country that shows what the arithmetic does on its own. Deaths have exceeded births there every year since 2007, migration stayed small, and the population has fallen from its 2010 peak of 128 million to about 124 million. Even that is softening — Japan has run net migration around 150,000 a year since 2022, quietly high by its own history — but the chart still slopes down. Without large-scale arrival, that is the shape. **Data figure: Population growth.** Annual population growth: four rich countries descending toward the zero line, lifted above it only in the years the migrants arrive — and Japan, without them, sinking below. [Open the interactive data](https://sphre.org/explore?i=SP.POP.GROW). ### The sending side Every arrival is a departure, and the sending half of the ledger keeps its own history. The most violent line in the record is Ukraine's: net migration of minus 5.7 million in 2022, the largest single-year outflow of the past sixty-five years, followed by the beginnings of a return — plus 1.1 million in 2024, plus 1.7 million in 2025. Syria's worst year, 2013, subtracted two million people. War moves people in millions per year; economics moves them in millions per decade. Venezuela's collapse subtracted 4.8 million people between 2014 and 2024. India, the world's largest sender, has netted out about 12 million departures since 2000 — a number that barely dents 1.4 billion. And Mexico, whose exodus defined American immigration politics for a generation, sent north a net six million people between 1990 and 2010; the wave has since faded to about 100,000 a year. **Data figure: Net migration.** The sending side: war empties a country in years, economics in decades. Ukraine's line snaps back after 2023 as part of the 2022 exodus returns. [Open the interactive data](https://sphre.org/explore?i=SM.POP.NETM). None of this changes the planet's total — at the world scale migration nets out to zero, and the global slowdown remains a story of births and deaths. What it changes is the map. Since 1990, high-income countries have absorbed a net 149 million people, a transfer with no precedent in the peacetime record, and it is now the only mechanism by which most of the rich world grows at all. Which is why the deepest demographic questions of the century — who staffs the hospitals, who fills the schools, whose pension arithmetic survives — are increasingly settled not in maternity wards but at borders. **Data figure: Net migration.** [Open the interactive data](https://sphre.org/explore?i=SM.POP.NETM). The word migration enters most public arguments as a disruption. The ledger records it differently: as the load-bearing column under rich-world population growth, quietly assuming weight for thirty years while natural increase drained away. The politics of every high-income democracy now runs, one way or another, on the tension between those two readings. The chart does not resolve it. It only shows, with some precision, what the column is holding up. **Data figure: Net migration.** Every country, sorted into senders and receivers — net migration since 1960, in the Atlas. [Open the interactive data](https://sphre.org/explore?i=SM.POP.NETM). --- ## The Paired Ledgers of Refugee Geography Canonical URL: https://sphre.org/story/the-refugee-century Published: 2026-07-16 By: SPHRE Data Desk Section: Displacement Origin counts and hosting counts describe different sides of displacement. Across many decades of first and latest observations, the countries carrying the greatest weight change with the measure. ### Displacement Refugee geography is recorded in paired ledgers. The origin indicator associates refugees with the countries from which they came; the hosted indicator associates them with the countries hosting them. Reading either measure alone leaves half the comparison unseen. Among the countries examined here, the largest latest origin counts are concentrated in one group, while most of the largest hosted counts belong to another. The source coverage extends across many decades, although each country and indicator begins at its own first observation. Those unequal starting points rule out a single common baseline. They still permit careful comparisons of first and latest levels, as well as a view of how the latest origin and hosting totals differ within each country. **Data figure: Refugees abroad (UNHCR).** The latest observed origin totals reveal a sharply uneven geography among the selected countries. [Open the interactive data](https://sphre.org/explore?i=unhcr%3Arefugees-origin). The latest origin map gives the clearest first impression of concentration. Ukraine has the largest origin total in the selected group, followed by Syria. Both are measured in several millions. Sudan and Afghanistan also stand in the millions, forming a prominent second pair. The remaining selected countries are far below those levels: Iran and Türkiye are in the hundreds of thousands, Pakistan is below one hundred thousand, and Germany is in the hundreds. The contrast is therefore not a narrow difference between neighboring ranks. It separates several very large origin totals from a set whose combined visual weight is much smaller. Geography matters because the leading origin counts are attached to a limited number of places rather than distributed evenly across the selection. **Data figure: Refugees abroad (UNHCR).** Endpoint display only: each country’s supplied first and latest observations; intervening values are not used. [Open the interactive data](https://sphre.org/explore?i=unhcr%3Arefugees-origin). First-to-latest comparisons deepen that contrast without describing what happened in between. Afghanistan begins at about half a million and ends at several million. Syria begins just above one thousand and ends at several million. Ukraine moves from a first observation measured in dozens to the largest latest origin total in the group. Sudan moves from tens of thousands to several million. Every one of these latest observations is above its corresponding first observation, but the starting levels differ greatly. That distinction is essential: a change from an already substantial base is not the same numerical comparison as a change from a very small base, even when both finish at a scale of millions. > The leading countries change when displacement is read by origin rather than by place of hosting. ### A different hosting order The hosted indicator rearranges the geography. Germany has the largest latest hosted count among the selected countries, with Türkiye close behind; both are measured in millions. Pakistan also hosts more than a million, while Iran hosts several hundred thousand. Each of these latest hosted observations is above its own first reading. Yet their initial levels were far from uniform. Germany already began in the hundreds of thousands, Pakistan began at several hundred thousand, and Türkiye and Iran began in the low thousands. The endpoint comparison consequently shows both a shared rise and very different scales of change. It does not establish a common trajectory, because the first observations occur in different years and no intermediate values are being used here. **Data figure: Refugees hosted (UNHCR).** Endpoint display only: supplied first and latest hosted observations with country-specific starting years. [Open the interactive data](https://sphre.org/explore?i=unhcr%3Arefugees-hosted). Placed beside the origin measure, these latest hosting levels reveal strongly asymmetric national profiles. Germany hosts millions while its origin count is only in the hundreds. Türkiye also hosts millions, compared with an origin count in the hundreds of thousands. Pakistan hosts more than a million while its origin total remains below one hundred thousand. Iran hosts several hundred thousand, several times its latest origin count. These comparisons do not turn the countries into permanent categories, nor do they explain why the ledgers differ. They show only that, at the latest endpoint, hosting outweighs origin by a wide margin in each case. The paired measures make that imbalance visible without treating hosting and origin as interchangeable forms of the same count. **Data figure: Refugees hosted (UNHCR).** Endpoint display only for the countries with the largest latest origin totals in this selection. [Open the interactive data](https://sphre.org/explore?i=unhcr%3Arefugees-hosted). The countries leading the origin ranking occupy a different position in the hosted ledger. Sudan is substantial on both sides: its latest origin count is several million, while its hosted count is in the hundreds of thousands. Afghanistan combines an origin total in the millions with a hosted total in the tens of thousands. Syria pairs several million by origin with a hosted count in the thousands. Ukraine has the largest latest origin count in the group but a hosted total of only a few thousand; it is also the selected country whose latest hosted observation is below its first. The other three latest hosted observations are above their respective first readings. Limited to these endpoints, the conclusion is geographic and comparative: the largest origins and the largest hosts are mostly different countries, while Sudan remains conspicuous in both ledgers. # Daily briefs ## Nigeria leads the African internet-use comparison; Kenya leads on mobile subscriptions Canonical URL: https://sphre.org/brief/africa-online-2026-07-29 Published: 2026-07-29 By: SPHRE Data Desk Section: Digital endpoints The latest World Bank readings distinguish population internet use from subscriptions per person as Mozambique prioritises digital infrastructure. News from Mozambique says the country is prioritising digital infrastructure for artificial intelligence, financial services and economic growth. The World Bank indicators available here do not include Mozambique, so the useful comparison is narrower: the latest readings for Nigeria, Kenya and Ethiopia, with the United States included only as additional context. At the latest internet-use endpoint, Nigeria ranks highest among the three African countries, followed by Kenya and Ethiopia. **Data figure: Internet users.** [Open the interactive data](https://sphre.org/explore?i=IT.NET.USER.ZS). ### Two measures, different rankings Seen from Nigeria, that endpoint places internet use above the comparable shares in Kenya and Ethiopia, while still leaving a majority of people outside the indicator’s “internet user” category. The measure is a population share, not a description of what people do online or how intensively they use it. Kenya’s latest share is lower than Nigeria’s, and Ethiopia’s is lower again; the large figure above fixes Nigeria’s latest magnitude without turning that ranking into a claim about causes. Mobile-cellular subscriptions produce a different endpoint ordering. Kenya is highest among the four countries shown, including the United States; Nigeria is above Ethiopia, and both are below the United States. From Kenya’s vantage, the latest total is greater than the population when expressed per hundred people. That does not mean every Kenyan has a subscription: the indicator counts subscriptions, not unique subscribers, and one person may account for more than one. Nigeria and Ethiopia likewise cannot be read as headcounts of connected people. The comparison establishes levels, not coverage, device ownership or the timing by which one technology spread relative to another. **Data figure: Mobile subscriptions.** [Open the interactive data](https://sphre.org/explore?i=IT.CEL.SETS.P2). > A subscription total and a population share answer different questions and should not be substituted for each other. Taken together, the endpoints keep two measurements distinct. Internet use is highest in Nigeria among the African countries compared, while mobile-cellular subscriptions per person are highest in Kenya across the full group. Ethiopia is lowest among the African countries on both latest measures. Those facts can frame Mozambique’s stated priority, but they cannot evaluate it. The clearest lesson is descriptive: a country’s subscription total and its share of internet users answer different questions and should not be substituted for each other. ### What to know - Nigeria has the highest latest internet-use share among the three African countries compared. - Kenya has the highest latest mobile-subscription level across the full comparison group. - Subscriptions are not unique subscribers and cannot be read as a population headcount. --- ## Ukraine’s military expenditure was 34.5% of GDP in 2024 Canonical URL: https://sphre.org/brief/guns-and-gdp Published: 2026-07-28 By: SPHRE Data Desk Section: Guns and GDP Among five selected countries, Ukraine has the highest latest share—and the largest gap between its first and latest observations. Among the five countries in this comparison, Ukraine has the largest latest military-expenditure share: 34.5% of gross domestic product in 2024. The figure puts the domestic economy at the center of the comparison. Read from inside Ukraine, it describes military expenditure relative to the country’s own annual output, rather than its position in another country’s budget or strategy. It is a measure of economic weight, not a verdict on priorities, capacity or results. **Data figure: Military spending.** [Open the interactive data](https://sphre.org/explore?i=MS.MIL.XPND.GD.ZS). The ratio is designed to compare burden rather than the cash size of a defense budget. Ukraine’s latest share exceeds Russia’s 7.05%, Poland’s 4.15%, the United States’ 3.42% and Germany’s 1.89%, all observed in 2024. That ordering is limited to these five countries. Because the denominator is GDP, a changed ratio can result from military expenditure, total output, or movement in both; the indicator alone does not separate those contributions. ### First and latest observations point in different directions The historical view should be read through its endpoints, without inferring when or why changes occurred. Look for the distance between each country’s first available observation and its latest one. Ukraine moves from 0.435% in 1993 to 34.5% in 2024. Russia moves from 4.43% in 1992 to 7.05%; Poland from 2.65% in 1980 to 4.15%. By contrast, the United States moves from 8.99% in 1960 to 3.42%, and Germany from 3.75% in 1960 to 1.89%. **Data figure: Military spending.** Ukraine’s first-to-latest gap is much larger than the endpoint differences for the other four countries. [Open the interactive data](https://sphre.org/explore?i=MS.MIL.XPND.GD.ZS). Those endpoint comparisons show that the direction of change is not shared. Ukraine, Russia and Poland finish above their first observations, while the United States and Germany finish below theirs. The starting dates also differ, so the gaps are not changes over a common interval. What remains directly comparable is each latest share of GDP, measured under the same indicator definition. > Within this five-country comparison, Ukraine’s latest military-spending share stands apart—and far above its own first observation. A GDP share expresses scale relative to the domestic economy; it does not count equipment, personnel or outcomes. For Ukraine, the latest reading frames military expenditure against the country’s own productive base. The restrained conclusion is substantial: its burden is exceptional within this group and far above its first observation. ### What to know - Ukraine’s military expenditure was 34.5% of GDP in 2024, the highest latest share among the five countries shown. - Ukraine rose from 0.435% in 1993 to 34.5% in 2024. - The countries’ first observations come from different years, so their endpoint gaps do not cover a common interval. --- ## Korea has the lowest latest fertility value in a four-country comparison Canonical URL: https://sphre.org/brief/korea-birth-record Published: 2026-07-27 By: SPHRE Data Desk Section: Demographic endpoints World Bank endpoints show lower fertility and a larger older-population share in Korea than at the start of the supplied record. The latest World Bank fertility observations place South Korea below Japan, Italy and China in this four-country comparison. That statement is limited to the latest values supplied for each economy; it does not describe the route each series took between observations. The long-record comparison establishes a narrower but important fact. South Korea’s fertility measure is lower at the latest endpoint than at the first endpoint, as are the corresponding measures for the other three countries. The figure is a period fertility rate, summarizing births implied by current age-specific rates. It is not a birth count, a forecast, or a direct measure of completed family size. **Data figure: Fertility rate.** [Open the interactive data](https://sphre.org/explore?i=SP.DYN.TFRT.IN). ### The latest fertility comparison **Data figure: Fertility rate.** Latest supplied observations only. [Open the interactive data](https://sphre.org/explore?i=SP.DYN.TFRT.IN). The endpoint comparison also changes the meaning of the theme’s “record” label. With only the supplied first and latest observations available for verification here, the defensible claim is a lower endpoint, not an uninterrupted fall, a new all-time minimum, or a particular pace of change. The latest cross-country panel is clearer: Korea is lowest among the four, China is next, and Japan and Italy are above both, with Italy slightly above Japan. These rankings concern the same indicator and latest observation year. They do not establish why the differences exist, whether they will persist, or how annual values moved between the two endpoints. > Korea is lowest on latest fertility among the four, while its older-population share is larger than at its first endpoint. ### A separate endpoint comparison for population aging **Data figure: Aged 65 and over.** [Open the interactive data](https://sphre.org/explore?i=SP.POP.65UP.TO.ZS). **Data figure: Aged 65 and over.** Latest supplied observations only. [Open the interactive data](https://sphre.org/explore?i=SP.POP.65UP.TO.ZS). The population-age measure adds a second endpoint comparison. In South Korea, the share of people aged sixty-five and above is larger at the latest endpoint than at the first. The same endpoint direction holds for Japan, Italy and China. At the latest observation, Japan has the largest older share in this group, followed by Italy, South Korea and China. This ordering is separate from the fertility ranking: Korea has the lowest latest fertility value, but not the largest latest older share. Read together, the indicators establish coexistence, not causation. They show lower fertility and a larger older-population share at Korea’s latest endpoints than at its first ones, without identifying mechanisms or future outcomes. ### What to know - Korea’s latest fertility value is the lowest among the four countries. - For every country shown, latest fertility is below its first supplied endpoint. - Korea’s latest older-population share is above its first endpoint but below those of Japan and Italy. --- ## India ranks above China at the latest population endpoint Canonical URL: https://sphre.org/brief/population-handover Published: 2026-07-25 By: SPHRE Data Desk Section: Population endpoints World Bank indicators show a reversal in the two countries’ population ranking while distinguishing total size from annual growth. The supplied news peg concerns an anti-immigrant campaign in New Zealand. The World Bank indicators offered here do not measure attitudes, campaign support, migration, or the effects of immigration. They provide a narrower comparison: total population and annual population growth for India, China, the United States and Nigeria. Reading the first and latest observations side by side separates what these data establish from claims they cannot test. **Data figure: Population.** Annual total population; first observations are from 1960 and latest observations are from 2025. [Open the interactive data](https://sphre.org/explore?i=SP.POP.TOTL). ### The ordering reverses At the 1960 starting point, China’s total population was larger than India’s. At the 2025 endpoint, India’s was larger than China’s. Both latest totals are also above their starting totals: India rose from 436 million to 1.46 billion, while China rose from 667 million to 1.41 billion. This establishes a reversal in their ordering and substantial growth in each country across the endpoints. It does not, on its own, identify the date of the reversal or describe the route taken between those observations. > At the latest endpoint, India ranks above China; at the first, China ranked above India. The other totals widen the comparison. The United States begins and ends below both India and China, rising from 181 million in 1960 to 342 million in 2025. Nigeria also begins and ends below the two Asian countries, but its total rises from 45.1 million to 238 million. Among these four countries, the latest totals therefore place India first, China second, the United States third and Nigeria fourth. Those ranks describe population size at the latest endpoint only. ### Growth rates are a separate measure **Data figure: Population growth.** Annual population growth in percent; first observations are from 1961 and latest observations are from 2025. [Open the interactive data](https://sphre.org/explore?i=SP.POP.GROW). The growth-rate endpoints add a separate comparison. In 2025, Nigeria has the highest annual population growth rate of the four, followed by India and the United States; China’s rate is negative. Against the first supplied growth observations in 1961, the latest rates are lower for India and the United States. Nigeria’s first and latest supplied rates are both 2.06 percent. China’s rate is negative at both endpoints, with its 2025 value closer to zero than its 1961 value. These indicators do not isolate births, deaths or migration. They check population size and annual change, not immigration’s consequences or public opinion. **Data figure: Population growth.** [Open the interactive data](https://sphre.org/explore?i=SP.POP.GROW). ### What to know - India ranks above China by total population at the latest endpoint; their ordering was reversed at the first endpoint. - All four countries have higher latest population totals than at their first observations. - Nigeria has the highest latest annual population growth rate in this comparison, while China’s is negative. --- ## One inflation measure, sharply different scales Canonical URL: https://sphre.org/brief/price-of-everything Published: 2026-07-24 By: SPHRE Data Desk Section: The long view on inflation The latest annual observations place the United States and United Kingdom in the low single digits, Türkiye in the tens and Argentina in the hundreds. The World Bank indicator measures the annual percentage change in a consumer basket of goods and services. It is a rate of change, not a price-level index and not a list of individual prices. In the supplied snapshot, the latest observations for the United States and United Kingdom are in the low single digits. Türkiye’s latest observation is in the tens, and Argentina’s is in the hundreds. That ordering is the clearest comparison supported by the endpoints: all four latest rates are positive, but their magnitudes differ sharply. > An inflation rate is a speed of change, not the price level itself. ### What a positive rate establishes Positive inflation has a precise but limited meaning. It says the measured basket cost more on average than in the comparison year. It does not show that every component rose, that every buyer faced the same change, or that prices returned to any earlier level. Nor can one endpoint establish whether inflation recently accelerated, eased or passed a peak. The latest years differ across the countries, so these are the newest annual observations in the supplied snapshot, not perfectly synchronized readings. **Data figure: Inflation.** Supplied endpoints — US: 1.46% (1960), 2.95% (2024); GB: 1% (1960), 3.88% (2025); TR: 5.66% (1960), 34.9% (2025); AR: 34.3% (2018), 220% (2024). [Open the interactive data](https://sphre.org/explore?i=FP.CPI.TOTL.ZG). ### Endpoints, not trajectories The starting points add historical context without describing the path between them. The supplied series begins in 1960 for the United States, United Kingdom and Türkiye, while Argentina’s supplied run begins in 2018. For the first three countries, the initial annual rates were positive and ranged from low single digits to mid-single digits. Argentina’s first supplied rate was already in the tens. Comparing those starting and latest observations establishes endpoints only; it cannot reveal how often rates changed direction, how long particular conditions lasted or what caused the differences. The large spread also makes percentage points the useful common unit. A higher annual rate indicates a faster increase in the measured consumer basket over that year, while a lower positive rate still indicates an increase. The indicator supports comparison across countries and time, but interpretation should preserve each observation’s year and each country’s available starting date. The chart therefore presents the supplied values without filling missing history or inferring intervening movements. ### What to know - The latest rates are positive in all four countries, but they occupy sharply different scales. - A lower positive inflation rate still indicates an increase in the measured consumer basket. - First and latest observations establish endpoints, not the path or causes between them. --- ## Internet use trails mobile subscriptions across three African countries Canonical URL: https://sphre.org/brief/africa-online Published: 2026-07-22 By: SPHRE Data Desk Section: Kenya, Nigeria and Ethiopia online The latest World Bank observations show different internet-use and mobile-subscription rankings for Kenya, Nigeria and Ethiopia. The World Bank’s latest observations put internet use at different levels in Kenya, Nigeria and Ethiopia. In 2024, Nigeria has the highest share among the three, Kenya follows, and Ethiopia has the lowest. The United States is included as a benchmark and stands well above each of them. This is an endpoint comparison, not evidence that the same ordering held in every intervening year or that one explanation accounts for the gaps. **Data figure: Internet users.** Individuals using the internet (% of population). 1990: KE 0%; NG 0%; ET 0%; US 0.785%. 2024: KE 35%; NG 41.2%; ET 21.9%; US 94.7%. [Open the interactive data](https://sphre.org/explore?i=IT.NET.USER.ZS). The starting observations provide a stark baseline. Internet use was recorded at zero in Kenya, Nigeria and Ethiopia in 1990, while the United States was still below one percent. By the latest observation, all four were higher, but the gains did not produce similar endpoints. The data establish change between those observations; they do not, on their own, establish when growth was fastest or why countries arrived at different levels. > Subscriptions and internet users are different measures, and their latest rankings do not match. ### Two indicators, two different endpoints Mobile cellular subscriptions offer a second, distinct measure. At the 2024 endpoint, Kenya and the United States report more subscriptions than people, while Nigeria and Ethiopia report fewer than one subscription per person. Kenya’s subscription rate is also above the United States rate. These figures count subscriptions per hundred people, not unique subscribers, devices, coverage, connection quality or internet users. Multiple subscriptions can be associated with one person, so the measure cannot be read as a population share. **Data figure: Mobile subscriptions.** Mobile cellular subscriptions per 100 people. 1960: KE 0; NG 0; ET 0; US 0. 2024: KE 126; NG 70.8; ET 65.1; US 113. [Open the interactive data](https://sphre.org/explore?i=IT.CEL.SETS.P2). Reading the indicators side by side therefore highlights a 2024 mismatch rather than a causal story. Kenya combines the highest mobile-subscription rate in the group with internet use below Nigeria’s and far below the United States benchmark. Nigeria, meanwhile, has the highest internet-use share among the three African countries despite a lower subscription rate than Kenya. Ethiopia is lowest among the four on both latest internet use and latest mobile subscriptions. Questions about prices, devices, power, skills, service quality or policy may be relevant for further investigation, but these two indicator endpoints do not verify their role. They show outcomes measured in different units and should remain analytically separate. **Data figure: Internet users.** Latest internet-use shares for the permitted country comparison. [Open the interactive data](https://sphre.org/explore?i=IT.NET.USER.ZS). ### What to know - Nigeria has the highest latest internet-use share among Kenya, Nigeria and Ethiopia. - Kenya has the group’s highest mobile-subscription rate, but not its highest internet-use share. - The indicators count different things and do not establish why their country rankings differ. --- ## Renewable power shares rose in three of five countries from 1990 to 2021 Canonical URL: https://sphre.org/brief/power-turns-green Published: 2026-07-16 By: SPHRE Data Desk Section: Renewable electricity shares World Bank endpoints show higher renewable shares for Germany, China and the United States, but lower shares for India and Brazil. The World Bank indicator compares electricity output from renewable sources with total electricity output. Its 1990 and 2021 observations point in different directions across the five countries shown here. Germany, China and the United States had higher renewable shares at the latest endpoint than at the first. India and Brazil had lower shares. These comparisons describe the composition of electricity output at two points in time; they do not establish what happened in every intervening year or identify the reasons for each change. **Data figure: Renewable electricity.** [Open the interactive data](https://sphre.org/explore?i=EG.ELC.RNEW.ZS). > The same indicator can show a higher endpoint in one country and a lower endpoint in another without explaining the causes. ### Higher and lower endpoints Germany had the largest increase between the two endpoints among the five countries. China and the United States also ended above their 1990 shares, though their 2021 levels were below Germany’s. India’s latest share was below its first observation. Brazil also ended below its starting share, but its 2021 endpoint was still the highest of the five. The country ranking at either endpoint is distinct from the direction of change: a country can post a decline and still have a higher renewable share than countries whose shares increased. **Data figure: Renewable electricity.** Renewable electricity output as a share of total electricity output. 1990 to 2021: DE 3.47% to 39.8%; CN 20.4% to 28.4%; US 11.5% to 20.3%; IN 24.8% to 19.1%; BR 94.5% to 77.4%. [Open the interactive data](https://sphre.org/explore?i=EG.ELC.RNEW.ZS). ### What the indicator does—and does not—show Because this measure is a share, it should not be read as the amount of renewable electricity generated. A higher percentage means renewable sources accounted for more of total electricity output at that endpoint; a lower percentage means they accounted for less. The supplied observations do not show generation volumes, capacity, policy effort, electricity demand or emissions, and they do not attribute the endpoint differences to particular technologies or fuels. They also end in 2021, so any post-2021 changes in renewable electricity share are outside this comparison. ### What to know - From 1990 to 2021, renewable electricity shares rose in Germany, China and the United States. - India and Brazil had lower shares in 2021 than in 1990, while Brazil still had the highest 2021 share among the five. - The indicator measures renewable electricity as a share of total output; it does not measure renewable generation volume. --- ## Three in four people are online. The last quarter is the hard part. Canonical URL: https://sphre.org/brief/three-quarters-online Published: 2026-07-10 By: SPHRE Data Desk Section: Significant digits Twenty years ago about one person in six used the internet; the S-curve has since climbed past 73 percent — and it is now visibly flattening at the top. In 2005, about 16 percent of the world's people used the internet. The share crossed half in 2019, jumped six points in the pandemic year of 2020 as work and school moved online, and reached roughly 74 percent in 2025. On the chart, that is a textbook adoption S-curve — and the world has now climbed onto its upper shoulder, where the slope begins to fade. You can see the ceiling in the countries that arrived first. High-income countries as a group sit at about 94 percent — South Korea at 98, the United States at 95 — figures that, once you subtract small children and the resolutely offline, amount to everyone. The rich world's curves have been effectively flat for years. There is nobody easy left to connect. **Data figure: Internet users.** Share of people using the internet: the top of the S-curve is pinned in the mid-90s while India climbs the steep middle and Ethiopia trails. [Open the interactive data](https://sphre.org/explore?i=IT.NET.USER.ZS). The remaining quarter is not a thinner version of the connected three-quarters; it is a different population. Low-income countries average about 23 percent online — roughly where the rich world stood two decades ago. In all, more than two billion people remain offline, concentrated where electricity, network coverage and incomes are weakest. The global curve is behaving accordingly: the yearly gain has fallen from six percentage points in 2020 to about two now. > The internet has run out of easy people to connect. That is what saturation looks like from the inside. Most of the world came online within a single generation because networks reached people who could afford to join them the moment the wire, or the signal, arrived. The last quarter requires the opposite: grids, towers and prices reaching people the market has so far skipped. S-curves flatten for a reason — the end of an adoption story is always slower, and more expensive, than its middle. **Data figure: Internet users.** [Open the interactive data](https://sphre.org/explore?i=IT.NET.USER.ZS). **Data figure: Internet users.** [Open the interactive data](https://sphre.org/explore?i=IT.NET.USER.ZS). ### What to know - About 74 percent of humanity used the internet in 2025, up from roughly 16 percent in 2005; the halfway mark was crossed in 2019. - High-income countries are saturated at about 94 percent online while low-income countries average about 23 — leaving more than two billion people offline. - The global curve is flattening: the yearly gain has slowed from six percentage points in 2020 to about two. --- ## Two-thirds of humanity now lives below replacement Canonical URL: https://sphre.org/brief/below-replacement-majority Published: 2026-07-10 By: SPHRE Data Desk Section: Significant digits The world's average fertility rate still clears the replacement bar — but the average conceals that most of the world's people already live under it. Replacement fertility — about 2.1 births per woman, the rate at which each generation exactly refills the one before it — is demography's most famous line, and the world as a whole still sits above it. Barely. The global average stood at 2.19 births per woman in 2024, down from 4.69 in 1960. Read only the average and the story looks unfinished: humanity still replacing itself, with a little to spare. The average is hiding something. Count countries instead. In 1960, five countries in the World Bank's ledger sat below replacement. By 1990 there were 53. In 2024 there were 117 out of 215 — a solid majority of the world's nations. Weight them by population and the tilt is starker still: about two-thirds of humanity, some 5.5 billion of 8.1 billion people, now live in a country where births no longer replace the people having them. **Data figure: Fertility rate.** Births per woman since 1960: four population giants arriving at the replacement line of roughly 2.1 — India crossed it in 2020. [Open the interactive data](https://sphre.org/explore?i=SP.DYN.TFRT.IN). The newest arrivals at the threshold are the ones that move the global number. India, for decades the engine of world population growth, slipped below replacement in 2020 and recorded about 1.96 births per woman in 2024. Indonesia and Bangladesh sit almost exactly on the line. Mexico, at 1.89, is already through. These are not the greying rich countries of the usual headlines; they are young, middle-income giants whose sheer momentum will keep them growing for decades even as the arithmetic underneath turns over. > The world's fertility rate has not crossed the replacement line. Two-thirds of the world's people already have. What holds the world average above the line is, increasingly, one continent. Nigeria still records about 4.4 births per woman, and much of sub-Saharan Africa remains far from replacement. When the global average finally crosses, it will be an African story. Almost everywhere else, the crossing has already happened. **Data figure: Fertility rate.** [Open the interactive data](https://sphre.org/explore?i=SP.DYN.TFRT.IN). **Data figure: Fertility rate.** [Open the interactive data](https://sphre.org/explore?i=SP.DYN.TFRT.IN). ### What to know - The world fertility rate was 2.19 births per woman in 2024 — still above the replacement level of about 2.1, but less than half its 1960 level of 4.69. - 117 of 215 countries — home to about two-thirds of humanity, some 5.5 billion people — are now below replacement, up from five countries in 1960. - India crossed below replacement in 2020; the global average is held above the line largely by Africa, where Nigeria still records about 4.4 births per woman. --- ## The world without power is down to one region Canonical URL: https://sphre.org/brief/last-unlit-region Published: 2026-07-10 By: SPHRE Data Desk Section: Significant digits Since 2000 the number of people living without electricity has halved, to about 680 million — and nearly nine in ten of them now live in sub-Saharan Africa. In 2000, 78 percent of the world's people had electricity and 1.34 billion did not. By 2023 access had reached 91.6 percent and the unelectrified were down to about 680 million — the population of the dark halved in a generation. Most of that halving happened in Asia, and it happened almost completely: India went from 60 percent access in 2000 to 99.5 in 2023, Bangladesh from 32 to 99.5. The world's largest poor countries simply finished the job. Sub-Saharan Africa is climbing the same hill, later and against a steeper slope. Access rose from 25.7 percent in 2000 — one person in four — to 53.3 percent in 2023, crossing the halfway line in 2021. Some of the national climbs inside that average are among the fastest anywhere in the record: Kenya went from 15 percent of its people with power in 2000 to 76 percent in 2023, Rwanda from 6 to 64, Ghana from 44 to 90. **Data figure: Access to electricity.** Share of the population with electricity: Asia's giants finish the climb, Kenya sprints, Nigeria grinds, DR Congo has barely begun. [Open the interactive data](https://sphre.org/explore?i=EG.ELC.ACCS.ZS). Then comes the honest denominator. Sub-Saharan Africa's population grew from 681 million in 2000 to 1.26 billion in 2023, and the grid has been racing it. Run the multiplication and the region had about 506 million people without electricity in 2000, roughly 620 million at the 2015 peak, and 588 million in 2023 — after a generation of genuinely fast electrification, more people live without power there than did at the start. Meanwhile everyone else finished: the region held 38 percent of the world's unelectrified people in 2000, and holds 87 percent today. > Sub-Saharan Africa is winning the percentage and still losing the headcount. What remains is concentrated and hard. Nigeria, at 61 percent access, holds about 88 million people without electricity — the largest unlit population on Earth. DR Congo, at 22 percent, holds another 82 million. The continent famously got online by phone, skipping the copper the rich world spent a century laying — but there is no leapfrogging a light bulb. The last 588 million need the pole, the cable and the grid, or the one technology that finally makes the wire optional: the solar panel. **Data figure: Access to electricity.** [Open the interactive data](https://sphre.org/explore?i=EG.ELC.ACCS.ZS). **Data figure: Access to electricity.** [Open the interactive data](https://sphre.org/explore?i=EG.ELC.ACCS.ZS). ### What to know - Access to electricity reached 91.6 percent of humanity in 2023, up from 78 percent in 2000; the number of people without power roughly halved, to about 680 million. - Sub-Saharan Africa crossed 50 percent access in 2021 and reached 53.3 percent in 2023 — but population growth means the region still had 588 million people without power, more than in 2000. - The unelectrified world has concentrated in one region: sub-Saharan Africa held 38 percent of the people without electricity in 2000 and 87 percent in 2023, with Nigeria (about 88 million) and DR Congo (about 82 million) the largest unlit populations. --- ## Four million refugees went home last year Canonical URL: https://sphre.org/brief/great-return Published: 2026-07-10 By: SPHRE Data Desk Section: Significant digits The world's refugee count has fallen for two years running, and 2025's drop was the steepest in the seventy-five-year record. The reasons run through Damascus, Kabul — and the limits of welcome in Tehran and Islamabad. For most of two decades the refugee ledger ran in one direction. The number of refugees under UNHCR's mandate — a count that excludes Palestinians under UNRWA's separate agency — nearly doubled between 2015 and 2023, from 16.1 million to a record 31.6 million. Then the line turned. In 2024 the count fell by about 700,000, the first decline since 2011. In 2025 it fell by 2.5 million more, to 28.5 million — the largest one-year drop in a record that reaches back to 1951. What turned it was not fewer wars but more homecomings. About 4.4 million refugees returned to their countries in 2025, the most since 1972, when nearly ten million streamed back into newly independent Bangladesh. Syria is the emblem: after the fall of the Assad government in December 2024, 1.3 million Syrian refugees went home in 2025, and the Syrian total — 6.8 million at its 2021 peak — is down to 4.9 million. Afghanistan's ledger moved even harder, and far less freely. Nearly two million Afghans returned in 2025, overwhelmingly from Iran and Pakistan, many under heavy pressure to leave; Iran, which hosted 3.5 million refugees at the end of 2024, recorded fewer than 800,000 a year later. **Data figure: Refugees abroad (UNHCR).** Refugees by country of origin: Afghanistan's four-decade mountain, Syria's long decade, Ukraine's single-year cliff — and Sudan's fresh climb. [Open the interactive data](https://sphre.org/explore?i=unhcr%3Arefugees-origin). The rest of the ledger shows why nobody at UNHCR is celebrating. Sudan's civil war has pushed 2.8 million people across its borders, more than three times the 2022 figure — Sudan now ranks third among origin countries, ahead of Afghanistan. Ukraine remains first, at 5.2 million. And the hosting table has been rewritten: with Iran's and Turkey's numbers falling, Germany, at 2.7 million, is now the world's largest refugee host — the first Western country to top that table since the United States in 1978. > The biggest line in the 2025 ledger is not a new exodus. It is the road home. **Data figure: Refugees abroad (UNHCR).** [Open the interactive data](https://sphre.org/explore?i=unhcr%3Arefugees-origin). **Data figure: Refugees abroad (UNHCR).** [Open the interactive data](https://sphre.org/explore?i=unhcr%3Arefugees-origin). ### What to know - Refugees under UNHCR's mandate peaked at a record 31.6 million at the end of 2023 and have fallen for two straight years, to 28.5 million at end-2025; the 2.5 million drop in 2025 is the largest in the record. - About 4.4 million refugees went home in 2025, the most since 1972 — 1.3 million to Syria after the Assad government fell, and nearly 2 million to Afghanistan, many under pressure from Iran and Pakistan. - The map keeps moving: Sudan (2.8 million refugees abroad) has passed Afghanistan to rank third among origin countries, and Germany (2.7 million hosted) is the first Western country to be the world's largest host since the United States in 1978. --- ## The grid spent 13 years getting less green Canonical URL: https://sphre.org/brief/grid-u-turn Published: 2026-07-09 By: SPHRE Data Desk Section: Significant digits Renewables' share of the world's electricity fell from 1990 to 2003 before wind and solar turned it around — the most underrated U-turn in the energy data. Here is a shape nobody expects to find in the climate data: from 1990 to 2003, the renewable share of the world's electricity went down. It started the period at 19.3 percent and bottomed out around 17.8 — thirteen years of a supposedly inevitable transition running in reverse. For anyone who assumes the world's grid has been greening steadily for as long as anyone has measured it, the first stretch of the record is a correction. Nothing was wrong with the dams. The problem was the denominator. The 1990s and early 2000s were the great age of coal-fired growth in Asia, and new fossil generation swamped a renewable fleet that was still mostly hydropower. China's own renewable share slid from about 20 percent in 1990 to 15 by 2003; India's fell from roughly 25 to under 12. The world was electrifying much faster than it was greening. **Data figure: Renewable electricity.** Renewable share of electricity output: the Asian giants dip through 2003 while Britain and Denmark climb from almost nothing. [Open the interactive data](https://sphre.org/explore?i=EG.ELC.RNEW.ZS). Then the line turned. Wind and solar — a rounding error in 1990 — began growing faster than electricity demand itself, and the world's renewable share climbed back through its old peak and kept going, reaching about 28 percent by 2020. The steepest conversions were engineered, not inherited: Britain went from under 2 percent renewable electricity in 1990 to about 40 percent two decades into this century; Denmark went from 3 percent to 79. > The green grid didn't grow out of the old one. It had to outrun it. That is the lesson buried in the U-turn: a share is a race. Renewables lost the 1990s not by shrinking but by growing more slowly than everything else, and they have been winning since only because wind and solar now outbuild the competition. Ten points of share gained in seventeen years, against a grid that never stopped expanding, is what winning looks like — slow arithmetic, fast construction. **Data figure: Renewable electricity.** [Open the interactive data](https://sphre.org/explore?i=EG.ELC.RNEW.ZS). **Data figure: Renewable electricity.** [Open the interactive data](https://sphre.org/explore?i=EG.ELC.RNEW.ZS). ### What to know - The renewable share of world electricity fell from 19.3 percent in 1990 to about 17.8 in 2003, as Asia's coal boom outgrew a mostly-hydro renewable fleet. - Wind and solar reversed the slide; by 2020 the world's renewable share had climbed to about 28 percent. - The steepest climbs were engineered, not inherited: Britain went from under 2 percent renewable electricity to about 40, Denmark from 3 to 79. --- ## The 28-year life-expectancy gap is down to 16 Canonical URL: https://sphre.org/brief/sixteen-year-gap Published: 2026-07-09 By: SPHRE Data Desk Section: Significant digits In 1960 a North American could expect to outlive a sub-Saharan African by nearly three decades. The distance has almost halved — because the bottom rose. In 1960, life expectancy at birth was 69.9 years in North America and 41.4 years in sub-Saharan Africa — a gap of 28.5 years between the world's luckiest and unluckiest regions. It was the cruelest single fact in the global ledger: the length of a life, set mostly by where it began. Sixty-four years of data later the fact is still true. It is just much smaller. By 2024 the gap had narrowed to 16.4 years, and the arithmetic of the narrowing is the point. North America added about nine years over the period; sub-Saharan Africa added more than twenty-one. The convergence came almost entirely from the bottom rising, not the top stalling — vaccines, antibiotics, clean water and the collapse of child mortality doing quiet, compounding work. **Data figure: Life expectancy.** Life expectancy at birth: China's 1960 figure is a famine-year trough; its line has since drawn level with the United States. [Open the interactive data](https://sphre.org/explore?i=SP.DYN.LE00.IN). The regional record belongs to East Asia, which gained 35 years over the period, from 41.7 in 1960 to 76.7 in 2024. China embodies the run: from 33.4 years in the famine year of 1960 to 78.0 today, statistically shoulder to shoulder with the United States at 78.9. The world average, meanwhile, crossed 70 in 2008 and now stands at about 73.5 — more than twenty-two years longer than in 1960. > Sixty-four years of medicine and plumbing bought back twelve of the twenty-eight years that geography once stole. Honesty requires the other half of the ledger. Sub-Saharan Africa's 62.8 years in 2024 still falls seven years short of what North America already had in 1960 — on this yardstick, the region runs more than six decades behind. And the same halving shows up between income groups, where the high-income-to-low-income gap fell from 27.1 years to 15.2. The pattern is global. So is the unfinished business. **Data figure: Life expectancy.** [Open the interactive data](https://sphre.org/explore?i=SP.DYN.LE00.IN). **Data figure: Life expectancy.** [Open the interactive data](https://sphre.org/explore?i=SP.DYN.LE00.IN). ### What to know - The life-expectancy gap between North America and sub-Saharan Africa narrowed from 28.5 years in 1960 to 16.4 in 2024. - East Asia gained 35 years of life expectancy over the period; China went from a famine-year 33.4 to 78.0, statistically level with the United States. - Sub-Saharan Africa today still sits about seven years below North America's 1960 level — the convergence is real, and unfinished. # Indicator catalog - Population (SP.POP.TOTL; people; Population & demography) — https://sphre.org/indicator/SP.POP.TOTL - Population growth (SP.POP.GROW; % per year; Population & demography) — https://sphre.org/indicator/SP.POP.GROW - Fertility rate (SP.DYN.TFRT.IN; births per woman; Population & demography) — https://sphre.org/indicator/SP.DYN.TFRT.IN - Birth rate (SP.DYN.CBRT.IN; per 1,000 people; Population & demography) — https://sphre.org/indicator/SP.DYN.CBRT.IN - Death rate (SP.DYN.CDRT.IN; per 1,000 people; Population & demography) — https://sphre.org/indicator/SP.DYN.CDRT.IN - Teenage fertility (SP.ADO.TFRT; births per 1,000 women 15–19; Population & demography) — https://sphre.org/indicator/SP.ADO.TFRT - Children under 15 (SP.POP.0014.TO.ZS; % of population; Population & demography) — https://sphre.org/indicator/SP.POP.0014.TO.ZS - Working-age population (SP.POP.1564.TO.ZS; % of population; Population & demography): Share of the population aged 15–64. — https://sphre.org/indicator/SP.POP.1564.TO.ZS - Aged 65 and over (SP.POP.65UP.TO.ZS; % of population; Population & demography) — https://sphre.org/indicator/SP.POP.65UP.TO.ZS - Dependency ratio (SP.POP.DPND; % of working-age population; Population & demography): Young and old dependents per 100 people of working age. — https://sphre.org/indicator/SP.POP.DPND - Net migration (SM.POP.NETM; people; Population & demography): Immigrants minus emigrants over the period. — https://sphre.org/indicator/SM.POP.NETM - Population density (EN.POP.DNST; people per sq. km; Population & demography) — https://sphre.org/indicator/EN.POP.DNST - Female share of population (SP.POP.TOTL.FE.ZS; % of population; Population & demography) — https://sphre.org/indicator/SP.POP.TOTL.FE.ZS - Life expectancy (SP.DYN.LE00.IN; years; Health & mortality) — https://sphre.org/indicator/SP.DYN.LE00.IN - Life expectancy, women (SP.DYN.LE00.FE.IN; years; Health & mortality) — https://sphre.org/indicator/SP.DYN.LE00.FE.IN - Life expectancy, men (SP.DYN.LE00.MA.IN; years; Health & mortality) — https://sphre.org/indicator/SP.DYN.LE00.MA.IN - Infant mortality (SP.DYN.IMRT.IN; per 1,000 live births; Health & mortality) — https://sphre.org/indicator/SP.DYN.IMRT.IN - Under-5 mortality (SH.DYN.MORT; per 1,000 live births; Health & mortality) — https://sphre.org/indicator/SH.DYN.MORT - Maternal mortality (SH.STA.MMRT; deaths per 100,000 live births; Health & mortality) — https://sphre.org/indicator/SH.STA.MMRT - Adult mortality, men (SP.DYN.AMRT.MA; per 1,000 male adults; Health & mortality): Probability of dying between ages 15 and 60. — https://sphre.org/indicator/SP.DYN.AMRT.MA - Adult mortality, women (SP.DYN.AMRT.FE; per 1,000 female adults; Health & mortality): Probability of dying between ages 15 and 60. — https://sphre.org/indicator/SP.DYN.AMRT.FE - Health spending (SH.XPD.CHEX.GD.ZS; % of GDP; Health & mortality) — https://sphre.org/indicator/SH.XPD.CHEX.GD.ZS - Health spending per person (SH.XPD.CHEX.PC.CD; current US$; Health & mortality) — https://sphre.org/indicator/SH.XPD.CHEX.PC.CD - Hospital beds (SH.MED.BEDS.ZS; per 1,000 people; Health & mortality) — https://sphre.org/indicator/SH.MED.BEDS.ZS - Physicians (SH.MED.PHYS.ZS; per 1,000 people; Health & mortality) — https://sphre.org/indicator/SH.MED.PHYS.ZS - Measles immunization (SH.IMM.MEAS; % of children 12–23 months; Health & mortality) — https://sphre.org/indicator/SH.IMM.MEAS - HIV prevalence (SH.DYN.AIDS.ZS; % of ages 15–49; Health & mortality) — https://sphre.org/indicator/SH.DYN.AIDS.ZS - Tobacco use (SH.PRV.SMOK; % of adults; Health & mortality): Current use of any tobacco product, ages 15+, age-standardized — includes smokeless tobacco. — https://sphre.org/indicator/SH.PRV.SMOK - Overweight adults (SH.STA.OWAD.ZS; % of adults; Health & mortality) — https://sphre.org/indicator/SH.STA.OWAD.ZS - Undernourishment (SN.ITK.DEFC.ZS; % of population; Health & mortality) — https://sphre.org/indicator/SN.ITK.DEFC.ZS - GDP (NY.GDP.MKTP.CD; current US$; Economy & growth) — https://sphre.org/indicator/NY.GDP.MKTP.CD - GDP growth (NY.GDP.MKTP.KD.ZG; % per year; Economy & growth) — https://sphre.org/indicator/NY.GDP.MKTP.KD.ZG - GDP per person (NY.GDP.PCAP.CD; current US$; Economy & growth) — https://sphre.org/indicator/NY.GDP.PCAP.CD - GDP per person growth (NY.GDP.PCAP.KD.ZG; % per year; Economy & growth) — https://sphre.org/indicator/NY.GDP.PCAP.KD.ZG - GDP per person, PPP (NY.GDP.PCAP.PP.CD; current international $; Economy & growth): Adjusted for purchasing power across countries. — https://sphre.org/indicator/NY.GDP.PCAP.PP.CD - GNI per person (NY.GNP.PCAP.CD; current US$; Economy & growth) — https://sphre.org/indicator/NY.GNP.PCAP.CD - Agriculture share of GDP (NV.AGR.TOTL.ZS; % of GDP; Economy & growth) — https://sphre.org/indicator/NV.AGR.TOTL.ZS - Industry share of GDP (NV.IND.TOTL.ZS; % of GDP; Economy & growth) — https://sphre.org/indicator/NV.IND.TOTL.ZS - Services share of GDP (NV.SRV.TOTL.ZS; % of GDP; Economy & growth) — https://sphre.org/indicator/NV.SRV.TOTL.ZS - Investment (NE.GDI.TOTL.ZS; % of GDP; Economy & growth): Gross capital formation. — https://sphre.org/indicator/NE.GDI.TOTL.ZS - Government consumption (NE.CON.GOVT.ZS; % of GDP; Economy & growth) — https://sphre.org/indicator/NE.CON.GOVT.ZS - Domestic savings (NY.GDS.TOTL.ZS; % of GDP; Economy & growth) — https://sphre.org/indicator/NY.GDS.TOTL.ZS - Inflation (FP.CPI.TOTL.ZG; % per year; Money, prices & debt) — https://sphre.org/indicator/FP.CPI.TOTL.ZG - Consumer price index (FP.CPI.TOTL; 2010 = 100; Money, prices & debt) — https://sphre.org/indicator/FP.CPI.TOTL - GDP deflator inflation (NY.GDP.DEFL.KD.ZG; % per year; Money, prices & debt) — https://sphre.org/indicator/NY.GDP.DEFL.KD.ZG - Real interest rate (FR.INR.RINR; %; Money, prices & debt) — https://sphre.org/indicator/FR.INR.RINR - Lending rate (FR.INR.LEND; %; Money, prices & debt) — https://sphre.org/indicator/FR.INR.LEND - Government debt (GC.DOD.TOTL.GD.ZS; % of GDP; Money, prices & debt): Central government debt, total. — https://sphre.org/indicator/GC.DOD.TOTL.GD.ZS - Tax revenue (GC.TAX.TOTL.GD.ZS; % of GDP; Money, prices & debt) — https://sphre.org/indicator/GC.TAX.TOTL.GD.ZS - Credit to private sector (FS.AST.PRVT.GD.ZS; % of GDP; Money, prices & debt) — https://sphre.org/indicator/FS.AST.PRVT.GD.ZS - Stock market size (CM.MKT.LCAP.GD.ZS; % of GDP; Money, prices & debt) — https://sphre.org/indicator/CM.MKT.LCAP.GD.ZS - Exchange rate (PA.NUS.FCRF; LCU per US$; Money, prices & debt) — https://sphre.org/indicator/PA.NUS.FCRF - Foreign reserves (FI.RES.TOTL.CD; current US$; Money, prices & debt): Total reserves including gold. — https://sphre.org/indicator/FI.RES.TOTL.CD - External debt (DT.DOD.DECT.GD.ZS; % of GNI; Money, prices & debt) — https://sphre.org/indicator/DT.DOD.DECT.GD.ZS - Unemployment (SL.UEM.TOTL.ZS; % of labor force; Work & income) — https://sphre.org/indicator/SL.UEM.TOTL.ZS - Youth unemployment (SL.UEM.1524.ZS; % of labor force 15–24; Work & income) — https://sphre.org/indicator/SL.UEM.1524.ZS - Labor force participation (SL.TLF.CACT.ZS; % of ages 15+; Work & income) — https://sphre.org/indicator/SL.TLF.CACT.ZS - Women in the labor force (SL.TLF.CACT.FE.ZS; % of female ages 15+; Work & income) — https://sphre.org/indicator/SL.TLF.CACT.FE.ZS - Labor force (SL.TLF.TOTL.IN; people; Work & income) — https://sphre.org/indicator/SL.TLF.TOTL.IN - Employment in agriculture (SL.AGR.EMPL.ZS; % of employment; Work & income) — https://sphre.org/indicator/SL.AGR.EMPL.ZS - Employment in industry (SL.IND.EMPL.ZS; % of employment; Work & income) — https://sphre.org/indicator/SL.IND.EMPL.ZS - Employment in services (SL.SRV.EMPL.ZS; % of employment; Work & income) — https://sphre.org/indicator/SL.SRV.EMPL.ZS - Gini index (SI.POV.GINI; index (0–100); Work & income): Income inequality; higher is more unequal. — https://sphre.org/indicator/SI.POV.GINI - Extreme poverty (SI.POV.DDAY; % of population; Work & income): Living on under $2.15 a day (2017 PPP). — https://sphre.org/indicator/SI.POV.DDAY - Income share of poorest 20% (SI.DST.FRST.20; % of income; Work & income) — https://sphre.org/indicator/SI.DST.FRST.20 - Income share of richest 10% (SI.DST.10TH.10; % of income; Work & income) — https://sphre.org/indicator/SI.DST.10TH.10 - Exports (NE.EXP.GNFS.ZS; % of GDP; Trade & globalization) — https://sphre.org/indicator/NE.EXP.GNFS.ZS - Imports (NE.IMP.GNFS.ZS; % of GDP; Trade & globalization) — https://sphre.org/indicator/NE.IMP.GNFS.ZS - Trade openness (NE.TRD.GNFS.ZS; % of GDP; Trade & globalization): Exports plus imports of goods and services. — https://sphre.org/indicator/NE.TRD.GNFS.ZS - Merchandise trade (TG.VAL.TOTL.GD.ZS; % of GDP; Trade & globalization) — https://sphre.org/indicator/TG.VAL.TOTL.GD.ZS - Foreign direct investment (BX.KLT.DINV.WD.GD.ZS; % of GDP; Trade & globalization): Net inflows. — https://sphre.org/indicator/BX.KLT.DINV.WD.GD.ZS - Current account balance (BN.CAB.XOKA.GD.ZS; % of GDP; Trade & globalization) — https://sphre.org/indicator/BN.CAB.XOKA.GD.ZS - Remittances received (BX.TRF.PWKR.DT.GD.ZS; % of GDP; Trade & globalization) — https://sphre.org/indicator/BX.TRF.PWKR.DT.GD.ZS - Fuel exports (TX.VAL.FUEL.ZS.UN; % of merchandise exports; Trade & globalization) — https://sphre.org/indicator/TX.VAL.FUEL.ZS.UN - Manufactures exports (TX.VAL.MANF.ZS.UN; % of merchandise exports; Trade & globalization) — https://sphre.org/indicator/TX.VAL.MANF.ZS.UN - Tourist arrivals (ST.INT.ARVL; arrivals; Trade & globalization) — https://sphre.org/indicator/ST.INT.ARVL - Tourism receipts (ST.INT.RCPT.CD; current US$; Trade & globalization) — https://sphre.org/indicator/ST.INT.RCPT.CD - Aid received (DT.ODA.ODAT.GN.ZS; % of GNI; Trade & globalization): Net official development assistance. — https://sphre.org/indicator/DT.ODA.ODAT.GN.ZS - Adult literacy (SE.ADT.LITR.ZS; % of ages 15+; Education) — https://sphre.org/indicator/SE.ADT.LITR.ZS - Youth literacy (SE.ADT.1524.LT.ZS; % of ages 15–24; Education) — https://sphre.org/indicator/SE.ADT.1524.LT.ZS - Primary enrollment (SE.PRM.NENR; % net; Education) — https://sphre.org/indicator/SE.PRM.NENR - Secondary enrollment (SE.SEC.NENR; % net; Education) — https://sphre.org/indicator/SE.SEC.NENR - Tertiary enrollment (SE.TER.ENRR; % gross; Education): Gross ratio; can exceed 100%. — https://sphre.org/indicator/SE.TER.ENRR - Primary completion (SE.PRM.CMPT.ZS; % of relevant age group; Education) — https://sphre.org/indicator/SE.PRM.CMPT.ZS - Education spending (SE.XPD.TOTL.GD.ZS; % of GDP; Education) — https://sphre.org/indicator/SE.XPD.TOTL.GD.ZS - Compulsory schooling (SE.COM.DURS; years; Education) — https://sphre.org/indicator/SE.COM.DURS - Pupil–teacher ratio, primary (SE.PRM.ENRL.TC.ZS; pupils per teacher; Education) — https://sphre.org/indicator/SE.PRM.ENRL.TC.ZS - Gender parity in school (SE.ENR.PRSC.FM.ZS; gender parity index; Education): Girls-to-boys enrollment ratio; 1 is parity. — https://sphre.org/indicator/SE.ENR.PRSC.FM.ZS - Energy use per person (EG.USE.PCAP.KG.OE; kg of oil equivalent; Energy & environment) — https://sphre.org/indicator/EG.USE.PCAP.KG.OE - Electricity use per person (EG.USE.ELEC.KH.PC; kWh; Energy & environment) — https://sphre.org/indicator/EG.USE.ELEC.KH.PC - Access to electricity (EG.ELC.ACCS.ZS; % of population; Energy & environment) — https://sphre.org/indicator/EG.ELC.ACCS.ZS - Renewable energy share (EG.FEC.RNEW.ZS; % of final consumption; Energy & environment) — https://sphre.org/indicator/EG.FEC.RNEW.ZS - Renewable electricity (EG.ELC.RNEW.ZS; % of electricity output; Energy & environment) — https://sphre.org/indicator/EG.ELC.RNEW.ZS - Energy imports (EG.IMP.CONS.ZS; % of energy use; Energy & environment): Net imports; negative means net exporter. — https://sphre.org/indicator/EG.IMP.CONS.ZS - CO2 emissions per person (EN.GHG.CO2.PC.CE.AR5; tonnes CO2e; Energy & environment) — https://sphre.org/indicator/EN.GHG.CO2.PC.CE.AR5 - Greenhouse gases per person (EN.GHG.ALL.PC.CE.AR5; tonnes CO2e; Energy & environment) — https://sphre.org/indicator/EN.GHG.ALL.PC.CE.AR5 - CO2 emissions (EN.GHG.CO2.MT.CE.AR5; million tonnes CO2e; Energy & environment) — https://sphre.org/indicator/EN.GHG.CO2.MT.CE.AR5 - Air pollution (EN.ATM.PM25.MC.M3; micrograms per cubic meter; Energy & environment): Mean annual PM2.5 exposure. — https://sphre.org/indicator/EN.ATM.PM25.MC.M3 - Protected areas (ER.PTD.TOTL.ZS; % of territorial area; Energy & environment) — https://sphre.org/indicator/ER.PTD.TOTL.ZS - Land area (AG.LND.TOTL.K2; sq. km; Land & agriculture) — https://sphre.org/indicator/AG.LND.TOTL.K2 - Agricultural land (AG.LND.AGRI.ZS; % of land area; Land & agriculture) — https://sphre.org/indicator/AG.LND.AGRI.ZS - Arable land (AG.LND.ARBL.ZS; % of land area; Land & agriculture) — https://sphre.org/indicator/AG.LND.ARBL.ZS - Arable land per person (AG.LND.ARBL.HA.PC; hectares; Land & agriculture) — https://sphre.org/indicator/AG.LND.ARBL.HA.PC - Forest area (AG.LND.FRST.ZS; % of land area; Land & agriculture) — https://sphre.org/indicator/AG.LND.FRST.ZS - Permanent cropland (AG.LND.CROP.ZS; % of land area; Land & agriculture) — https://sphre.org/indicator/AG.LND.CROP.ZS - Cereal yield (AG.YLD.CREL.KG; kg per hectare; Land & agriculture) — https://sphre.org/indicator/AG.YLD.CREL.KG - Cereal production (AG.PRD.CREL.MT; metric tons; Land & agriculture) — https://sphre.org/indicator/AG.PRD.CREL.MT - Fertilizer use (AG.CON.FERT.ZS; kg per hectare of arable land; Land & agriculture) — https://sphre.org/indicator/AG.CON.FERT.ZS - Rural population (SP.RUR.TOTL.ZS; % of population; Land & agriculture) — https://sphre.org/indicator/SP.RUR.TOTL.ZS - Share living in cities (SP.URB.TOTL.IN.ZS; % of population; Cities & infrastructure) — https://sphre.org/indicator/SP.URB.TOTL.IN.ZS - Urban population (SP.URB.TOTL; people; Cities & infrastructure) — https://sphre.org/indicator/SP.URB.TOTL - Urban population growth (SP.URB.GROW; % per year; Cities & infrastructure) — https://sphre.org/indicator/SP.URB.GROW - Largest city population (EN.URB.LCTY; people; Cities & infrastructure) — https://sphre.org/indicator/EN.URB.LCTY - Largest city share (EN.URB.LCTY.UR.ZS; % of urban population; Cities & infrastructure) — https://sphre.org/indicator/EN.URB.LCTY.UR.ZS - Big-city population (EN.URB.MCTY.TL.ZS; % of population; Cities & infrastructure): Living in agglomerations of over 1 million. — https://sphre.org/indicator/EN.URB.MCTY.TL.ZS - Basic drinking water (SH.H2O.BASW.ZS; % of population; Cities & infrastructure) — https://sphre.org/indicator/SH.H2O.BASW.ZS - Basic sanitation (SH.STA.BASS.ZS; % of population; Cities & infrastructure) — https://sphre.org/indicator/SH.STA.BASS.ZS - Air passengers (IS.AIR.PSGR; passengers; Cities & infrastructure) — https://sphre.org/indicator/IS.AIR.PSGR - Aircraft departures (IS.AIR.DPRT; departures; Cities & infrastructure) — https://sphre.org/indicator/IS.AIR.DPRT - Rail lines (IS.RRS.TOTL.KM; route-km; Cities & infrastructure) — https://sphre.org/indicator/IS.RRS.TOTL.KM - Internet users (IT.NET.USER.ZS; % of population; Technology & connectivity) — https://sphre.org/indicator/IT.NET.USER.ZS - Mobile subscriptions (IT.CEL.SETS.P2; per 100 people; Technology & connectivity) — https://sphre.org/indicator/IT.CEL.SETS.P2 - Fixed telephone lines (IT.MLT.MAIN.P2; per 100 people; Technology & connectivity) — https://sphre.org/indicator/IT.MLT.MAIN.P2 - Fixed broadband (IT.NET.BBND.P2; per 100 people; Technology & connectivity) — https://sphre.org/indicator/IT.NET.BBND.P2 - R&D spending (GB.XPD.RSDV.GD.ZS; % of GDP; Technology & connectivity) — https://sphre.org/indicator/GB.XPD.RSDV.GD.ZS - Researchers (SP.POP.SCIE.RD.P6; per million people; Technology & connectivity) — https://sphre.org/indicator/SP.POP.SCIE.RD.P6 - Patent applications (IP.PAT.RESD; applications; Technology & connectivity): Filed by residents. — https://sphre.org/indicator/IP.PAT.RESD - Scientific articles (IP.JRN.ARTC.SC; articles; Technology & connectivity) — https://sphre.org/indicator/IP.JRN.ARTC.SC - High-tech exports (TX.VAL.TECH.MF.ZS; % of manufactured exports; Technology & connectivity) — https://sphre.org/indicator/TX.VAL.TECH.MF.ZS - Women in parliament (SG.GEN.PARL.ZS; % of seats; Society, gender & state) — https://sphre.org/indicator/SG.GEN.PARL.ZS - Female-to-male labor ratio (SL.TLF.CACT.FM.ZS; %; Society, gender & state): Female participation rate as a share of male. — https://sphre.org/indicator/SL.TLF.CACT.FM.ZS - Birth registration (SP.REG.BRTH.ZS; % of children under 5; Society, gender & state) — https://sphre.org/indicator/SP.REG.BRTH.ZS - Military spending (MS.MIL.XPND.GD.ZS; % of GDP; Society, gender & state) — https://sphre.org/indicator/MS.MIL.XPND.GD.ZS - Armed forces personnel (MS.MIL.TOTL.P1; people; Society, gender & state) — https://sphre.org/indicator/MS.MIL.TOTL.P1 - Homicide rate (VC.IHR.PSRC.P5; per 100,000 people; Society, gender & state) — https://sphre.org/indicator/VC.IHR.PSRC.P5 - Suicide rate (SH.STA.SUIC.P5; per 100,000 people; Society, gender & state) — https://sphre.org/indicator/SH.STA.SUIC.P5 - Life expectancy (long-run) (owid:life-expectancy-long-run; years; Climate, history & governance): Reaches back to the 1700s for some countries — well before the World Bank series starts. — https://sphre.org/indicator/owid:life-expectancy-long-run - Population (long-run) (owid:population-long-run; people; Climate, history & governance): HYDE and Gapminder historical reconstructions joined to UN WPP. The chart reaches 10,000 BCE upstream; our snapshot keeps 1800 onward, where the annual series begins. — https://sphre.org/indicator/owid:population-long-run - Maternal mortality (long-run) (owid:maternal-mortality-long-run; deaths per 100,000 live births; Climate, history & governance): Historical estimates reaching back to the 1700s for some countries. — https://sphre.org/indicator/owid:maternal-mortality-long-run - Child mortality (long-run) (owid:child-mortality-long-run; deaths per 100 live births; Climate, history & governance): Share of children dying before age five — Gapminder historical estimates back to 1751 joined to UN IGME. — https://sphre.org/indicator/owid:child-mortality-long-run - Measles cases reported (owid:measles-cases; reported cases; Climate, history & governance): WHO surveillance data — traces vaccination-era disease decline. — https://sphre.org/indicator/owid:measles-cases - Coal production (owid:coal-production; terawatt-hours; Climate, history & governance): Reaches back to the 1700s for early industrializers like the UK. — https://sphre.org/indicator/owid:coal-production - Nuclear electricity generation (owid:nuclear-generation; terawatt-hours; Climate, history & governance) — https://sphre.org/indicator/owid:nuclear-generation - Solar electricity generation (owid:solar-generation; terawatt-hours; Climate, history & governance) — https://sphre.org/indicator/owid:solar-generation - Wind electricity generation (owid:wind-generation; terawatt-hours; Climate, history & governance) — https://sphre.org/indicator/owid:wind-generation - Renewable share of primary energy (owid:renewable-energy-share; % of primary energy; Climate, history & governance): Energy Institute data on renewables (excluding traditional biomass) as a share of primary energy consumption. — https://sphre.org/indicator/owid:renewable-energy-share - Clean cooking fuel access (owid:clean-cooking-fuels; % of population; Climate, history & governance): Primary reliance on clean fuels and technologies for cooking (WHO). — https://sphre.org/indicator/owid:clean-cooking-fuels - CO2 emissions (globalcarbon:co2; million tonnes CO2; Carbon & emissions): Annual production-based emissions of CO2 from fossil fuels and industry, excluding land-use change. — https://sphre.org/indicator/globalcarbon:co2 - CO2 emissions per person (globalcarbon:co2-per-capita; tonnes CO2 per person; Carbon & emissions): CO2 from fossil fuels and industry, divided by population. — https://sphre.org/indicator/globalcarbon:co2-per-capita - Greenhouse gases per person (globalcarbon:ghg-per-capita; tonnes CO2 equivalent per person; Carbon & emissions): All greenhouse gases including land use (100-year CO2-equivalent basis), divided by population. — https://sphre.org/indicator/globalcarbon:ghg-per-capita - Total greenhouse gases (globalcarbon:total-ghg; million tonnes CO2 equivalent; Carbon & emissions): All greenhouse gases including land use (100-year CO2-equivalent basis), not just CO2. — https://sphre.org/indicator/globalcarbon:total-ghg - Cumulative CO2 emissions (globalcarbon:cumulative-co2; million tonnes CO2; Carbon & emissions): Total CO2 emitted since the first year of available data (1750), excluding land-use change. — https://sphre.org/indicator/globalcarbon:cumulative-co2 - CO2 from coal (globalcarbon:coal-co2; million tonnes CO2; Carbon & emissions): Annual CO2 emissions from burning coal. — https://sphre.org/indicator/globalcarbon:coal-co2 - CO2 from oil (globalcarbon:oil-co2; million tonnes CO2; Carbon & emissions): Annual CO2 emissions from burning oil. — https://sphre.org/indicator/globalcarbon:oil-co2 - CO2 from gas (globalcarbon:gas-co2; million tonnes CO2; Carbon & emissions): Annual CO2 emissions from burning natural gas. — https://sphre.org/indicator/globalcarbon:gas-co2 - CO2 from cement (globalcarbon:cement-co2; million tonnes CO2; Carbon & emissions): Annual CO2 emissions from cement production. — https://sphre.org/indicator/globalcarbon:cement-co2 - Consumption-based CO2 emissions (globalcarbon:consumption-co2; million tonnes CO2; Carbon & emissions): CO2 adjusted for trade — emissions embedded in goods actually consumed, not just produced, within a country. — https://sphre.org/indicator/globalcarbon:consumption-co2 - Refugees hosted (UNHCR) (unhcr:refugees-hosted; people; Displacement & migration): People granted refugee status, by country of asylum. Source: UNHCR. — https://sphre.org/indicator/unhcr:refugees-hosted - Refugees abroad (UNHCR) (unhcr:refugees-origin; people; Displacement & migration): People granted refugee status, by country of origin. Source: UNHCR. — https://sphre.org/indicator/unhcr:refugees-origin - Asylum seekers pending (unhcr:asylum-seekers; people; Displacement & migration): People with a pending asylum application at year end, by country of asylum. Source: UNHCR. — https://sphre.org/indicator/unhcr:asylum-seekers - Internally displaced persons (unhcr:idps; people; Displacement & migration): People displaced within their own country and of concern to UNHCR. Source: UNHCR. — https://sphre.org/indicator/unhcr:idps - DTP3 immunization (who:dtp3-immunization; % of one-year-olds; Global health): Children who received three doses of diphtheria-tetanus-pertussis vaccine by age one. — https://sphre.org/indicator/who:dtp3-immunization - Measles immunization, 2nd dose (who:mcv2-immunization; % of children; Global health): Children who received a second measles-vaccine dose by the nationally recommended age. — https://sphre.org/indicator/who:mcv2-immunization - Tuberculosis incidence (who:tb-incidence; per 100,000 people; Global health): Estimated new and relapse tuberculosis cases per year. — https://sphre.org/indicator/who:tb-incidence - Malaria incidence (who:malaria-incidence; per 1,000 at risk; Global health): Estimated cases per 1,000 population at risk; only countries with ongoing transmission are estimated. — https://sphre.org/indicator/who:malaria-incidence - NCD mortality, ages 30–70 (who:ncd-mortality-30-70; % probability; Global health): Probability of dying between ages 30 and 70 from cardiovascular disease, cancer, diabetes, or chronic respiratory disease. — https://sphre.org/indicator/who:ncd-mortality-30-70 - Smoking prevalence (who:smoking-prevalence; % of adults; Global health): Current tobacco smoking, ages 15+, age-standardized. Narrower than the tobacco-use series, which also counts smokeless products. — https://sphre.org/indicator/who:smoking-prevalence - Alcohol consumption (who:alcohol-consumption; litres of pure alcohol per person 15+; Global health): Recorded consumption per person aged 15 and over, all beverage types. — https://sphre.org/indicator/who:alcohol-consumption - Adult obesity (who:adult-obesity; % of adults; Global health): Body-mass index of 30 or more, ages 18+, age-standardized. — https://sphre.org/indicator/who:adult-obesity - UHC service coverage index (who:uhc-coverage; index (0–100); Global health): Universal health coverage across 14 tracer services (SDG 3.8.1); higher is better. — https://sphre.org/indicator/who:uhc-coverage - Net migration (UN estimates) (unwpp:net-migration; people; Ageing & migration): Immigrants minus emigrants per year, UN WPP 2024 estimates — starting in 1950, a decade before the World Bank series. — https://sphre.org/indicator/unwpp:net-migration - Median age (unwpp:median-age; years; Ageing & migration): Age that splits the population in half; UN WPP 2024 estimates. — https://sphre.org/indicator/unwpp:median-age - Life expectancy at 65 (unwpp:e65; years; Ageing & migration): Average further years lived by those reaching age 65 — ageing at older ages, not infant survival. Five-year intervals before 2016, annual after (see snapshot-unwpp.mjs for why). — https://sphre.org/indicator/unwpp:e65 - GDP per person (Maddison) (maddison:gdp-per-capita; international-$ (2011 prices); Maddison historical economy): Direct official Maddison Project Database 2023 estimates, reaching back centuries for some countries. — https://sphre.org/indicator/maddison:gdp-per-capita - Population (Maddison) (maddison:population; people; Maddison historical economy): Historical mid-year population estimates from the direct Maddison Project Database 2023 release. — https://sphre.org/indicator/maddison:population - Population (PWT) (pwt:population; people; Productivity & inputs): Penn World Table population used as the denominator for its per-person economic measures. — https://sphre.org/indicator/pwt:population - Real GDP per person (PWT) (pwt:rgdpe-per-capita; 2021 international-$ per person; Productivity & inputs): Expenditure-side real GDP at chained 2021 purchasing-power parities, divided by PWT population; designed for comparing living standards across countries and over time. — https://sphre.org/indicator/pwt:rgdpe-per-capita - Total factor productivity (pwt:tfp-index; index (2021 = 1); Productivity & inputs): Total factor productivity at constant national prices. Use for within-country change; the level is not a direct cross-country comparison. — https://sphre.org/indicator/pwt:tfp-index - Labour compensation share (pwt:labour-share; % of GDP; Productivity & inputs): Share of GDP paid as labour compensation at current national prices. — https://sphre.org/indicator/pwt:labour-share - Voice & accountability (wgi:voice-accountability; governance score (0–100); Governance & institutions): Participation in selecting government, freedom of expression and association, and a free media; higher is stronger. — https://sphre.org/indicator/wgi:voice-accountability - Political stability (wgi:political-stability; governance score (0–100); Governance & institutions): Likelihood of political instability or politically motivated violence, including terrorism; higher is more stable. — https://sphre.org/indicator/wgi:political-stability - Government effectiveness (wgi:government-effectiveness; governance score (0–100); Governance & institutions): Quality and independence of public services and policy formulation and implementation; higher is more effective. — https://sphre.org/indicator/wgi:government-effectiveness - Regulatory quality (wgi:regulatory-quality; governance score (0–100); Governance & institutions): Ability to formulate and implement policies and regulations that support private-sector development; higher is stronger. — https://sphre.org/indicator/wgi:regulatory-quality - Rule of law (wgi:rule-of-law; governance score (0–100); Governance & institutions): Confidence in and adherence to society’s rules, including contracts, property rights, police, and courts; higher is stronger. — https://sphre.org/indicator/wgi:rule-of-law - Control of corruption (wgi:control-of-corruption; governance score (0–100); Governance & institutions): Extent to which public power is protected from private gain and capture by elites or private interests; higher is stronger. — https://sphre.org/indicator/wgi:control-of-corruption - Organized-violence fatalities (ucdp:organized-violence-fatalities; deaths (best estimate); Conflict & organized violence): Fatalities from state-based, non-state, and one-sided organized violence within country borders. UCDP best estimate. Its GED inclusion rule can record zero even when violence occurred if the relevant dyad never crossed the 25-fatality calendar-year threshold. — https://sphre.org/indicator/ucdp:organized-violence-fatalities - State-based violence fatalities (ucdp:state-based-fatalities; deaths (best estimate); Conflict & organized violence): Fatalities in conflicts where at least one party is a state government, located within the country. UCDP best estimate. Its GED inclusion rule can record zero even when violence occurred if the relevant dyad never crossed the 25-fatality calendar-year threshold. — https://sphre.org/indicator/ucdp:state-based-fatalities - Non-state violence fatalities (ucdp:non-state-fatalities; deaths (best estimate); Conflict & organized violence): Fatalities in organized conflict where neither primary party is a state government, located within the country. UCDP best estimate. Its GED inclusion rule can record zero even when violence occurred if the relevant dyad never crossed the 25-fatality calendar-year threshold. — https://sphre.org/indicator/ucdp:non-state-fatalities - One-sided violence fatalities (ucdp:one-sided-fatalities; deaths (best estimate); Conflict & organized violence): Fatalities from deliberate attacks on civilians by a government or formally organized group, located within the country. UCDP best estimate. Its GED inclusion rule can record zero even when violence occurred if the relevant dyad never crossed the 25-fatality calendar-year threshold. — https://sphre.org/indicator/ucdp:one-sided-fatalities - Unemployment (ILO national) (ilostat:unemployment-national; % of labour force, ages 15+; Labour markets (ILO)): Harmonized national-source estimate under the 13th ICLS definition; source methods may differ and flagged breaks remain visible. — https://sphre.org/indicator/ilostat:unemployment-national - Employment-to-population (ILO national) (ilostat:employment-population-national; % of population ages 15+; Labour markets (ILO)): Employed people as a share of the population aged 15+, from ILOSTAT’s harmonized national-source series. — https://sphre.org/indicator/ilostat:employment-population-national - Labour-force participation (ILO national) (ilostat:labour-force-participation-national; % of population ages 15+; Labour markets (ILO)): Employed plus unemployed people as a share of the population aged 15+, from harmonized national sources. — https://sphre.org/indicator/ilostat:labour-force-participation-national - Youth not in work or education (ILO national) (ilostat:neet-national; % of people ages 15–24; Labour markets (ILO)): People ages 15–24 who are neither employed nor enrolled in education or formal training, from harmonized national sources. — https://sphre.org/indicator/ilostat:neet-national - Informal employment (ILO national) (ilostat:informal-employment-national; % of employment; Labour markets (ILO)): Employment classified as informal using ILOSTAT’s harmonized 13th-ICLS criteria; national source methods and series breaks still matter. — https://sphre.org/indicator/ilostat:informal-employment-national - Population (IDB estimate/projection) (idb:population; people; IDB demographic model): Midyear population, 1950–2100. IDB combines estimates and projections; the projection base varies by country and point status is not exposed in the bulk file. Treat this as a modeled trajectory, not an observed-data layer. — https://sphre.org/indicator/idb:population - Fertility (IDB estimate/projection) (idb:fertility-rate; births per woman; IDB demographic model): Period total fertility rate, from each country’s available base year through 2100. IDB combines estimates and projections; the projection base varies by country and point status is not exposed in the bulk file. Treat this as a modeled trajectory, not an observed-data layer. — https://sphre.org/indicator/idb:fertility-rate - Life expectancy (IDB estimate/projection) (idb:life-expectancy; years; IDB demographic model): Period life expectancy at birth, both sexes, from each country’s available base year through 2100. IDB combines estimates and projections; the projection base varies by country and point status is not exposed in the bulk file. Treat this as a modeled trajectory, not an observed-data layer. — https://sphre.org/indicator/idb:life-expectancy - Median age (IDB estimate/projection) (idb:median-age; years; IDB demographic model): Age dividing the population into equal younger and older halves. IDB combines estimates and projections; the projection base varies by country and point status is not exposed in the bulk file. Treat this as a modeled trajectory, not an observed-data layer. — https://sphre.org/indicator/idb:median-age - Net migration rate (IDB estimate/projection) (idb:net-migration-rate; per 1,000 people; IDB demographic model): Immigrants minus emigrants per 1,000 midyear population. IDB combines estimates and projections; the projection base varies by country and point status is not exposed in the bulk file. Treat this as a modeled trajectory, not an observed-data layer. — https://sphre.org/indicator/idb:net-migration-rate - Birth rate (IDB estimate/projection) (idb:crude-birth-rate; per 1,000 people; IDB demographic model): Live births per 1,000 midyear population. IDB combines estimates and projections; the projection base varies by country and point status is not exposed in the bulk file. Treat this as a modeled trajectory, not an observed-data layer. — https://sphre.org/indicator/idb:crude-birth-rate - Death rate (IDB estimate/projection) (idb:crude-death-rate; per 1,000 people; IDB demographic model): Deaths per 1,000 midyear population. IDB combines estimates and projections; the projection base varies by country and point status is not exposed in the bulk file. Treat this as a modeled trajectory, not an observed-data layer. — https://sphre.org/indicator/idb:crude-death-rate - Infant mortality (IDB estimate/projection) (idb:infant-mortality; per 1,000 live births; IDB demographic model): Deaths before age one per 1,000 live births, both sexes. IDB combines estimates and projections; the projection base varies by country and point status is not exposed in the bulk file. Treat this as a modeled trajectory, not an observed-data layer. — https://sphre.org/indicator/idb:infant-mortality - Dietary energy supply (faostat:food-supply-energy; kcal per person per day; Food supply & nutrition): Food available for human consumption in FAO food balances, expressed as dietary energy per person per day. This is national supply availability, not measured food intake. — https://sphre.org/indicator/faostat:food-supply-energy - Protein supply (faostat:food-supply-protein; grams per person per day; Food supply & nutrition): Protein in food available for human consumption in FAO food balances, per person per day. This is national supply availability, not measured protein intake. — https://sphre.org/indicator/faostat:food-supply-protein - Primary mathematics proficiency (uis:math-proficiency-primary; % of assessed students; Education quality & conditions (UIS)): Students at the end of primary education reaching the minimum mathematics proficiency level; assessment programmes may not be directly comparable. — https://sphre.org/indicator/uis:math-proficiency-primary - Primary reading proficiency (uis:reading-proficiency-primary; % of assessed students; Education quality & conditions (UIS)): Students at the end of primary education reaching the minimum reading proficiency level; assessment programmes may not be directly comparable. — https://sphre.org/indicator/uis:reading-proficiency-primary - Home-language instruction, early grades (uis:home-language-instruction-early-grades; % of students; Education quality & conditions (UIS)): Early-grade students whose first or home language is also their language of instruction; UIS marks these observations as UIS estimates. — https://sphre.org/indicator/uis:home-language-instruction-early-grades - Bullying, lower secondary (uis:bullying-lower-secondary; % of students; Education quality & conditions (UIS)): Lower-secondary students reporting bullying during the prior 12 months; UIS marks these observations as UIS estimates. — https://sphre.org/indicator/uis:bullying-lower-secondary - Accessible primary-school infrastructure (uis:accessible-primary-schools; % of primary schools; Education quality & conditions (UIS)): Primary schools with adapted infrastructure and materials for students with disabilities; presence does not measure quality or operational condition. — https://sphre.org/indicator/uis:accessible-primary-schools - Primary teacher attrition (uis:teacher-attrition-primary; % of teachers; Education quality & conditions (UIS)): Primary teachers leaving the profession during the school year as a share of the prior-year teaching workforce. — https://sphre.org/indicator/uis:teacher-attrition-primary - Human Development Index (undp:hdi; index, 0–1; Human development): UNDP composite of health, education, and income dimensions. — https://sphre.org/indicator/undp:hdi - Inequality-adjusted HDI (undp:ihdi; index, 0–1; Human development): HDI adjusted for inequality in the distribution of each dimension. — https://sphre.org/indicator/undp:ihdi - HDI loss from inequality (undp:hdi-inequality-loss; %; Human development): Percentage loss in potential human development due to inequality. — https://sphre.org/indicator/undp:hdi-inequality-loss - Gender Inequality Index (undp:gender-inequality-index; index, 0–1; Human development): UNDP composite of reproductive health, empowerment, and labour-market inequality. — https://sphre.org/indicator/undp:gender-inequality-index - Planetary pressures-adjusted HDI (undp:planetary-pressures-hdi; index, 0–1; Human development): HDI adjusted for carbon dioxide emissions and material footprint per person. — https://sphre.org/indicator/undp:planetary-pressures-hdi - Total energy consumption (eia:total-energy-consumption; terajoules; International energy (EIA)): Annual national energy consumption in EIA’s native terajoule series. — https://sphre.org/indicator/eia:total-energy-consumption - Energy consumption per person (eia:energy-consumption-per-capita; million Btu per person; International energy (EIA)): Annual national energy consumption divided by population, in EIA’s native unit. — https://sphre.org/indicator/eia:energy-consumption-per-capita - Net electricity generation (eia:electricity-net-generation; billion kWh (TWh); International energy (EIA)): Annual electricity generated minus power consumed by generating stations. — https://sphre.org/indicator/eia:electricity-net-generation - Renewable electricity generation (eia:renewable-electricity-net-generation; billion kWh (TWh); International energy (EIA)): Annual net electricity generation from renewable sources, including hydroelectricity. — https://sphre.org/indicator/eia:renewable-electricity-net-generation - Solar electricity generation (eia:solar-electricity-net-generation; billion kWh (TWh); International energy (EIA)): Annual net electricity generation from solar energy. — https://sphre.org/indicator/eia:solar-electricity-net-generation - Wind electricity generation (eia:wind-electricity-net-generation; billion kWh (TWh); International energy (EIA)): Annual net electricity generation from wind energy. — https://sphre.org/indicator/eia:wind-electricity-net-generation - Nuclear electricity generation (eia:nuclear-electricity-net-generation; billion kWh (TWh); International energy (EIA)): Annual net electricity generation from nuclear power. — https://sphre.org/indicator/eia:nuclear-electricity-net-generation - Lithium mine production (usgs-mcs:lithium-mine-production; metric tons lithium content; Minerals & materials): Mine production in metric tons of lithium content. Withheld values remain no-data; publisher estimates and reported values retain their source-row notes. — https://sphre.org/indicator/usgs-mcs:lithium-mine-production - Cobalt mine production (usgs-mcs:cobalt-mine-production; metric tons cobalt content; Minerals & materials): Mine production in metric tons of cobalt content. The 2024 and 2025 values in this release are identified by USGS as estimates. — https://sphre.org/indicator/usgs-mcs:cobalt-mine-production - Nickel mine production (usgs-mcs:nickel-mine-production; metric tons nickel content; Minerals & materials): Mine production in metric tons of nickel content. Publisher estimate and territory notes remain attached to their source rows. — https://sphre.org/indicator/usgs-mcs:nickel-mine-production - Natural graphite mine production (usgs-mcs:natural-graphite-mine-production; metric tons; Minerals & materials): Mine production of natural graphite. A USGS em dash is a published zero; missing countries are no-data and are never filled with zero. — https://sphre.org/indicator/usgs-mcs:natural-graphite-mine-production - Copper mine production (usgs-mcs:copper-mine-production; thousand metric tons copper content; Minerals & materials): Mine production in thousand metric tons of copper content, preserving the source table unit without conversion. — https://sphre.org/indicator/usgs-mcs:copper-mine-production - Tax wedge, single worker (oecd:tax-wedge-single-worker; % of labour cost; Taxes, health & broadband (OECD)): Income tax plus employee and employer social contributions minus cash benefits, as a share of total labour cost for a single worker at the average wage. — https://sphre.org/indicator/oecd:tax-wedge-single-worker - Tax wedge, one-earner family (oecd:tax-wedge-one-earner-couple; % of labour cost; Taxes, health & broadband (OECD)): The same wedge for a one-earner married couple with two children at the average wage; family cash benefits can push it negative. — https://sphre.org/indicator/oecd:tax-wedge-one-earner-couple - Out-of-pocket health spending (oecd:health-out-of-pocket-share; % of health spending; Taxes, health & broadband (OECD)): Household out-of-pocket payments as a share of current expenditure on health (System of Health Accounts). — https://sphre.org/indicator/oecd:health-out-of-pocket-share - Pharmaceutical spending per person (oecd:pharmaceutical-spending-per-capita; US$ PPP per person; Taxes, health & broadband (OECD)): Spending on pharmaceuticals and other medical non-durable goods per person, in current US dollars at purchasing power parity. — https://sphre.org/indicator/oecd:pharmaceutical-spending-per-capita - Fixed broadband subscriptions (oecd:fixed-broadband-per-100; per 100 people; Taxes, health & broadband (OECD)): Fixed broadband subscriptions per 100 inhabitants, all access technologies. — https://sphre.org/indicator/oecd:fixed-broadband-per-100 - Fibre share of broadband (oecd:fibre-share-of-broadband; % of fixed broadband; Taxes, health & broadband (OECD)): Fibre connections as a share of all fixed broadband subscriptions. — https://sphre.org/indicator/oecd:fibre-share-of-broadband - Goods exports (total) (trade:exports-total; current US$; Trade): Annual world total of merchandise exports in current US dollars, from the per-country trade series snapshots (WITS backbone plus the UN Comtrade API for the freshest years). Goods only — services are not in this series. — https://sphre.org/indicator/trade:exports-total - Goods imports (total) (trade:imports-total; current US$; Trade): Annual world total of merchandise imports in current US dollars, from the per-country trade series snapshots (WITS backbone plus the UN Comtrade API for the freshest years). Goods only — services are not in this series. — https://sphre.org/indicator/trade:imports-total