The R package mpmaggregate (v0.2.5) is now available on CRAN.
The package aggregates matrix population models into lower-dimensional models.
Thanks to my coauthors, Roberto Salguero-Gómez and Hiroyuki Yokomizo.
@robsalgo.bsky.social
#rstats #ecology #demography
Population increased in two-thirds of EU countries from 2024 to 2025. Hungary recorded the second-largest population decline (−0.5%). Overall, the EU’s population grew by 0.3%.
#demography #population #EU #Poland #Hungary #Germany
Slope chart titled "Life expectancy increased in every country," created for #30DayChartChallenge Day 4 by Ilya Kashnitsky (@ikashnitsky.phd), using data from the {owidapi} R package. Two vertical axes represent the years 1960 (left) and 2020 (right), with the y-axis showing life expectancy at birth in years, ranging from approximately 25 to over 85. Each country is represented by a diagonal line connecting its 1960 value to its 2020 value, with a small circular flag icon at each endpoint. All lines slope upward from left to right, visually confirming that life expectancy increased in every country over this 60-year period. Lines are color-coded by world region: cyan/teal for the Americas, blue for Europe, green for Asia, pink/magenta for Africa, and orange for Oceania, as shown in a world map legend positioned at the lower center of the image. Country names are listed vertically along both axes. The chart background is light cyan. The title text is bold and dark teal, with subtitle text in smaller grey font reading "#30DayChartChallenge Day 4 · Slope | 1960 -> 2020 · Lines colored by world region." African nations cluster at the lower end of the 1960 axis, while European and high-income countries appear near the top of both axes, though with notably smaller gains. The most dramatic upward slopes are visible among Asian and African countries, indicating the largest absolute gains in life expectancy.
DAY 4 -- slope #30DayChartChallenge 🚠
This is probably the most important development for humans in the recent history -- the tremendous growth of life expectancy across all countries 🌐 #demography
🔗 #rstats code: github.com/ikashnitsky/...
🧙♂️ pplx chat (refactored): github.com/ikashnitsky/...
[8/8] La démographie reconfigure la puissance mondiale. D’ici 2100, l’Inde pourrait atteindre 1,5 milliard d’habitants contre 800 millions pour la Chine. La taille et l’âge des populations redessinent les hiérarchies, sans déterminer totalement les trajectoires. #geography #demography #population
[1/8] John Rennie Short (University of Maryland) analyse comment la structure par âge transforme les territoires. Il montre que jeunesse, vieillissement et transition démographique recomposent croissance, mobilités et rapports de puissance à l’échelle mondiale. #geography #demography #population
Only 8.5% receive it.
Among Hungarian households that need long-term care, just 8.5% receive professional home care services — the third-lowest rate in the EU. The EU average is 28.3%.
#demography #Hungary #population
Annual survival in a dynamic species: pronghorn survival patterns across their northern range vist.ly/4x6s8 #Pronghorn #Survival #Demography
🌍 Quels pays attirent ou perdent des habitants ?
Le taux de migration nette révèle de fortes inégalités d’attractivité dans le monde.
🗺️ Cartes du monde atlasocio.com/cartes/reche...
📊 Classement mondial atlasocio.com/classements/...
#migration #demography
From youth bulges to graying societies: The demographic dynamics that are upending the world#Babyboom #Babyboomers #Demography #GenZ #GenZprotests #populations #Pronatalism #Youth
[6/6] Le recensement actualise les données depuis 2011, où 1,21 milliard d’habitants étaient comptés. En 2023, l’Inde atteint 1,42 milliard et devient le pays le plus peuplé. La planification repose sur cette connaissance fine du territoire. #geography #demography #population #development #India
[1/6] En Inde, explique Abdoollah Earally, le recensement mobilise 3 millions d’agents pour compter 1,4 milliard d’habitants. Cet outil cartographie la population et permet d’ajuster les politiques publiques dans un territoire vaste et très contrasté. #geography #demography #India
Is this #demography erasure?
#Published: "Family breakups beyond childhood: Later-life parental divorce and adult sibling ties" by @beydacineli.bsky.social & Zafer Büyükkeçeci (doi.org/10.20377/jfr...). #JFR #JFamRes #openaccess #openscience #sociology #demography
Look at this technological stack that @samclark.net uses in his new paper, look at the screenshot: : python, positron, uv, quarto, duckdb — all the best new tools 🤩 (well, except for python in my case, I guess I stay with R #rstats)
The #demography paper:
🔗 arxiv.org/pdf/2603.24299
Perhaps Charlie could …. ‘do his own research’ 🧐
This would be a good place to start ….
#Demography
#FallingBirthRates
#YouTube
All countries (like Spain 🇪🇸) should be doing everything possible to support parents in a time of falling birth rates.
The thinking here in the UK 🇬🇧 is beyond bizarre and extremely short-sighted.
#Demography
#FallingBirthRates
👶 Learning Individual Reproductive Behavior from Aggregate Fertility Rates via Neural Posterior Estimation
Ciganda et al. use neural posterior estimation to recover individual reproductive behaviour from fertility rates.
#Demography #NeuralNetworks
doi.org/10.1093/jrss...
N-IUSSP: How seasonal mortality shapes life expectancy in Europe (2000-2019)
www.niussp.org/health-and-m...
#demography
#populationstudies
#Published: "The sibling postcard exercise – substance and methodology" by @rosedwards.bsky.social, Susie Weller & Luisa Weissberg (doi.org/10.20377/jfr...). #JFR #JFamRes #openaccess #openscience #sociology #demography
The dots are too scattered to make sense up until the last couple of years and by then the slope is too small to really see. But the lines show a slight increase in COVID rates by immigration rates during the first year, the blue line. The second year, the red one, shows the most pronounced negative relationship, followed by an almost parallel sloping line for the third year. The fourth and fifth years show much lower COVID death rates that slope less, and I don't know if the reason I can see it is I spend so much time looking at scatter plots I don't know if the reason I can see it is because I spend so much time playing with them . Anyway, the slopes, aka regression coefficients, by years are: 2020 = 0.77, 2021 = -1.77, 2022 = -0.75, 2023 = -0.25 and 2024 = -0.16. Yes, all of them after vaccine became available are negative. Now the reason I put this together is in response to someone blaming immigrants for causing our COVID deaths. I actually think most of our contact with germs in the rest of the world is through air planes and just like immigrants, the ones coming from the rest of the world, evein if they are Americans who just spent a little time there, most of them hit coastal states first. The major difference I see is that after COVID vaccines are available, the percent immigrant is negative related to death rates and that may related the the Southern Baptist refusing vaccination and they are home grown not imported.
Here are five years of COVID death rates plotted by state percent foreign immigrants. See text for comments. 🧪💡☠️ #Sociology #Population #Political #Demography
previous most viewed #census and #demography post from a #CensusSDC member or affiliate:
March: KY’s @UofLKSDC
Feb: @TexasDemography
Jan: NY’s @PADcornell
Dec: @OEOAZGOV @AZcommerce
Nov: @kemgardnerinst @UtahSDC
Oct: MN’s @minnpop @ipums
Sept: @UNCpopcenter
Aug: @TexasDemography
RE: https://fosstodon.org/@haraldkliems/116296609719459825
I figured I should put these graphs into a blog post, with the #RStats code and a bit of text around it. haraldkliems.netlify.app/posts/2026-03-26-some-wi...
#blogging #demography #Wisconsin
Line chart titled "Population estimates for Wisconsin counties. Only counties over 150,000 population included. Each line represents a county. Year (2020-2025) on the x axis, population on the y axis.
Looking at the largest counties by populationn in Wisconsin, Milwaukee county population declined, Dane, Waukesha, Racine went up modestly, and the other counties appear relatively stable.
#Wisconsin #demography
Line chart titled "Census Bureau population estimates for Dane County." On the x axis is the year (2020 to 2025), on the y axis is the population. Except between 2020 and 2021, population grew between 4000 and 9000 people each year. Population in 2025 is 590375.
The latest US Census Bureau 2025 county-level population estimates are out. Some quick charts: In Wisconsin, Dane County continues its relatively steady growth, adding about 4000 people compared to the previous year […]
[Original post on fosstodon.org]
South Korea’s fertility crisis didn’t begin when births fell below 1.
The state spent decades teaching families to have fewer children, then couldn’t easily reverse course after housing, education and work had already changed the math.
#DataViz #Demography #SouthKorea
#demography #fertility
📢We updated #HFD fertility data series for 8 countries!
✔️Through 2023: France, Netherlands, and Poland
✔️Through 2024: Norway, Portugal, Switzerland, Taiwan, and USA
👉 humanfertility.org
📢Next @ESHD_EU Webminar!
European Society of Historical #Demography TODAY at 3 pm (CET)
Fabio Gatti (University of Bern and Bocconi University)
Religion and Post-Slavery: Church Competition in Colonial #Jamaica, 1828–1920.
All previous webinars here👉https://www.eshd.eu/eshd-webinar-series/
A webpage showing a newsletter promotion. On the left is a large image of a park scene in winter with many people walking along a wide path lined with trees. A white banner across the image reads ‘Changing Populations.’ To the right of the image is a subscription form with fields for name, discipline, profession, and organisation, alongside the heading ‘Subscribe’ and a brief description about signing up for the newsletter.
📨 If you’ve enjoyed this issue of #ChangingPopulations, don’t forget to subscribe to be the first to receive all things #population change and #demography in future newsletters -a new one will be published in the summer ⬇️
▶️ www.cpc.ac.uk/news/newslet... @bspsuk.bsky.social @populationeu.bsky.social
This is an excellent explanation of China’s bizarre short-sighted one child policy ….
Credit @mattbevan.bsky.social
#Demography
#FallingBirtRates
