Evidence map›Paper›PMID 38574050›Full record

ArticlePloS one2024

Long-term population projections: Scenarios of low or rebounding fertility.

Dean Spears, Sangita Vyas, Gage Weston, Michael Geruso

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Dean SpearsEconomics Department, University of Texas at Austin, Austin, TX, United States of America.
Sangita VyasPopulation Wellbeing Initiative, University of Texas at Austin, Austin, TX, United States of America.ORCID 0000-0002-7815-0952
Gage WestonPopulation Wellbeing Initiative, University of Texas at Austin, Austin, TX, United States of America.ORCID 0009-0005-5907-3751
Michael GerusoEconomics Department, University of Texas at Austin, Austin, TX, United States of America.

Funding

Program Development and Pilot CoreP30AG066614 · NIA · UNIVERSITY OF TEXAS AT AUSTIN · PI DEBRA J. UMBERSON · 2020 to 2026
$5.2M
Scientific & Technical CoreP2CHD042849 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI Elizabeth T. Gershoff · 2017 to 2026
$5.2M
Projecting the future of early life mortality in the developing worldK01HD098313 · NICHD · UNIVERSITY OF TEXAS AT AUSTIN · PI SPEARS, DEAN · 2019 to 2023
$661k
NIA NIH HHS P30 AG066614NICHD NIH HHS K01 HD098313NICHD NIH HHS P2C HD042849
6 · The paper itself

Abstract

The size of the human population is projected to peak in the 21st century. But quantitative projections past 2100 are rare, and none quantify the possibility of a rebound from low fertility to replacement-level fertility. Moreover, the most recent long-term deterministic projections were published a decade ago; since then there has been further global fertility decline. Here we provide updated long-term cohort-component population projections and extend the set of scenarios in the literature to include scenarios in which future fertility (a) stays below replacement or (b) recovers and increases. We also characterize old-age dependency ratios. We show that any stable, long-run size of the world population would persistently depend on when an increase towards replacement fertility begins. Without such an increase, the 400-year span when more than 2 billion people were alive would be a brief spike in history. Indeed, four-fifths of all births-past, present, and future-would have already happened.

Indexed as

Birth RatePopulation ForecastDeveloping CountriesFertilityForecastingHumansPopulation DynamicsPopulation Growth

Identifiers

PMID38574050
PMCPMC10994275

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.