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Study suggests global population may be significantly undercounted

  • By Al Mayadeen English
  • Source: News websites
  • 20 Mar 2025 15:04
4 Min Read

A new study highlights that the lack of adequate reference data has hindered efforts to fully assess the accuracy of global population datasets.

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  • People walk by the historic Lahaina banyan tree in February 2018, in Lahaina, Hawaii. (AP)People walk by the historic Lahaina banyan tree in February 2018, in Lahaina, Hawaii. (AP)

A new study suggests that there could be billions more people living on Earth than currently estimated, claiming that rural population figures worldwide may be significantly undercounted.

The United Nations currently estimates the global population at about 8.2 billion, with projections indicating it could peak at over 10 billion by the mid-2080s. However, research published in Nature Communications argues that rural populations could be underestimated by as much as 53 to 84 percent in the data used between 1975 and 2010.

"This is remarkable, as countless studies have employed these datasets without questioning their accuracy in the rural domain," the scientists note.

The study highlights that the lack of adequate reference data has hindered efforts to fully assess the accuracy of global population datasets. Researchers point to "fundamental limitations" in national population censuses, particularly when measuring rural populations.

“Communities in remote locations or affected by conflict and violence are difficult to access, and census enumerators often face language barriers and resistance to participation,” the researchers explain.

As an example, they suggest that the 2012 census in Paraguay “may have missed a quarter of the population.”

"For the first time, our study provides evidence that a significant proportion of the rural population may be missing from global population datasets," said Josias Láng-Ritter, co-author of the study from Aalto University.

He added, "The results are remarkable, as these datasets have been used in thousands of studies and extensively support decision-making, yet their accuracy has not been systematically evaluated."

The researchers assessed the five most widely used global population datasets, which map the planet into evenly spaced grid cells with population counts based on census data. They then compared these figures with resettlement data from over 300 rural dam projects across 35 countries. Such data is often more accurate because dam companies compensate those affected by resettlement.

The wider context

The study focused on data from 1975 to 2010, as more recent dam data was unavailable. According to the findings, datasets from 2010 were the least biased, but still missed between one-third and three-quarters of the rural population.

"While our study shows accuracy has somewhat improved over decades, the trend is clear: global population datasets miss a significant portion of the rural population," said Dr. Láng-Ritter.

Although the study does not provide a new global population estimate, it indicates that even the most accurate data underestimates the rural population by half compared to reported figures. The researchers caution that even current data may miss parts of the global population, and earlier datasets have influenced decision-making for decades, potentially distorting the understanding of rural-to-urban migration.

Discrepancies were particularly noticeable in China, Brazil, Australia, Poland, and Colombia, where more data was available.

The study’s findings have “far-reaching consequences,” the researchers warn, especially considering that over 40 percent of the world’s 8.2 billion people are estimated to live in rural areas. The undercounting could lead to the underrepresentation of rural residents in global decision-making.

"To provide rural communities with equal access to services and other resources, we need to have a critical discussion about the past and future applications of these population maps," Dr. Láng-Ritter concluded.

The scientists call for stronger population censuses, alternative counting methods, and a more balanced calibration of population models to address the inaccuracies identified in the study.

  • Aalto University
  • Finland
  • global population

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