There could be billions more people living on Earth than currently thought, according to a new study which claims rural figures worldwide could be vastly underestimated.
Currently, the UN estimates the world population to be about 8.2 billion, which is projected to peak at over 10 billion by the mid-2080.
However, research, published in the journal Nature Communications, found that rural populations in these estimates could be undercounted anywhere between 53 per cent to 84 per cent over the study period between 1975 and 2010.
“This is remarkable, as countless studies have employed these datasets without questioning their accuracy in the rural domain,” scientists write.
Scientists say the lack of proper reference data has prevented attempts at comprehensively gauging the accuracy of global population datasets.
They warn that there are “fundamental limitations” with national population censuses, especially while gauging rural populations.
“Communities in remote locations or impacted by conflict and violence are difficult to access, and census enumerators often face language barriers and resistance to participation,” researchers write.
Citing an example, they say 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, a co-author of the study from Aalto University.
“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,” Dr Láng-Ritter said.
Researchers assessed the five most widely used global population datasets that map the planet into evenly spaced, high-resolution grid cells with population counts based on census data.
They then compared these numbers with resettlement data from over 300 rural dam projects across 35 countries.
Such resettlement data can provide independently gathered comparison points of people’s movement between rural and urban areas, scientists say.
This relocation data is usually precise, they say, since dam companies pay compensation to those affected.
Researchers particularly focussed on maps from 1975 to 2010 due to a lack of dam data from later years.
Datasets from 2010 had the least bias, according to the study, missing between one-third to three-quarters of the rural population.
However, researchers say there is “strong reason” to believe even the latest data misses part of the global 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,” Dr Láng-Ritter said.
The study stops short of offering a new global population estimate, but says even in the most accurate dataset, the rural population is “underestimated by half compared to reported figures”.
Even if the most recent population maps are closer to reality, researchers caution that earlier datasets have influenced decision-making for decades and may provide a “distorted picture” of people’s movement from the countryside to cities.
While the undercounting appeared systemic worldwide, researchers found the discrepancies particularly noticeable in China, Brazil, Australia, Poland and Colombia where information was more readily available.
The latest findings have “far-reaching consequences”, according to researchers, as current estimates suggest over 40 per cent of the world’s 8.2 billion people live in rural areas.
They caution that the needs of rural residents could be under-represented in decision-making globally.
For instance, scientists say the currently used data may contribute to insufficient health care and transport resources being allocated for rural regions by policymakers.
“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 said.
Scientists call for much more strengthened population censuses, alternative population counts, and a more balanced calibration of population models to rectify inaccuracies identified in the study.
