Chance of Global Population Stability by 2100 at 30% - 11 Billion People Predicted

It is unlikely that the global population will stabilise before the end of the century, with just a 30% chance of current growth rates levelling out.

Experts believe the number of people on Earth will reach 11 billion by 2100, two billion more than previous estimates have suggested.

Corresponding author Adrian Raftery, from the University of Washington, said: "The consensus over the past 20 years or so was that world population, which is currently around seven billion, would go up to nine billion and level off or probably decline.

"We found there's a 70% probability the world population will not stabilise this century. Population, which had sort of fallen off the world's agenda, remains a very important issue."

Published in the journal Science, researchers used the most recent United Nation population data to make their estimates.

They found the biggest area of growth will be in Africa, because birth rates in sub-Saharan Africa have not fallen as had been predicted. By 2100, the population in Africa is expected to increase by 45%, reaching 5.1 billion.

The population in Asia is expected to peak in 2050, but then start to decline, while North America, Europe, Latin America, and the Caribbean will remain steady, researchers said.

Researchers say their new estimates are more accurate because they have used data combined with expert forecasts regarding mortality rates, fertility rates, and international migration. They also narrowed the range of uncertainty by not using scenarios where women have 0.5 children more or less than forecast.

"In a given year and country the fertility rate might be half a child higher, but the probability that it would be half a child higher in all countries in all years in the future is very low," Raftery said, adding their model found with 80% probability that the global population will be between 9.6 billion and 12.3 billion by 2100.

"This work provides a more statistically driven assessment that allows us to quantify the predictions, and offer a confidence interval that could be useful in planning," first author Patrick Gerland said.