Weather IA
ia-meteo

Super El Niño: Projected Heat-Related Mortality Peak in Nigeria

A study by the Climate Impact Lab estimates that Super El Niño could cause an additional 451,000 heat-related deaths worldwide by February 2027, with Nigeria having the highest projected rate.

WE

Rédaction Weather IA

vendredi 25 septembre 2026 à 12:318 min
Partager :Twitter/XFacebookWhatsApp
Super El Niño: Projected Heat-Related Mortality Peak in Nigeria

Between now and February 2026, Super El Niño could be responsible for approximately 451,000 additional heat-related deaths globally, according to researchers at the Climate Impact Lab of the University of Chicago. Among all regions studied, Nigeria stands out with the highest projected mortality rate, far exceeding estimates for other African countries and even traditionally heat-vulnerable areas. This alarming projection is based on an exhaustive analysis of over 24,000 geographical zones, where each additional degree in temperature correlates with a measurable increase in the number of deaths.

What the study reveals: Precise results and key figures

The report indicates that if the El Niño phenomenon persists at its current intensity, the total number of heat-related deaths could rise by 451,000, with Nigeria leading the ranking. The country, already facing frequent heatwave episodes, would see its mortality rate increase by several times the global average. Researchers did not provide an exact figure for each country but noted that regions in West Africa, where healthcare systems are often under-resourced, have the highest prediction uncertainties.

Furthermore, the study shows that the relationship between temperature and mortality is not linear: each degree above the critical threshold exponentially increases the risk of death, especially in areas with limited access to air conditioning and emergency care, such as Nigeria. The authors emphasize that these figures are projections based on the best available data, and prediction uncertainty remains high, especially in regions with scarce historical data.

How: Research method and data used

To establish these projections, the Climate Impact Lab team combined several sources of atmospheric data and public health data. Future temperatures come from predictive models of the ECMWF and the Copernicus program, enriched by predictions from GraphCast and Pangu-Weather, two systems based on neural networks and machine learning. These models integrate high-resolution satellite data, allowing for local temperature variations to be tracked.

Heat projections were then crossed with a vast database of epidemiological studies quantifying the link between extreme temperatures and deaths. Researchers used machine learning algorithms to adjust mortality coefficients based on characteristics such as age, sex, and pre-existing conditions.

Was this article helpful?

Commentaires

Connectez-vous pour laisser un commentaire