A study led by the University of Malaga has shown that outbreaks of Ebola virus do not occur randomly over time; rather, their appearance is linked to specific large-scale meteorological patterns, even with oscillations occurring in regions thousands of miles away from Central Africa, where they are currently suffering from an epidemic of this disease, which can be fatal.
The scientific team, which also includes the Spanish Institute of Oceanography, the Manchester Metropolitan University and the Center for International Forestry Research, calls these links “teleconnections” and advocates their analysis as a “clue” to predict where and when the risk of Ebola increases.
According to the latest report from the National Institute of Public Health (INSP) of the Democratic Republic of the Congo, based on data collected through September 26, more than 8,000 confirmed infections have been recorded in the latest outbreak, which began in May, including 3,901 deaths, with a case fatality rate of nearly 50 percent.
This new finding, obtained after collecting data on 49 outbreaks in Africa between 1976 and 2025 and comparing them in a database with 26 climate oscillation indices, could be used as a means of epidemiological surveillance, capable of detecting early warning signals to identify periods and regions where weather conditions may be more favorable for the occurrence of new outbreaks. The paper has been published in the scientific journal Stochastic Environmental Research and Risk Assessment.
From the Pacific to Africa: following a climatic track
The scientists used this data until 2018 to build the models and dedicated the years 2019-2025 to seeing if they could forecast new outbreaks. They identified four climatic oscillation indices that were particularly associated with the distribution of outbreaks: the Caribbean Sea Surface Temperature Index (CAR) – no longer available since February 2020 – , the Dipole Mode Index (IMD), the Quasi-Biennial Oscillation (QBO) and the Pacific Decadal Oscillation (PDO), the latter being the most frequent indicator or “signal” and, therefore, the most important macroclimatic factor of the model.
“Our proposed interpretation is that these large oscillations modify meteorological patterns, for example, precipitation in the African continent, and these can alter ecological conditions that favor the occurrence of outbreaks”, explains the Zoology professor at UMA Raimundo Real, one of the authors of this paper.
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In this sense, the Biogeography and Macroecology professor also at the University of Malaga Jesús Olivero, another of the authors of the paper, clarifies that this does not mean that these distant climate indicators directly cause Ebola, but they may serve as an early warning “clue” of environmental conditions more closely linked to the biological phenomenon. “Early warning systems are essential for combating infectious diseases. To achieve this, it is not enough to detect cases of the disease early; we must anticipate them by monitoring risk factors, and our predictive tool could be key to this effort,” adds Olivero.
Surveillance tool
The researchers estimate that the “useful window” of these large climatic oscillations would be six to twelve months before a potential event, so their predictive capacity is still limited and further research along these lines would be needed before they could be considered an autonomous predictive system. Nevertheless, the study represents an initial step as a surveillance tool that could help activate preparedness measures when climate conditions indicate an increased risk, identifying periods and locations that warrant closer epidemiological monitoring.
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