Related Experiment Videos
Excess mortality attributable to the 2025 Iberian Peninsula blackout
Garyfallos Konstantinoudis1, Julien Riou2
1Grantham Institute for Climate Change and the Environment, Imperial College London, London, UK. g.konstantinoudis@imperial.ac.uk.
Nature Communications
|July 20, 2026
Summary
The 2025 Iberian blackout increased mortality in Spain, especially among elderly women, but not in Portugal. This highlights the underestimated health burden of power outages and the need for climate change preparedness.
Area of Science:
- Environmental Health
- Public Health
- Epidemiology
Background:
- Widespread power outages, or blackouts, can have significant health consequences.
- These impacts range from direct effects like medical equipment failure to indirect consequences such as disrupted healthcare services.
Purpose of the Study:
- To investigate the association between the 2025 Iberian blackout and all-cause mortality in Spain and Portugal.
- To identify specific demographic groups and temporal patterns of mortality following the event.
Main Methods:
- Ecological study design analyzing mortality data from Spain and Portugal.
- Time-series analysis comparing observed mortality during and after the blackout period to expected levels.
Main Results:
- The 2025 Iberian blackout was associated with a significant increase in mortality in Spain (+167 deaths, +2.4% relative increase) in the two days following the event.
- Increased mortality in Spain was particularly notable among women aged 85 and older.
- No significant increase in mortality was observed in Portugal, nor on the day of the blackout in either country.
Conclusions:
- The study demonstrates a clear association between the Iberian blackout and increased mortality in Spain, underscoring the health risks posed by power outages.
- Findings suggest that the health burden of blackouts is underestimated and varies geographically, potentially due to differences in outage impact or local resilience.
- Improved public health preparedness for widespread power outages is crucial, especially in the context of a changing climate.
Related Concept Videos
Hazard Ratio
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial evaluating a...
For example, in a clinical trial evaluating a...
Causality in Epidemiology
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
Relative Risk
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
Bias in Epidemiological Studies
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
Prevalence and Incidence
In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health condition at a...
Prevalence indicates the proportion of individuals in a population who have a specific disease or health condition at a...
Confounding in Epidemiological Studies
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This phenomenon...