After the COVID-19 pandemic and epidemics caused by the Zika and Ebola viruses, there is increasing interest in learning about zoonotic diseases: those transmitted from animals to humans.

To support actions to control further outbreaks, the EU is endorsing the One Health approach, which acknowledges the close links between the health of humans, domestic and wild animals, plants, and the wider environment. This approach recognises that environmental factors can be major drivers of infectious disease outbreaks, and highlights the role of climate change within this.

In Europe, Orthohantavirus puumalaense (PUUV) is a virus hosted by the bank vole (a small rodent native to Europe); when transmitted to humans, it causes a disease characterised by kidney failure and fever called nephropathia epidemica (NE). Humans are usually infected by PUUV during outdoor work or recreation, when they inhale infectious particles from the saliva, urine, or faeces of infected voles.

The incidence of NE has doubled in Western Europe in the past 20 years. A key driver of outbreaks is a sudden increase in numbers of local bank voles, something influenced by various chronological factors - warm, dry summers, for example, which produce lots of seeds the following autumn, thereby increasing bank vole reproduction, survival, and overall numbers.

Rainfall and temperature can also influence transmission of PUUV, with colder and more humid conditions increasing the virus' 'lifespan' in the environment. Factors affecting the levels of contact between humans and bank voles are also important, including weather conditions, with warm spring weather making people more likely to engage in outdoor activity and thereby promoting outbreaks later in that year.

Previous research has shown that the timing of NE peaks varies across Europe. This suggests a need for a way to utilise local data to identify patterns of NE cases across the region, and create an early and localised warning system for viral risk.

This study addresses this need. Researchers accessed data on monthly registered NE cases at health institutes in Belgium, France, Germany, and the Netherlands over the period from 2004 to 2012, to gain information on the timing and location of disease onset. They then looked at the level of the smallest reported administrative unit of area in each country, extracting values for 28 climate and land-cover variables for that area (including maximum temperature, total rainfall, frost and snow days, and measures of vegetation growth and suitable vole habitat).

Climate variables were gathered up to three years before disease onset. The study used a 'Bayesian spatiotemporal statistical model' to predict disease spread over space and time. This type of model enabled regional comparison and hotspot prediction.

The results showed a lot of variation in NE cases across western Europe and identified two hotspots with consistently elevated levels of NE cases (one in southwestern/central Germany, and one in southern Belgium-northeastern France). Further analysis showed hotspot location was mostly determined by land-cover factors, such as the presence of mixed or broad-leaved forest (the preferred habitat of bank voles).

However, fluctuations in climate tended to influence the intensity of the outbreak. The study also identified key climate-related triggers for NE outbreaks, such as mild winters in the year preceding disease onset and optimum summer temperatures two years prior. The latter scenario increases the number of tree seeds and, therefore, the number of bank voles, which in turn increases the risk of an NE outbreak.

Overall, the study demonstrates that it is possible to model how environmental factors influence the spread of infectious disease across Western Europe, and to use this to predict where and when outbreaks may occur. The research model used historical data but was successful in describing outbreaks of viral disease in Europe, demonstrating its potential to produce yearly maps for NE incidence, and to act as a forecasting tool for targeted risk prevention strategies and preparedness.

The researchers highlight that there are some limitations in using data from different countries, which vary in spatial resolution. They recommend that future studies try to harmonise data to improve consistency and accuracy. In addition, many of the observed NE cases were assigned to an individual's region of residence, rather than the source of the PUUV infection. This could be misleading, because it is known that most infections occur during work or leisure activities in woods or forests, likely to be some distance from a person's home.

These example limitations highlight the challenges of modelling over time and without accurate spatial data. The researchers call for future work to build more detailed datasets to enhance the precision of this approach to outbreak prediction.

Reference:

Erazo, D., Vincenti-Gonzalez, M.F., Ghisbain, G. et al. (2025) Impact of Environmental Factors on the Distribution Patterns of Nephropathia Epidemica Cases in Western Europe. Environmental Health Perspectives Volume 133, Issue 5. doi: 10.1289/EHP15457.

To cite this article/service:

"Science for Environment Policy": European Commission DG Environment News Alert Service, edited by the Science Communication Unit, The University of the West of England, Bristol.

Notes on content:

The contents and views included in Science for Environment Policy are based on independent, peer-reviewed research and do not necessarily reflect the position of the European Commission. Please note that this article is a summary of only one study. Other studies may come to other conclusions.