ArticleEcoHealth2019
Population Dynamics of Bank Voles Predicts Human Puumala Hantavirus Risk.
Article in EcoHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
14 citing papers in PubMed, 32 citations in OpenAlex.
- Beyond the laboratory: the bank vole (Clethrionomys glareolus) as a novel model organism in biological research.Frontiers in zoology · 2025Review
- Biomagnification and potential health effects of per- and polyfluoroalkyl substances (PFAS) in a terrestrial food web.Scientific reports · 2025Article
- Ecological determinants driving orthohantavirus prevalence in small mammals of Europe: a systematic review.One health outlook · 2025Review
- Hantavirus co-circulation in common shrews (Virus evolution · 2025Article
- High-resolution early warning system for human Puumala hantavirus infection risk in Germany.Scientific reports · 2024Article
- Nephropathia Epidemica Caused by Puumala Virus in Bank Voles, Scania, Southern Sweden.Emerging infectious diseases · 2024Article
- Article
- The impact of wildlife and environmental factors on hantavirus infection in the host and its translation into human risk.Proceedings. Biological sciences · 2023Article
- Population fluctuations and synanthropy explain transmission risk in rodent-borne zoonoses.Nature communications · 2022Article
- Article
- The Distribution ofPathogens (Basel, Switzerland) · 2021Article
- Puumala Virus Variants Circulating in Forests of Ardennes, France: Ten Years of Genetic Evolution.Pathogens (Basel, Switzerland) · 2021Article
- Rodent host population dynamics drive zoonotic Lyme Borreliosis and Orthohantavirus infections in humans in Northern Europe.Scientific reports · 2021Article
- Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Predicting risk of zoonotic diseases, i.e., diseases shared by humans and animals, is often complicated by the population ecology of wildlife host(s). We here demonstrate how ecological knowledge of a disease system can be used for early prediction of human risk using Puumala hantavirus (PUUV) in bank voles (Myodes glareolus), which causes Nephropathia epidemica (NE) in humans, as a model system. Bank vole populations at northern latitudes exhibit multiannual fluctuations in density and spatial distribution, a phenomenon that has been studied extensively. Nevertheless, existing studies predict NE incidence only a few months before an outbreak. We used a time series on cyclic bank vole population density (1972-2013), their PUUV infection rates (1979-1986; 2003-2013), and NE incidence in Sweden (1990-2013). Depending on the relationship between vole density and infection prevalence (proportion of infected animals), either overall density of bank voles or the density of infected bank voles may be used to predict seasonal NE incidence. The density and spatial distribution of voles at density minima of a population cycle contribute to the early warning of NE risk later at its cyclic peak. When bank voles remain relatively widespread in the landscape during cyclic minima, PUUV can spread from a high baseline during a cycle, culminating in high prevalence in bank voles and potentially high NE risk during peak densities.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.