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Abstract
BackgroundWorldwide, the number of recorded human hantavirus infections as well as the number of affected countries is on the rise. In Europe, most human hantavirus infections are caused by the Puumala virus (PUUV), with bank voles (Myodes glareolus) as reservoir hosts. Generally, infection outbreaks have been related to environmental conditions, particularly climatic conditions, food supply for the reservoir species and land use. However, although attempts have been made, the insufficient availability of environmental data is often hampering accurate temporal and spatially explicit models of human hantavirus infections.MethodsIn the present study, dynamics of human PUUV infections between 2001 and 2015 were explored using ArcGIS in order to identify spatio-temporal patterns.ResultsPercentage cover of forest area was identified as an important factor for the spatial pattern, whereas beech mast was found explaining temporal patterns of human PUUV infections in Germany. High numbers of infections were recorded in 2007, 2010 and 2012 and areas with highest records were located in Baden-Wuerttemberg (southwest Germany) and North Rhine-Westphalia (western Germany).ConclusionMore reliable data on reservoir host distribution, pathogen verification as well as an increased awareness of physicians are some of the factors that should improve future human infection risk assessments in Germany.
Highlights
Hantaviruses are tri-segmented, negative-stranded enveloped RNA viruses consisting of at least 23 recognized species (Vaheri et al, 2013; Plyusnin & Sironen, 2014)
Puumala virus (PUUV) infections, with bank voles (Myodes glareolus) as reservoir host species (Brummer-Korvenkontio et al, 1980; Klingström et al, 2002), are the most prevalent type of human hantavirus infections in Germany (Schwarz et al, 2009), the Dobrava-Belgrade orthohantavirus (DOBV) has been identified in the eastern part of Germany, where the host species of its genotype Kurkino, the striped field mouse (Apodemus agrarius), occurs (Schlegel et al, 2009; Klempa et al, 2013)
(temporal patterns) (3) Are there any seasonal patterns? (4) What are the driving factors for the spatial and temporal patterns in Germany? (5) Has there been an increase of PUUV infections over the last 15 years? Overall or in certain regions? (6) Does the spatial extent of areas strongly affected by PUUV infections expand? What might be reasons for this? we considered the percentage of strong beech fructification, the percentage of forest and urban area as well as precipitation and temperature with regard to their influence on temporal and spatial patterns of the recorded number of PUUV infections in Germany
Summary
Hantaviruses (family Hantaviridae) are tri-segmented, negative-stranded enveloped RNA viruses consisting of at least 23 recognized species (Vaheri et al, 2013; Plyusnin & Sironen, 2014). How to cite this article Cunze et al (2018), Spatial and temporal patterns of human Puumala virus (PUUV) infections in Germany. Two syndromes are known so far: the haemorrhagic fever with renal syndrome (HFRS) and Hantavirus cardiopulmonary syndrome (HCPS) (Krüger, Ulrich & Lundkvist, 2001). Whereas the latter is only found in North and South America, HFRS occurs in Europe, Asia and Africa (Hooper et al, 2001; Witkowski et al, 2014). In Europe, most human hantavirus infections are caused by the Puumala virus (PUUV), with bank voles (Myodes glareolus) as reservoir hosts. More reliable data on reservoir host distribution, pathogen verification as well as an increased awareness of physicians are some of the factors that should improve future human infection risk assessments in Germany
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