| Literature DB >> 32326472 |
Ute Ziegler1,2, Pauline Dianne Santos3, Martin H Groschup1,2, Carolin Hattendorf4, Martin Eiden1, Dirk Höper3, Philip Eisermann4, Markus Keller1, Friederike Michel1, Robert Klopfleisch5, Kerstin Müller6, Doreen Werner7, Helge Kampen8, Martin Beer3, Christina Frank9, Raskit Lachmann9, Birke Andrea Tews8, Claudia Wylezich3, Monika Rinder10, Lars Lachmann11, Thomas Grünewald12, Claudia A Szentiks13, Michael Sieg14, Jonas Schmidt-Chanasit4,15, Daniel Cadar4, Renke Lühken4,15.
Abstract
One year after the first autochthonous transmission of West Nile virus (WNV) to birds and horses in Germany, an epizootic emergence of WNV was again observed in 2019. The number of infected birds and horses was considerably higher compared to 2018 (12 birds, two horses), resulting in the observation of the first WNV epidemy in Germany: 76 cases in birds, 36 in horses and five confirmed mosquito-borne, autochthonous human cases. We demonstrated that Germany experienced several WNV introduction events and that strains of a distinct group (Eastern German WNV clade), which was introduced to Germany as a single introduction event, dominated mosquito, birds, horse and human-related virus variants in 2018 and 2019. Virus strains in this clade are characterized by a specific-Lys2114Arg mutation, which might lead to an increase in viral fitness. Extraordinary high temperatures in 2018/2019 allowed a low extrinsic incubation period (EIP), which drove the epizootic emergence and, in the end, most likely triggered the 2019 epidemic. Spatiotemporal EIP values correlated with the geographical WNV incidence. This study highlights the risk of a further spread in Germany in the next years with additional human WNV infections. Thus, surveillance of birds is essential to provide an early epidemic warning and thus, initiate targeted control measures.Entities:
Keywords: Germany; West Nile virus; bird; epidemic; epizooty; horses; human; mosquitoes; transmission risk; zoonoses
Year: 2020 PMID: 32326472 PMCID: PMC7232143 DOI: 10.3390/v12040448
Source DB: PubMed Journal: Viruses ISSN: 1999-4915 Impact factor: 5.048
West Nile virus (WNV)-positive birds, horses and mosquito-borne, autochthonous humans for the federal states of Germany in 2018/2019. Numbers in brackets indicate the number of samples with WNV sequences acquired in this study.
| Federal State | Birds (2018) | Horses (2018) | Birds (2019) | Horses (2019) | Humans (2019) | Sum |
|---|---|---|---|---|---|---|
| Bavaria (BY) | 2 (2) | 0 | 0 | 0 | 0 |
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| Berlin (BE) | 3 (1) | 0 | 33 (6) | 0 | 1 (1) |
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| Brandenburg (BB) | 0 | 1 | 6 (3) | 7 | 0 |
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| Hamburg (HH) | 0 | 0 | 1 (1) | 0 | 0 |
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| Mecklenburg-Western Pomerania (MV) | 1 | 0 | 0 | 0 | 0 |
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| Saxony (SN) | 1 (1) | 0 | 21 (8) | 9 (1) | 3 |
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| Saxony-Anhalt (ST) | 5 (2) | 1 | 15 (10) | 19 | 1 (1) |
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| Thuringia (TH) | 0 | 0 | 0 | 1 | 0 |
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In addition to the 37 WNV sequences, two more genome sequences were obtained from WNV-positive mosquito pools collected in Berlin.
Figure 1Spatial risk of West Nile virus (WNV) transmission in Germany. Average extrinsic incubation period between 15th July to 14th August 2018/2019 and distribution of WNV-positive birds, horses, humans and mosquitoes.
Detection of WNV infections in different bird species in 2018 and 2019.
| Bird Species | Scientific Name | Housing | Number of | Affected |
|---|---|---|---|---|
| Eurasian Blackbird |
| wild | 3 | ST, MV |
| Andean Flamingo |
| captive | 1 | BE |
| Great Grey Owl |
| captive | 6 | SN, ST, BY |
| Unspecified buzzard | wild | 1 | ST | |
| Blue Tit |
| wild | 3 | SN, ST |
| Chilean Flamingo |
| captive | 6 | BE, SN |
| Eurasian Jay |
| wild | 1 | BB |
| Coconut Lorikeet |
| captive | 1 | ST |
| Scarlet-chested Parrot |
| captive | 1 | SN |
| Eurasian Golden Plover |
| wild | 1 | SN |
| Northern Goshawk |
| wild/captive | 19 | BB, BE, SN, ST |
| House Sparrow |
| wild | 4 | SN, ST |
| Dunnock |
| wild | 1 | HH |
| Humboldt-Penguin |
| captive | 1 | BB |
| Inka-Tern |
| captive | 1 | BE |
| Black-tailed Gull |
| captive | 8 | BE |
| Kagu |
| captive | 1 | BE |
| Domestic Canary |
| captive | 2 | SN |
| Great Tit |
| wild | 3 | SN |
| American Flamingo |
| captive | 3 | BE |
| Hooded Crow |
| wild | 1 | BE |
| Unspecified pelican | captive | 1 | ST | |
| Javan Pond Heron |
| captive | 1 | BE |
| Common Wood Pigeon |
| wild | 1 | BE |
| Snowy Owl |
| captive | 8 | BE, ST |
| Chinese Merganser |
| captive | 1 | BE |
| Swift Parrot |
| captive | 1 | SN |
| Little Owl |
| wild | 2 | BB |
| European Goldfinch |
| captive | 1 | SN |
| Eurasian Eagle-Owl |
| wild | 1 | SN |
| Tawny Owl |
| wild | 1 | ST |
| White Eared Pheasant |
| captive | 2 | BE |
* abbreviations as in Table 1.
Figure 2Bayesian maximum clade credibility (MCC) tree; (a) representing the time scale phylogeny; (b) effective population size; and (c) evolutionary rate of the European and German WNV lineage 2. The colored branches of MCC trees represent the most probable geographic location of their descendant nodes (see color codes); (a) the main clades are indicated to the right of the tree (SEEC, South Eastern European clade; CEC, Central and Eastern European clade), including the newly proposed German clade (EGC, Eastern German clade). Time is reported in the axis below the tree and represents the year before the last sampling time (2019). The German WNV strains sequenced in this study are highlighted. The estimated tMRCA of German WNV strains of EGC clade is shown with 95% posterior time intervals in parentheses. Bayesian posterior probabilities (≥90%) and 1000 parallel maximum likelihood bootstrap replicates (≥70%) are indicated at the nodes (asterisks); (b) temporal variation in the effective population size of the European WNV lineage 2; (b1) and EGC; (b2) estimated using the coalescent Gaussian Markov Random field (GMRF) Bayesian Skyride model of polyprotein sequences. The Bayesian Skyride plot represents temporal variation in the virus effective population size (Ne) through time. The blue line represents the median Ne estimate and the shaded area corresponds to the 95% high-probability density (HDP) intervals; (c) evolutionary rate estimates with 95% credible intervals for the distribution of evolutionary rates observed for the whole European WNV lineage 2 and for WNV from the 2018–2019 German epidemic.
Figure 3A median-joining haplotype network constructed from complete WNV NS5 gene alignment of the Central European WNV clade (CEC). Each colored vertex represents a sampled viral haplotype, with different colors indicating the different country of origin. The size of each vertex is relative to the number of sampled viral strains and the dashes on branches show the number of mutations between nodes. The Eastern German clade (EGC) is highlighted.
Figure 4Temporally framed snapshots of the dispersal patterns (2018–2019) among regions in Germany for the Eastern German WNV clade. Lines between locations represent branches in the Bayesian maximum clade credibility (MCC) tree along which the relevant location transition occurs. Circle diameters are proportional to the square root of the number of MCC branches maintaining a particular location state at each time point.
Figure 5Calculated migration pattern of WNV between German locations based on Bayes factor test for significant non-zero rates. The arrows indicate the origin and the direction of migration between locations, while the colors indicate the strength of the connections.
Figure 6Spatial dynamics of the European clade of WNV lineage 2 including the origin of the German WNV reconstructed from the Bayesian maximum clade credibility (MCC) tree, a flexible demographic prior with location states and a Bayesian Stochastic Search Variable Selection (BSSVS); (a) the directed lines between locations connect the sources and target countries. Circles represent discrete geographical locations of viral strains and represent branches in the MCC tree along with where the relevant location transition occurs. All introductions for Germany are shown. Circle diameters of locations are proportional to square root of the number of MCC branches maintaining a particular location state at each time-point. Discrete locations are geographic coordinates for each European country; (b) the directed lines between the source of viral strains (Czech Republic and Austria) and target locations in Germany. Location circle diameters are proportional to square root of the number of MCC branches maintaining a particular location state at each time-point; (c) migration pattern of WNV between Czech Republic–Germany and Austria–Germany based on Bayes factor (BF) test for significant non-zero rates. Viral migration patterns are indicated between the different regions of Germany and neighboring countries and are proportional to the strength of the transmission rate. The color of the connections indicates the origin and the direction of migration and are proportional with the strength of connections. Only well supported paths between locations are shown.
Figure 7Schematic representation of the WNV genome and the positions of amino acid mutations. The position of the unique amino acid mutation of the Eastern German clade (colored in red/blue) in the NS3 gene is highlighted. The specific non-synonymous amino acid mutations for the CEC are shown in black, while the mutation in the NS5 specific for the subclade including the Eastern German group, one Austrian, one Czech and two German strains is presented in green.