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1
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Godarzi B, Chandler F, van der Linden A, Sikkema RS, de Bruin E, Veldhuizen E, van Amerongen A, Gröne A. A species-independent lateral flow microarray immunoassay to detect WNV and USUV NS1-specific antibodies in serum. One Health 2024; 18:100668. [PMID: 38261918 PMCID: PMC10796932 DOI: 10.1016/j.onehlt.2023.100668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 12/22/2023] [Indexed: 01/25/2024] Open
Abstract
Arboviruses such as West Nile Virus (WNV) and Usutu Virus (USUV) are emerging pathogens that circulate between mosquitoes and birds, occasionally spilling over into humans and horses. Current serological screening methods require access to a well-equipped laboratory and are not currently available for on-site analysis. As a proof of concept, we propose here a species-independent lateral flow microarray immunoassay (LMIA) able to quickly detect and distinguish between WNV Non-Structural 1 (NS1) and USUV NS1-specific antibodies. A double antigen approach was used to test sera collected from humans, horses, European jackdaws (Corvus monedula), and common blackbirds (Turdus merula). Optimization of the concentration of capture antigen spotted on the LMIA membrane and the amount of detection antigen conjugated to detector particles indicated that maximizing both parameters increased assay sensitivity. Upon screening of a larger serum panel, the optimized LMIA showed significantly higher spot intensity for a homologous binding event. Using a Receiver Operating Characteristics (ROC) curve, WNV NS1 LMIA results in humans, horses, and C. monedula showed good correlation when compared to "gold standard" WNV FRNT90. The most optimal derived sensitivity and specificity of the WNV NS1 LMIA relative to corresponding WNV FRNT90-confirmed sera were determined to be 96% and 86%, respectively. While further optimization is required, this study demonstrates the feasibility of developing a species-independent LMIA for on-site analysis of WNV, USUV, and other arboviruses. Such a tool would be useful for the on-site screening and monitoring of relevant species in more remote or low-income regions.
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Affiliation(s)
- Bijan Godarzi
- Department of Biomolecular Health Sciences, Utrecht University, Yalelaan 1, 3584 CL Utrecht, the Netherlands
- BioSensing & Diagnostics, Wageningen University and Research, Bornse Weilanden 9, 6708 WG Wageningen, the Netherlands
| | - Felicity Chandler
- Department of Viroscience, Erasmus MC, Wytemaweg 80, 3015CN Rotterdam, the Netherlands
| | - Anne van der Linden
- Department of Viroscience, Erasmus MC, Wytemaweg 80, 3015CN Rotterdam, the Netherlands
| | - Reina S. Sikkema
- Department of Viroscience, Erasmus MC, Wytemaweg 80, 3015CN Rotterdam, the Netherlands
| | - Erwin de Bruin
- Department of Biomolecular Health Sciences, Utrecht University, Yalelaan 1, 3584 CL Utrecht, the Netherlands
| | - Edwin Veldhuizen
- Department of Biomolecular Health Sciences, Utrecht University, Yalelaan 1, 3584 CL Utrecht, the Netherlands
| | - Aart van Amerongen
- BioSensing & Diagnostics, Wageningen University and Research, Bornse Weilanden 9, 6708 WG Wageningen, the Netherlands
| | - Andrea Gröne
- Department of Biomolecular Health Sciences, Utrecht University, Yalelaan 1, 3584 CL Utrecht, the Netherlands
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2
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Wang R, Liu S, Sun H, Xu C, Wen Y, Wu X, Zhang W, Nie K, Li F, Fu S, Yin Q, He Y, Xu S, Liang G, Deng L, Wei Q, Wang H. Metatranscriptomics Reveals the RNA Virome of Ixodes Persulcatus in the China-North Korea Border, 2017. Viruses 2023; 16:62. [PMID: 38257762 PMCID: PMC10819109 DOI: 10.3390/v16010062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 12/19/2023] [Accepted: 12/27/2023] [Indexed: 01/24/2024] Open
Abstract
In recent years, numerous viruses have been identified from ticks, and some have been linked to clinical cases of emerging tick-borne diseases. Chinese northeast frontier is tick infested. However, there is a notable lack of systematic monitoring efforts to assess the viral composition in the area, leaving the ecological landscape of viruses carried by ticks not clear enough. Between April and June 2017, 7101 ticks were collected to perform virus surveillance on the China-North Korea border, specifically in Tonghua, Baishan, and Yanbian. A total of 2127 Ixodes persulcatus were identified. Further investigation revealed the diversity of tick-borne viruses by transcriptome sequencing of Ixodes persulcatus. All ticks tested negative for tick-borne encephalitis virus. Transcriptome sequencing expanded 121 genomic sequence data of 12 different virus species from Ixodes persulcatus. Notably, a new segmented flavivirus, named Baishan Forest Tick Virus, were identified, closely related to Alongshan virus and Harz mountain virus. Therefore, this new virus may pose a potential threat to humans. Furthermore, the study revealed the existence of seven emerging tick-borne viruses dating back to 2017. These previously identified viruses included Mudanjiang phlebovirus, Onega tick phlebovirus, Sara tick phlebovirus, Yichun mivirus, and three unnamed viruses (one belonging to the Peribunyaviridae family and the other two belonging to the Phenuiviridae family). The existence of these emerging tick-borne viruses in tick samples collected in 2017 suggests that their history may extend further than previously recognized. This study provides invaluable insights into the virome of Ixodes persulcatus in the China-North Korea border region, enhancing our ongoing efforts to manage the risks associated with tick-borne viruses.
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Affiliation(s)
- Ruichen Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
| | - Shenghui Liu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
| | - Hongliang Sun
- Changchun Institute of Biological Products Co., Ltd., Changchun 130012, China; (H.S.); (X.W.)
| | - Chongxiao Xu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
| | - Yanhan Wen
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
| | - Xiwen Wu
- Changchun Institute of Biological Products Co., Ltd., Changchun 130012, China; (H.S.); (X.W.)
| | - Weijia Zhang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
| | - Kai Nie
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
| | - Fan Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
| | - Shihong Fu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
| | - Qikai Yin
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
| | - Ying He
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
| | - Songtao Xu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
| | - Guodong Liang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
| | - Liquan Deng
- School of Public Health, Jilin University, Changchun 130021, China
| | - Qiang Wei
- National Pathogen Resource Center, Chinese Center for Disease Control and Prevention, Beijing 102206, China
| | - Huanyu Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China; (R.W.); (S.L.); (C.X.); (Y.W.); (W.Z.); (K.N.); (F.L.); (S.F.); (Q.Y.); (Y.H.); (S.X.); (G.L.)
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3
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Krol L, Blom R, Dellar M, van der Beek JG, Stroo AC, van Bodegom PM, Geerling GW, Koenraadt CJ, Schrama M. Interactive effects of climate, land use and soil type on Culex pipiens/torrentium abundance. One Health 2023; 17:100589. [PMID: 37415720 PMCID: PMC10320611 DOI: 10.1016/j.onehlt.2023.100589] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Revised: 04/27/2023] [Accepted: 06/19/2023] [Indexed: 07/08/2023] Open
Abstract
The incidence and risk of mosquito-borne disease outbreaks in Northwestern Europe has increased over the last few decades. Understanding the underlying environmental drivers of mosquito population dynamics helps to adequately assess mosquito-borne disease risk. While previous studies have focussed primarily on the effects of climatic conditions (i.e., temperature and precipitation) and/or local environmental conditions individually, it remains unclear how climatic conditions interact with local environmental factors such as land use and soil type, and how these subsequently affect mosquito abundance. Here, we set out to study the interactive effects of land use, soil type and climatic conditions on the abundance of Culex pipiens/torrentium, highly abundant vectors of West Nile virus and Usutu virus. Mosquitoes were sampled at 14 sites throughout the Netherlands. At each site, weekly mosquito collections were carried out between early July and mid-October 2020 and 2021. To assess the effect of the aforementioned environmental factors, we performed a series of generalized linear mixed models and non-parametric statistical tests. Our results show that mosquito abundance and species richness consistently differ among land use- and soil types, with peri-urban areas with peat/clay soils having the highest Cx. pipiens/torrentium abundance and sandy rural areas having the lowest. Furthermore, we observed differences in precipitation-mediated effects on Cx. pipiens/torrentium abundance between (peri-)urban and other land uses and soil types. In contrast, effects of temperature on Cx. pipiens/torrentium abundance remain similar between different land use and soil types. Our study highlights the importance of both land use and soil type in conjunction with climatic conditions for understanding mosquito abundances. Particularly in relation to rainfall events, land use and soil type has a marked effect on mosquito abundance. These findings underscore the importance of local environmental parameters for studies focusing on predicting or mitigating disease risk.
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Affiliation(s)
- Louie Krol
- Institute of Environmental Sciences, Leiden University, the Netherlands
- Deltares, Daltonlaan 600, Utrecht, the Netherlands
| | - Rody Blom
- Laboratory of Entomology, Wageningen University and Research, Wageningen, the Netherlands
| | - Martha Dellar
- Institute of Environmental Sciences, Leiden University, the Netherlands
- Deltares, Daltonlaan 600, Utrecht, the Netherlands
| | | | - Arjan C.J. Stroo
- Centre for Monitoring of Vectors, Netherlands Food and Consumer Product Safety Authority, Ministry of Agriculture, Nature and Food Quality, Wageningen, the Netherlands
| | | | - Gertjan W. Geerling
- Deltares, Daltonlaan 600, Utrecht, the Netherlands
- Department of Environmental Science, Radboud Institute for Biological and Environmental Sciences, Radboud University, Nijmegen, the Netherlands
| | | | - Maarten Schrama
- Institute of Environmental Sciences, Leiden University, the Netherlands
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4
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Giesen C, Herrador Z, Fernandez B, Figuerola J, Gangoso L, Vazquez A, Gómez-Barroso D. A systematic review of environmental factors related to WNV circulation in European and Mediterranean countries. One Health 2023. [DOI: 10.1016/j.onehlt.2022.100478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
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5
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Esser HJ, Lim SM, de Vries A, Sprong H, Dekker DJ, Pascoe EL, Bakker JW, Suin V, Franz E, Martina BEE, Koenraadt CJM. Continued Circulation of Tick-Borne Encephalitis Virus Variants and Detection of Novel Transmission Foci, the Netherlands. Emerg Infect Dis 2022; 28:2416-2424. [PMID: 36288572 PMCID: PMC9707572 DOI: 10.3201/eid2812.220552] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Tick-borne encephalitis virus (TBEV) is an emerging pathogen that was first detected in ticks and humans in the Netherlands in 2015 (ticks) and 2016 (humans). To learn more about its distribution and prevalence in the Netherlands, we conducted large-scale surveillance in ticks and rodents during August 2018-September 2020. We tested 320 wild rodents and >46,000 ticks from 48 locations considered to be at high risk for TBEV circulation. We found TBEV RNA in 3 rodents (0.9%) and 7 tick pools (minimum infection rate 0.02%) from 5 geographically distinct foci. Phylogenetic analyses indicated that 3 different variants of the TBEV-Eu subtype circulate in the Netherlands, suggesting multiple independent introductions. Combined with recent human cases outside known TBEV hotspots, our data demonstrate that the distribution of TBEV in the Netherlands is more widespread than previously thought.
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6
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Garcia-Vozmediano A, De Meneghi D, Sprong H, Portillo A, Oteo JA, Tomassone L. A One Health Evaluation of the Surveillance Systems on Tick-Borne Diseases in the Netherlands, Spain and Italy. Vet Sci 2022; 9:vetsci9090504. [PMID: 36136720 PMCID: PMC9501221 DOI: 10.3390/vetsci9090504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 09/06/2022] [Accepted: 09/13/2022] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Ixodid ticks and tick-borne diseases are expanding their geographical range, but surveillance activities vary among countries. We analysed the surveillance systems in place in the Netherlands, Spain and Italy, to identify ideal elements to monitor tick-borne diseases, by using a One Health evaluation protocol. We identified differences among the three surveillance systems, with the Dutch initiative showing a high level of transdisciplinary collaboration, good identification of the actors and engagement of the public in research and education. Measurable outcomes have been generated, such as the reduction in tick bites and the discovery of new pathogens and tick species. In Italy and Spain, surveillance systems are based on compulsory notification to health authorities; legislation seems relevant but law enforcement alongside the availability of economic resources is rather fragmented and limited to the most severe diseases. The non-scientific community is marginally considered and collaborations are limited to local initiatives. Research activities in both countries have mostly contributed to gaining knowledge on the distribution of tick species and the discovery of new pathogens. Although all TBD surveillance plans comply with the EU regulations, the initiatives characterised by trans-disciplinary collaboration may be more effective for the surveillance and prevention of tick-transmitted diseases. Abstract To identify ideal elements for the monitoring and prevention of tick-borne diseases (TBD), we analysed the surveillance systems in place in the Netherlands, Spain and Italy. We applied a semi-quantitative evaluation to identify outcomes and assess the degree of One Health implementation. Differences emerged in the surveillance initiatives, as well as the One Health scores. The Dutch surveillance is dominated by a high level of transdisciplinary and trans-sectoral collaboration, enabling communication and data sharing among actors. Different project-based monitoring, research and educational activities are centrally coordinated and the non-scientific community is actively involved. All this yielded measurable health outcomes. In Italy and Spain, TBD surveillance and reporting systems are based on compulsory notification. Law enforcement, alongside dedicated time and availability of economic resources, is fragmented and limited to the most severe health issues. Veterinary and human medicine are the most involved disciplines, with the first prevailing in some contexts. Stakeholders are marginally considered and collaborations limited to local initiatives. Research activities have mostly contributed to gaining knowledge on the distribution of tick vectors and discovery of new pathogens. Although all TBD surveillance plans comply with EU regulations, initiatives characterised by transdisciplinary collaboration may be more effective for the surveillance and prevention of TBD.
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Affiliation(s)
- Aitor Garcia-Vozmediano
- Department of Veterinary Sciences, University of Turin, L. go Braccini, 2, 10095 Grugliasco, TO, Italy
- Correspondence:
| | - Daniele De Meneghi
- Department of Veterinary Sciences, University of Turin, L. go Braccini, 2, 10095 Grugliasco, TO, Italy
- Network for EcoHealth and One Health (NEOH), European Chapter of Ecohealth International, Kreuzstrasse 2, P.O. Box, 4123 Allschwil, Switzerland
| | - Hein Sprong
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan 9, 3720 MA Bilthoven, The Netherlands
| | - Aránzazu Portillo
- Center of Rickettsiosis and Arthropod-Borne Diseases (CRETAV), Department of Infectious Diseases, San Pedro University Hospital-Center for Biomedical Research of La Rioja (CIBIR), Calle Piqueras 98, 26006 Logroño, La Rioja, Spain
| | - José A. Oteo
- Center of Rickettsiosis and Arthropod-Borne Diseases (CRETAV), Department of Infectious Diseases, San Pedro University Hospital-Center for Biomedical Research of La Rioja (CIBIR), Calle Piqueras 98, 26006 Logroño, La Rioja, Spain
| | - Laura Tomassone
- Department of Veterinary Sciences, University of Turin, L. go Braccini, 2, 10095 Grugliasco, TO, Italy
- Network for EcoHealth and One Health (NEOH), European Chapter of Ecohealth International, Kreuzstrasse 2, P.O. Box, 4123 Allschwil, Switzerland
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7
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Spatial Analysis of Mosquito-Borne Diseases in Europe: A Scoping Review. SUSTAINABILITY 2022. [DOI: 10.3390/su14158975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Mosquito-borne infections are increasing in endemic areas and previously unaffected regions. In 2020, the notification rate for Dengue was 0.5 cases per 100,000 population, and for Chikungunya <0.1/100,000. In 2019, the rate for Malaria was 1.3/100,000, and for West Nile Virus, 0.1/100,000. Spatial analysis is increasingly used in surveillance and epidemiological investigation, but reviews about their use in this research topic are scarce. We identify and describe the methodological approaches used to investigate the distribution and ecological determinants of mosquito-borne infections in Europe. Relevant literature was extracted from PubMed, Scopus, and Web of Science from inception until October 2021 and analysed according to PRISMA-ScR protocol. We identified 110 studies. Most used geographical correlation analysis (n = 50), mainly applying generalised linear models, and the remaining used spatial cluster detection (n = 30) and disease mapping (n = 30), mainly conducted using frequentist approaches. The most studied infections were Dengue (n = 32), Malaria (n = 26), Chikungunya (n = 26), and West Nile Virus (n = 24), and the most studied ecological determinants were temperature (n = 39), precipitation (n = 24), water bodies (n = 14), and vegetation (n = 11). Results from this review may support public health programs for mosquito-borne disease prevention and may help guide future research, as we recommended various good practices for spatial epidemiological studies.
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8
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Vlaskamp DR, Thijsen SF, Reimerink J, Hilkens P, Bouvy WH, Bantjes SE, Vlaminckx BJ, Zaaijer H, van den Kerkhof HH, Raven SF, Reusken CB. First autochthonous human West Nile virus infections in the Netherlands, July to August 2020. ACTA ACUST UNITED AC 2021; 25. [PMID: 33213687 PMCID: PMC7678035 DOI: 10.2807/1560-7917.es.2020.25.46.2001904] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
Abstract
In October 2020, the first case of autochthonous West Nile virus neuroinvasive disease was diagnosed in the Netherlands with a presumed infection in the last week of August. Investigations revealed five more cases of local West Nile virus (WNV) infection. The cases resided in a region where WNV was detected in a bird and mosquitoes in August 2020. Molecular analysis was successful for two cases and identified the presence of WNV lineage 2.
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Affiliation(s)
- Danique Rm Vlaskamp
- These authors contributed equally.,Department of Neurology, St. Antonius hospital, Nieuwegein, the Netherlands
| | - Steven Ft Thijsen
- Department of Medical Microbiology and Immunology, Diakonessenhuis Hospital, Utrecht, the Netherlands.,These authors contributed equally
| | - Johan Reimerink
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.,These authors contributed equally
| | - Pieter Hilkens
- Department of Neurology, St. Antonius hospital, Nieuwegein, the Netherlands
| | - Willem H Bouvy
- Department of Neurology, Diakonessenhuis Hospital, Utrecht, the Netherlands
| | - Sabine E Bantjes
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Bart Jm Vlaminckx
- Department of Medical Microbiology and Immunology, St. Antonius Hospital, Nieuwegein, the Netherlands
| | - Hans Zaaijer
- Sanquin Blood Supply Foundation and Amsterdam University Medical Centre, Amsterdam, the Netherlands
| | - Hans Htc van den Kerkhof
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Stijn Fh Raven
- Department of Infectious Diseases, Public Health Service region Utrecht, Utrecht, the Netherlands.,Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.,These authors contributed equally
| | - Chantal Bem Reusken
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.,These authors contributed equally
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9
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Sikkema RS, Schrama M, van den Berg T, Morren J, Munger E, Krol L, van der Beek JG, Blom R, Chestakova I, van der Linden A, Boter M, van Mastrigt T, Molenkamp R, Koenraadt CJ, van den Brand JM, Oude Munnink BB, Koopmans MP, van der Jeugd H. Detection of West Nile virus in a common whitethroat ( Curruca communis) and Culex mosquitoes in the Netherlands, 2020. ACTA ACUST UNITED AC 2021; 25. [PMID: 33034280 PMCID: PMC7545818 DOI: 10.2807/1560-7917.es.2020.25.40.2001704] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
On 22 August, a common whitethroat in the Netherlands tested positive for West Nile virus lineage 2. The same bird had tested negative in spring. Subsequent testing of Culex mosquitoes collected in August and early September in the same location generated two of 44 positive mosquito pools, providing first evidence for enzootic transmission in the Netherlands. Sequences generated from the positive mosquito pools clustered with sequences that originate from Germany, Austria and the Czech Republic.
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Affiliation(s)
| | - Maarten Schrama
- Institute of Environmental Sciences, Leiden University, Leiden, the Netherlands
| | - Tijs van den Berg
- Vogeltrekstation -Dutch Centre for Avian Migration and Demography, NIOO-KNAW, Wageningen, the Netherlands
| | - Jolien Morren
- Vogeltrekstation -Dutch Centre for Avian Migration and Demography, NIOO-KNAW, Wageningen, the Netherlands
| | | | - Louie Krol
- Naturalis Biodiversity Center, Leiden, the Netherlands.,Institute of Environmental Sciences, Leiden University, Leiden, the Netherlands
| | | | - Rody Blom
- Laboratory of Entomology, Wageningen University and Research, Wageningen, the Netherlands
| | | | | | - Marjan Boter
- Viroscience, ErasmusMC, Rotterdam, the Netherlands
| | - Tjomme van Mastrigt
- Department of Animal Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, the Netherlands.,Wildlife Ecology and Conservation group, Wageningen University and Research, Wageningen, the Netherlands.,Vogeltrekstation -Dutch Centre for Avian Migration and Demography, NIOO-KNAW, Wageningen, the Netherlands
| | | | | | - Judith Ma van den Brand
- Division of Pathology, Utrecht University, Utrecht, the Netherlands.,Dutch Wildlife Health Centre (DWHC), Utrecht, the Netherlands
| | | | | | - Henk van der Jeugd
- Vogeltrekstation -Dutch Centre for Avian Migration and Demography, NIOO-KNAW, Wageningen, the Netherlands
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