Spatial patterns of avian influenza in wild birds from Denmark, 2006-2020

Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning

Standard

Spatial patterns of avian influenza in wild birds from Denmark, 2006-2020. / Kjær, Lene Jung; Boklund, Anette Ella; Kirkeby, Carsten; Hjulsager, Charlotte Kristiane ; Larsen, Lars; Halasa, Tariq; Ward, Michael P.

2021. Abstract fra SVEPM Conference and Annual General Meeting 2021.

Publikation: Konferencebidrag › Konferenceabstrakt til konference › Forskning

Harvard

Kjær, LJ, Boklund, AE, Kirkeby, C, Hjulsager, CK, Larsen, L, Halasa, T & Ward, MP 2021, 'Spatial patterns of avian influenza in wild birds from Denmark, 2006-2020', SVEPM Conference and Annual General Meeting 2021, 24/03/2021 - 26/03/2021.

APA

Kjær, L. J., Boklund, A. E., Kirkeby, C., Hjulsager, C. K., Larsen, L., Halasa, T., & Ward, M. P. (2021). Spatial patterns of avian influenza in wild birds from Denmark, 2006-2020. Abstract fra SVEPM Conference and Annual General Meeting 2021.

Vancouver

Kjær LJ, Boklund AE, Kirkeby C, Hjulsager CK, Larsen L, Halasa T o.a.. Spatial patterns of avian influenza in wild birds from Denmark, 2006-2020. 2021. Abstract fra SVEPM Conference and Annual General Meeting 2021.

Author

Kjær, Lene Jung ; Boklund, Anette Ella ; Kirkeby, Carsten ; Hjulsager, Charlotte Kristiane ; Larsen, Lars ; Halasa, Tariq ; Ward, Michael P. / Spatial patterns of avian influenza in wild birds from Denmark, 2006-2020. Abstract fra SVEPM Conference and Annual General Meeting 2021.

Bibtex

@conference{b3f0fc95bbee411b99c1720345b6c6d6,
title = "Spatial patterns of avian influenza in wild birds from Denmark, 2006-2020",
abstract = "We investigated factors affecting avian influenza virus (AIV) detections in Danish wild birds using data from the passive and active AIV surveillance in wild birds from 2006-2020. We used this data and machine learning (ML) algorithms along with landscape and environmental variables to develop predictive models of AIV occurrence in Denmark. We furthermore assessed potential accessibility bias in the passive AIV surveillance data submitted by the public. The passive AIV surveillance data was biased regarding accessibility to areas compared to random locations within Denmark. ML models differed in their predictive power and were used to predict the risk of AIV presence throughout Denmark. Our results suggest that landscape variables may affect AIV presence and enabled us to create risk maps of AIV occurrence in Danish wild birds. This may aid future targeted surveillance efforts within Denmark.",
author = "Kj{\ae}r, {Lene Jung} and Boklund, {Anette Ella} and Carsten Kirkeby and Hjulsager, {Charlotte Kristiane} and Lars Larsen and Tariq Halasa and Ward, {Michael P.}",
year = "2021",
month = mar,
day = "25",
language = "English",
note = "null ; Conference date: 24-03-2021 Through 26-03-2021",
url = "https://www.svepm2021.org/",

}

RIS

TY - ABST

T1 - Spatial patterns of avian influenza in wild birds from Denmark, 2006-2020

AU - Kjær, Lene Jung

AU - Boklund, Anette Ella

AU - Kirkeby, Carsten

AU - Hjulsager, Charlotte Kristiane

AU - Larsen, Lars

AU - Halasa, Tariq

AU - Ward, Michael P.

PY - 2021/3/25

Y1 - 2021/3/25

N2 - We investigated factors affecting avian influenza virus (AIV) detections in Danish wild birds using data from the passive and active AIV surveillance in wild birds from 2006-2020. We used this data and machine learning (ML) algorithms along with landscape and environmental variables to develop predictive models of AIV occurrence in Denmark. We furthermore assessed potential accessibility bias in the passive AIV surveillance data submitted by the public. The passive AIV surveillance data was biased regarding accessibility to areas compared to random locations within Denmark. ML models differed in their predictive power and were used to predict the risk of AIV presence throughout Denmark. Our results suggest that landscape variables may affect AIV presence and enabled us to create risk maps of AIV occurrence in Danish wild birds. This may aid future targeted surveillance efforts within Denmark.

AB - We investigated factors affecting avian influenza virus (AIV) detections in Danish wild birds using data from the passive and active AIV surveillance in wild birds from 2006-2020. We used this data and machine learning (ML) algorithms along with landscape and environmental variables to develop predictive models of AIV occurrence in Denmark. We furthermore assessed potential accessibility bias in the passive AIV surveillance data submitted by the public. The passive AIV surveillance data was biased regarding accessibility to areas compared to random locations within Denmark. ML models differed in their predictive power and were used to predict the risk of AIV presence throughout Denmark. Our results suggest that landscape variables may affect AIV presence and enabled us to create risk maps of AIV occurrence in Danish wild birds. This may aid future targeted surveillance efforts within Denmark.

UR - https://www.svepm2021.org/index.php?langue=en&onglet=5&acces=&idUser=&emailUser=&messageConfirmation=

M3 - Conference abstract for conference

Y2 - 24 March 2021 through 26 March 2021

ER -

ID: 259511224