tetano
Editor, Senior Moderator
Transbound Emerg Dis
. 2021 Feb 18.
doi: 10.1111/tbed.14040. Online ahead of print.
Landscape effects and spatial patterns of avian influenza virus in Danish wild birds, 2006-2020
Lene Jung Kjaer[SUP] 1 [/SUP], Charlotte Kristiane Hjulsager[SUP] 2 [/SUP], Lars Erik Larsen[SUP] 1 [/SUP], Anette Ella Boklund[SUP] 1 [/SUP], Tariq Halasa[SUP] 1 [/SUP], Michael P Ward[SUP] 3 [/SUP], Carsten Thure Kirkeby[SUP] 1 [/SUP]
Affiliations
Abstract
Avian influenza (AI) is a contagious disease of birds with zoonotic potential. AI virus (AIV) can infect most bird species, but clinical signs and mortality vary. Assessing the distribution and factors affecting AI presence can direct targeted surveillance to areas at risk of disease outbreaks, or help identify disease hotspots or areas with inadequate surveillance. Using virus surveillance data from passive and active AIV wild bird surveillance, 2006-2020, we investigated the association between the presence of AIV and a range of landscape factors and game bird release. Furthermore, we assessed potential bias in the passive AIV surveillance data submitted by the public, via factors related to public accessibility. Lastly, we tested the AIV data for possible hot- and cold spots within Denmark. The passive surveillance data was biased regarding accessibility to areas (distance to roads, cities and coast) compared to random locations within Denmark. For both the passive and active AIV surveillance data, we found significant (P<0.01) associations with variables related to coast, wetlands and cities, but not game bird release. We used these variables to predict the risk of AIV presence throughout Denmark, and found high-risk areas concentrated along the coast and fjords. For both passive and active surveillance data, low-risk clusters were mainly seen in Jutland and northern Zealand, whereas high-risk clusters were found in Jutland, Zealand, Funen and the southern Isles such as Lolland and Falster. Our results suggest that landscape affects AIV presence, as coastal areas and wetlands attract waterfowl and migrating birds and therefore might increase the potential for AIV transmission. Our findings have enabled us to create risk maps of AIV presence in wild birds and pinpoint high-risk clusters within Denmark. This will aid targeted surveillance efforts within Denmark and potentially aid in planning the location of future poultry farms.
Keywords: AIV surveillance; Avian influenza; high-risk clusters; landscape; spatial patterns; wild birds.
. 2021 Feb 18.
doi: 10.1111/tbed.14040. Online ahead of print.
Landscape effects and spatial patterns of avian influenza virus in Danish wild birds, 2006-2020
Lene Jung Kjaer[SUP] 1 [/SUP], Charlotte Kristiane Hjulsager[SUP] 2 [/SUP], Lars Erik Larsen[SUP] 1 [/SUP], Anette Ella Boklund[SUP] 1 [/SUP], Tariq Halasa[SUP] 1 [/SUP], Michael P Ward[SUP] 3 [/SUP], Carsten Thure Kirkeby[SUP] 1 [/SUP]
Affiliations
- PMID: 33600073
- DOI: 10.1111/tbed.14040
Abstract
Avian influenza (AI) is a contagious disease of birds with zoonotic potential. AI virus (AIV) can infect most bird species, but clinical signs and mortality vary. Assessing the distribution and factors affecting AI presence can direct targeted surveillance to areas at risk of disease outbreaks, or help identify disease hotspots or areas with inadequate surveillance. Using virus surveillance data from passive and active AIV wild bird surveillance, 2006-2020, we investigated the association between the presence of AIV and a range of landscape factors and game bird release. Furthermore, we assessed potential bias in the passive AIV surveillance data submitted by the public, via factors related to public accessibility. Lastly, we tested the AIV data for possible hot- and cold spots within Denmark. The passive surveillance data was biased regarding accessibility to areas (distance to roads, cities and coast) compared to random locations within Denmark. For both the passive and active AIV surveillance data, we found significant (P<0.01) associations with variables related to coast, wetlands and cities, but not game bird release. We used these variables to predict the risk of AIV presence throughout Denmark, and found high-risk areas concentrated along the coast and fjords. For both passive and active surveillance data, low-risk clusters were mainly seen in Jutland and northern Zealand, whereas high-risk clusters were found in Jutland, Zealand, Funen and the southern Isles such as Lolland and Falster. Our results suggest that landscape affects AIV presence, as coastal areas and wetlands attract waterfowl and migrating birds and therefore might increase the potential for AIV transmission. Our findings have enabled us to create risk maps of AIV presence in wild birds and pinpoint high-risk clusters within Denmark. This will aid targeted surveillance efforts within Denmark and potentially aid in planning the location of future poultry farms.
Keywords: AIV surveillance; Avian influenza; high-risk clusters; landscape; spatial patterns; wild birds.