TY - JOUR
T1 - First expert elicitation of knowledge on drivers of emergence of influenza D in Europe
AU - Saegerman, Claude
AU - Bianchini, Juana
AU - Snoeck, Chantal J.
AU - Moreno, Ana
AU - Chiapponi, Chiara
AU - Zohari, Siamak
AU - Ducatez, Mariette F.
N1 - Publisher Copyright:
© 2020 Wiley-VCH GmbH
PY - 2021/11/29
Y1 - 2021/11/29
N2 - The influenza D virus (IDV) was first identified and characterized in 2011. Considering the virus’ zoonotic potential, its genome nature (segmented RNA virus), its worldwide circulation in livestock and its role in bovine respiratory disease, an increased interest is given to IDV. However, few data are available on drivers of emergence of IDV. We first listed fifty possible drivers of emergence of IDV in ruminants and swine. As recently carried out for COVID-19 in pets (Transboundary and Emerging Diseases, 2020), a scoring system was developed per driver and scientific experts (N = 28) were elicited to (a) allocate a score to each driver, (b) weight the drivers’ scores within each domain and (c) weight the different domains among themselves. An overall weighted score was calculated per driver, and drivers were ranked in decreasing order. Drivers with comparable likelihoods to play a role in the emergence of IDV in ruminants and swine in Europe were grouped using a regression tree analysis. Finally, the robustness of the expert elicitation was verified. Eight drivers were ranked with the highest probability to play a key role in the emergence of IDV: current species specificity of the causing agent of the disease; influence of (il)legal movements of live animals (ruminants, swine) from neighbouring/European Union member states and from third countries for the disease to (re-)emerge in a given country; detection of emergence; current knowledge of the pathogen; vaccine availability; animal density; and transport vehicles of live animals. As there is still limited scientific knowledge on the topic, expert elicitation of knowledge and multi-criteria decision analysis, in addition to clustering and sensitivity analyses, are very important to prioritize future studies, starting from the top eight drivers. The present methodology could be applied to other emerging animal diseases.
AB - The influenza D virus (IDV) was first identified and characterized in 2011. Considering the virus’ zoonotic potential, its genome nature (segmented RNA virus), its worldwide circulation in livestock and its role in bovine respiratory disease, an increased interest is given to IDV. However, few data are available on drivers of emergence of IDV. We first listed fifty possible drivers of emergence of IDV in ruminants and swine. As recently carried out for COVID-19 in pets (Transboundary and Emerging Diseases, 2020), a scoring system was developed per driver and scientific experts (N = 28) were elicited to (a) allocate a score to each driver, (b) weight the drivers’ scores within each domain and (c) weight the different domains among themselves. An overall weighted score was calculated per driver, and drivers were ranked in decreasing order. Drivers with comparable likelihoods to play a role in the emergence of IDV in ruminants and swine in Europe were grouped using a regression tree analysis. Finally, the robustness of the expert elicitation was verified. Eight drivers were ranked with the highest probability to play a key role in the emergence of IDV: current species specificity of the causing agent of the disease; influence of (il)legal movements of live animals (ruminants, swine) from neighbouring/European Union member states and from third countries for the disease to (re-)emerge in a given country; detection of emergence; current knowledge of the pathogen; vaccine availability; animal density; and transport vehicles of live animals. As there is still limited scientific knowledge on the topic, expert elicitation of knowledge and multi-criteria decision analysis, in addition to clustering and sensitivity analyses, are very important to prioritize future studies, starting from the top eight drivers. The present methodology could be applied to other emerging animal diseases.
KW - clustering analysis
KW - drivers
KW - expert elicitation
KW - influenza D virus
KW - multi-criteria decision analysis
KW - ruminants
KW - sensitivity analysis
KW - swine
UR - http://www.scopus.com/inward/record.url?scp=85104630641&partnerID=8YFLogxK
UR - https://www.ncbi.nlm.nih.gov/pubmed/33249766
U2 - 10.1111/tbed.13938
DO - 10.1111/tbed.13938
M3 - Article
C2 - 33249766
AN - SCOPUS:85104630641
SN - 1865-1674
VL - 68
SP - 3349
EP - 3359
JO - Transboundary and Emerging Diseases
JF - Transboundary and Emerging Diseases
IS - 6
ER -