Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021-2022

Diletta Fornasiero
* ORCID logo ,
Alice Fusaro
ORCID logo ,
Bianca Zecchin
ORCID logo ,
Matteo Mazzucato
,
Francesca Scolamacchia
ORCID logo ,
Grazia Manca
,
Calogero Terregino
,
Tiziano Dorotea
* ORCID logo ,
Paolo Mulatti
Version 1 : Received: 20 December 2022 / Approved: 22 December 2022 / Online: 22 December 2022 (01:14:38 CET)

A peer-reviewed article of this Preprint also exists.

Fornasiero, D.; Fusaro, A.; Zecchin, B.; Mazzucato, M.; Scolamacchia, F.; Manca, G.; Terregino, C.; Dorotea, T.; Mulatti, P. Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021–2022. Pathogens 2023, 12, 100. Fornasiero, D.; Fusaro, A.; Zecchin, B.; Mazzucato, M.; Scolamacchia, F.; Manca, G.; Terregino, C.; Dorotea, T.; Mulatti, P. Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021–2022. Pathogens 2023, 12, 100.

Abstract

Between October 2021 and April 2022, 317 outbreaks caused by highly pathogenic avian influen-za (HPAI) H5N1 viruses were notified in poultry farms in the northeastern Italian Regions. The complete genomes of 214 strains were used to estimate the genetic network based on the virus similarity. An exponential random graph model (ERGM) was used to assess the effect of at-risk contacts, same owners, in-bound/out-bound risk windows overlap, genetic differences, geograph-ic distances, same species and poultry company, on the probability of observing a link within the genetic network, which can be interpreted as the potential propagation of the epidemic via lateral spread or a common source of infection. The variables same poultry company (Est.=0.548, C.I.=[0.179;0.918]) and risk windows overlap (Est.=0.339, C.I.=[0.309;0.368]) were associated with a higher probability of link formation, while the genetic differences (Est.=-0.563, C.I.=[-0.640;-0.486]) and geographic distances (Est.=-0.058, C.I.=[-0.078;-0.038]) indicated a re-duced probability. The integration of epidemiological data with genomic analyses allows moni-toring the epidemic evolution and helps explain the dynamics of lateral spreads suggesting the potential diffusion routes. The 2021-2022 epidemic stresses the need to further strengthen the bi-osecurity measures, and to encourage the reorganisation of the poultry production sector to mini-mize the impact of future epidemics.

Keywords

HPAI; H5N1; Italy; genetic network; epidemiological investigation; contact tracing; ERGM

Subject

Biology and Life Sciences, Virology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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