Estimating the burden and modeling mitigation strategies of pork-related hepatitis E virus foodborne transmission in representative European countries

Yunpeng Ji, Pengfei Li, Yueqi Jia, Xiaohua Wang, Qinyue Zheng, Maikel P. Peppelenbosch, Zhongren Ma*, Qiuwei Pan*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
6 Downloads (Pure)

Abstract

Hepatitis E virus (HEV) is an emerging zoonotic pathogen posing global health burden, and the concerns in Europe are tremendously growing. Pigs serve as a main reservoir, contributing to pork-related foodborne transmission. In this study, we aim to specifically simulate this foodborne transmission route and to assess potential interventions. We firstly established a dose-response relationship between the risk of transmission to human and the amount of ingested viruses. We further estimated the incidence of HEV infection specifically attributed to pork-related foodborne transmission in four representative European countries. Finally, we demonstrated a proof-of-concept of mitigating HEV transmission by implementing vaccination in human and pig populations. Our modeling approach bears essential implications for better understanding the transmission of pork-related foodborne HEV and for developing mitigation strategies.

Original languageEnglish
Article number100350
JournalOne Health
Volume13
DOIs
Publication statusPublished - Dec 2021

Bibliographical note

Funding Information:
We thank the Changjiang Scholars and Innovative Research Team in University grant (No. IRT_17R88 ) from the Ministry of Education of the People's Republic of China to Z. Ma, and the Netherlands Organization for Scientific Research (NWO) for funding a VIDI grant ( 91719300 ) to Q.P.

Publisher Copyright:
© 2021

Fingerprint

Dive into the research topics of 'Estimating the burden and modeling mitigation strategies of pork-related hepatitis E virus foodborne transmission in representative European countries'. Together they form a unique fingerprint.

Cite this