Multi levels Hepatitis E Virus Spread In Various Epidemiological Contexts: Combining Complex Network Analysis &amp; Disease Transmission Model
Creators: name: Pachka, Hammami
name: Stefan, Widgren
name: Grosbois Vladimir
name: Apollini Andrea
name: Nicolas, Rose
name: Mathieu, Andraud
Publisher: name: Zenodo
Year: 2021

description: Hepatitis E virus (HEV) infects pigs and humans. Its spread among pigs occurs within-farm through faecal–oral route including direct and environmental transmission (Andraud et al., 2013). Live animal movements are known as the major driver of between farms spread (Saline et al. 2020). Strongly structured in space and time, the swine production chain is made of various interconnected farms, forming a complex network. We aimed to simulate realistic between-farm movements to feed a multilevel epidemiological model. Swine movements from 2017 to 2019 provided by the National Swine Identification database (BDporc) were analysed using network analysis (NA) methods. Exponential random graph models (ERGM) were then used to identify the key drivers of trade partner choices and the associated probabilities of contact between farms. In the 36-month period, 2.512.174 loading and unloading events were recorded involving 16.377 premises. Because of the large size of the dataset, analysis was limited to specific subsets of the data, using semestrial data and type of transported animals (breeding sows, piglets and growing pigs). For each data subset, an ERGM was selected using a stepwise forward approach based on AICs comparison and analyzing goodness-of-fit. In all cases, the company, type of farm, free-ranging characteristics, size and batch rearing systems were identified as explanatory variables of the network structure. Network statistics and levels included were subnetwork-specific. ERGM outcomes allow simulating pig trade networks with characteristics similar to the observed one (Figure 1), to prospect on the global impact of the network structure on pathogen transmission. Simulated movements fed a multi-level model developed with SimInf package (Widgren et al. 2019). First run on French data, the model will be extended to England and Germany. The simulated prevalence of HEV positive pigs sent to slaughterhouses, will feed a Quantitative microbiological risk assessment model (QMRA) to evaluate the risk of human exposure to HEV through swine products (Snary et al., 2016). <strong>Acknowledgements</strong><br> We would like to thank the comprehensive French national pig identification database (BDporc) for providing the data. This work was supported by funding from the European Union’s Horizon 2020 Research and Innovation programme under grant agreement No 773830: One Health European Joint Programme.
description: {"references": ["Andraud, M., Dumarest, M., Cariolet, R., Aylaj, B., Barnaud, E., Eono, F., Pavio, N., Rose, N., 2013. Direct contact and environmental contaminations are responsible for HEV transmission in pigs. Vet Res 44, 102. https://doi.org/10.1186/1297-9716-44-102", "Salines, M., Andraud, M., Rose, N., Widgren, S., 2020. A between-herd data-driven stochastic model to explore the spatio-temporal spread of hepatitis E virus in the French pig production network. PLoS ONE 15, e0230257. https://doi.org/10.1371/journal.pone.0230257", "Widgren, S., Bauer, P., Eriksson, R., Engblom, S., 2019. SimInf: An R Package for Data-Driven Stochastic Disease Spread Simulations. Journal of Statistical Software 91, 1\u201342. https://doi.org/10.18637/jss.v091.i12", "Snary, E.L., Swart, A.N., Simons, R.R.L., Domingues, A.R.C., Vigre, H., Evers, E.G., Hald, T., Hill, A.A., 2016. A Quantitative Microbiological Risk Assessment for Salmonella in Pigs for the European Union. Risk Anal 36, 437\u2013449. https://doi.org/10.1111/risa.12586"]}