Combining network analysis with epidemiological data to inform risk-based surveillance: Application to hepatitis E virus (HEV) in pigs

Abstract

Animal movements between farms are a major route of pathogen spread in the pig production sector. This study aimed to pair network analysis and epidemiological data in order to evaluate the impact of animal movements on pathogen prevalence in farms and assess the risk of local areas being exposed to diseases due to incoming movements. Our methodology was applied to hepatitis E virus (HEV), an emerging foodborne zoonotic agent of concern that is highly prevalent in pig farms. Firstly, the pig movement network in France (data recorded in 2013) and the results of a nation-wide seroprevalence study (data collected in 178 farms in 2009) were modelled and analysed. The link between network centrality measures of farms and HEV seroprevalence levels was explored using a generalised linear model. The in-degree and ingoing closeness of farms were found to be statistically associated with high HEV within-farm seroprevalence (p<0.05). Secondly, the risk of a French département (i.e. French local administrative areas) being exposed to HEV was calculated by combining the distribution of farm-level HEV prevalence in source départements with the number of movements coming from those same départements. By doing so, the risk of exposure for départements was mapped, highlighting differences between geographical patterns of HEV prevalence and the risk of exposure to HEV. These results suggest that not only highly prevalent areas but also those having at-risk movements from infected areas should be monitored. Pathogen management and surveillance options in the pig production sector should therefore take animal movements into consideration, paving the way for the development of targeted and risk-based disease surveillance strategies.

Modeling Epidemics in Seed Systems to Guide Management Strategies: The Case of Sweetpotato in Northern Uganda

“…8). The utility of node degree for prioritization is consistent with literature on pathogen spread in animal trade networks, where centrality measures (such as degree) have been significantly associated with on-farm disease levels and disease progress (Kiss et al 2006;Lee et al 2017;Salines et al 2018).…”

Identifying outbreaks of Porcine Epidemic Diarrhea virus through animal movements and spatial neighborhoods

“…A number of studies have examined swine movement networks as a main transmission route for disease spread 16,[35][36][37][38][39] , network analysis and epidemiological data have recently been used to assess risk of local areas being exposed to pathogens as a consequence of animal introduction 40 . The approach presented here provides a realistic understanding of PEDV dynamics by capturing long distance spread via animal movements and linking it with epidemiological factors related to local area spread between neighboring farms.…”

Natural viral co‐infections in pig herds affect hepatitis E virus (HEV) infection dynamics and increase the risk of contaminated livers at slaughter

“…Other studies also pointed a number of farm‐specific factors that influence HEV infection features, for example farm size, genetic background, lack of hygiene measures, origin of drinking water, frequency of pig exchanges, etc. (Di Bartolo et al, ; Hinjoy et al, ; Jinshan et al, ; Li et al, ; Salines et al, ; Walachowski et al, ). This is the reason why the farm variable was included as a repeated and frailty effect in the GEE and survival models respectively.…”

“…farm size, mingling practices, origin of drinking water, presence of a hygiene lock) (Hinjoy et al, ; Jinshan, Manglai, Takahashi, Nagashima, & Okamoto, ; Li et al, ; Walachowski et al, ). Between‐farm pig movements and the contact network topology have also been found to influence the epidemiological HEV situation of farms (Salines, Andraud, & Rose, ). However, individual risk factors related to piglets’ specific characteristics (e.g.…”