Tackling hepatitis E virus spread and persistence on farrow-to-finish pig farms: Insights from a stochastic individual-based multi-pathogen model

Salines, Morgane; Rose, Nicolas; Andraud, Mathieu

doi:10.1016/j.epidem.2019.100369

Cited by 12 publications

(25 citation statements)

References 34 publications

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“…The field of application and the representation structure is somehow correlated with the specific target/final user. Hence, models on regulated diseases will be often developed at the between herd scale and will address questions from policy makers in animal health [68,74,104,105], whereas models developed for enzootic diseases are more generally developed on a herd level scale to answer more applied questions on disease control rather relevant for veterinarians and farmers [43,57,60]. These models can put together available data from observational and experimental origin and can provide estimates of non measurable facts.…”

Section: Discussionmentioning

confidence: 99%

“…These approaches based on data-designed models need to be distinguished from pure model development of complex structured population in which a pathogen or a combination of pathogens is spreading. This latter strategy has been often developed in porcine health management to understand infection dynamics in a comprehensive way by filling the gap of unobserved phenomenon (by observational or experimental studies) [48,49,60]. Hence the objective is rarely the pure prediction per se with the exception in specific cases of regulated diseases for the question of the impact of the pathogen in case of introduction in a free territory.…”

Section: Discussionmentioning

confidence: 99%

“…PRRS). Salines et al [60] analyzed the spread of HEV in farrow-to-finish pig farms through the development of an agent-based framework describing the co-circulation of HEV along with an immune-modulating virus. Such approach allowed for the analysis of modifications of husbandry practices acting on individual animals, but having a more general impact on the course of infection (e.g.…”

Section: Mat 1)mentioning

confidence: 99%

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Modelling infectious viral diseases in swine populations: a state of the art

Andraud

Rose

2020

Porc Health Manag

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Mathematical modelling is nowadays a pivotal tool for infectious diseases studies, completing regular biological investigations. The rapid growth of computer technology allowed for development of computational tools to address biological issues that could not be unravelled in the past. The global understanding of viral disease dynamics requires to account for all interactions at all levels, from within-host to between-herd, to have all the keys for development of control measures. A literature review was performed to disentangle modelling frameworks according to their major objectives and methodologies. One hundred and seventeen articles published between 1994 and 2020 were found to meet our inclusion criteria, which were defined to target papers representative of studies dealing with models of viral infection dynamics in pigs. A first descriptive analysis, using bibliometric indexes, permitted to identify keywords strongly related to the study scopes. Modelling studies were focused on particular infectious agents, with a shared objective: to better understand the viral dynamics for appropriate control measure adaptation. In a second step, selected papers were analysed to disentangle the modelling structures according to the objectives of the studies. The system representation was highly dependent on the nature of the pathogens. Enzootic viruses, such as swine influenza or porcine reproductive and respiratory syndrome, were generally investigated at the herd scale to analyse the impact of husbandry practices and prophylactic measures on infection dynamics. Epizootic agents (classical swine fever, foot-and-mouth disease or African swine fever viruses) were mostly studied using spatio-temporal simulation tools, to investigate the efficiency of surveillance and control protocols, which are predetermined for regulated diseases. A huge effort was made on model parameterization through the development of specific studies and methodologies insuring the robustness of parameter values to feed simulation tools. Integrative modelling frameworks, from within-host to spatio-temporal models, is clearly on the way. This would allow to capture the complexity of individual biological variabilities and to assess their consequences on the whole system at the population level. This would offer the opportunity to test and evaluate in silico the efficiency of possible control measures targeting specific epidemiological units, from hosts to herds, either individually or through their contact networks. Such decision support tools represent a strength for stakeholders to help mitigating infectious diseases dynamics and limiting economic consequences.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Mat 1)mentioning

confidence: 99%

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Modelling infectious viral diseases in swine populations: a state of the art

Andraud

Rose

2020

Porc Health Manag

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“…As described in Salines, Rose [ 24 ], an MSEIR–Maternally Immune (M), Susceptible (S), Exposed (E), Infectious (I) and Recovered (R)–model including an environmental compartment was considered to describe HEV infection dynamics taking those factors into account ( Fig 4 ). Briefly, new-born piglets born from immune sows acquire anti-HEV maternally-derived antibodies by colostrum intake (health state M), providing complete but temporary protection towards infection.…”

Section: Methodsmentioning

confidence: 99%

“…porcine reproductive and respiratory syndrome virus (PRRSV) or porcine circovirus type 2 (PCV2) [ 19 , 22 , 23 ]. Recently, we have developed a stochastic individual-based model representing HEV spread and persistence on a farrow-to-finish pig farm in which pigs may be co-infected with IMVs [ 24 ]. This model gave insights on HEV spread and persistence and evidenced or confirmed several risk factors, e.g.…”

Section: Introductionmentioning

confidence: 99%

A between-herd data-driven stochastic model to explore the spatio-temporal spread of hepatitis E virus in the French pig production network

et al. 2020

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Hepatitis E virus is a zoonotic pathogen for which pigs are recognized as the major reservoir in industrialised countries. A multiscale model was developed to assess the HEV transmission and persistence pattern in the pig production sector through an integrative approach taking into account within-farm dynamics and animal movements based on actual data. Within-farm dynamics included both demographic and epidemiological processes. Direct contact and environmental transmission routes were considered along with the possible co-infection with immunomodulating viruses (IMVs) known to modify HEV infection dynamics. Movements were limited to 3,017 herds forming the largest community on the swine commercial network in France and data from the national pig movement database were used to build the contact matrix. Between-herd transmission was modelled by coupling within-herd and network dynamics using the SimInf package. Different introduction scenarios were tested as well as a decrease in the prevalence of IMV-infected farms. After introduction of a single infected gilt, the model showed that the transmission pathway as well as the prevalence of HEV-infected pigs at slaughter age were affected by the type of the index farm, the health status of the population and the type of the infected farms. These outcomes could help design HEV control strategies at a territorial scale based on the assessment of the farms’ and network’s risk.

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