Experimental infectious pancreatic necrosis infections: propagative or point-source epidemic?

Smith, Graham C.; Bebak, Julie; McAllister, P.E.

doi:10.1016/s0167-5877(00)00176-8

Cited by 17 publications

(9 citation statements)

References 23 publications

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“…All the 10 oysters were exposed together for 24 h in a tank with titrated contaminated seawater, then were transferred to clean water for the 12-day monitoring. Hence, we cannot be sure that what we observed in tanks was transmission, a point-source outbreak without any transmission, or a mixture of both, as revealed in the experimentally initiated epidemics of infectious pancreatic necrosis in rainbow trout fry (59). This may explain the overestimation of the kinetics of infection by the model involving the baseline range of parameters sampled from the distributions fitted to experimental individual data.…”

Section: Discussionmentioning

confidence: 86%

Modeling the Transmission of Vibrio aestuarianus in Pacific Oysters Using Experimental Infection Data

et al. 2019

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Vibrio aestuarianus is a bacterium related to mortality outbreaks in Pacific oysters, Crassostrea gigas , in France, Ireland, and Scotland since 2011. Knowledge about its transmission dynamics is still lacking, impairing guidance to prevent and control the related disease spread. Mathematical modeling is a relevant approach to better understand the determinants of a disease and predict its dynamics in imperfectly observed pathosystems. We developed here the first marine epidemiological model to estimate the key parameters of V. aestuarianus infection at a local scale in a small and closed oyster population under controlled laboratory conditions. Using a compartmental model accounting for free-living bacteria in seawater, we predicted the infection dynamics using dedicated and model-driven collected laboratory experimental transmission data. We estimated parameters and showed that waterborne transmission of V. aestuarianus is possible under experimental conditions, with a basic reproduction number R 0 of 2.88 (95% CI: 1.86; 3.35), and a generation time of 5.5 days. Our results highlighted a bacterial dose–dependent transmission of vibriosis at local scale. Global sensitivity analyses indicated that the bacteria shedding rate, the concentration of bacteria in seawater that yields a 50% chance of catching the infection, and the initial bacterial exposure dose W 0 were three critical parameters explaining most of the variation in the selected model outputs related to disease spread, i.e., R 0 , the maximum prevalence, oyster survival curve, and bacteria concentration in seawater. Prevention and control should target the exposure of oysters to bacterial concentration in seawater. This combined laboratory–modeling approach enabled us to maximize the use of information obtained through experiments. The identified key epidemiological parameters should be better refined by further dedicated laboratory experiments. These results revealed the importance of multidisciplinary approaches to gain consistent insights into the marine epidemiology of oyster diseases.

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Section: Discussionmentioning

confidence: 86%

Modeling the Transmission of Vibrio aestuarianus in Pacific Oysters Using Experimental Infection Data

et al. 2019

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“…Parameter 2 -Presence and duration of the latent infection period Fish become infectious and begin shedding the virus after about 2 days of latency (McAllister, 2007). Experimental infection trials using fingerling trout indicate that there is a latent period of about 2 days after infection before infected fish begin to shed detectable quantities of IPNV into the water (Smith et al, 2000).…”

Section: Animal Populationmentioning

confidence: 99%

Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): infectious pancreatic necrosis (IPN)

Nielsen¹,

Álvarez²,

Calistri³

et al. 2023

EFS2

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Infectious pancreatic necrosis (IPN) was assessed according to the criteria of the Animal Health Law (AHL), in particular, the criteria of Article 7 on disease profile and impacts, Article 5 on its eligibility to be listed, Annex IV for its categorisation according to disease prevention and control rules as in Article 9, and Article 8 for listing animal species related to IPN. The assessment was performed following a methodology previously published. The outcome reported is the median of the probability ranges provided by the experts, which indicates whether each criterion is fulfilled (lower bound ≥ 66%) or not (upper bound ≤ 33%), or whether there is uncertainty about fulfilment. Reasoning points are reported for criteria with an uncertain outcome. According to the assessment here performed, it is uncertain whether IPN can be considered eligible to be listed for Union intervention according to Article 5 of the AHL (50-90% probability). According to the criteria in Annex IV, for the purpose of categorisation related to the level of prevention and control as in Article 9 of the AHL, the AHAW Panel concluded that IPN does not meet the criteria in Section 1 (Category A; 0-1% probability of meeting the criteria) and it is uncertain whether it meets the criteria in Sections 2, 3, 4 and 5 (Categories B, C, D and E; 33-66%, 33-66%, 50-90% and 50-99% probability of meeting the criteria, respectively). The animal species to be listed for IPN according to Article 8 criteria are provided.

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“…The scenarios were discussed with fish disease experts and their parameters were derived from published work for two salmonid diseases; Furunculosis (Aeromonas salmonicida) and Infectious Pancreatic Necrosis (infectious pancreatic necrosis virus). (20,26,27) The low scenario simulated a relatively low spreading disease with low mortality rates, whereas the high scenario modeled a fast spreading disease with high mortality. The medium scenario simulated intermediate spread and mortality.…”

Section: Scenarios For Intrapond Modelmentioning

confidence: 99%

Disease Spread Models to Estimate Highly Uncertain Emerging Diseases Losses for Animal Agriculture Insurance Policies: An Application to the U.S. Farm‐Raised Catfish Industry

Zagmutt

Sempier²,

Hanson³

2013

Risk Analysis

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Emerging diseases (ED) can have devastating effects on agriculture. Consequently, agricultural insurance for ED can develop if basic insurability criteria are met, including the capability to estimate the severity of ED outbreaks with associated uncertainty. The U.S. farm-raised channel catfish (Ictalurus punctatus) industry was used to evaluate the feasibility of using a disease spread simulation modeling framework to estimate the potential losses from new ED for agricultural insurance purposes. Two stochastic models were used to simulate the spread of ED between and within channel catfish ponds in Mississippi (MS) under high, medium, and low disease impact scenarios. The mean (95% prediction interval (PI)) proportion of ponds infected within disease-impacted farms was 7.6% (3.8%, 22.8%), 24.5% (3.8%, 72.0%), and 45.6% (4.0%, 92.3%), and the mean (95% PI) proportion of fish mortalities in ponds affected by the disease was 9.8% (1.4%, 26.7%), 49.2% (4.7%, 60.7%), and 88.3% (85.9%, 90.5%) for the low, medium, and high impact scenarios, respectively. The farm-level mortality losses from an ED were up to 40.3% of the total farm inventory and can be used for insurance premium rate development. Disease spread modeling provides a systematic way to organize the current knowledge on the ED perils and, ultimately, use this information to help develop actuarially sound agricultural insurance policies and premiums. However, the estimates obtained will include a large amount of uncertainty driven by the stochastic nature of disease outbreaks, by the uncertainty in the frequency of future ED occurrences, and by the often sparse data available from past outbreaks.

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Experimental infectious pancreatic necrosis infections: propagative or point-source epidemic?

Cited by 17 publications

References 23 publications

Modeling the Transmission of Vibrio aestuarianus in Pacific Oysters Using Experimental Infection Data

Modeling the Transmission of Vibrio aestuarianus in Pacific Oysters Using Experimental Infection Data

Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): infectious pancreatic necrosis (IPN)

Disease Spread Models to Estimate Highly Uncertain Emerging Diseases Losses for Animal Agriculture Insurance Policies: An Application to the U.S. Farm‐Raised Catfish Industry

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