Claire Guinat

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Guinat

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Claire

ORCID

0000-0002-8245-9290

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Publications1 - 10 of 32

Bayesian phylodynamics reveals the transmission dynamics of avian influenza A(H7N9) virus at the human-live bird market interface in China
Guinat, Claire; Tang, Hao; Yang, Qiqi; et al. (2023)
Proceedings of the National Academy of Sciences of the United States of America
In 2013 to 2017, avian influenza A(H7N9) virus has caused five severe epidemic waves of human infections in China. The role of live bird markets (LBMs) in the transmission dynamics of H7N9 remains unclear. Using a Bayesian phylodynamic approach, we shed light on past H7N9 transmission events at the human-LBM interface that were not directly observed using case surveillance data-based approaches. Our results reveal concurrent circulation of H7N9 lineages in Yangtze and Pearl River Delta regions, with evidence of local transmission during each wave. Our results indicate that H7N9 circulated in humans and LBMs for weeks to months before being first detected. Our findings support the seasonality of H7N9 transmission and suggest a high number of underreported infections, particularly in LBMs. We provide evidence for differences in virus transmissibility between low and highly pathogenic H7N9. We demonstrate a regional spatial structure for the spread of H7N9 among LBMs, highlighting the importance of further investigating the role of local live poultry trade in virus transmission. Our results provide estimates of avian influenza virus (AIV) transmission at the LBM level, providing a unique opportunity to better prepare surveillance plans at LBMs for response to future AIV epidemics.
Unravelling direct and indirect contact patterns between duck farms in France and their association with the 2016–2017 epidemic of Highly Pathogenic Avian Influenza (H5N8)
Bauzile, Billy; Sicard, G.; Guinat, Claire; et al. (2022)
Preventive Veterinary Medicine
Live animal movements generate direct contacts (via the exchange of live animals) and indirect contacts (via the transit of transport vehicles) between farms, which can contribute to the spread of pathogens. However, most analyses focus solely on direct contacts and can therefore underestimate the contribution of live animal movements in the spread of infectious diseases. Here, we used French live duck movement data (2016–2018) from one of the largest transport companies to compare direct and indirect contact patterns between duck farms and evaluate how these patterns were associated with the French 2016–2017 epidemic of highly pathogenic avian influenza H5N8. A total number of 614 farms were included in the study, and two directed networks were generated: the animal introduction network (exchange of live ducks) and the transit network (transit of transport vehicles). Following descriptive analyses, these two networks were scrutinized in relation to farm infection status during the epidemic. Results showed that farms were substantially more connected in the transit network than in the animal introduction network and that the transit of transport vehicles generated more opportunities for transmission than the exchange of live animals. We also showed that animal introduction and transit networks’ statistics decreased substantially during the epidemic (January–March 2017) compared to non-epidemic periods (January–March 2016 and January–March 2018). We estimated a probability of 33.3 % that a farm exposed to the infection through either of the two live duck movement networks (i.e. that was in direct or indirect contact with a farm that was reported as infected in the following seven days) becomes infected within seven days after the contact. However, we also demonstrated that the level of exposure of farms by these two contact patterns was low, leading only to a handful of transmission events through these routes. As a consequence, we showed that live animal movement patterns are efficient transmission routes for HPAI but have been efficiently reduced to limit the spread during the French 2020–2021 epidemic. These results underpin the relevance of studying indirect contacts resulting from the movement of animals to understand their transmission potential and the importance of accounting for both routes when designing disease control strategies.
Inferring within-herd transmission parameters for African swine fever virus using mortality data from outbreaks in the Russian Federation
Guinat, Claire; Porphyre, Thibaud; Gogin, Andrey; et al. (2018)
Transboundary and Emerging Diseases
Mortality data are routinely collected for many livestock and poultry species, and they are often used for epidemiological purposes, including estimating transmission parameters. In this study, we infer transmission rates for African swine fever virus (ASFV), an important transboundary disease of swine, using mortality data collected from nine pig herds in the Russian Federation with confirmed outbreaks of ASFV. Parameters in a stochastic model for the transmission of ASFV within a herd were estimated using approximate Bayesian computation. Estimates for the basic reproduction number varied amongst herds, ranging from 4.4 to 17.3. This was primarily a consequence of differences in transmission rate (range: 0.7–2.2), but also differences in the mean infectious period (range: 4.5–8.3 days). We also found differences amongst herds in the mean latent period (range: 5.8–9.7 days). Furthermore, our results suggest that ASFV could be circulating in a herd for several weeks before a substantial increase in mortality is observed in a herd, limiting the usefulness of mortality data as a means of early detection of an outbreak. However, our results also show that mortality data are a potential source of data from which to infer transmission parameters, at least for diseases which cause high mortality.
Biosecurity measures in French poultry farms are associated with farm type and location
Delpont, Mattias; Guinat, Claire; Guérin, Jean‐Luc; et al. (2021)
Preventive Veterinary Medicine
The severe impact of recently reported Highly Pathogenic Avian Influenza (HPAI) outbreaks have emphasized the need to better monitor biosecurity practices among the different French poultry production systems. Between October 2016 and September 2018, a large national cross-sectional study was carried out in France to assess biosecurity levels in high-risk poultry farms and identify farm biosecurity profiles, using Multiple Correspondence and Hierarchical Cluster Analyses. Results indicate that there is substantial room for improvement in cleaning and disinfection, anteroom management and delimitation of farm and production units for more than 50 % of the 1,004 analyzed farms. The farm biosecurity profile showing the highest level of biosecurity included commercial intensive poultry farms (gallinaceous poultry farms, in North-Western France), and those with a recent history of HPAI outbreak (duck farms, in South-Western France). The farms biosecurity profiles showing the lowest level of biosecurity included farms with multiple species (duck and gallinaceous poultry) or multiple production types (broilers and egg-layers), located in regions with a lower poultry density and without a recent history of HPAI outbreak. Outcomes provide support to adapt biosecurity improvement and inspection plans.
Biosecurity risk factors for highly pathogenic avian influenza (H5N8) virus infection in duck farms, France
Guinat, Claire; Comin, Arianna; Kratzer, Gilles; et al. (2020)
Transboundary and Emerging Diseases
Highly pathogenic avian influenza (HPAI) subtype H5N8 outbreaks occurred in poultry farms in France in 2016–2017, resulting in significant economic losses and disruption to the poultry industry. Current evidence on associations between actual on‐farm biosecurity risk factors and H5N8 occurrence is limited. Therefore, a retrospective matched case–control study was undertaken to investigate the inter‐relationships between on‐farm biosecurity practices and H5N8 infection status to provide new insights regarding promising targets for intervention. Data were collected on 133 case and 133 control duck farms (i.e. the most affected species) located in one area of the country that was mostly affected by the disease. Data were analysed using Additive Bayesian Networks which offer a rich modelling framework by graphically illustrating the dependencies between variables. Factors indirectly and directly positively associated with farm infection were inadequate management of vehicle movements (odds ratio [OR] 9.3, 95% credible interval [CI] 4.0–22.8) and inadequate delimitation of farm and units (OR 3.0, 95% CI 1.6–5.8), respectively. Inadequate disposal of dead birds was instead negatively associated with the outcome (OR 0.1, 95% CI 0.0–0.3). The findings highlight that reinforcing farm access control systems and reducing the number of visitors are key biosecurity measures to control farm vulnerability to H5N8 infection and could help setting priorities in biosecurity practices to prevent outbreaks’ re‐occurrence.
Exploring pig trade patterns to inform the design of risk-based disease surveillance and control strategies
Guinat, Claire; Relun, A.; Wall, Ben; et al. (2016)
Scientific Reports
An understanding of the patterns of animal contact networks provides essential information for the design of risk-based animal disease surveillance and control strategies. This study characterises pig movements throughout England and Wales between 2009 and 2013 with a view to characterising spatial and temporal patterns, network topology and trade communities. Data were extracted from the Animal and Plant Health Agency (APHA)’s RADAR (Rapid Analysis and Detection of Animal-related Risks) database, and analysed using descriptive and network approaches. A total of 61,937,855 pigs were moved through 872,493 movements of batches in England and Wales during the 5-year study period. Results show that the network exhibited scale-free and small-world topologies, indicating the potential for diseases to quickly spread within the pig industry. The findings also provide suggestions for how risk-based surveillance strategies could be optimised in the country by taking account of highly connected holdings, geographical regions and time periods with the greatest number of movements and pigs moved, as these are likely to be at higher risk for disease introduction. This study is also the first attempt to identify trade communities in the country, information which could be used to facilitate the pig trade and maintain disease-free status across the country in the event of an outbreak.
Experimental pig-to-pig transmission dynamics for African swine fever virus, Georgia 2007/1 strain
Guinat, Claire; Gubbins, Simon; Vergne, Timothée; et al. (2016)
Epidemiology and Infection
African swine fever virus (ASFV) continues to cause outbreaks in domestic pigs and wild boar in Eastern European countries. To gain insights into its transmission dynamics, we estimated the pig-to-pig basic reproduction number (R 0) for the Georgia 2007/1 ASFV strain using a stochastic susceptible-exposed-infectious-recovered (SEIR) model with parameters estimated from transmission experiments. Models showed that R 0 is 2·8 [95% confidence interval (CI) 1·3–4·8] within a pen and 1·4 (95% CI 0·6–2·4) between pens. The results furthermore suggest that ASFV genome detection in oronasal samples is an effective diagnostic tool for early detection of infection. This study provides quantitative information on transmission parameters for ASFV in domestic pigs, which are required to more effectively assess the potential impact of strategies for the control of between-farm epidemic spread in European countries.
Transmission routes of African swine fever virus to domestic pigs: Current knowledge and future research directions
Guinat, Claire; Gogin, Andrey; Blome, Sandra; et al. (2016)
Veterinary Record
African swine fever (ASF) is a major threat to the pig industry in Europe. Since 2007, ASF outbreaks have been ongoing in the Caucasus, Eastern Europe and the Baltic countries, causing severe economic losses for many pig farmers and pork producers. In addition, the number of ASF cases in wild boar populations has dramatically increased over the past few years. Evidence supports direct contact with infectious domestic pigs and wild boars, and consumption of contaminated feed, as the main transmission routes of ASF virus (ASFV) to domestic pigs. However, significant knowledge gaps highlight the urgent need for research to investigate the dynamics of indirect transmission via the environment, the minimal infective doses for contaminated feed ingestion, the probability of effective contacts between infectious wild boars and domestic pigs, the potential for recovered animals to become carriers and a reservoir for transmission, the potential virus persistence within wild boar populations and the influence of human behaviour for the spread of ASFV. This will provide an improved scientific basis to optimise current interventions and develop new tools and strategies to reduce the risk of ASFV transmission to domestic pigs.
Exploring the wind-borne spread of highly pathogenic avian influenza H5N8 during the 2016-2017 epizootic in France
Guinat, Claire; Rouchy, Nathalie; Camy, F.; et al. (2019)
Avian Diseases
In winter 2016-2017, highly pathogenic avian influenza (HPAI) H5N8 virus spread in France, causing an unprecedented epizootic. During the epidemic, southwest France, where most outbreaks were reported, experienced severe weather, with three consecutive storms (Leiv, Kurt, and Marcel) from 3 to 5 February 2017. Although little information is available, one hypothesis is that the spread of HPAI-H5N8 from an infected poultry holding could have been passively facilitated by prevailing wind during the risk period. The aim of this study was therefore to assess the contribution of the wind-borne route to the spatial distribution of HPAI H5N8 outbreaks during the risk period at the beginning of February 2017. The PERLE model, an atmospheric dispersion model (ADM) developed by Météo-France, the French meteorological agency, was used to generate the predicted area at risk of infection from a suspected point source. Model outputs show that the spatial pattern of dust-particle deposition was directed east-southeast in accordance with wind direction. This contrasted with the spatial distribution of HPAI H5N8 outbreaks, which spread westward. These observations suggest that the wind-borne route alone was insufficient to explain the spatial distribution of outbreaks over large distances in southwest France at the beginning of February 2017. Finally, this study illustrates the relevance of close collaboration between governmental authorities, veterinary research institutes, and meteorological agencies involving interdisciplinary research for successful outbreak investigations. © 2018 American Association of Avian Pathologists
Highly pathogenic avian influenza H5N8 in south-west France 2016–2017: A modeling study of control strategies
Andronico, Alessio; Courcoul, Aurélie; Bronner, Anne; et al. (2019)
Epidemics
In the winter 2016–2017 the largest epidemic of highly pathogenic avian influenza (HPAI) ever recorded in the European Union spread to all 28 member states. France was hit particularly hard and reported a total of 484 infected premises (IPs) by March 2017. We developed a mathematical model to analyze the spatiotemporal evolution of the epidemic and evaluate the impact of control strategies. We estimated that farms rearing ducks were on average 2.5 times more infectious and 5.0 times more susceptible to HPAI than farms rearing other avian species. The implementation of surveillance zones around IPs reduced transmission by a factor of 1.8 on average. Compared to the strengthening of pre-emptive culling measures enforced by French authorities in February 2017, we found that a faster depopulation of diagnosed IPs would have had a larger impact on the total number of infections. For example, halving the time delay from detection to slaughter of infected animals would have reduced the total number of IPs by 52% and total cull numbers by 50% on average. This study showcases the possible contribution of modeling to inform and optimize control strategies during an outbreak.

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