Biology subjects

Andraud, M.

Publications and source records attributed to Andraud, M..

9 recordsLinked to original sources

bioRxiv2025

Comparing Livestock Mobility-Informed Strategies for Peste des Petits Ruminants Control in Nigeria: The Central Role of the Network Backbone

Animal mobility is central to pastoral livelihoods and regional trade in West Africa, but it also facilitates the spread of transboundary animal diseases such as Peste des petits ruminants (PPR). In Nigeria, PPR outbreaks recur regularly, yet surveillance and control remain limited in the absence of routine animal-movement tracking. Here, we assess and compare movement-informed control options for PPR using a reconstructed livestock mobility network from a one-time market survey conducted in three northern Nigerian states. We simulate transmission on this network and evaluate three intervention strategies: (i) targeting vulnerable villages, (ii) targeting the links that connect movement communities, and (iii) targeting villages belonging to the network backbone. Across scenarios, backbone-based targeting consistently produced the largest reductions in network connectivity and epidemic outcomes, outperforming strategies focused on vulnerable nodes or inter-community links. These results suggest that backbone-informed control could provide a practical, resource-efficient pathway to strengthen PPR control in settings where routine movement data are scarce.

animal behavior and cognition↗

bioRxiv2024

Simulating the diffusion of PPR-like disease to improve surveillanc

Animal mobility is a founding element of pastoral culture and fundamental to the economy in West Africa. Herds movement, involving mainly cattle, sheep, and goats, is vital for adapting to climate fluctuations, optimizing natural resources, and managing risks in livestock production, as well as livestock trade and exchanges. However, these movements contribute to the spread of transboundary animal diseases such as Peste des petits ruminants (PPR). Nigeria experienced its first PPR outbreak in the 1960s-1970s, and outbreaks have regularly occurred since then. Yet, no adequate surveillance system has been put in place, and the absence of proper animal movement tracking remains a critical shortcoming in addressing this ongoing threat. Because of this, we rely on ad-hoc activities, like mobility surveys, to collect this information. However, these data could be partial and limited in time and space, hindering the capacity to identify suitable areas for monitoring disease circulation (sentinel nodes). Market survey data from three northern states are collected once to reconstruct the small ruminant mobility network. A group of areas with a high potential to infect each other were identified (Contagion Cluster). A stochastic Susceptible-Infected-Recovered (SIR) was used to simulate the spread of a PPR-like disease through movements. Sentinel nodes and their key characteristics were identified using Random Forest classification. The network (missing movement) was predicted with a hierarchical random graph (HRG), and uncertainty analysis assessed the effects of missing movements on the epidemic extent and identity and characteristics of sentinel nodes. The number of sentinel nodes varied with the epidemics severity, but their characteristics remained consistent. The uncertainty analysis results showed that adding 1% of the most probable missing links did not affect the final size of the epidemic. However, a significant difference appears when adding more than 3% of the missing links, causing a gradual fluctuation in the epidemics final size. The final size of the epidemic stabilized when adding more than 50% of the most probable links. The challenge posed by incomplete animal movement data underscores the need for further research and data collection efforts. However, predicting missing links presents a promising method for enhancing the reliability of epidemic prediction and sentinel node identification. This potential to improve disease surveillance and control strategies is a significant implication of our study.

bioinformatics↗

bioRxiv2024

A multi-host mechanistic model of African swine fever emergence and control in Romania

African swine fever (ASF) has devastating effects on swine production, farmer livelihood, animal welfare, and biodiversity. Extremely difficult to control, epidemic management is further complicated when spillover between domestic pig and wild boar populations is suspected. To quantify ASF viral transmission between domestic pigs and wild boar, a spatially-explicit stochastic mechanistic model was constructed using village centroids to represent aggregated backyard pig herds and a hexagonal raster of forest coverage to represent wild boar abundance. The model was parameterized to the initial six months of the ongoing Romanian epidemic through approximate Bayesian computation. It was estimated that a median of 69.4% (interquartile range: 53.0-80.0%) of domestic pig herd cases came from other infected domestic pig herds while 20.4% (11.2-33.8%) originated from infected wild boar sources, and 8.4% (4.7-14.2%) stemmed from external sources not explicitly represented. Also, 31.9% of infected wild boar habitat (16.7-56.2%) originated from domestic pig herds and 68.1% (43.8-83.3%) came from neighboring infected wild boar populations. Furthermore, it was found that habitats with a forest coverage greater than 15% were 2.6 times more infectious and 5.3 times more susceptible than other habitats. All alternative control scenarios, including culling domestic pig herds upon local domestic pig or wild boar case detection, improved epidemic outcomes, with the greatest decrease in final epidemic size being observed from the reactive culling of entire villages following case detection. These results can be used to further inform policy recommendations in ASF-epidemic regions. Significance StatementThe current African swine fever (ASF) pandemic is devastating to affected nations, and quantifying transmission parameters is critical to informing control strategies. Disease spillover between wild and domestic hosts further complicates control efforts, yet the influence of spillover events on epidemic propagation remains unknown. Using the context of Romania--one of the European nations with the most severe epidemic and where spillover transmission is strongly suspected--we show that targeting spillover mechanisms is critical for achieving holistic disease control, and then demonstrate the impact of alternative control scenarios had they been enacted. These results can inform control strategy policy decisions in the many nations at-risk for or actively experiencing ASF epidemics.

ecology↗

bioRxiv2023

Pig herd management and infection transmission dynamics: a challenge for modellers.

The control of epidemics requires a thorough understanding of the complex interactions between pathogen transmission, disease impact, and population dynamics and management. Mechanistic epidemiological modelling is an effective way to address this issue, but handling highly structured and dynamic systems, remains challenging. We therefore developed a novel approach that combines Multi-Level Agent-Based Systems (MLABS) with spatial and temporal organization, allowing for a tuned representation of the transmission processes amongst the host population. We applied this method to model the spread of a PRRSv-like virus in pig farms, integrating the clinical consequences (conception and reproduction failures), in terms of animal husbandry practices. Results highlighted the importance to account for spatial and temporal structuring and herd management policies in epidemiological models. Indeed, disease-related abortions, inducing reassignments of sows in different batches, was shown to enhance the transmission process, favouring the persistence of the virus at the herd level. Supported by a declarative Domain-Specific Language (DSL), our approach provides flexible and powerful solutions to address the issues of on-farm epidemics and broader public health concerns. The present application, based on a simple Susceptible-Exposed-Infected-Recovered (SEIR) model, opens the way to the representation of more complex epidemiological systems, including more specific features such as maternally derived antibodies, vaccination, or dual infections, along with their respective clinical consequences on the management practices.

ecology↗

bioRxiv2022

Two major epidemics of highly pathogenic avian influenza virus H5N8 and H5N1 in domestic poultry in France, 2020-2022

The spread of highly pathogenic avian influenza (HPAI) viruses worldwide has serious consequences for animal health and a major economic impact on the poultry production sector. Since 2014, Europe has been severely hit by several HPAI epidemics, with France being the most affected country. Most recently, France was again affected by two devastating highly pathogenic avian influenza epidemics in 2020-21 and 2021-22. We conducted a descriptive analysis of the 2020-21 and 2021-22 epidemics, in a first step towards identifying the poultry sectors remaining vulnerabilities regarding HPAI viruses in France. We examined the spatio-temporal distribution of outbreaks that occurred in France in 2020-21 and 2021-22, and we assessed the outbreaks spatial distribution in relation to two High-Risk Zones recently incorporated into French legislation to strengthen HPAI prevention and control. There were 468 reported outbreaks during the 2020-21 epidemic, and 1,223 outbreaks during the 2021-22 epidemic. In both epidemics, most outbreaks (80.6% and 74.0%) were located into the two High-Risk Zones. The southwestern High-Risk Zone was affected in both epidemics, while the western High-Risk Zone was affected for the first time in 2021-22, explaining the extremely high number of outbreaks reported. We showed that the spatial distribution model used to create the two High-Risk Zones was able to predict the location of outbreaks for the 2020-21 and 2021-22 epidemics. These zones were characterized by high poultry farm densities; future efforts should therefore focus on reducing the density of susceptible poultry in highly dense areas.

ecology↗

bioRxiv2021

Phylodynamic assessment of control measures for highly pathogenic avian influenza epidemics in France

Phylodynamic methods have successfully been used to describe viral spread history but their applications for assessing specific control measures are rare. In 2016-17, France experienced a devastating epidemic of a highly pathogenic avian influenza virus (H5N8 clade 2.3.4.4b). Using 196 viral genomes, we conducted a phylodynamic analysis combined with generalised linear model and showed that the large-scale preventive culling of ducks significantly reduced the viral spread between departements (French administrative division). We also found that the virus likely spread more frequently between departements that shared borders, but the spread was not linked to duck transport between departements. Duck transport within departements increased the within-departement transmission intensity, although the association was weak. Together, these results indicated that the virus spread in short-distances, either between adjacent departements or within departements. Results also suggested that the restrictions on duck transport within departements might not have stopped the viral spread completely. Overall, by testing specific hypothesis related to different control measures, we demonstrated that phylodynamics methods are capable of investigating the impacts of control measures on viral spread.

evolutionary biology↗

bioRxiv2021

Modeling the role of mortality-based response triggers on the effectiveness of African swine fever control strategies

African swine fever (ASF) is considered the most impactful transboundary swine disease. In the absence of effective vaccines, control strategies are heavily dependent on mass depopulation and movement restrictions. Here we developed a nested multiscale model for the transmission of ASF, combining spatially explicit network model of animal movements with a deterministic compartmental model for the dynamics of two ASF strains within-pixels of 3 km x 3 km, amongst the pig population in one Brazilian state. The model outcomes are epidemic duration, number of secondary infected farms and pigs, and distance of ASF spread. The model also shows the spatial distribution of ASF epidemics. We analyzed quarantine-based control interventions in the context of mortality trigger thresholds for the deployment of control strategies. The mean epidemic duration of a moderately virulent strain was 11.2 days assuming the first infection is detected (best-case scenario) and 15.9 days when detection is triggered at 10 % mortality. For a highly virulent strain, the epidemic duration was 6.5 days and 13.1 days, respectively. The distance from the source to infected locations and the spatial distribution was not dependent on strain virulence. Under the best-case scenario, we projected an average number of infected farms of 23.77 farms and 18.8 farms for the moderate and highly virulent strains, respectively. At 10% mortality-trigger, the predicted number of infected farms was on average 46.27 farms and 42.96 farms, respectively. We also demonstrated that the establishment of ring quarantine zones regardless of size (i.e., 5 km, 15 km) was outperformed by backward animal movement tracking. The proposed modeling framework provides an evaluation of ASF epidemic potential, providing a ranking of quarantine-based control strategies that could assist animal health authorities in planning the national preparedness and response plan.

ecology↗

bioRxiv2020

Inferring within-flock transmission dynamics of highly pathogenic avian influenza (H5N8) in France, 2020

Following the emergence of highly pathogenic avian influenza (H5N8) in France in early December 2020, we used duck mortality data of the index case to investigate within-flock transmission dynamics. A stochastic epidemic model was adjusted to the daily mortality data and model parameters were estimated using an approximate Bayesian computation sequential Monte Carlo (ABC-SMC) algorithm. Results suggested that the virus was introduced 4 days (95% credible interval: 3 - 5) prior to the day suspicion was reported and that the transmission rate was 3.7 day-1 (95%CI: 2.6 - 5.3). On average, ducks started being infectious 3.1 hours (95%CI: 0.4 - 8.0) after infection and remained infectious for 4.4 days (95%CI: 3.1 - 5.6). Model outputs also suggested that the number of infectious ducks was already 3239 (95%CI: 26 - 3706) the day before suspicion, emphasising the substantial latent threat this virus could pose to other poultry farms and to neighbouring wildlife. These estimations can be applied to upcoming outbreaks and made available to veterinary services within few hours. This study illustrates how mechanistic models can provide rapid relevant insights to contribute to the management of infectious disease outbreaks of farmed animals.

ecology↗

bioRxiv2019

Dynamics of Livestock-Associated Methicillin Resistant Staphylococcus aureus in pig farms networks: insight from mathematical modeling and French data

Livestock-associated methicillin resistant Staphylococcus aureus (LA-MRSA) colonizes livestock animals worldwide, especially pigs and calves. Although frequently carried asymptomatically, LA-MRSA can cause severe infections in humans. It is therefore important to better understand LA-MRSA spreading dynamics within pig farms and over pig farms networks, and to compare different strategies of control and surveillance. For this purpose, we propose a stochastic meta-population model of LA-MRSA spread along the French pig-farm network (n=10,542 farms), combining within- and between-farms dynamics, based on detailed data on breeding practices and pig exchanges between holdings. We calibrate the model using French epidemiological data. We then identify farm-level factors associated with the spreading potential of LA-MRSA in the network. We also show that, assuming control measures applied in a limited (n=100) number of farms, targeting farms depending on their centrality in the network is the only way to significantly reduce LA-MRSA global prevalence. Finally, we investigate the scenario of emergence of a new LA-MRSA strain, and find that the farms with the highest indegree would be the best sentinels for a targeted surveillance of such a strains introduction.

microbiology↗