Biology subjects

Desvars-Larrive, A.

Publications and source records attributed to Desvars-Larrive, A..

3 recordsLinked to original sources

bioRxiv2024

Investigating the impact of edge weight selection on the pig trade network topology

Traceability of animal movements and robust surveillance are crucial for identifying and controlling animal diseases. Risk-based surveillance, i.e. network-based approaches, can identify higher-risk holdings or trades. However, node ranking, useful to identify "influential" nodes (holdings) in the network, varies with the considered metrics. We use a dataset of pig movements in Upper Austria from 2021 to study the robustness of node ranking through three centrality metrics and compare them with epidemic model ranking. Incorporating edge weights may influence the network analysis, therefore, we simulate two representations using edge weights based on: i) the frequency of exchanges between holdings ("frequency-based") and ii) the number of pigs exchanged ("volume-based"). We compare the impact of the edge weight on the network topology, community structure, and node ranking in a network with 5,766 nodes and 92,914 edges. Results revealed distinct edge weight distributions: frequency-based network exhibited a bimodal pattern, while volume-based was more uniform. Strength centrality exhibited the highest correlation with simulation-based rankings, particularly for the top 5% highest-ranked nodes ({tau}b = 0.51 for frequency-based and{tau} b = 0.5 for volume-based). These findings highlight that using strength centrality to identify critical nodes can significantly enhance surveillance strategies, making them more efficient and field-deployable, enhancing traditional methods without requiring extensive simulations. Author summaryEarly detection of infectious diseases through surveillance activities is important to prevent severe impacts on the livestock sector and avoid major economic losses that often result from delayed detection. Prioritizing surveillance efforts through a data-driven approach presents a strategic advantage compared to random sampling. Here, we propose two network representations of the Upper Austrian pig trade network 2021, which show livestock holdings as nodes and animal movements as links between these nodes, which can represent the volume of pigs exchanged or the frequency of these exchanges. Using network analysis methods, we identify "influential" holdings in the network, i.e., those playing a key role in the network, either due to their numerous connections with other holdings, their position on many trade paths, or their crucial role in disease transmission dynamics. We show that using strength centrality can effectively identify key holdings for targeted surveillance. Adopting network-based surveillance can facilitate resource allocation for veterinary surveillance programs, offering a cost-effective strategy for disease management, enabling tailored, more effective, and timely interventions.

bioinformatics↗

bioRxiv2023

A systematic review on leptospirosis in cattle: a European perspective

BackgroundLeptospirosis is a zoonotic disease which is globally distributed. Bovine leptospirosis often results in economic losses through its severe impact on reproduction performance. However, a clear overview of the disease characteristics in European cattle is lacking. The objective of this review was to summarise the current knowledge and state of the research on the epidemiology of bovine leptospirosis in Europe. MethodologyWe conducted a systematic literature review following the PRISMA guidelines. We screened four electronic databases (Pubmed, Web of Science, Scopus, CABI) and included studies published between 2001 and 2021, in English, German, and French. Identified papers were filtered according to predefined inclusion and exclusion criteria. ResultsSixty-two studies were included. Reported seroprevalences were remarkably variable among studies, probably reflecting local variations but also heterogeneity in the study designs, laboratory methods, and sample sizes. The five most reported circulating serogroups in European cattle were Sejroe, Australis, Grippotyphosa, Icterohaemorrhagiae, and Pomona. Abortion and fertility disorders were the most frequently reported signs of leptospirosis in European cattle and were generally associated with chronic infections. The acute form primarily affected juveniles and foetuses. Risk factors positively associated with leptospirosis in cattle were diverse, related to environmental (e.g. geographic location), climatic (e.g. flooding), and medical (e.g. presence of other diseases) parameters, as well as farming practices (e.g. purchase policy, herd size) and individual factors (e.g. animal age and breed). ConclusionsClinical features of bovine leptospirosis in Europe cover a large range of signs and confirmation of infection requires laboratory tests. The epidemiology of the disease is very local, most probably influenced by context-specific factors. This work highlights several research gaps, including a lack of research data from several countries, a lack of methodological harmonisation, a lack of large-scale studies, an underrepresentation of beef herds in the studies, and a lack of molecular investigations. Author SummaryLeptospirosis is a zoonotic disease that has been reported in cattle worldwide. This review systematically evaluated the available literature (2001-2021) on (i) the methods of diagnostics, (ii) (sero)prevalence, (iii) circulating serogroups/serovars, (iv) clinical signs, (v) and risk factors associated with leptospirosis in European cattle. We found that the prevalence of the disease was very variable among studies. Similarly, a wide range of clinical signs were described, but the most frequently reported ones were abortion and fertility disorders. Risk factors of infection in cattle included herd size, purchase of animals, access to pasture and natural water sources, contact with other animal species, presence of other diseases on farm, animal age, and occurrence of extreme weather events. This review highlights that leptospirosis should be considered as a differential diagnosis in case of abortion or reproductive failure in European cattle and emphasises the need for integrated disease prevention and control measures at farm or regional level. We identified several research gaps, particularly a lack of research data from several countries, a lack of large-scale studies, an underrepresentation of beef herds, and a limited use of molecular tools in the studies.

microbiology↗

bioRxiv2022

SARS-ANI: A Global Open Access Dataset of Reported SARS-CoV-2 Events in Animals

The zoonotic origin of SARS-CoV-2, the etiological agent of COVID-19, is not yet fully resolved. Although natural infections in animals are reported in a wide range of species, large knowledge and data gaps remain regarding SARS-CoV-2 animal hosts. We used two major health databases to extract unstructured data and generated a comprehensive global dataset of thoroughly documented SARS-CoV-2 events in animals. The dataset integrates relevant epidemiological and clinical data on each event and is readily usable for analytical purposes. We also share the code for technical and visual validation of the data and created a user-friendly dashboard for data exploration. Data on SARS-CoV-2 occurrence in animals is critical to adapt monitoring strategy, prevent the formation of animal reservoirs, and tailor future human and animal vaccination programs. The FAIRness and analytical flexibility of the data will support research efforts on SARS-CoV-2 at the human-animal-environment interface. We intend to update this dataset weekly for at least one year and, through collaborative processes, to develop the dataset further and expand its use.

microbiology↗