Prevalence of avian influenza viruses, Mycobacterium avium, and Mycobacterium avium, subsp. paratuberculosis in marsh-dwelling passerines in Slovakia, 2008

Borovská, Petra; Kabát, Peter; Ficová, Martina; Trnka, Alfréd; Svetlíková, D; Betáková, Tatiana

doi:10.2478/s11756-011-0016-3

Cited by 6 publications

(2 citation statements)

References 29 publications

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“…Although certain passerines were found to be infected with Mycobacterium spp. (Borovská et al 2011) there are no sufficient data to explicitly implicate Sylvidae as a major reservoir compared to other animal hosts. Similarly, the members of the family Macroscelidae were reportedly infected with Mycobacteria (Clancy et al 2013), the evidence is not sufficient to conclude the validity of the results.…”

Section: Feature Analysismentioning

confidence: 99%

Building a one-vs-all classifier for spatial prediction of detected pathogens

2023

MODSIM2023, 25th International Congress on Modelling and Simulation.

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More than 75% of human infectious diseases are caused by the transmission of pathogens from animals to humans (that is, zoonotic spillover). This demonstrates the importance of understanding the relative risks of each pathogen in each spatial region. In this study, we build one-vs-all classifiers to distinguish Mycobacterium and Listeria amongst all other recorded bacteria. We selected these two bacteria as they cause morbidity and fatality among humans and animals. We overcome the impact of class imbalance caused by spatial and taxonomical biases in detected pathogen occurrence data by under-sampling the majority negative samples and keeping all the minority positive samples. We further improved the prediction results by including animal richness data (number of genera present). Our findings highlight that there is a weak relationship between the predictive features and the relative occurrence of the target pathogen. We also identified that the inclusion of spatial-temporal information in the prediction process could increase generalisability. The biological study of the detected features suggests that more targeted infectious diseases surveillance data is required to validate the predicted results.

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Section: Feature Analysismentioning

confidence: 99%

Building a one-vs-all classifier for spatial prediction of detected pathogens

2023

MODSIM2023, 25th International Congress on Modelling and Simulation.

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“…Third, prior studies of AIV in songbirds or mammals have often included habitat types with little or no potential for interaction among species of concern (i.e., waterfowl), thus missing or diluting the most important sampling locations ( Peterson et al, 2008 ; Siengsanan et al, 2009 ; Fuller et al, 2010 ; Thinh et al, 2012 ; but see also Zhao et al, 2014 ; Caron et al, 2014 ; Leon et al, 2013 ; Peterson et al, 2008 ; Siengsanan et al, 2009 ; Fuller et al, 2010 ). In contrast, ideal sampling should focus on habitats where potential bridge hosts, including small mammals and birds, are most likely to interact with known AIV reservoirs like migratory waterfowl and shorebirds (e.g., wetlands and marshes) and to interact with poultry or their feed (e.g., commercial poultry operations, or feed-mills that serve those operations) ( Caron et al, 2014 ; Caron et al, 2015 ; Gronesova et al, 2008 ; Borovská et al, 2011 ; Cumming et al, 2011 ). Hence, the actual role of small birds and mammals in spreading AIV has not been definitively evaluated, particularly in the United States, even though these species have the potential to carry AIV biologically and mechanically.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the role of wild songbirds or rodents in spreading avian influenza virus across an agricultural landscape

Houston

Azeem

Lundy

et al. 2017

PeerJ

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BackgroundAvian influenza virus (AIV) infections occur naturally in wild bird populations and can cross the wildlife-domestic animal interface, often with devastating impacts on commercial poultry. Migratory waterfowl and shorebirds are natural AIV reservoirs and can carry the virus along migratory pathways, often without exhibiting clinical signs. However, these species rarely inhabit poultry farms, so transmission into domestic birds likely occurs through other means. In many cases, human activities are thought to spread the virus into domestic populations. Consequently, biosecurity measures have been implemented to limit human-facilitated outbreaks. The 2015 avian influenza outbreak in the United States, which occurred among poultry operations with strict biosecurity controls, suggests that alternative routes of virus infiltration may exist, including bridge hosts: wild animals that transfer virus from areas of high waterfowl and shorebird densities.MethodsHere, we examined small, wild birds (songbirds, woodpeckers, etc.) and mammals in Iowa, one of the regions hit hardest by the 2015 avian influenza epizootic, to determine whether these animals carry AIV. To assess whether influenza A virus was present in other species in Iowa during our sampling period, we also present results from surveillance of waterfowl by the Iowa Department of Natural Resources and Unites Stated Department of Agriculture.ResultsCapturing animals at wetlands and near poultry facilities, we swabbed 449 individuals, internally and externally, for the presence of influenza A virus and no samples tested positive by qPCR. Similarly, serology from 402 animals showed no antibodies against influenza A. Although several species were captured at both wetland and poultry sites, the overall community structure of wild species differed significantly between these types of sites. In contrast, 83 out of 527 sampled waterfowl tested positive for influenza A via qPCR.DiscussionThese results suggest that even though influenza A viruses were present on the Iowa landscape at the time of our sampling, small, wild birds and rodents were unlikely to be frequent bridge hosts.

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Challenging the conceptual framework of maintenance hosts for influenza A viruses in wild birds

Caron

Cappelle

Gaidet

2016

Journal of Applied Ecology

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The conceptual framework considering Anseriformes and Charadriiformes as the main maintenance hosts for influenza A viruses (IAV) in wild birds has shaped IAV research and surveillance over the last decades. We challenge this framework by reviewing the world-wide surveillance data on non-Anseriformes and non-Charadriiformes (NANC) species, generally considered as playing little role in IAV maintenance, available in literature and online data bases (close to 200 sources). Globally, we found an IAV infection rate of 1·51% (95% CI, 1·44–1·59%) for c. 101 000 birds tested from NANC species. If Anseriformes have, as expected, a higher infection rate than any other bird orders, eight bird orders have an infection rate higher or close to the Charadriiformes infection rate, challenging the status of Charadriiformes. We interpret the attention paid in favour of Charadriiformes by an extrapolation bias from data collected in hotspots of IAV infection in Charadriiformes (e.g. Delaware Bay, USA). The growing data on IAV in wild birds world-wide, summarised here, support two non-exclusive hypotheses: (i) the quality of the diagnostic tools and techniques used explain the patterns observed; (ii) IAV maintenance is determined by complex multi-host systems composed of multiple bird species, dependent on the ecosystem and its bird diversity and composition. Synthesis and applications. Our results have two main implications. First, new research and surveillance should be designed in order to understand influenza A viruses ecology in wild birds across the world, along with appropriate diagnostic tools and new hypotheses and dedicated protocols. This should be done in line with our new conceptual framework that conveys less a priori than its predecessor. Second, our results call for more bridging between biological and epidemiological sciences in order to tackle disease ecology in multi-host systems. (Résumé d'auteur

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Prevalence of avian influenza viruses, Mycobacterium avium, and Mycobacterium avium, subsp. paratuberculosis in marsh-dwelling passerines in Slovakia, 2008

Cited by 6 publications

References 29 publications

Building a one-vs-all classifier for spatial prediction of detected pathogens

Building a one-vs-all classifier for spatial prediction of detected pathogens

Evaluating the role of wild songbirds or rodents in spreading avian influenza virus across an agricultural landscape

Challenging the conceptual framework of maintenance hosts for influenza A viruses in wild birds

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