Wildlife Disease Monitoring: Methods and Perspectives

Mazzamuto, Maria Vittoria; Schilling, Anna‐Katarina; Romeo, Claudia

doi:10.3390/ani12213032

Cited by 7 publications

(5 citation statements)

References 13 publications

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“…Current wildlife health surveillance schemes present major flaws (Ryser-Degiorgis, 2013;OIE, 2019;Lawson et al, 2021;Machalaba et al, 2021;Giacinti et al, 2022;Mazzamuto et al, 2022;Delgado et al, 2023;Pruvot et al, 2023) and have not been able to forecast and prevent the onset of new epidemics jumping interspecific barriers and even becoming pandemics (Konda et al, 2020;Delahay et al, 2021;Sharun et al, 2021;Keusch et al, 2022). The combination of WHM and HCM to achieve effective IWM has the potential to overcome these limitations, but it also faces new A modeling study including both host community (HCM) and wildlife health monitoring (WHM) variables obtained from literature review and publicly available databases not only identified the host species of Rift Valley fever virus, but also allowed to disentangle the factors driving a wildlife species to be such a host.…”

Section: Discussionmentioning

confidence: 99%

“…Establishing, developing, and implementing wildlife health surveillance programs is a worldwide priority and a challenge within the One Health approach (Ryser-Degiorgis, 2013;OIE, 2019;Lawson et al, 2021;Machalaba et al, 2021;Giacinti et al, 2022;Mazzamuto et al, 2022;Delgado et al, 2023;Pruvot et al, 2023). Traditionally, wildlife health surveillance is considered to encompass general surveillance (also called scanning or passive surveillance) and targeted surveillance (formerly called active surveillance) (Ryser-Degiorgis, 2013;OIE, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…While general surveillance better suits the investigation of disease or mortality outbreaks, particularly for new or emerging diseases in an area or population, targeted surveillance allows the detection of pathogens asymptomatically infecting the animals (Ryser-Degiorgis, 2013;OIE, 2019), monitoring prevalence trends (Barroso et al, 2020a(Barroso et al, , 2020b, and assessing the outcome of interventions (Boadella et al, 2012). Proposals to standardize and harmonize wildlife health surveillance at local, regional, and global scale have been and are currently being developed, with little success in achieving successful implementation up to date (Boadella et al, 2011a;Hanisch et al, 2012;Stephen, 2018;Tomaselli et al, 2018;OIE, 2019;Lawson et al, 2021;Machalaba et al, 2021;Giacinti et al, 2022;Mazzamuto et al, 2022;Pruvot et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Overcoming the limitations of wildlife disease monitoring

Barroso,

López-Olvera,

Kiluba wa Kiluba

et al. 2024

Res. dir. One health

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Integrated Wildlife Monitoring (IWM) combines infection dynamics and the ecology of wildlife populations, including aspects defining the host community network. Developing and implementing IWM is a worldwide priority that faces major constraints and biases that should be considered and addressed when implementing these systems. We identify eleven main limitations in the establishment of IWM, which could be summarized into funding constraints and lack of harmonization and information exchange. The solutions proposed to overcome these limitations and biases comprise: (i) selecting indicator host species through network analysis, (ii) identifying key pathogens to investigate and monitor, potentially including non-specific health markers, (iii) improve and standardize harmonized methodologies that can be applied worldwide as well as communication among stakeholders across and within countries, and (iv) the integration of new non-invasive technologies (e.g., camera trapping (CT) and environmental nucleic acid detection) and new tools that are under ongoing research (e.g., artificial intelligence to speed-up CT analyses, microfluidic PCR to overcome sample volume constraints, or filter paper samples to facilitate sample transport). Achieving and optimizing IWM is a must that allows identifying the drivers of epidemics and predicting trends and changes in disease and population dynamics before a pathogen crosses the interspecific barriers.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Overcoming the limitations of wildlife disease monitoring

Barroso,

López-Olvera,

Kiluba wa Kiluba

et al. 2024

Res. dir. One health

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“…Obtaining data by sampling wild birds could seem difficult, as it requires considerable logistical efforts, but this is not completely true. Bird ringing camps and wild animal rescue centers (only if sampling is carried out at arrival) are fundamental components of epidemiological surveillance work (Mazzamuto et al 2022). There are easy, economic, atraumatic, and non‐invasive methods for sampling birds without interfering in their welfare, both in wildlife rescue centers and in bird ringing camps.…”

Section: A Wild Bird Monitoring Approach For Amr Surveillancementioning

confidence: 99%

Wild birds and the ecology of antimicrobial resistance: an approach to monitoring

Guardia,

Varriale,

Minichino

et al. 2024

J Wildl Manag

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Tackling the global threat of antimicrobial resistance (AMR) requires joint efforts according to the principles of the One Health approach. In this context, wildlife, and especially wild birds, are recognized as an important bridge between environment, humans and livestock in perpetuating AMR. Over the last decades, important progress has been made in understanding the role of wild birds as carriers of antibiotic‐resistant bacteria and their genes (ARGs) within ecosystems; however, there are still many knowledge gaps regarding transmission sources and routes. This commentary summarizes studies from recent years focusing on AMR in wild birds, highlighting the most frequently found zoonotic bacteria harboring ARGs and the possible exchange scenarios between humans, livestock, and wild birds. We emphasize the need to standardize and optimize a wild bird monitoring approach for AMR surveillance that includes non‐invasive sampling methods, culture‐independent techniques for identification of ARGs, database integration and implementation, and machine learning technology. This multidisciplinary perspective, which could involve veterinarians, biologists, ornithologists, conservationists, and managers, may represent part of the solution, not only for wildlife conservation but also for global health, considering that the goal is to reverse the route of AMR.

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“…While there are entire books, guidelines, and journal issues written on methods for sample collection in wild birds for infectious diseases (Martin et al, 2006;Mazzamuto et al, 2022), there remains no standardization for samples collected from wild birds or the environment near wild bird populations. The most common samples collected in live wild birds are cloacal and tracheal or oropharyngeal swabs, and blood for serology, immunology, and overall health.…”

Section: Sample Collection Techniquesmentioning

confidence: 99%

Transboundary determinants of avian zoonotic infectious diseases: challenges for strengthening research capacity and connecting surveillance networks

Fair,

Al-Hmoud,

Alrwashdeh

et al. 2024

Front. Microbiol.

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As the climate changes, global systems have become increasingly unstable and unpredictable. This is particularly true for many disease systems, including subtypes of highly pathogenic avian influenzas (HPAIs) that are circulating the world. Ecological patterns once thought stable are changing, bringing new populations and organisms into contact with one another. Wild birds continue to be hosts and reservoirs for numerous zoonotic pathogens, and strains of HPAI and other pathogens have been introduced into new regions via migrating birds and transboundary trade of wild birds. With these expanding environmental changes, it is even more crucial that regions or counties that previously did not have surveillance programs develop the appropriate skills to sample wild birds and add to the understanding of pathogens in migratory and breeding birds through research. For example, little is known about wild bird infectious diseases and migration along the Mediterranean and Black Sea Flyway (MBSF), which connects Europe, Asia, and Africa. Focusing on avian influenza and the microbiome in migratory wild birds along the MBSF, this project seeks to understand the determinants of transboundary disease propagation and coinfection in regions that are connected by this flyway. Through the creation of a threat reduction network for avian diseases (Avian Zoonotic Disease Network, AZDN) in three countries along the MBSF (Georgia, Ukraine, and Jordan), this project is strengthening capacities for disease diagnostics; microbiomes; ecoimmunology; field biosafety; proper wildlife capture and handling; experimental design; statistical analysis; and vector sampling and biology. Here, we cover what is required to build a wild bird infectious disease research and surveillance program, which includes learning skills in proper bird capture and handling; biosafety and biosecurity; permits; next generation sequencing; leading-edge bioinformatics and statistical analyses; and vector and environmental sampling. Creating connected networks for avian influenzas and other pathogen surveillance will increase coordination and strengthen biosurveillance globally in wild birds.

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Wildlife Disease Monitoring: Methods and Perspectives

Abstract: In the last few decades, scientific interest in wildlife diseases has steadily grown and has recently been boosted by the SARS-CoV-2 pandemic, which highlighted that the health of humans, livestock, wildlife and, ultimately, of the whole environment is inextricably linked [...]

Cited by 7 publications

References 13 publications

Overcoming the limitations of wildlife disease monitoring

Overcoming the limitations of wildlife disease monitoring

Wild birds and the ecology of antimicrobial resistance: an approach to monitoring

Transboundary determinants of avian zoonotic infectious diseases: challenges for strengthening research capacity and connecting surveillance networks

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