A paper in Nature Communications in July 2024 presents the concept of a “zoonotic web”, describing the “complex relationships” between zoonotic agents, hosts, vectors, food, and environmental sources. Created from a dataset of naturally occurring zoonotic interactions in Austria by a team from Complexity Science Hub (CSH), the web offers insights into zoonotic sources and spillovers. The authors present a “flexible network-based approach” to bring understanding of zoonotic transmission chains and facilitate the development of “locally relevant” One Health strategies against zoonoses.
Understanding interfaces
Zoonoses are caused by pathogens that are “naturally transmissible” between humans and animals; zoonotic agent transmission is enabled at “interfaces” where humans and animals, or animal products, interact. The researchers acknowledge that “approximately 99% of endemic zoonotic infections in humans” originate from domesticated animals in anthropogenic environments. Over 60% of human emerging infectious diseases (EIDs) are zoonotic, with more than 70% of these zoonotic emergences caused by pathogens with wildlife origin.
“However, the full host breadth of endemic and emerging zoonotic agents, as well as their animal and environmental reservoirs are rarely identified nor mapped.”
As interactions in “most” zoonotic disease systems occur among multiple animal host species and environmental sources and involve multiple infectious agents, the authors state that exploring disease dynamics “necessitates considering the complex ecology of the interactions”. However, a “lack of datasets” makes it hard to follow a transdisciplinary perspective. Additionally, network approaches tend to focus on the host-pathogen relationships over other sources of zoonotic infection, such as contaminated environment or food.
“A comprehensive understanding of circulating zoonotic agents, their hosts, vectors, food and environmental sources, and the key interfaces where spillover events may occur is essential for developing effective integrated One Health monitoring, prevention, and control of zoonoses.”
Zoonotic and emerging diseases have consequences on “multiple aspects” of society, but it is possible to predict the establishment of reservoirs, understand the facilitators of spillovers, and prevent such spillovers at the source through enhanced monitoring efforts and data collection. The authors describe a “pressing need” to develop analytical tools to “optimise surveillance strategies” that are “tailored” to regional or national contexts and conduct national studies.
“Bridging this gap is crucial for developing effective, locally relevant strategies to monitor and mitigate potential changes in spillover risk that could impact human and animal health.”
The study
The study is based in Austria, which has a “growing population” of nine million people. It is home to around 45,870 fauna species, of which 626 are vertebrates, including 110 mammalian and 418 avian species. 35% of 3.9 million Austrian households have pets and the country has ~53,300 cattle, 1 million pigs, and 5 million poultry. 133,000 hunting permits are issued each year. These figures demonstrate the significance of the “human-animal interfaces at the national scale”.
Although the country follows various European and national regulations on epidemiological surveillance and responses, the authors suggest that official figures “tend to overlook” non-regulated zoonotic agents circulating in the territory that present a public health risk. They conducted a literature search over 47 years of publications to generate a real-world network that describes the “web” of zoonotic interactions in Austria and to characterise the “various interfaces” through while spillover might occur.
The idea of a “zoonotic web” is presented as a “representation of zoonotic actors at human-animal-environment interfaces” to be used for One Health approaches. The researchers used it as a bipartite network and turned it into a one-mode projection representing the network of zoonotic agent sharing among zoonotic sources, weighting relationships (edges) between the sources (nodes) by the number of agents they shared.
Findings
The authors find that “most” zoonotic agents are “capable of infecting both human and diverse animal species across various taxa, while evolving within multi-source, multi-agent ecological communities”. This is “consistent” with “established principles in the parasite community ecology”. They suggest that the analysis of the zoonotic web provides “greater value” for studying potential zoonotic transmission chains than the host-pathogen network approach.
In their investigations of the centrality of zoonotic sources, they identified that certain sources “play a disproportionate role in the sharing of zoonotic agents”. They highlight the “crucial role” of arthropod vectors and foodstuffs in the risk of zoonotic disease emergence and transmission through the web, which offers potential targets for One Health surveillance programmes.
A key outcome is that ten genera of zoonotic agents constituted 41% of the published research on zoonotic diseases in Austria; seven of these involve agents subject to compulsory surveillance and reporting in humans and/or animals. This “underscores an imbalance” in research interest, which the authors attribute to funding opportunities and global- or national-level prioritisation.
“Bias may lead to a skewed assessment of the overall zoonotic risk, especially concerning potentially ‘neglected’ zoonoses such as certain helminth infections.”
Between 1975 and 2022, eight zoonotic agents emerged in Austria. Although there is “often an emphasis” on viral emergence, this research offers a “different perspective”: six out of eight emerging pathogens in Austria were bacteria and helminths.
“This highlights the importance of broadening our focus beyond viral threats and acknowledging the substantial role that bacterial and helminthic pathogens play in the landscape of emerging diseases.”
Another observation is that four emerging zoonoses are transmitted by arthropod vectors; as climate change and globalisation evolve, the authors identify a “growing likelihood” of new arthropod species populations becoming established in Austria. This increases the risk of future EID events.
The researchers express surprise at finding that no COVID-19-related publications concerning human cases describe it as a zoonotic disease, despite SARS-CoV-2 being notifiable for both humans and animals. Additionally, the publication that investigated SARS-CoV-2 in Austrian animals did not mention zoonotic potential.
The importance of studying the source-source network of zoonotic agent sharing to reveal indirect interactions is highlighted by the researchers. They present the example of an agent that is found in two sources, where its prevalence in one could affect the other, but acknowledge that indirect interactions could “lack epidemiological significance”. They show that the zoonotic agent sharing network in Austria is “organised” into six communities.
- Primarily comprising central hosts having higher values of centrality in the unipartite zoonotic agent sharing network and generally living in proximity to humans or having frequent interactions with humans. This community includes livestock, companion animals, synanthropic species, game species, and captive primates.
- Encompassing diverse reptiles and amphibians, including non-traditional pet (NTP) species and wild boar.
- Consisting of various avian taxa, including birds of prey, ducks, waterfowl, gamebirds, chickens, and pigeons – the hosts were broadly designated, lacking specific scientific nomenclature.
- Including various food products and environmental matrices related to food production as well as public lavatory and Meleagris gallopavo (turkey).
- Featuring mostly clustered West Nile virus (WNV) hosts and Usutu virus (USUV) hosts, including various bird species, the vector Culex, and horses.
- Representing USUV hosts and exclusively including bird species.
The highest risk of zoonotic spillover is identified from sources within the first community, where the most zoonotic agents are shared. Another observation is that a “limited number of highly connected zoonotic agents” in the bipartite zoonotic web, including USUV, S. enterica, WNV, and Influenza A, could “at least partly” drive zoonotic agent sharing community assemblage.
From the grouping of most food products into one community, the authors infer that anthropogenic activities, especially those that relate to food processing and transformation, might further influence the pattern of assembly within zoonotic source communities. This indicates that a combination of local epidemiological, ecological, human-related, and behavioural factors informs zoonotic agent sharing community patterns.
The researchers highlight the presence of central zoonotic sources in the network, with a higher number of interactions with zoonotic agents. These act as “hubs” or “bridge different zoonotic source communities” to act as “connectors”. For example, some livestock species, companion animals, wildlife, and vectors act as “bridge hosts” through which zoonotic agents can potentially spillover from maintenance populations or communities to target “protected” populations.
Implications
The authors offer a cross-disciplinary method for “unveiling the intricate web of zoonotic interactions involving multiple sources and infectious agents within an ecological system”. This approach also enables the identification of “influential” agents and sources that might have “epidemiological significance”. It could be applied in various settings to expose knowledge gaps and areas where understanding “may not always reflect on-the-ground realities”.
“This work emphasises the need for further modelling and empirical studies to explore how maintenance is influenced by multiple source-agent interactions. Establishing efficient and context-adapted One Health network-based surveillance and control strategies requires supplementing the network analysis with multi-source data, ensuring a holistic, multidimensional understanding of the zoonotic web to unravel the complex dynamics of zoonotic transmission chains.”
Commenting on the paper, CSH’s Dr Amélie Desvars-Larrive suggests that it started with the intention of characterising and visualising the zoonotic interfaces in Austria. From this came the first comprehensive overview of zoonotic pathogen transmission, a “complex system”. This could be useful for zoonosis surveillance programmes.
“With our interactive map, we aim to educate and spark curiosity. While we all encounter various pathogens, only a few lead to illness, so there’s no need for excessive concern.”
However, Dr Desvars-Larrive emphasises the importance of promoting awareness and demanding better data availability.
“We’re only seeing the tip of the iceberg in our data – only those zoonoses that have been diagnoses. For instance, leptospirosis, still relatively rare in Austria, can mimic flu-like symptoms. If not clearly diagnosed as leptospirosis, it won’t show up in the data.”
Therefore, this network is a good starting point to “facilitate the development of One Health strategies against zoonoses”.
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