Post COVID‐19: a solution scan of options for preventing future zoonotic epidemics - Wiley
I. INTRODUCTION
The COVID-19 pandemic has alerted the world to the risks of emerging diseases of zoonotic origin and has prompted widespread concern and interest in acting to prevent future similar pandemics. Many solutions have been proposed, in particular related to complete bans of wildlife trade and wildlife markets, but such solutions are considered impractical by some and, if implemented, could cause major socio-economic shocks and food insecurity (Booth et al., 2021) and would only cover part of the problem. Thus, more holistic solutions should be examined to understand additional mechanisms that could drive spillover from other animals to humans. There is a need for larger scale rethinking of the means of reducing risk for emerging diseases that could spill over from animals into humans, and especially those diseases that could spread rapidly due to high transmission rates from human to human (Dobson et al., 2020; Morens, Daszak & Taubenberger, 2020).
Herein we (i) review the risks posed by different transmission pathways for zoonotic disease spillover, and (ii) use solution scanning as a methodological approach to consider and collate the possible options for reducing these risks. We also identify important outstanding questions and pragmatic approaches for the future.
Solution scanning, which involves listing all the known options for addressing a particular problem, represents a more transparent and rigorous strategy for assessing possible policy options than the traditional approach of selecting a subjective subset of policies from a combination of the experience and beliefs of practitioners and politicians (Sutherland et al., 2014). While a complete review of the evidence base for all available policy options would be preferable, especially for complex policy problems where outcomes may be location or context specific, the scale and duration of such reviews are often impractical. Solution scanning can be a valuable first step in this decision-making process, by creating a comprehensive and transparent basis for subsequent assessment of evidence, effectiveness and contextualised considerations for the practical implementation of different options (Sutherland et al., 2014; Sutherland & Burgmann, 2015). This approach has been used successfully for a range of topics including agro-forestry, options for the conservation of marine biodiversity, and sustainable intensification of agricultural practices or place-based food networks (Jacquet et al., 2011; Hernandez-Morcillo et al., 2018; Plieninger et al., 2018; Dicks et al., 2019). Solution scanning is also the first stage of subject-wide evidence synthesis, for example to assess the effectiveness of biodiversity conservation interventions (Sutherland et al., 2019).
II. MAJOR TRANSMISSION PATHWAYS FOR ZOONOTIC DISEASE TRANSFER
(1) Importance of zoonotic pathogens, including COVID-19
The pandemic potential of zoonotic pathogens is strictly linked to their ability to generate sustained human-to-human transmissibility. This is the case with SARS-CoV-2 (the virus responsible for COVID-19) which caused a global pandemic affecting over 200 countries and territories in under 100 days and resulting in over 175 million known infections and 3811561 assigned human deaths by 15th June 2021 [WHO Coronavirus Disease (COVID-19) Dashboard covid19.who.int]. Although there is debate about its exact source and infection pathway, COVID-19 appears to have been the result of zoonotic transmission from an original wildlife host, possibly via an intermediate animal host, following close contact with people (Andersen et al., 2020; Wu et al., 2020). While the direct reservoir of SARS-CoV-2 might never be identified, it is clear that close proximity of different wild and domestic animal species in a wildlife market setting (often conflated with 'wet market', which may, or may not, have wildlife and simply refers to the existence of fresh produce) may enable recombination between more distant coronaviruses and the emergence of recombinants with novel phenotypes (Li et al., 2020). This is particularly relevant given that multiple relatives of SARS-CoV-2 and SARS-CoV (the cause of the 2003 SARS epidemic) circulate in wildlife species in Southeast Asia and southern China (Zhou et al., 2021). Preventing such situations as well as reducing direct human contact with wild animals appears critical for preventing new coronavirus zoonoses.
Several other major recent pandemic and epidemic disease outbreaks have zoonotic origins including HIV-AIDS, Ebola and SARS (Wang & Eaton, 2007; Allen et al., 2017); 60% of human emerging disease events are caused by zoonotic pathogens, with most (72%) originating in wildlife (Jones et al., 2008). Furthermore, most known human pathogens are zoonotic (80% of viruses, 50% of bacteria, 40% of fungi, 70% of protozoa and 95% of helminths) (Taylor, Latham & Woolhouse, 2001). Although most zoonotic pathogens are not capable of sustained human-to-human transmission, some can cause major disease outbreaks; thus, preventing the transfer of pathogens from other animal species into humans is a key societal challenge. Predicting and reducing the risk of such outbreaks is imperative if we are to avoid future detrimental impacts on human health and the global economy, such as those caused by the COVID-19 pandemic.
(2) Disease transfer pathways
Transfer of pathogens from animals to humans can occur through diverse pathways involving interactions with free-living or captive wildlife, livestock or other domesticated animals (Table 1; Fig. 1). It is important to note that, in practice, the distinctions between these categories of animals are often poorly understood and category differentiation may be imprecise but differences have significant implications for exposure to various pathogens.
| Term | Description |
|---|---|
| Wildlife | We use the IUCN terminology to define wildlife as "living things that are neither human nor domesticated", but due to the nature of our review we focus on both terrestrial and aquatic animals, especially mammals and birds, and exclude fish, plants, fungi and aquatic invertebrates (e.g. molluscs and crustaceans) due to lower opportunity for disease transmission that would result in human–human infections. |
| Wild sourced | Animals taken from the wild directly for trade, which may include legal or illegal trade in live wild animals (e.g. for food or exotic pets) or their parts and derivatives (e.g. for food or medicine). This includes ranched or captive-raised animals, where eggs or young were taken from the wild and then reared in captivity for commercial purposes. |
| Farmed and captive wildlife | We consider wild animals bred in captivity as distinct from wild-sourced animals. We define farmed wild animals as those with a phenotype not significantly affected by human selection and raised in controlled conditions and productive farm systems (e.g. mink Neovison vison for fur; bears, primarily Ursus thibetanus, or Tokay geckos Gekko gekko for traditional medicine; tigers Panthera tigris in tiger farms; bamboo rats, often Rhizomys sinensis, raised for food) and use 'captive wildlife' for those in zoological and other collection types (e.g. tigers in zoos). |
| Domesticated species | We consider domesticated species as those whose phenotype is driven by long-term human selection. Within this category we use the terms 'livestock' for animals raised primarily for meat and other animal products (e.g. pigs, poultry, cattle, sheep, goats, some camelids such as dromedary and llamas), 'pets' to refer to animals such as cats and dogs kept as companions or ornamentally, and 'feral' or 'unmanaged and free roaming' as per the OIE–World Organisation for Animal Health definition to refer to domestic animals normally kept as pets or livestock but which are living without direct human supervision or control, often in areas where they are not native (e.g. stray dogs, cats and goats). |
A conceptual diagram of animal-use supply chains and their interfaces, identifying different intervention points and intervention options at different stages in the supply chain.
The rate of zoonotic pathogen emergence is increasing globally, and human population density is a strong predictor of emerging disease events (Jones et al., 2008), indicating that pathogen emergence is driven by human-induced changes bringing wildlife, livestock and humans into closer and more frequent contact (Morse et al., 2012). The risk of disease transmission depends on both intrinsic factors (e.g. pathogen life history, host availability and immunity and transmission route) and external factors (e.g. land-use, human population changes, socio-economic provisions) such that the nature of risks varies among locations and over time (Becker et al., 2020), and influences both the probability of pathogen transmission from animal to human, and the probability of an infected person developing the disease (Han, Kramer & Drake, 2016).
The spillover of a pathogen from animals requires a series of stages, including the reservoir host being at sufficient density to retain the pathogen, pathogen release, human exposure to the pathogen, and the pathogen overcoming structural barriers, innate immune responses and molecular compatibility (Plowright et al., 2017). The global connectivity of human society greatly increases the movement of humans, disease vectors (Tatem, Hay & Rogers, 2006) and various pathogen-infected animals (Can, D'Cruze & Macdonald, 2019), magnifying the likelihood of the spillover and spread of a pathogen, particularly in areas of high human population size and density.
(3) Disease transfer involving wild animals
Most emerging infectious diseases are thought to have originated in wild animals, especially non-human primates, rodents and bats (Wolfe, Dunavan & Diamond, 2007; Jones et al., 2008; Han et al., 2016), although many of these were transmitted to humans via intermediate hosts, such as companion, farmed or feral animals (Wolfe et al., 2007). As an example, there is a broad consensus that human viruses responsible for HIV-AIDS resulted from multiple cross-species spillovers of simian immunodeficiency viruses involving the chimpanzee Pan troglodytes, western gorilla Gorilla gorilla and sooty mangabey Cercocebus atys. Lentiviruses, such as HIV, penetrate mucous membranes; therefore contact with non-human primate body fluids associated with the hunting, butchering and consumption of animals likely led to spillovers. One transmission event, probably occurring between 1910 and 1930, gave rise to the HIV strain behind pandemic AIDS (Sharp & Hahn, 2011). Ebola has been suggested to have been transmitted from bats (Leroy et al., 2005; Saéz et al., 2015), either directly or via an intermediate host, while MERS (Middle-East Respiratory Syndrome) most probably originated in a species of bat, with the dromedary camel Camelus dromedarius as an intermediate host (Mohd, Al-Tawfiq & Memish, 2016).
Our knowledge of pathogen prevalence in wildlife populations is heavily biased by host species, pathogen type and sample availability, but studies can provide deep insights into the diversity of potential zoonotic pathogens (e.g. for bat-borne coronaviruses; Anthony et al., 2017). Species are defined as being capable of harbouring a particular zoonotic pathogen following the detection of that pathogen, but only pathogens that can be reliably detected and identified are recognised. In the natural host, however, infection loads may be low and not readily detectable even with modern molecular methods; testing might also be conducted on samples that are suboptimal for certain viruses that then could be missed. Furthermore, most host taxa have not been included in such studies and remain completely untested. Fewer than 300 viruses from 25 high-risk viral families are known to infect people, yet it is estimated that there are around 1.7 million viruses from these same viral families that have not yet been discovered in mammals and birds. Of these, some 700000 are considered to have zoonotic potential (Carroll et al., 2018).
Zoonotic diseases can emerge from a wide variety of wild species, including marine turtles (Aguirre et al., 2006) and marine mammals (Waltzek et al., 2012), but the risk appears variable, with the highest risk taxa being rodents (Han et al., 2015, 2016), non-human primates (Pedersen et al., 2005) and bats (Luis et al., 2013). Transmission in this context can occur through a range of direct and indirect pathways (e.g. infected faeces, urine, saliva, invertebrate vectors), from interactions with species in natural habitats or during the supply, transport and use of wildlife or wildlife products.
Based on the number of different infected host species, as well as phylogenetic relatedness among hosts, zoonotic pathogens can be characterised as specialists (a single wildlife host species) or generalists (multiple wildlife host species). The latter often can persist by being maintained in multiple wildlife species. Understanding pathogen ecology and evolution offers many advantages in terms of strengthening surveillance programs aimed at preventing or reducing human exposure and zoonotic infection, as well as informing early warning systems for outbreak detection.
Many host species characteristics contribute to a heightened risk of zoonotic transfer. Several zoonoses of high impact for humans originated from non-human primates, probably in part because the phylogenetic barrier to transmission to humans is low (Wolfe et al., 2007). In rodents, reservoir species are associated with a fast-paced life-history strategy, rapid maturation and high fecundity (Han et al., 2015); these characteristics mean that some species carry multiple pathogens, increasing the probability of a rodent being infected with a pathogen with zoonotic potential. The high population size and density of many rodents is probably also an important factor. It is hypothesised that pathogen-prone rodent species may have low investment in immune defences, but 'outrun' the risk of a lethal infection by producing offspring quickly (Han et al., 2015).
The comparatively high zoonotic disease risk from bats (Luis et al., 2013) has been linked to large colony sizes and high mobility due to flight, resulting in even larger effective population sizes and many bat species having the capacity to host a wide range of pathogens. The highest predictor of zoonotic viral richness in bats was the distribution overlap with sympatric species, suggesting that interspecific transmission probably plays a key role in the pathogen complement harboured by bats (Luis et al., 2013). Evolved physiological adaptations to flight might also have enabled bats to harbour a larger range of pathogens in the absence of disease (O'Shea et al., 2014), as their immune systems seem to have been modified to enable protective cellular mechanisms, a dampened interferon response, and a key innate defence pathway that is functionally different from non-bat mammals, implying that bats may be more effective at co-existing with a large number of viruses (Xie et al., 2018). The rigours of flight mean that bat metabolisms can increase by up to 16 times the basal rate, producing sufficient heat to kill most mammals (Speakman & Thomas, 2003; O'Shea et al., 2014). As a consequence of these costs, bats have adapted mechanisms to prevent degradation of cellular mechanisms by heat or oxygen radicals, affecting their ability to withstand infections (Healy et al., 2014; Huang et al., 2019). Together, these properties allow them to be asymptomatic reservoirs of multiple viruses, thus enabling these viruses to persist within bat populations. Stress responses in most mammals are shown to increase the probability of spillover (Hara et al., 2011), yet such studies in bats are only now being conducted (Subudhi, Rapin & Misra, 2019). Understanding how the role of habitat loss and degradation combines with natural stressors (e.g. reproduction and migration) is urgently needed. However, studies show that at least some mechanisms of physical stress in bats do increase viral shedding; for example, bats infected with the fungal pathogen Pseudogymnoascus destructans can have a viral load that is increased by up to 60 times that of bats without this fungal infection (Davy et al., 2018).
In addition to these hypotheses, a simpler explanation is that both rodents and bats are also highly diverse vertebrate orders (2361 rodent species and 1420 bat species) and more species-rich reservoir groups host more virus species and therefore a larger number of zoonotic pathogens (Letko et al., 2020; Mollentze & Streicker, 2020).
Other, non-taxon-specific characteristics also contribute to zoonotic pathogen risk. For example, migratory species can have a profound effect on pathogen dispersal, but these effects are complex and context dependent (Altizer, Bartel & Han, 2011; Poulin & de Angeli Dutra, 2021). Migration can play a key role in introducing disease to populations naïve to the pathogen, and the heavy toll of migration can reduce immune function, so increasing infection burden. Conversely, migration can allow individuals to escape infected areas and, hence, reduce host population pathogen levels. The unsuccessful migration of infected individuals might also lead to overall reductions in pathogen prevalence (Huber et al., 2020).
Where pathogens are thought to be of wildlife origin, their emergence is often associated with a high diversity of pathogens in a wide range of host species (Jones et al., 2008; Allen et al., 2017; Anthony et al., 2017), and many emerge in biodiverse tropical regions. However, the role of biodiversity in zoonotic disease emergence is complex. Studies have identified a general trend, known as the 'dilution effect', where increasing host diversity can reduce a given parasite abundance in both wild animals and humans (Civitello et al., 2015; Huang et al., 2017), although this effect depends on specific conditions, context and on the metrics used (Salkeld, Padgett & Jones, 2013; Roberts & Heesterbeek, 2018). While empirical evidence exists for the dilution effect in several multi-host pathogen systems, the mechanism is often unclear, for example whether it is due to actual dilution or to reduced host density (Begon, 2008).
Pathogen transmission from wildlife to humans is influenced by extrinsic factors, such as land-use change (Allen et al., 2017) and agricultural intensification (Jones et al., 2013). Such factors play a particularly important role in driving the emergence of zoonotic diseases in biodiverse tropical forest regions (Keesing et al., 2010), where expanding human populations (and associated agriculture or other activities) into natural habitats leads to increased opportunities for human-to-wildlife contact (Han et al., 2016; Bloomfield, McIntosh & Lambin, 2020) and increased pathogen transmission at human–livestock–wildlife interfaces (Gebreyes et al., 2014). Multi-host pathogen models indicate that pathogen transmission between species inhabiting intact and converted habitat is highest when rates of habitat conversion are intermediate (Johnson et al., 2020). However, the potential severity of epidemics increases at higher rates of habitat conversion (Faust et al., 2018). Land-use change that reduces local biodiversity may increase spillover risk (Civitello et al., 2015), as exemplified by Lyme disease in North America (Ostfeld & Keesing, 2000, 2012). While the diversity of wildlife species declines with habitat degradation, it has been shown that those species more able to live in human-modified habitat tend to have a higher rate of carriage of zoonotic pathogens than those that decline or disappear (Gibb et al., 2020).
Hunting, whether commercially or for subsistence, and the transport, sale, preparation and use of wild animals and wild animal products are also important points of human–wildlife contact. Direct wildlife use, especially for human consumption, is most commonly an issue for zoonotic emergence in the 'paleotropics', where high species diversity of high-risk taxa (e.g. of bats and primates) is combined with subsistence hunting and use (Han et al., 2016). Harvesting rates of wild meat in tropical areas are currently primarily driven by an increase in demand in fast-growing urban centres (Coad et al., 2019). Interactions between wildlife and humans can have complex and hard-to-predict effects, by increasing both stress and movement of species and therefore increased spread of disease and spillover risk. For example, the culling of badgers Meles meles is known to increase the movement of surviving animals and, hence, the spread of bovine tuberculosis (Woodroffe et al., 2006).
It seems likely that it is human interactions with, and destruction of, biodiversity that leads to increased likelihood of zoonotic disease emergence. However, the pathways to overcome this are likely to be complex. It has been suggested that protecting ecosystems not currently posing a major threat of disease to humans or wildlife might prevent increases in disease emergence, yet when managing a specific disease for which the ecology is reasonably well understood, it might be more effective to manage the particular species (vectors or amplifying or diluting hosts) or habitats that are known to decrease or increase the likelihood of pathogen spillover, for example, through vaccination, culling, predator supplementation or habitat manipulation (Rohr et al., 2019).
(4) Disease transfer involving domestic animals
Many zoonotic outbreaks result from pathogen transmission from domestic animals. Human pathogens considered to originate from the domestication process of animals include diphtheria, influenza A, measles, mumps, pertussis, rotavirus, and smallpox (Wolfe et al., 2007) and contacts between humans and domestic animals have led to recent zoonotic emergence events, such as the H1N1 (Swine Flu) pandemic in 2009 and MERS in 2012. The emergence of many of these diseases has been facilitated by the increased human population size and the development of commercial agriculture and livestock domestication (Wolfe et al., 2007; Jones et al., 2013), as well as agricultural encroachment leading to increased livestock–wildlife interactions and more opportunities for livestock acting as bridging species for novel zoonotic pathogens such as Nipah (Pulliam et al., 2011). Due to thousands of years of domestication, high contact rates and significant amounts of study, ungulates are the mammalian group with which humans are known to share the most pathogens (Cleaveland, Laurenson & Taylor, 2001). In temperate regions, the majority of the heaviest-burden zoonotic diseases impact humans through domestic livestock. Transmission routes of pathogens from livestock are facilitated by poor hygiene and biosecurity measures, such as lack of protective equipment for farm workers (Ramirez et al., 2006), and can occur through a variety of direct and indirect interactions during the rearing of livestock. Numerous other zoonotic diseases involve a vector stage, such as Rift Valley fever or Crimean-Congo haemorrhagic fever (CCHF), where the host is a tick and the vector is a mammal (Wilson et al., 1991).
(5) Disease transfer involving wild or exotic pets
Although information is comparatively scarce, wild or exotic pets (i.e. not domesticated animal pets) are another possible source of novel zoonoses with epidemic potential. For example, in 2003 six states in the USA experienced an outbreak of monkeypox, the first cases of human monkeypox reported outside the African continent. This outbreak resulted from prairie dogs Cynomys sp. sold as pets after being housed in close proximity to infected rodents recently imported from Ghana (Centers for Disease Control and Prevention, 2003). In 1999, an Egyptian rousette bat Rousettus aegyptiacus sold in a pet shop in France was diagnosed with Lagos bat lyssavirus encephalitis, resulting in the treatment of 120 exposed persons (Chomel, Belotto & Meslin, 2007). Variegated squirrels Sciurus variegatoides imported from Latin America as exotic pets were the identified host of a novel zoonotic Bornavirus (VSBV-1) that infected, and led to fatal progressive encephalitis or meningoencephalitis, in three squirrel breeders in Germany in 2011–2013 (Hoffmann et al., 2015).
Some actions to combat zoonotic disease depend on an understanding of links between animal welfare and pathogen transmission, including the immune response, which is directly influenced by welfare (Broom & Fraser, 2015). For example, poor welfare during the transport of cattle or sheep can result in the opportunistically pathogenic bacterium Mannheimia (Pasteurella) haemolytica causing disease (Broom & Kirkden, 2004). Disease and mortality rates are higher in farm animals that have poor levels of welfare, and in wild animals if stressed when brought into captivity (EFSA, 2006; Leday et al., 2018). If wild animals are captured and kept, capture stress as well as transport stress and other stressors (e.g. being caged with or next to conspecifics or other species; close proximity to people; rough handling; inadequate food or water; exposure to the elements; poor hygiene, etc.) increases their susceptibility to infection with pathogens and the likelihood that they will shed pathogens with or without the development of clinical disease, perhaps thereby infecting humans or other animals (Broom & Kirkden, 2004; Broom & Johnson, 2019).
(6) State of knowledge on coronaviruses – origins and transfer
Seven coronaviruses (CoVs) are currently known to infect humans (Andersen et al., 2020), four of which are regularly found in human populations in which they cause only mild symptoms (Corman et al., 2018). However, the betacoronaviruses, SARS-CoV-1, MERS and SARS-CoV-2, have been associated with fatalities and, in the case of MERS, with high fatality rates (Zhou et al., 2020b). There is evidence that CoVs that infect humans have their origins in either bat or rodent species (Salata et al., 2019). Intermediate species have included both domestic and captive wild animals (including cattle and swine), masked palm civets Paguma larvata and dromedaries (Drexler, Corman & Drosten, 2014; Corman et al., 2018). Diverse CoVs have been found in bats in China, with 6.5% of all bats in one study testing positive for at least one coronavirus (Tang et al., 2006), and with SARs-like viruses confirmed in horseshoe bats Rhinolophus spp. in 2005 (Li et al., 2005). Since then, further betacoronaviruses have been detected in wild-caught rhinolophid bats across the Old World (Gouilh et al., 2011). Over 200 novel coronaviruses have been identified in bats and approximately 35% of the sequenced bat virome is composed of coronaviruses (Banerjee et al., 2019).
Although many CoVs are limited to bats, some are found in a more diverse selection of mammals. Coronavirus studies have predominantly focused on non-bat hosts, which include both mammals (alpha and betacoronavirus) and birds (gamma and deltacoronavirus), yet few betacoronaviruses have been detected outside bats in the wild. In bats, CoVs have been found in bat families across the globe (Drexler et al., 2014), with groups such as Hipposideridae known to host these viruses asymptomatically for extended periods. Typically, CoVs have a highly restricted host range: even bats within the same cave often show different viruses in different species, with only those detected in Miniopterus spp. known to be capable of jumping between hosts (Gouilh et al., 2011), normally as a consequence of roosting in direct physical contact with other bat species. The destruction or disturbance of caves by people can lead to different species and taxa being forced to share caves and, given their different abilities to host or pass on betacoronaviruses, this increases the risk of virus spread across species. Furthermore, as rhinolophid bats (in which SARS-like viruses have been detected) can develop clinical coronaviral disease, spillover risk may be higher from this group (Wong et al., 2019). The shared use of bat caves by non-bat hosts, such as Viverridae (civets and genets), increases the risk of spillover into new host species (Song et al., 2005), especially as betacoronaviruses are most commonly detected in faeces (Wong et al., 2019). Rapid adaptation of SARS-CoVs has been observed to occur between hosts (such as masked palm civets and humans) and host shifts have also been observed to occur amongst bat species in wild populations (Cui et al., 2007; Latinne et al., 2020; Zhou et al., 2020a).
The wildlife trade, both legal and illegal, has received enormous global media attention for its potential role in the emergence of novel zoonoses like SARS and COVID-19. Illegal wildlife trade alone is estimated to be a multibillion-dollar industry, comparable to the international trades in narcotics and weapons, and which raises significant human and animal health concerns, especially given its volume, the complete lack of regulation and the fact that the origins of wildlife sometimes match recognised emerging infectious disease hotspots (Smith et al., 2017). However, there remains considerable uncertainty around which species have been involved in the transfer of the causative coronaviruses to humans, as well as exactly when such transfers occurred (Corman et al., 2018; Salata et al., 2019). The virus with the closest match to SARS-CoV-2 has been found in several species of horseshoe bat Rhinolophus spp., which likely represent the ancestral or evolutionary (natural) host of the virus (Zhou et al., 2020a), although the ability of this closest known relative of SARS-CoV-2 to infect humans is poor (Wan et al., 2020). A related virus has been detected in Malayan pangolin Manis javanica (Zhang, Wu & Zhang, 2020). While different overall from any known bat CoV, the pangolin CoV receptor binding domain part of the spike protein (which allows the virus to infect a new host) is almost identical to that found in the human virus (Zhou et al., 2020a), but a polybasic cleavage site in SARS-CoV-2 is absent from both known pangolin and bat CoVs, so the origin and route to human infection of SARS-CoV-2 remains unknown (Andersen et al., 2020). The potential for the transmission of zoonotic CoVs through wildlife markets and farm systems, however, has been clearly noted for SARS-CoV (Wong et al., 2019) and actions to prevent such zoonotic spillover risk in future have been widely discussed (e.g. Kelly et al., 2020; Nabi et al., 2020; Ribeiro et al., 2020; Wang et al., 2020).
III. SOLUTION SCANNING: IDENTIFYING OPTIONS FOR MINIMISING ZOONOTIC DISEASE TRANSFER
(1) The need for solution scanning
Creating a future in which society is more resilient to zoonotic diseases will require coordination and planning among different professionals, considering a broad range of prevention options related to wild, feral and domestic animals, all of which have potential to be the source of future epidemics in humans. These will range from medical and veterinary interventions to simple behavioural and societal interventions that could greatly reduce the risk of pathogen transfer (Morse et al., 2012). Solution scanning uses published research and guidance, the experience of experts and practitioners, and brainstorming to identify a range of potential solutions to a specific problem (Sutherland et al., 2014). This includes solutions that have not been reviewed, might not have evidence of effectiveness or may indeed be ineffective, inconvenient, controversial or have negative side effects. It is therefore important that practitioners and policy makers identify possible interventions as a starting point in decision-making before evidence synthesis and consideration of each option's advantages and disadvantages are conducted. The need for this is illustrated by previous research that showed that 92 conservation practitioners responsible for addressing a problem were only aware of 57% of the possible actions (Walsh, Dicks & Sutherland, 2015).
We conducted a solution scan to identify options for reducing the animal–human transfer of zoonotic pathogens with high potential for human-to-human transmission, such as COVID-19. The solution scan was compiled by documenting our own experience of actions, consulting guidance and scientific literature, and contacting a number of experts and practitioners working in different countries, contexts and institutions in order to explore the range of options available. The approach is based on methods developed as part of subject-wide evidence synthesis (Sutherland et al., 2020). This solutions scan was initiated as a collaboration between BioRISC (the Biosecurity Research Initiative at St Catharine's College, Cambridge), Conservation Evidence based in the Department of Zoology, University of Cambridge, and numerous other researchers worldwide. The options considered here are diverse, reflecting the variety of possible transmission pathways at the wildlife–livestock–human interface that are discussed in Section II from wildlife, domesticated and captive animals (Table 1). Our review excludes other sources of potential zoonotic disease emergence which could be responsible for future pandemics including (i) the evolution of antimicrobial resistance (AMR), (ii) pathogen release from laboratories, or (iii) the intentional creation of life. It is important to note that AMR is a topic of enormous importance: AMR could be responsible for 10 million deaths per year by 2050 if left unchecked (O'Neill, 2014). However, we exclude AMR from this study due to differences in the type of pathways of disease emergence, including pathogen selection in effluent pollution and the overuse and misuse of antibiotics in farming and medical settings. Nevertheless, many of the animal husbandry options considered herein, in particular those related to improvements in hygiene and health standards, are directly relevant to enabling reduced use of antimicrobials on farms and thus avoiding the selection of resistant strains.
(2) Interpreting the list of options
We stress that the list provided below is a list of options for consideration and testing, not a list of recommendations or prescriptions. Many options listed may not be feasible, practical or affordable in some situations. For example, the options available to small-scale subsistence farmers will differ from those available to large-scale commercial farms. Similarly, options available in countries with poor animal health and hygiene infrastructure, weak governance and low capacity to regulate or control the local wild meat trade, international wildlife trade, and few available medical testing facilities, will differ from those available to countries with state-of-the-art facilities, diagnostic equipment or strict law enforcement.
It should be recognised that solution scanning is a dynamic process which means that the current list should not be viewed as exhaustive. While effort has been made to compile as complete a list as possible using expert opinion and international collaboration, the vast literature available on specific livestock groups has not been systematically searched, and there may be further options available. This is also true for the wildlife trade literature given the diversity of ways in which animals are used across the globe (e.g. wild meat, exotic pets, medicines, curios, medical research, etc.). Additions to the list are welcome and can be sent to biorisc@caths.cam.ac.uk, and will be added to an updated list of options available at https://covid-19.biorisc.com.
IV. THE LIST OF OPTIONS
The options outlined below are split into four main sections, (1) supply-side measures, (2) transport and sale, (3) measures to tackle consumption, and (4) measures to create appropriate enabling environments (Fig. 1). Measures are focussed on the diverse categories of animals defined in Table 1. The options listed here need to be assessed for the local context of implementation (e.g. likely effectiveness, costs, feasibility, acceptability), including for their broader implications for the local human communities potentially affected.
(1) Supply side
Supply-side measures are any that are applied to the production or sourcing of animals (i.e. rearing of farmed wildlife or livestock or hunting – endeavouring to kill or capture wild animals). They focus on preventing or reducing production, or altering the production process to reduce risk ('tSas-Rolfes et al., 2019).
Supply-side interventions to prevent zoonotic emergence from wildlife may focus on: (i) entirely preventing hunting and collection of high-risk species (area-based or species-based restrictions); (ii) controlling the rate of hunting and collection through limits to numbers or specific characteristics of the animals taken; or (iii) regulating hunting, consolidation and trade through enforced standards. Preventing or reducing hunting, collecting and disturbance of wild species, especially of high-risk species, should decrease the transmission of zoonotic diseases to livestock and people (Johnson et al., 2020). For example, it can reduce the rate of contact between hunters and animals in the wild, and therefore reduce direct animal-to-human transmission. It can also reduce the movement of wild animals out of natural habitats, to places where they have more contact with people and other animals (e.g. markets and other vendors) (Swift et al., 2007). For species that are lower risk for direct transmission, regulated harvesting, with licensing, standards and health or hygiene checks at critical control points, could reduce high-risk practices that cause tra...
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