Opportunities for Transdisciplinary Science to Mitigate Biosecurity Risks From the Intersectionality of Illegal Wildlife Trade With Emerging Zoonotic Pathogens

Existing collaborations among public health practitioners, veterinarians, and ecologists do not sufficiently consider illegal wildlife trade in their surveillance, biosafety, and security (SB&S) efforts even though the risks to health and biodiversity from these threats are significant. We highlight multiple cases to illustrate the risks posed by existing gaps in understanding the intersectionality of the illegal wildlife trade and zoonotic disease transmission. We argue for more integrative science in support of decision-making using the One Health approach. Opportunities abound to apply transdisciplinary science to sustainable wildlife trade policy and programming, such as combining on-the-ground monitoring of health, environmental, and social conditions with an understanding of the operational and spatial dynamics of illicit wildlife trade. We advocate for (1) a surveillance sample management system for enhanced diagnostic efficiency in collaboration with diverse and local partners that can help establish new or link existing surveillance networks, outbreak analysis, and risk mitigation strategies; (2) novel analytical tools and decision support models that can enhance self-directed local livelihoods by addressing monitoring, detection, prevention, interdiction, and remediation; (3) enhanced capacity to promote joint SB&S efforts that can encourage improved human and animal health, timely reporting, emerging disease detection, and outbreak response; and, (4) enhanced monitoring of illicit wildlife trade and supply chains across the heterogeneous context within which they occur. By integrating more diverse scientific disciplines, and their respective scientists with indigenous people and local community insight and risk assessment data, we can help promote a more sustainable and equitable wildlife trade.

Introduction

The contemporary scope and scale of the illegal wildlife trade (IWT) is unprecedented (Goldenberg et al., 2017; UNODC, 2020). This transnational environmental crime includes harms against tens of thousands of vertebrates (Scheffers et al., 2019) generating an estimated $5–$23 billion annually (May, 2017). IWT threatens species, ecosystems and societies both locally and globally (Hinsley et al., 2017; May, 2017). IWT is linked to the spread of zoonotic diseases (Gómez and Aguirre, 2008; Pavlin et al., 2009) and is associated with kleptocracy, corruption, money laundering, degradation of the rule of law, national insecurity, undercutting of sustainable development investments, erosion of cultural resources, and convergence with other serious crimes (Shelley, 2018). IWT-related risks are reinforced by the cross-border and transboundary nature of wildlife crime, diversity of wildlife populations, community-based management regimes, and rural-urban connectivity (Hübschle, 2017; Gore et al., 2019). Efforts to reduce risks associated with IWT may generate new risks. For example, indigenous peoples and local communities (IPLCs) have long been seen as either culprits of biodiversity decline or as “unseen sentinels” effectively managing and monitoring their territories. A binary approach to IWT solutions can exclude IPLC cultural and livelihood dimensions of risk management, provoke existing or new environmental injustices. It may also preclude informed consent of people who will be directly affected by decision making (Matias et al., 2020).

Transdisciplinary science can support efforts to promote sustainable and equitable trade of wildlife because IWT involves both overt and covert human behaviors. These behaviors create new biosecurity risks, including spaces, exposure pathways, and transmission routes for emerging and resurgent pathogens. Humans across all stages of the IWT supply chain—from IPLCs to law enforcement officials to conservation biologists—are at risk from exposure to trafficked wildlife and their pathogens, regardless of their intention in interacting with wildlife (Van Borm et al., 2005; Gómez and Aguirre, 2008). Despite the overall human health risks associated with exposure to pathogens with pandemic potential, the connections of IWT with zoonotic pathogens and vector spread, the intersectionality of the issue has not received sufficient attention from the scientific community (UNODC, 2020; WWF Global Science, 2020). Widespread infections and epidemics are potential outcomes of the trafficked wildlife and as seen most recently with COVID-19, a disproportionate risk from pandemics falls on already vulnerable human populations.

A serious problem confronts policy makers who seek to support evidenced based decisions because the intersectionality can create new, significant, or modified biosecurity and environmental risks that remain unquantified. Failing to understand the impact in unmodeled, unmanaged, and unmitigated human health risks can have serious impacts as illustrated by the following discussion of the biosecurity risks associated with pathogens of pandemic potential and IWT. Conversely, opportunities abound to leverage collaborative research and innovative analytic approaches to expand our understanding of IWT and manage future risks in an equitable and sustainable manner (Aguirre and Nichols, 2020). After our discussions of the risks, we consider the biosecurity risks associated with pathogens of pandemic potential and IWT by identifying four scientific opportunities for the use of transdisciplinary science to mitigate biosecurity risks associated with pathogens of pandemic potential and IWT.

Past as Prologue and the Repeating Biosecurity Risks of Zoonotic Transmission

Destruction of habitats in many parts of the world have promoted contact with new species and their pathogens. Furthermore, urban demand for wildlife in particular, illustrated by the size and number of wet markets and wildmeat consumption, often of endangered or threatened wildlife species, are not only hastening species extinction but are changing human-wildlife interactions in ways not previously seen.

Several “stuttering” events occurred over decades since the 1920s before HIV crossed over to humans and was first detected in the 1980s. Wildmeat hunting and subsequent consumption of these catches is thought to be the primary human-wildlife interaction that enabled the spillover of AIDS from chimpanzees to humans (Wolfe et al., 2007; Ordaz-Nemeth et al., 2017). Today, interactions across species are influenced by the rise of the internet and social media that facilitate illicit trade and poaching of endangered and other species across the globe.

In Africa this has been even visually documented. The open and dark web, social media, smart phones and mobile banking enable IWT as ever before (IFAW, 2012; Lavorgna, 2014). Virtual platforms for buying and selling products blur the lines between the legal and illegal wildlife trade, and the lack of monitoring and regulation of virtual “ecosystems” complicate efforts to reduce biosafety risks and promote sustainable trade. The ability to engage in IWT anonymously has increased access to wildlife for diverse stakeholders while at the same time obfuscating some options for pandemic-related contact tracing (Siriwat and Nijman, 2018; FATF, 2020).

Human-wildlife interactions enable zoonotic infections in at least two ways. First, infections can move from animals to humans. This infection pathway is most common in geographies where wet markets, wildmeat hunting, and trade of non-native species are common. This trade is driven by legitimate and illegitimate motivations. These interactions increase the spatial and temporal likelihood of transmission. Second, infections may transfer from humans to other animal species through a process known as zooanthroponosis (Messenger et al., 2014). This less common pathway of transmission can still generate substantial risks. For example, SARS-CoV-2 has been reported in domestic dogs, domestic cats, tigers, and lions (Gönültas et al., 2020; Wang et al., 2020). Spillover of SARS-CoV-2 from humans to mink was also reported in several countries confirmed through contact tracing. As a result, millions of minks have been culled globally (Kevany, 2020; Koopmans, 2020).

Several epidemics and pandemics devastating to humans were detected in recent times including H1N1 swine flu (1.4B infected; 151-575k dead), Ebola virus of 2014-16 in West Africa (28.6 k cases and 11.3 k deaths). Zika virus, SARS and MERS emerged in between these others. These emerging infectious diseases (EIDs) underscore the intersectionality of environmental and animal well-being with maintenance of human health. These outbreaks not only caused the death of hundreds to thousands of people, they increased risks from comorbidity factors such as diabetes, negatively impacted economies, and caused tensions among decision-makers (Madhav et al., 2017; Khubchandani et al., 2020).

The large number of initial patients of COVID-19 associated with a wet market in Wuhan, China originally suggested that the locale, where people closely interacted with legally (and potentially illegally) traded wildlife, was key in its transmission among humans. Some scientists have speculated that the market could, however, have been a focus of human-to-human rather than animal-to-human spread (Mackenzie and Smith, 2020). However, SARS-CoV-2 was not detected in Sunda pangolins (Manis javanica) confirming that this may have been an incidental host in the transmission (Lee et al., 2020). Zoonotic transmission of COVID-19 has not been determined, and ultimately, scientists may never be able to determine a specific animal host and whether it was linked to legally or illegally traded wildlife (Dhama et al., 2020).

A One Health Approach to Surveillance, Biosafety, and Security

Existing collaborations among medical personnel and veterinarians seldom consider the role of IWT in zoonotic transmission of pathogens in surveillance, biosafety, and security (SB&S) efforts (Graham et al., 2013). This observation is striking within the context of One Health (OH), or “the collaborative effort of multiple disciplines—working locally, nationally, and globally—to attain optimal health for people, animals and our environment” (American Veterinary Medical Association, 2008). A OH approach is well-suited for globally distributed challenges such as IWT and pandemics. OH can accommodate dynamic changes in the relationship among humans, wildlife, and ecosystems.

Although academia has moved toward more transdisciplinary research, many challenges remain in governments where agencies tasked with different mandates discourage strong collaborations. A legislation framework will be required to deal with the restrictive nature and slow response to dynamic changes in the landscape (Hyatt et al., 2015). Despite these challenges, integrating theories, methods, and analytical techniques from diverse disciplines with different skill sets can serve as a force multiplier for the policy-relevance of science focused on the threats to human security and global health posed by pathogens of pandemic potential. Pandemic-related impacts such as those associated with COVD-19 (e.g., human death and illness, economic declines, politicization of science) and the increasing sophistication, impact, and economic value of IWT combine to demonstrate that future collaborations and more diverse partnerships are needed. Incorporating OH approaches may be most effective at advancing sustainable and equitable objectives if they engage diverse experts across domains such as conservation criminology, transnational crime, and corruption, supply chain analytics, operations research, and data science. Such transdisciplinary science can at least help clarify a common vision for sustainable use, establish shared values and goals, prioritize equitable allocation of limited resources, guide response protocols, support scalability of decision-making tools, and enhance communication.

We propose four collaborative initiatives to help extend and enhance SB&S efforts in support of more sustainable and equitable treatment of IWT. The OH framework accommodates the range of transdisciplinary perspectives involved in assessing existing SB&S efforts and detection networks for zoonotic pathogens that pose disease burdens for humans and animals. Beyond leveraging existing capacity, technology, and health systems identified through an OH assessment, bespoke, cutting-edge, and locally-sensitive decision and location science-based surveillance and response models can be incorporated to support more effective policy-making and sustainable use of wildlife (Hyatt et al., 2015; Aguirre et al., 2019; Wilcox et al., 2019).

Opportunities to Mitigate Biosecurity Risks Using Transdisciplinary Science

One pathway for improving detection of pathogens in trafficked wildlife is through enhanced technical capacity for effective detection networks, outbreak analysis, and surveillance. Such capacity can generate inferences and inform efforts to decrease the risk of transmission of these pathogens to people and animals. Endemic and cross-boundary zoonotic pathogens (e.g., anthrax, bovine tuberculosis, brucellosis, echinococcosis, Lyme disease) are often underreported or are reported late, due to a lack of local diagnostic capacity and missing data on disease prevalence (Halliday et al., 2012; Tambo et al., 2014). A surveillance system focusing on specific pathogens by country or region along supply chain components of trafficked wildlife requires an understanding of the factors promoting emergence. Identifying approaches for prevention, rapid control, and mitigation is key (https://www.unodc.org/documents/Advocacy-Section/Wildlife_trafficking_COVID_19_GPWLFC_public.pdf). The health, societal, economic, and geopolitical impacts caused directly and indirectly by the COVID-19 pandemic, illustrate the range of risks associated with leaders or public officials who are unable (or unwilling) to identify and respond promptly and adequately to emerging zoonotic pathogens.

Populating a data landscape with analytically relevant variables will enable tracking of trends over time, facilitate aggregation, and disaggregation of data, support monitoring and evaluation efforts, enhance transparency in decision making, and promote accountability to donors. At present, the data landscape is devoid of many of these characteristics, to the detriment of sustainable wildlife use and human health and well-being. We propose actionable opportunities to address these shortcomings.

First, decision makers, civil society, and partner sectors may leverage enhanced SB&S to respond in an appropriate and timely manner to EIDs and strengthen national and local response capacities to prevent future outbreaks. A range of relevant activities includes:

• Comprehensive and co-created prevention education component for at-risk populations.

• A surveillance sample management system for enhanced diagnostic efficiency in collaboration with local partners to further establish or link existing surveillance networks (e.g., Rhinoceros DNA Index System in South Africa https://erhodis.org/).

• Integration of systems analysis and decision science methods within an economic, environmental, social ecosystem and IPLC perspective.

• Integrate transport industry such as aviation providers into enforcement efforts to prevent zoonotic transmission and wildlife trade (USAID, 2020).

• Consideration of the spatiality and intersectionality of wildlife trafficking and biosafety from cross-boundary zoonotic transmission.

Many stakeholders around the world already have the ability to create and manage highly efficient systems and networks across domain areas including logistics, commerce, and health care. SB&S can use those same tools to weaken illicit networks having negative outcomes including health risks, corruption, or abuse (Wood, 1993; Guo et al., 2016). That said, these methods require not only data regarding the nature of disease risk, but also need information on the behaviors of people who participate in those networks that lead to pathogen spillover (Alexander and McNutt, 2010). This requires multi-cultural perspectives and sensitivities.

Second, there exists an opportunity to leverage insights from IPLCs using community-based participatory methods and combining such knowledge with expert assessments, inducing the development of novel analytical tools and approaches that decision-makers can use to respectfully and equitably support local livelihoods by addressing the following enduring challenges: monitoring, detection, prevention, interdiction, and remediation. Improved decision-making for these challenges can be achieved with insights from IPLCs, through a clearer understanding about the operational environment and the economic and societal drivers that motivate local community members to participate in IWT.

Third, decision support models informing behavioral change policies can dramatically enhance local capacity to prevent, detect, and respond to pathogen risks. Supporting compliance with existing rules and enhancing crime analysis and prevention capacity of law enforcement authorities can help address the needs of community members who may otherwise resort to participation in IWT. Participatory methods can help ensure that local populations inform the development of solutions and these strategies are more likely to be consistent with cultural needs and priorities.

At the same time decision-support tools also need to be based on broad systematic evidence appropriate for long term sustainability—and it is imperative that these tools provide ease-of-use and interpretability for implementation by local stakeholders unfamiliar with sophisticated models and diagnostic tools; for example, the common use of Nobuto filter-paper blood samples collected during field surveys to detect exposure to an array of infectious diseases including avian influenza, canine distemper, malaria, and sylvatic plague (Advantec, 2009). Community outreach and engagement can produce accurate and reliable information about the prevalence of wildlife trafficking and EIDs that would otherwise not be known; community engagement will support the sustainability of detection and prevention strategies. We know that poverty, deforestation, urbanization, and human behavior are comorbidity factors underlying EID emergence that may progress into a pandemic (Patz et al., 2004; Aguirre and Tabor, 2009; Hassell et al., 2017). These variables influence epidemiology of pandemics in dynamic ways. Even without the benefit of hindsight on the pandemic, past responses to pandemics reveals that local capacity building, integrative research and transdisciplinary collaborations using the social ecological systems and resilience approach (Wilcox et al., 2019) will be prerequisites to untangle these complex issues that may result in severe harm across large populations. Broader efforts can and should be integrated with our understanding of the illicit wildlife trade. Best practices from efforts to combat other elements of the illicit economy such as study of supply chains, corruption, and illicit financial flows is crucial (Aguirre et al., 2020; FATF, 2020).

Finally, more can be done to harmonize a “network of networks”—including local communities—with enhanced capacity to promote joint SB&S efforts that encourage improved human and animal health, timely reporting, emerging disease detection, and outbreak response along with reporting on IWT. We already have global structures in place to support such a network of networks through science diplomacy, such as The One Health Tripartite Agreement between the Food and Agricultural Organization, World Health Organization and World Organization for Animal Health, supported by the World Bank Group (Vandersmissen and Welburn, 2014).

We can promote resilience in ecosystem function by enhancing education for justice, promoting legislative science advice, and funding interdisciplinary research teams. Science teams can help increase awareness and data integration capacity to facilitate new threat information that can be used strategically and tactically in both responsive and proactive ways. Such information could be particularly useful when it intentionally captures local community knowledge and integrates datasets to dramatically decrease the biosafety security gap between urban and rural areas (OECD, 2020).

Prevention Outweighs Reactive Approaches

Future efforts for containing zoonotic disease of pandemic potential may require a significant shift from scientific prediction to prevention, interdiction, and remediation strategies to deliver any practically beneficial outcomes (Dobson et al., 2020). It also requires efforts to reduce habitat destruction. The COVID-19 pandemic demonstrates that finding a virus, and managing the virus from a public health perspective, are two very different things. The world population and its many different cultures constitutes a complex system within which the virus circulates. Across the social, biological, and engineering sciences there is knowledge, and there are methods that can individually be brought to bear to more fully understand this complex system. More importantly, when diverse disciplines and their resources are brought together to address a complex challenge, they can answer questions and gain insights that no single discipline could generate in isolation.

Conclusions

Supporting SB&S efforts by government agencies and authorities [i.e., 1972 Biological Weapons Convention, 2004 UN Security Council Resolution 1540, 2005 World Health Organization International Health Regulations, Biosafety Level 4 containment laboratories (BSL-4)] from the local to the international levels, is critical for sustainable use of wildlife. These SB&S efforts can create new—and enhance existing—collaborations and capacity to address security issues at the intersection of human and animal health, wildlife trafficking, and infectious pathogens. This intersectionality is well-situated within the OH approach, particularly within the context of current consumption rates of animals for food, culture, traditional medicine, or the exotic pet trade. These activities have persisted for millennia and are highly likely to persist in a post-COVID-19 world. If there are wildlife consumption or trade bans instituted in countries where wildlife products are consumed, what will the impact of these be on curbing disease transmission? How successful would a ban of limited scope be in reducing the risks to human health and well-being from zoonotic transmission? In reality, banning wet markets is unlikely to wholly eliminate or even significantly reduce the disease transmission risks associated with IWT. It may, for example, help drive IWT underground, decrease nutritional options for vulnerable populations, degrade social and cultural identity or alter expressions of power and status. These are phenomena with policy implications that can be most accurately addressed by transdisciplinary scientific research with policy analysis (Alves and Rosa, 2007; Aguirre et al., 2019). Attention can be focused on the supply chains that allow zoonotic pathogens to be so rapidly distributed around the globe. Local capacity building is an essential element of global prevention, and such capacity can be combined with resourceful and well-trained networks at the global level to encourage diverse approaches to sustain biodiversity. This requires unprecedented cooperation by those in the OH world with the specialists in illicit trade in wildlife and illicit supply chains. This also requires transdisciplinary teams spanning science and engineering, environmental studies and social science as well as NGOs and corporations.

We need to ensure that businesses are not complicit in shipping animals with harmful diseases around the world. This requires closer cooperation with the business community such as occurred with the Routes partnership (USAID, 2020). We need interdisciplinary research to address illicit supply chains. More work is needed with the tech sector to ensure that online platforms and social media are not facilitators of illicit sales of endangered species of poached animals, and illicitly obtained flora and fauna. By involving participants at all levels and in all sectors of society we can encourage policies that improve environmental conditions in local communities and at the regional level. Habitat conservation, wildlife protection and a focus on the diverse skill sets of communities is key to accomplishing these objectives. By integrating more diverse scientific disciplines, and their respective scientists with indigenous people and local community insight and risk assessment data, we can promote a more sustainable and equitable wildlife trade.

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Author Contributions

All the authors participated in the drafting the manuscript and discussion of all topics related to this perspective manuscript.

Disclaimer

The views expressed in this article are those of the authors and do not necessarily reflect the views of their professional or personal affiliations.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

Advantec (2009). Blood Sampling Paper (Nobuto's) User's Manual. Toyo Roshi Kaisha, Ltd., Dublin, California.

Google Scholar

Aguirre, A. A., Basu, N., Kahn, L. H., Morin, X. K., Echaubard, P., Wilcox, B. A., et al. (2019). Transdisciplinary and social-ecological health frameworks—Novel approaches to emerging parasitic and vector-borne diseases. Parasite Epidemiol. Control 4:e00084. doi: 10.1016/j.parepi.2019.e00084

PubMed Abstract | CrossRef Full Text | Google Scholar

Aguirre, A. A., Catherina, R., Frye, H., and Shelley, L. (2020). Illicit wildlife trade, wet markets and COVID-19: preventing future pandemics. World Med. Health Pol. 12, 256–265. doi: 10.1002/wmh3.348

PubMed Abstract | CrossRef Full Text | Google Scholar

Aguirre, A. A., and Nichols, W. J. (2020). The Conservation Mosaic Approach to Reduce Corruption and the Illicit Sea Turtle Take and Trade. Targeting Natural Resource Corruption Practice Note, April, USAID, WWF, CMI U4 Anti-Corruption, TraCCC and TRAFFIC (Washington, DC), 8.

Google Scholar

Aguirre, A. A., and Tabor, G. M. (2009). Global factors driving emerging infectious diseases: Impact on wildlife populations. Ann. N. Y. Acad. Sci. 1149, 1–3. doi: 10.1196/annals.1428.052

PubMed Abstract | CrossRef Full Text | Google Scholar

Alexander, K. A., and McNutt, J. W. (2010). Human behavior influences infectious disease emergence at the human–animal interface. Front. Ecol. Environ. 8, 522–526, doi: 10.1890/090057

CrossRef Full Text | Google Scholar

Alves, R. R. N., and Rosa, I. M. L. (2007). Biodiversity, traditional medicine and public health: Where do they meet? J. Ethnobiol. Ethnomed. 3:14. doi: 10.1186/1746-4269-3-14

PubMed Abstract | CrossRef Full Text | Google Scholar

American Veterinary Medical Association (2008). One Health Initiative Task Force. One Health: A New Professional Imperative. Schaumberg, IL, USA.

Google Scholar

Dhama, K., Patel, S. K., Sharun, K., Pathak, M., Tiwari, R., Yatoo, M. I., et al. (2020). SARS-CoV-2 jumping the species barrier: zoonotic lessons from SARS, MERS and recent advances to combat this pandemic virus, Travel Med. Infect. Dis. 37:101830. doi: 10.1016/j.tmaid.2020.101830

PubMed Abstract | CrossRef Full Text | Google Scholar

Dobson, A. P., Pimm, S. L., Hannah, L., Ahumada, J. A., Ando, A. W., Bernstein, A., et al. (2020). Ecology and economics for pandemic prevention. Science 369, 379–381. doi: 10.1126/science.abc3189

PubMed Abstract | CrossRef Full Text | Google Scholar

FATF (2020). Money Laundering and the Illegal Wildlife Trade, Financial Action Task Force. Available online at: http://www.fatf-gafi.org/publications/methodsandtrends/documents/money-laundering-wildlife-trade.html

Google Scholar

Goldenberg, S. Z., Douglas-Hamilton, I., Daballen, D., and Wittemyer, G. (2017). Challenges of using behavior to monitor anthropogenic impacts on wildlife: a case study on illegal killing of African elephants. Anim. Conserv. 20, 215–224. doi: 10.1111/acv.12309

CrossRef Full Text | Google Scholar

Gómez, A., and Aguirre, A. A. (2008). Infectious diseases and the illegal wildlife trade. Anim. Biodiversity Emerg. Dis. Ann. NY Acad. Sci. 1149, 16–19. doi: 10.1196/annals.1428.046

PubMed Abstract | CrossRef Full Text | Google Scholar

Gönültas, S., Karabagli, M., Bastug, Y., Can Çilesiz, N., and Kadioglu, A. (2020). COVID-19 and animals: what do we know? Turk. J. Urol. 46, 249–252. doi: 10.5152/tud.2020.140520

PubMed Abstract | CrossRef Full Text | Google Scholar

Gore, M. L., Braszak, P., Brown, J., Cassey, P., Duffy, R., Fisher, J., et al. (2019). Transnational environmental crime threatens sustainable development. Nat. Sustain. 2, 784–786. doi: 10.1038/s41893-019-0363-6

CrossRef Full Text | Google Scholar

Graham, R. L., Donaldson, E. F., and Baric, R. S. (2013). A decade after SARS: strategies for controlling emerging coronaviruses. Nat. Rev. Microbiol. 11, 836–48. doi: 10.1038/nrmicro3143

PubMed Abstract | CrossRef Full Text | Google Scholar

Guo, Q., An, B., Zick, Y., and Miao, C. (2016). “Optimal interdiction of illegal network flow,” in Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16), 2507–2513.

Google Scholar

Halliday, J., Daborn, C., Auty, H., Mtema, Z., Lembo, T., Bronsvoort, B. M., et al. (2012). Bringing together emerging and endemic zoonoses surveillance: shared challenges and a common solution. In Phil. Trans. R. Soc. B: Biol. Sci. 367, 2872–2880. doi: 10.1098/rstb.2011.0362

PubMed Abstract | CrossRef Full Text | Google Scholar

Hassell, J. M., Begon, M., Ward, M. J., and Fèvre, E. M. (2017). Urbanization and disease emergence: dynamics at the wildlife–livestock–human interface. Trends Ecol. Evol. 32, 55–67. doi: 10.1016/j.tree.2016.09.012

PubMed Abstract | CrossRef Full Text | Google Scholar

Hinsley, A., Nuno, A., Ridout, M., St John, F. A. V. S., and Roberts, D. L. (2017). Estimating the extent of CITES noncompliance among traders and end-consumers: lessons from the global orchid trade. Conserv. Let. 10, 602–609. doi: 10.1111/conl.12316

CrossRef Full Text | Google Scholar

Hübschle, A. (2017). The social economy of rhino poaching: of economic freedom fighters, professional hunters and marginalized local people. Curr. Soc. 65, 427–447. doi: 10.1177/0011392116673210

CrossRef Full Text | Google Scholar

Hyatt, A., Aguirre, A. A., Jeggo, M., and Woods, R. (2015). Effective coordination and management of emerging infectious diseases in wildlife. EcoHealth 12, 408–411. doi: 10.1007/s10393-015-1045-0

PubMed Abstract | CrossRef Full Text | Google Scholar

IFAW (2012). Killing with Keystrokes 2.0, International Fund for Animal Welfare. Available online at: https://d1jyxxz9imt9yb.cloudfront.net/resource/203/attachment/original/FINAL_Killing_with_Keystrokes_2.0_report_2011.pdf.

Google Scholar

Kevany S. (2020) A Million Mink Culled in Netherlands and Spain Amid Covid-19 Fur Farming Havoc. Available online at: https://www.unodc.org/unodc/en/data-and-analysis/wildlife.html.

Google Scholar

Khubchandani, J., Jordan, T. R., and Yang, Y. T. (2020). Ebola, Zika, Corona…what is next for our world? Int. J. Environ. Res. Public Health 17:3171. doi: 10.3390/ijerph17093171

PubMed Abstract | CrossRef Full Text | Google Scholar

Koopmans, M. (2020). SARS-CoV-2 and the human-animal interface: outbreaks on mink farms. Lancet Inf. Dis. 21, 18–19. doi: 10.1016/S1473-3099(20)30912-9

PubMed Abstract | CrossRef Full Text | Google Scholar

Lavorgna, A. (2014). Wildlife trafficking in the Internet age. Crime Sci. 3:5. doi: 10.1186/s40163-014-0005-2

CrossRef Full Text | Google Scholar

Lee, J., Hughes, T., Lee, M. H., Field, H., Rovie-Ryan, J. J., and Sitam, F. T. (2020) No evidence of coronaviruses or other potentially zoonotic viruses in Sunda pangolins (Manis javanica) entering the wildlife trade via Malaysia. Ecohealth 17, 406–418. doi: 10.1007/s10393-020-01503-x.

CrossRef Full Text | Google Scholar

Mackenzie, J. S., and Smith, D. W. (2020). COVID-19: a novel zoonotic disease caused by a coronavirus from China: what we know and what we don't. Microbiol. Aust. 41, 41–50. doi: 10.1071/MA20013

PubMed Abstract | CrossRef Full Text | Google Scholar

Madhav, N., Oppenheim, B., Gallivan, M., Mulembakani, P., Rubin, E., and Wolfe, N. (2017). “Pandemics: risks, impacts, and mitigation,” in Disease Control Priorities, 3rd Ed. (Vol. 9): Improving Health and Reducing Poverty (The World Bank), 315–345. doi: 10.1596/978-1-4648-0527-1_ch17

PubMed Abstract | CrossRef Full Text | Google Scholar

Matias, T., Doninski, F. H., and Marks, D. F. (2020). Human needs in COVID-19 isolation. J. Health Psychol. 25, 871–882. doi: 10.1177/1359105320925149

PubMed Abstract | CrossRef Full Text | Google Scholar

May, C. (2017). Transnational crime and the developing world. Global Financial Integrity 166.

Google Scholar

Messenger, A. M., Barnes, A. N., and Gray, G. C. (2014). Reverse zoonotic disease transmission (zooanthroponosis): a systematic review of seldom-documented human biological threats to animals. PLoS ONE 9:e89055. doi: 10.1371/journal.pone.0089055

PubMed Abstract | CrossRef Full Text | Google Scholar

OECD (2020). Policy Implications of Coronavirus Crisis for Rural Development. Organization for Economic Co-operation and Development. OECD Publishing, Paris, France. Available online at: http://www.oecd.org/coronavirus/policy-responses/policy-implications-of-coronavirus-crisis-for-rural-development-6b9d189a/

Google Scholar

Ordaz-Nemeth, I., Arandjelovic, M., Boesch, L., Gatiso, T., Grimes, T., Kuehl, H. S., et al. (2017). The socio-economic drivers of bushmeat consumption during the West African Ebola crisis. PLoS Negl. Trop. Dis. 11:e0005450. doi: 10.1371/journal.pntd.0005450

PubMed Abstract | CrossRef Full Text | Google Scholar

Patz, J. A., Daszak, P., Tabor, G. M., Aguirre, A. A., Pearl, M., Epstein, J., et al. (2004). Unhealthy landscapes: policy recommendations pertaining to land use change and disease emergence. Environ. Health Perspect. 112, 1092–1098. doi: 10.1289/ehp.6877

PubMed Abstract | CrossRef Full Text | Google Scholar

Pavlin, B. I., Schloegel, L. M., and Daszak, P. (2009). Risk of importing zoonotic diseases through the wildlife trade, United States. Emerg. Inf. Dis. 15, 1721–1726. doi: 10.3201/eid1511.090467

PubMed Abstract | CrossRef Full Text | Google Scholar

Scheffers, B. R, Oliveira, B. F., Lamb, I., and Edwards, D.P. (2019). Global wildlife trade across the tree of life. Science 366, 71–76. doi: 10.1126/science.aav5327

PubMed Abstract | CrossRef Full Text | Google Scholar

Shelley, L. (2018). Dark Commerce: How a New Illicit Economy is Threatening Our Future. Princeton: Princeton University Press. doi: 10.1515/9780691184296

CrossRef Full Text | Google Scholar

Siriwat, P., and Nijman, V. (2018). Illegal pet trade on social media as an emerging impediment to the conservation of Asian otter species. J. Asia-Pacific Biodiver. 11, 469–475. doi: 10.1016/j.japb.2018.09.004

CrossRef Full Text | Google Scholar

Tambo, E., Ugwu, C., and Ngogang, J. (2014). Need of surveillance response systems to combat Ebola outbreaks and other emerging infectious diseases in African countries. Inf. Dis. Poverty 3:29. doi: 10.1186/2049-9957-3-29

PubMed Abstract | CrossRef Full Text | Google Scholar

UNODC (2020) World Wildlife Crime Report 2020 United Nations Office on Drugs and Crime. Available online at: https://www.theguardian.com/world/2020/jul/17/spain-to-cull-nearly-100000-mink-in-coronavirus-outbreak.

Google Scholar

USAID (2020). Reducing Opportunities for Unlawful Transport of Endangered Species (ROUTES) Partnership. Available online at: https://routespartnership.org/

Google Scholar

Van Borm, S., Thomas, I., Hanquet, G., Lambrecht, B., Boschmans, M., Dupont, G., et al. (2005). Highly pathogenic H5N1 influenza virus in smuggled Thai eagles, Belgium. Emerg. Infect. Dis. 11, 702–705. doi: 10.3201/eid1105.050211

PubMed Abstract | CrossRef Full Text | Google Scholar

Vandersmissen, A., and Welburn, S. C. (2014). Current initiatives in One Health: consolidating the One Health Global Network. Rev. Sci. Tech. OIE 33, 421–432. doi: 10.20506/rst.33.2.2297

PubMed Abstract | CrossRef Full Text | Google Scholar

Wang, L., Mitchell, P. K., Calle, P. P., Bartlett, S. L., McAloose, D., Killian, M. L., et al. (2020). Complete genome sequence of SARS-CoV-2 in a tiger from a U.S. zoological collection. Microbiol. Resour. Announc. 9:e00468–20. doi: 10.1128/MRA.00468-20

PubMed Abstract | CrossRef Full Text | Google Scholar

Wilcox, B. A., Aguirre, A. A., De Padua, N., Siriaroonrat, B., and Echaubard, P. (2019). Operationalizing one heath employing social-ecological systems theory: lessons from the Greater Mekong Subregion. Front. Publ. Health 7:85. doi: 10.3389/fpubh.2019.00085

CrossRef Full Text | Google Scholar

Wolfe, N. D., Panosian Dunavan, C., and Diamond, J. (2007). Origins of major human infectious diseases. Nature 447, 279–283. doi: 10.1038/nature05775

PubMed Abstract | CrossRef Full Text | Google Scholar

Wood, R. K. (1993). Deterministic network interdiction. Math. Comput. Model. 17, 1–18. doi: 10.1016/0895-7177(93)90236-R

CrossRef Full Text | Google Scholar

WWF Global Science (2020). Beyond Boundaries: Insights Into Emerging Zoonotic Diseases, Nature, and Human Well-Being. Internal science brief. Unpublished, Washington, DC.

Google Scholar