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Rigorous wildlife disease surveillence needed
Fri, 2020-07-10 19:55 — mike kraft Rigorous wildlife disease surveillance Evidence suggests that zoonotic (animal origin) coronaviruses have caused three recent emerging infectious disease (EID) outbreaks: severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and the current coronavirus disease 2019 (COVID-19) pandemic. In the search for an intermediate host for SARS coronavirus 2 (SARS-CoV-2, which causes COVID-19), studies have identified SARS-CoV-2–like strains in bats ([ 1 ][1]) and pangolins ([ 2 ][2]), but these do not contain the same polybasic cleavage site that is present in SARS-CoV-2 ([ 3 ][3]). It is unknown what the intermediate host for this spillover event was because to date there are no international or national conventions on pathogen screening associated with animals, animal products, or their movements, and capacity for EID diagnostics is limited along much of the human-wildlife interface. EID risks associated with the wildlife trade remain the largest unmet challenge of current disease surveillance efforts. Although viruses represent a fraction of ∼1400 known human pathogens, they place a disproportionate burden on global health ([ 4 ][4]). Around 89% of the 180 recognized RNA viruses with the potential to harm humans are zoonotic. Coronaviruses are only the tip of the spillover iceberg: HIV came from nonhuman primates, Ebola came from bats, and H5N1 and H1N1 influenza strains came from birds and pigs, respectively. Indeed, 60% of EIDs are zoonotic in nature, and more than 70% of these have an origin in wildlife ([ 5 ][5]). Unchecked exploitation of wildlife—whether for sustenance or profit, legal or illegal—puts humans in direct contact with myriad unfamiliar species. Increased contact occurs in the global practice of bushmeat and game hunting and in wildlife farms, which often unsustainably and illegally supply wildlife for consumption or trade ([ 6 ][6]). Imported, hunted, and farmed wildlife then reach a common endpoint, wildlife markets. There, animals endure debilitating and immunocompromising conditions that promote disease transmission: packed cages, poor biosecurity, and unhygienic shedding of animal excreta ([ 7 ][7]). Direct human-wildlife contact, mixing of nonendemic wildlife species, and limited health and safety standards are all criteria for a zoonotic hotspot. Many wildlife markets around the world meet these criteria, yet disease surveillance in them is largely absent. More broadly, although the Convention on the International Trade in Endangered Species (CITES) regulates international wildlife trade on the basis of species' endangered status, only a few countries use strict veterinary import controls, and there are no global regulations on pathogen screening associated with the international trade in wildlife. Pathogen biosurveillance and how humans interact with wildlife are at the crux of EID risk management and response. After bats were identified as likely reservoirs for a range of zoonotic events (such as Hendra, Nipah, SARS, MERS, and Ebola) ([ 8 ][8]), surveillance of a single cave in southwest China between 2011 and 2015 revealed 11 novel coronaviruses ([ 9 ][9]). From 2015 to 2017, of 1497 people tested in the surrounding Yunnan, Guangxi, and Guangdong districts, nine (0.6%) were positive for prior bat coronavirus antibodies, and 265 (17%) reported SARS- or influenzatype symptoms associated with contact with poultry, carnivores, rodents, shrews, or bats ([ 10 ][10]). These findings, formally reported in September 2019, provided a warning about the risk of zoonotic coronaviruses that was neither heard nor heeded. The COVID-19 pandemic is evidence that bridging the gap between research and response is critical to anticipating and mitigating future spillover events. PREDICT, the intermittently federally funded offshoot of the 2009 United States Agency for International Development (USAID) Emerging Pandemic Threats program that partially financed the study of bat coronaviruses ([ 10 ][10]), screened 164,000 animals and humans and detected 949 novel viruses in zoonotic hotspots across 30 countries between 2009 and 2019. The Global Virome Project—a collaboration between experts in global health and pandemic prevention—aims to sequence all animal virus strains over a 10-year period, with a projected cost of $1.2 billion. Both projects share stakeholders, and although their missions are likely to adapt to a post–COVID-19 world, one of their stated goals includes strengthening existing laboratory capacities along the human-wildlife interface. But are there sufficient numbers of animal pathogen reference laboratories? According to the World Organisation for Animal Health (OIE) ([ 11 ][11]), there are 125 reference laboratories certified to screen for one or more target pathogens (and not for broad pathogen surveillance). Their global distribution does not reflect EID risks. Southeast Asia, Africa, and Central and South America carry the burden of EID risk, yet 78 (62%) of reference laboratories are in Europe and North America; only 33 (26%) are in Asia (14 in China and 8 in Japan), with 12 (34%) spread between 7 countries; 3 (∼2%) are in Africa; 4 (∼3%) are in Australia, and 8 (∼6%) are in South America. Although this does not account for laboratory size or screening methods and capacity, it is evident that many regions with zoonotic hotspots lack testing facilities with the capability of conducting disease surveillance. What can be done to mitigate future zoonotic EIDs? Centralized biosurveillance efforts produce results but are expensive, maintained by a select few countries, and subject to political whims, as evidenced by the 2019 shift in funding for PREDICT, a recent recall of U.S. National Institutes of Health (NIH) support for the EcoHealth Alliance, and the withdrawal of the United States from the World Health Organization (WHO). As such, they are not immediately scalable, nor do they stimulate widespread capacity. The international wildlife trade is a substantial global industry in need of greater oversight. Because ill-conceived restrictions would affect millions of people and likely drive these activities deeper underground, further impeding regulation ([ 12 ][12]), the first step is to establish a more cost-effective, decentralized disease surveillance system. It would empower local wildlife and public health professionals to test for diseases year round, at source, without criminalizing public participation in screening programs. Such screening was not technologically feasible after the emergence of the H1N1 influenza virus in 2009, but now, affordable modern technologies enable quick in situ biosample processing, whole-genome sequencing, metagenomics, and metabarcoding of pathogens. This would enable proactive, broad, routine wildlife pathogen screening in remote areas rather than reactive targeted testing. Decentralized laboratories must be able to extract genomic material and conduct metagenomic sequencing and targeted pathogen testing if necessary. As demand increases, individual technologies have evolved to be smaller, simpler, and more affordable. Multiplex polymerase chain reaction (PCR)–based viral enrichment protocols with portable DNA sequencers (such as MinION) have been deployed for in situ monitoring of Ebola virus, Zika virus, and now SARS-CoV-2 infections ([ 13 ][13]). Practical training in applying these laboratory solutions (such as miniature centrifuges, thermocyclers, and electrophoresis setups) is well documented, even in remote locations ([ 14 ][14]). However, most pathogen screening efforts that use such equipment have been in response to human disease outbreaks. These technologies could be used to regularly monitor entire pathogen families of increased global concern in animals and areas with increased risk of zoonotic spillover, including wildlife markets or farms and free-ranging high-risk taxa such as primates and bats ([ 15 ][15]). Local wildlife scientists and health care workers can be trained on how to safely use facilities with broadly accessible molecular equipment in local facilities with standard biosecurity practices to prevent risk of pathogen spillover into the community. Restricting such training and activities to relatively few specialized centers impedes broad surveillance efforts. Any animal surveillance program should integrate with testing programs for humans to capture early zoonotic pathogen circulation between human and nonhuman populations. Sources of zoonotic pathogens are frequently unclear and often not possible to determine after the early stages of a spillover event. Monitoring could remove much of this uncertainty, allowing molecular epidemiology to inform short- and long-term responses on both a local and global level. To complement decentralized laboratories, a publicly accessible, centralized, curated system for monitoring pathogens must be established for three main reasons: (i) This would provide instant pathogen classifications based on comparative genomics, further cross-linked to reference data on prevalence by species and region. (ii) A centralized curated system could alert to EID indicators, including gains and losses of strains, pathogen-specific changes in host species numbers, rapid increases in mutation rates that may indicate pathogen spillover into a naive host, and pathogen detection in traded animals that do not occur in wild counterparts. (iii) For virus families that are poised to spillover into human populations, genomic sequence data can reveal diversity of key pathogen proteins in circulating strains (for example, the spike protein that mediates human cell entry of coronaviruses, and the RNA-dependent RNA polymerase that is important for viral replication). Such approaches assist in identifying broad-spectrum antivirals and vaccination targets as well as treatment-resistant pathogen variants that pose a risk of generating future EIDs. An example of a disease-focused public database that could be expanded is the GISAID (global initiative on sharing all influenza data) EpiFlu repository, a global initiative developed for sharing influenza virus sequence data and currently also documenting SARS-CoV-2 sequences. It facilitates data access for registered users while securing data ownership by requiring that contributors be acknowledged in derivative research. Additionally, the database could include report-generating features such as those in the Zoological Information Management Software (ZIMS), used by more than 1000 Species360–accredited zoological institutions worldwide to upload biomedical data and compute reference ranges across multiple variables and species. An internationally recognized standard for managing wildlife trade on the basis of known disease risks should be established. Currently, few countries consider disease risk as a factor in regulating wildlife imports and exports, and a disease status equivalent to CITES is lacking. Pathogen screening is also not required nor facilitated before, during, or after translocating wildlife products, leaving pathogen status to be declared by the shipper, who may not have the experience to make such determinations. Because a large number of animals naturally carry pathogens that could spillover to humans if improperly handled, the means to identify the species for which security standards should be enhanced, or for which trade and consumption should potentially be prohibited, is needed. An important caveat is that such classifications can stigmatize animals to their detriment and incite fear-based human behaviors that may threaten species conservation. A decentralized network could improve feedback between those who screen samples and those who curate data to bolster the safety of wildlife and humans, a fundamentally “One Health” approach. This would increase localized knowledge of EID risks, provide earlier warnings and faster global responses to spillovers, and inform wildlife trade policy. This model is more robust to shifting political landscapes and funding and does not ignore the role of advanced regional research laboratories, which also provide vital targeted pathogen screening. Research laboratories can also provide samples for or generate high-quality host de novo reference genome assemblies and expand regional capacity for biobanking, including cell cultures, which will improve understanding of the co-evolutionary processes that underlie pathogen-host range and susceptibility. By giving more parties a stake in the effort, decentralization is more likely to succeed in garnering geographically representative participation that explicitly includes the most at-risk, under-resourced regions. [science.sciencemag.org/content/369/6500/145/suppl/DC1][16] 1. [↵][17]1. R. Lu et al ., Lancet 395, 565 (2020). [OpenUrl][18][CrossRef][19][PubMed][20] 2. [↵][21]1. X. Li et al ., J. Med. Virol. 6, 6 (2020). [OpenUrl][22] 3. [↵][23]1. K. G. Andersen, 2. A. Ram-baut, 3. W. I. Lipkin, 4. E. C. Holmes, 5. R. F. Garry , Nat. Med. 26, 450 (2020). [OpenUrl][24][CrossRef][25][PubMed][26] 4. [↵][27]1. M. E. J. Woolhouse et al ., Microbiol. Spectr. 1, 81 (2014). [OpenUrl][28] 5. [↵][29]1. K. E. Jones et al ., Nature 451, 990 (2008). [OpenUrl][30][CrossRef][31][PubMed][32][Web of Science][33] 6. [↵][34]1. L. Tensen , Glob. Ecol. Conserv. 6, 286 (2016). [OpenUrl][35] 7. [↵][36]1. S. E. Baker 1 , Bioscience 63, 928 (2013). [OpenUrl][37][CrossRef][38] 8. [↵][39]1. H.-J. Han et al ., Virus Res. 205, 1 (2015). [OpenUrl][40][CrossRef][41][PubMed][42] 9. [↵][43]1. B. Hu et al ., PLOS Pathog. 13, e1006698 (2017). [OpenUrl][44][CrossRef][45][PubMed][26] 10. [↵][46]1. H. Li et al ., Biosaf. Health 1, 84 (2019). [OpenUrl][47] 11. [↵][48]OIE, List of Laboratories; [www.oie.int/scientific-expertise/reference-laboratories/list-of-laboratories][49]. 12. [↵][50]1. M. 't Sas-Rolfes, 2. D. W. S. Challender, 3. A. Hinsley, 4. D. Veríssimo, 5. E. J. Milner-Gulland , Annu. Rev. Environ. Resour. 44, 201 (2019). [OpenUrl][51] 13. [↵][52]Oxford Nanopore Technologies, COVID-19: Community News; [www.nanoporetech.com/about-us/news/covid19-community][53]. 14. [↵][54]1. M. Watsa, 2. G. A. Erkenswick, 3. A. Pomerantz, 4. S. Prost , PLOS Biol. 18, e3000667 (2020). [OpenUrl][55][CrossRef][56] 15. [↵][57]1. C. K. Johnson et al ., Proc. Biol. Sci. 287, 20192736 (2020). [OpenUrl][58] [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-4 [5]: #ref-5 [6]: #ref-6 [7]: #ref-7 [8]: #ref-8 [9]: #ref-9 [10]: #ref-10 [11]: #ref-11 [12]: #ref-12 [13]: #ref-13 [14]: #ref-14 [15]: #ref-15 [16]: http://science.sciencemag.org/content/369/6500/145/suppl/DC1 [17]: #xref-ref-1-1 "View reference 1 in text" [18]: {openurl}?query=rft.jtitle%253DLancet%26rft.volume%253D395%26rft.spage%253D565%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS0140-6736%252820%2529302518%26rft_id%253Dinfo%253Apmid%252F32007145%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [19]: /lookup/external-ref?access_num=10.1016/S0140-6736(20)302518&link_type=DOI [20]: /lookup/external-ref?access_num=32007145&link_type=MED&atom=%2Fsci%2F369%2F6500%2F145.atom [21]: #xref-ref-2-1 "View reference 2 in text" [22]: {openurl}?query=rft.jtitle%253DJ.%2BMed.%2BVirol.%26rft.volume%253D6%26rft.spage%253D6%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [23]: #xref-ref-3-1 "View reference 3 in text" [24]: {openurl}?query=rft.jtitle%253DNat.%2BMed.%26rft.volume%253D26%26rft.spage%253D450%26rft_id%253Dinfo%253Adoi%252F10.1038%252Fs41591-020-0820-9%26rft_id%253Dinfo%253Apmid%252Fhttp%253A%252F%252Fwww.n%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [25]: /lookup/external-ref?access_num=10.1038/s41591-020-0820-9&link_type=DOI [26]: /lookup/external-ref?access_num=http://www.n&link_type=MED&atom=%2Fsci%2F369%2F6500%2F145.atom [27]: #xref-ref-4-1 "View reference 4 in text" [28]: {openurl}?query=rft.jtitle%253DMicrobiol.%2BSpectr.%26rft.volume%253D1%26rft.spage%253D81%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [29]: #xref-ref-5-1 "View reference 5 in text" [30]: {openurl}?query=rft.jtitle%253DNature%26rft.stitle%253DNature%26rft.aulast%253DJones%26rft.auinit1%253DK.%2BE.%26rft.volume%253D451%26rft.issue%253D7181%26rft.spage%253D990%26rft.epage%253D993%26rft.atitle%253DGlobal%2Btrends%2Bin%2Bemerging%2Binfectious%2Bdiseases.%26rft_id%253Dinfo%253Adoi%252F10.1038%252Fnature06536%26rft_id%253Dinfo%253Apmid%252F18288193%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [31]: /lookup/external-ref?access_num=10.1038/nature06536&link_type=DOI [32]: /lookup/external-ref?access_num=18288193&link_type=MED&atom=%2Fsci%2F369%2F6500%2F145.atom [33]: /lookup/external-ref?access_num=000253313100048&link_type=ISI [34]: #xref-ref-6-1 "View reference 6 in text" [35]: {openurl}?query=rft.jtitle%253DGlob.%2BEcol.%2BConserv.%26rft.volume%253D6%26rft.spage%253D286%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [36]: #xref-ref-7-1 "View reference 7 in text" [37]: {openurl}?query=rft.jtitle%253DBioscience%26rft_id%253Dinfo%253Adoi%252F10.1525%252Fbio.2013.63.12.6%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [38]: /lookup/external-ref?access_num=10.1525/bio.2013.63.12.6&link_type=DOI [39]: #xref-ref-8-1 "View reference 8 in text" [40]: {openurl}?query=rft.jtitle%253DVirus%2BRes.%26rft.volume%253D205%26rft.spage%253D1%26rft_id%253Dinfo%253Adoi%252F10.1016%252Fj.virusres.2015.05.006%26rft_id%253Dinfo%253Apmid%252F25997928%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [41]: /lookup/external-ref?access_num=10.1016/j.virusres.2015.05.006&link_type=DOI [42]: /lookup/external-ref?access_num=25997928&link_type=MED&atom=%2Fsci%2F369%2F6500%2F145.atom [43]: #xref-ref-9-1 "View reference 9 in text" [44]: {openurl}?query=rft.jtitle%253DPLOS%2BPathog.%26rft.volume%253D13%26rft.spage%253De1006698%26rft_id%253Dinfo%253Adoi%252F10.1371%252Fjournal.ppat.1006698%26rft_id%253Dinfo%253Apmid%252Fhttp%253A%252F%252Fwww.n%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [45]: /lookup/external-ref?access_num=10.1371/journal.ppat.1006698&link_type=DOI [46]: #xref-ref-10-1 "View reference 10 in text" [47]: {openurl}?query=rft.jtitle%253DBiosaf.%2BHealth%26rft.volume%253D1%26rft.spage%253D84%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [48]: #xref-ref-11-1 "View reference 11 in text" [49]: http://www.oie.int/scientific-expertise/reference-laboratories/list-of-laboratories [50]: #xref-ref-12-1 "View reference 12 in text" [51]: {openurl}?query=rft.jtitle%253DAnnu.%2BRev.%2BEnviron.%2BResour.%26rft.volume%253D44%26rft.spage%253D201%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [52]: #xref-ref-13-1 "View reference 13 in text" [53]: http://www.nanoporetech.com/about-us/news/covid19-community [54]: #xref-ref-14-1 "View reference 14 in text" [55]: {openurl}?query=rft.jtitle%253DPLOS%2BBiol.%26rft.volume%253D18%26rft.spage%253De3000667%26rft_id%253Dinfo%253Adoi%252F10.1371%252Fjournal.pbio.3000667%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [56]: /lookup/external-ref?access_num=10.1371/journal.pbio.3000667&link_type=DOI [57]: #xref-ref-15-1 "View reference 15 in text" [58]: {openurl}?query=rft.jtitle%253DProc.%2BBiol.%2BSci.%26rft.volume%253D287%26rft.spage%253D20192736%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx Science
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