Ranking the risk of animal-to-human spillover for newly discovered viruses.

The death toll and economic loss resulting from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic are stark reminders that we are vulnerable to zoonotic viral threats. Strategies are needed to identify and characterize animal viruses that pose the greatest risk of spillover and spread in humans and inform public health interventions. Using expert opinion and scientific evidence, we identified host, viral, and environmental risk factors contributing to zoonotic virus spillover and spread in humans. We then developed a risk ranking framework and interactive web tool, SpillOver, that estimates a risk score for wildlife-origin viruses, creating a comparative risk assessment of viruses with uncharacterized zoonotic spillover potential alongside those already known to be zoonotic. Using data from testing 509,721 samples from 74,635 animals as part of a virus discovery project and public records of virus detections around the world, we ranked the spillover potential of 887 wildlife viruses. Validating the risk assessment, the top 12 were known zoonotic viruses, including SARS-CoV-2. Several newly detected wildlife viruses ranked higher than known zoonotic viruses. Using a scientifically informed process, we capitalized on the recent wealth of virus discovery data to systematically identify and prioritize targets for investigation. The publicly accessible SpillOver platform can be used by policy makers and health scientists to inform research and public health interventions for prevention and rapid control of disease outbreaks. SpillOver is a living, interactive database that can be refined over time to continue to improve the quality and public availability of information on viral threats to human health.

Genomic Epidemiology and Management of Salmonella in Island Ecosystems Used for Takahe Conservation.

Translocation and isolation of threatened wildlife in new environments may have unforeseen consequences on pathogen transmission and evolution in host populations. Disease threats associated with intensive conservation management of wildlife remain speculative without gaining an understanding of pathogen dynamics in meta-populations and how location attributes may determine pathogen prevalence. We determined the prevalence and population structure of an opportunistic pathogen, Salmonella, in geographically isolated translocated sub-populations of an endangered New Zealand flightless bird, the takahe (Porphyrio hochstetteri). Out of the nine sub-populations tested, Salmonella was only isolated from takahe living on one private island. The apparent prevalence of Salmonella in takahe on the private island was 32% (95% CI 13-57%), with two serotypes, Salmonella Mississippi and Salmonella houtenae 40:gt-, identified. Epidemiological investigation of reservoirs on the private island and another island occupied by takahe identified environmental and reptile sources of S. Mississippi and S. houtenae 40:gt- on the private island. Single nucleotide polymorphism analysis of core genomes revealed low-level diversity among isolates belonging to the same serotype and little differentiation according to host and environmental source. The pattern observed may be representative of transmission between sympatric hosts and environmental sources, the presence of a common unsampled source, and/or evidence of a recent introduction into the ecosystem. This study highlights how genomic epidemiology can be used to ascertain and understand disease dynamics to inform the management of disease threats in endangered wildlife populations.

Microbial Genomics of a Host-Associated Commensal Bacterium in Fragmented Populations of Endangered Takahe.

Isolation of wildlife into fragmented populations as a consequence of anthropogenic-mediated environmental change may alter host-pathogen relationships. Our understanding of some of the epidemiological features of infectious disease in vulnerable populations can be enhanced by the use of commensal bacteria as a proxy for invasive pathogens in natural ecosystems. The distinctive population structure of a well-described meta-population of a New Zealand endangered flightless bird, the takahe (Porphyrio hochstetteri), provided a unique opportunity to investigate the influence of host isolation on enteric microbial diversity. The genomic epidemiology of a prevalent rail-associated endemic commensal bacterium was explored using core genome and ribosomal multilocus sequence typing (rMLST) of 70 Campylobacter sp. nova 1 isolated from one third of the takahe population resident in multiple locations. While there was evidence of recombination between lineages, bacterial divergence appears to have occurred and multivariate analysis of 52 rMLST genes revealed location-associated differentiation of C. sp. nova 1 sequence types. Our results indicate that fragmentation and anthropogenic manipulation of populations can influence host-microbial relationships, with potential implications for niche adaptation and the evolution of micro-organisms in remote environments. This study provides a novel framework in which to explore the complex genomic epidemiology of micro-organisms in wildlife populations.

Using a common commensal bacterium in endangered Takahe as a model to explore pathogen dynamics in isolated wildlife populations.

Predicting and preventing outbreaks of infectious disease in endangered wildlife is problematic without an understanding of the biotic and abiotic factors that influence pathogen transmission and the genetic variation of microorganisms within and between these highly modified host communities. We used a common commensal bacterium, Campylobacter spp., in endangered Takahe (Porphyrio hochstetteri) populations to develop a model with which to study pathogen dynamics in isolated wildlife populations connected through ongoing translocations. Takahe are endemic to New Zealand, where their total population is approximately 230 individuals. Takahe were translocated from a single remnant wild population to multiple offshore and mainland reserves. Several fragmented subpopulations are maintained and connected through regular translocations. We tested 118 Takahe from 8 locations for fecal Campylobacter spp. via culture and DNA extraction and used PCR for species assignment. Factors relating to population connectivity and host life history were explored using multivariate analytical methods to determine associations between host variables and bacterial prevalence. The apparent prevalence of Campylobacter spp. in Takahe was 99%, one of the highest reported in avian populations. Variation in prevalence was evident among Campylobacter species identified. C. sp. nova 1 (90%) colonized the majority of Takahe tested. Prevalence of C. jejuni (38%) and C. coli (24%) was different between Takahe subpopulations, and this difference was associated with factors related to population management, captivity, rearing environment, and the presence of agricultural practices in the location in which birds were sampled. Modeling results of Campylobacter spp. in Takahe metapopulations suggest that anthropogenic management of endangered species within altered environments may have unforeseen effects on microbial exposure, carriage, and disease risk. Translocation of wildlife between locations could have unpredictable consequences including the spread of novel microbes between isolated populations.

Network analysis of translocated Takahe populations to identify disease surveillance targets.

Social network analysis is being increasingly used in epidemiology and disease modeling in humans, domestic animals, and wildlife. We investigated this tool in describing a translocation network (area that allows movement of animals between geographically isolated locations) used for the conservation of an endangered flightless rail, the Takahe (Porphyrio hochstetteri). We collated records of Takahe translocations within New Zealand and used social network principles to describe the connectivity of the translocation network. That is, networks were constructed and analyzed using adjacency matrices with values based on the tie weights between nodes. Five annual network matrices were created using the Takahe data set, each incremental year included records of previous years. Weights of movements between connected locations were assigned by the number of Takahe moved. We calculated the number of nodes (i(total)) and the number of ties (t(total)) between the nodes. To quantify the small-world character of the networks, we compared the real networks to random graphs of the equivalent size, weighting, and node strength. Descriptive analysis of cumulative annual Takahe movement networks involved determination of node-level characteristics, including centrality descriptors of relevance to disease modeling such as weighted measures of in degree (k(i)(in)), out degree (k(i)(out)), and betweenness (B(i)). Key players were assigned according to the highest node measure of k(i)(in), k(i)(out), and B(i) per network. Networks increased in size throughout the time frame considered. The network had some degree small-world characteristics. Nodes with the highest cumulative tie weights connecting them were the captive breeding center, the Murchison Mountains and 2 offshore islands. The key player fluctuated between the captive breeding center and the Murchison Mountains. The cumulative networks identified the captive breeding center every year as the hub of the network until the final network in 2011. Likewise, the wild Murchison Mountains population was consistently the sink of the network. Other nodes, such as the offshore islands and the wildlife hospital, varied in importance over time. Common network descriptors and measures of centrality identified key locations for targeting disease surveillance. The visual representation of movements of animals in a population that this technique provides can aid decision makers when they evaluate translocation proposals or attempt to control a disease outbreak.