Improved surveillance for early detection of a potential invasive species: the alien Rose-ringed parakeet <Emphasis Type="Italic">Psittacula krameri</Emphasis> in Australia

The Rose-ringed parakeet Psittacula krameri is the most widely introduced parrot in the world, and is an important agricultural pest and competitor with native wildlife. In Australia, it is classified as an ‘extreme threat’, yet captive individuals frequently escape into the wild. The distribution and frequency of incursions are currently unknown, as are the potential impacts of the species in Australia. This lack of critical ecological information greatly limits effective biosecurity surveillance and decision-making efforts. We compiled a unique dataset, which combined passive surveillance sources from government and online resources, for all available information on parakeet detections at-large in Australia. We investigated whether geographic variables successfully predicted parakeet incursions, and used species distribution models to assess the potential distribution and economic impacts on agricultural assets. We recorded 864 incursions for the period 1999–2013; mostly escaped birds reported to missing animal websites. Escapes were reported most frequently within, or around, large cities. Incursions were best predicted by factors related to human presence and activity, such as global human footprint and intensive land uses. We recommend surveillance of high (predicted) establishment areas adjacent to cities where a feral parakeet population could most affect horticultural production. Novel passive surveillance datasets combined with species distribution models can be used to identify the regions where potential invasive species are most likely to establish. Subsequently, active surveillance can be targeted to the areas of highest predicted potential risk. We recommend an integrated approach that includes outreach programs involving local communities, as well as traditional biosecurity surveillance, for detecting new incursions.     

The community ecology of pathogens: coinfection,coexistence and community composition

Disease and community ecology share conceptual and theoretical lineages, and there has been a resurgence of interest in strengthening links between these fields. Building on recent syntheses focused on the effects of host community composition on single pathogen systems, we examine pathogen (microparasite) communities using a stochastic metacommunity model as a starting point to bridge community and disease ecology perspectives. Such models incorporate the effects of core community processes, such as ecological drift, selection and dispersal, but have not been extended to incorporate host–pathogen interactions, such as immunosuppression or synergistic mortality, that are central to disease ecology. We use a two‐pathogen susceptible‐infected (SI) model to fill these gaps in the metacommunity approach; however, SI models can be intractable for examining species‐diverse, spatially structured systems. By placing disease into a framework developed for community ecology, our synthesis highlights areas ripe for progress, including a theoretical framework that incorporates host dynamics, spatial structuring and evolutionary processes, as well as the data needed to test the predictions of such a model. Our synthesis points the way for this framework and demonstrates that a deeper understanding of pathogen community dynamics will emerge from approaches working at the interface of disease and community ecology.     

Patterns of infection,origins, and transmission of ranaviruses among the ectothermic vertebrates of Asia

Ranaviral infections, a malady of ectothermic vertebrates, are becoming frequent, severe, and widespread, causing mortality among both wild and cultured species, raising odds of species extinctions and economic losses. This increase in infection is possibly due to the broad host range of ranaviruses and the transmission of these pathogens through regional and international trade in Asia, where outbreaks have been increasingly reported over the past decade. Here, we focus attention on the origins, means of transmission, and patterns of spread of this infection within the region. Infections have been recorded in both cultured and wild populations in at least nine countries/administrative regions, together with mass die‐offs in some regions. Despite the imminent seriousness of the disease in Asia, surveillance efforts are still incipient. Some of the viral strains within Asia may transmit across host–taxon barriers, posing a significant risk to native species. Factors such as rising temperatures due to global climate change seem to exacerbate ranaviral activity, as most known outbreaks have been recorded during summer; however, data are still inadequate to verify this pattern for Asia. Import risk analysis, using protocols such as Pandora+, pre‐border pathogen screening, and effective biosecurity measures, can be used to mitigate introduction of ranaviruses to uninfected areas and curb transmission within Asia. Comprehensive surveillance using molecular diagnostic tools for ranavirus species and variants will help in understanding the prevalence and disease burden in the region. This is an important step toward conserving native biodiversity and safeguarding the aquaculture industry.     

Abundance and detection of feral cats decreases after severe fire on Kangaroo Island,Australia

Predation by feral cats (Felis catus) has caused the extinction of many native species in Australia and globally. There is growing evidence that the impacts of feral cats can be amplified in post-fire environments, as cats are drawn to hunt in or around recently burnt areas and are also more effective hunters in open habitats. In 2018–2019, we established arrays of camera traps to estimate the abundance of feral cats on Kangaroo Island, South Australia. Much of the island (including five of our seven survey sites) was subsequently burnt in a severe wildfire (December 2019–February 2020). We re-sampled the sites 3–8 months post-fire (seven sites) and 11–12 months post-fire (three sites). At two unburnt sites sampled post-fire, it was possible to produce density estimates of cats using a spatially explicit capture–recapture approach. Where estimating density was not possible (due to low detections or individual cats not being distinguishable), the number of individuals and percentage of trap nights with detections was compared between the sampling periods. Some low-level cat control occurred within 2 km of three of the seven arrays (all within the burn scar) within 3 months of the fire. Across the five burnt sites, there was a decline in cat detections post-fire (including those without post-fire cat control). At 3–8 months post-fire, there was, on average, a 57% reduction in the number of individual cats, and a 65% reduction in the number of nights with cat detections, relative to pre-fire levels. Although cat detections declined following the fire, reduced population sizes of prey species and reduced cover as a result of the fire might still mean that cat predation is a threat to some surviving prey species. Management that reduces feral cat predation pressure on wildlife following wildfire should enhance the likelihood of post-fire wildlife persistence and recovery.     

Using ecological stoichiometry to understand and predict infectious diseases

A key characteristic of host–parasite interactions is the theft of host nutrients by the parasite, yet we lack a general framework for understanding and predicting the interplay of host and parasite nutrition that applies across biological levels of organization. The elemental nutrients (C, N, P, Fe, etc.), and ecological stoichiometry provide a framework for understanding host–parasite interactions and their relation to ecosystem functioning. Here we use the ecological stoichiometry framework to develop hypotheses and predictions regarding the relationship between elemental nutrients and host–parasite interactions. We predict that a suite of host and parasite traits, stoichiometric homeostasis, host diet stoichiometry, and biogeochemical cycling are related to disease dynamics, host immunity and resistance, and bacterial growth form determination. We show that ecological stoichiometry is capable of expanding our understanding of host–parasite interactions, and complementing other approaches such as population and community ecology, and molecular biology, for studying infectious diseases.     

Local adaptation of a parasite to solar radiation impacts disease transmission potential,spore yield,and host fecundity*

Environmentally transmitted parasites spend time in the abiotic environment, where they are subjected to a variety of stressors. Learning how they face this challenge is essential if we are to understand how host–parasite interactions may vary across environmental gradients. We used a zooplankton–bacteria host–parasite system where availability of sunlight (solar radiation) influences disease dynamics to look for evidence of parasite local adaptation to sunlight exposure. We also examined how variation in sunlight tolerance among parasite strains impacted host reproduction. Parasite strains collected from clearer lakes (with greater sunlight penetration) were most tolerant of the negative impacts of sunlight exposure, suggesting local adaptation to sunlight conditions. This adaptation came with both a cost and a benefit for parasites: parasite strains from clearer lakes produced relatively fewer transmission stages (spores) but these strains were more infective. After experimental sunlight exposure, the most sunlight-tolerant parasite strains reduced host fecundity just as much as spores that were never exposed to sunlight. Sunlight availability varies greatly among lakes around the world. Our results suggest that the selective pressure sunlight exposure exerts on parasites may impact both parasite and host fitness, potentially driving variation in disease epidemics and host population dynamics across sunlight availability gradients.     

A sensitive environmental DNA (eDNA) assay leads to new insights on Ruffe (<Emphasis Type="Italic">Gymnocephalus cernua</Emphasis>) spread in North America

Detection of invasive species before or soon after they establish in novel environments is critical to prevent widespread ecological and economic impacts. Environmental DNA (eDNA) surveillance and monitoring is an approach to improve early detection efforts. Here we describe a large-scale conservation application of a quantitative polymerase chain reaction assay with a case study for surveillance of a federally listed nuisance species (Ruffe, Gymnocephalus cernua) in the Laurentian Great Lakes. Using current Ruffe distribution data and predictions of future Ruffe spread derived from a recently developed model of ballast-mediated dispersal in US waters of the Great Lakes, we designed an eDNA surveillance study to target Ruffe at the putative leading edge of the invasion. We report a much more advanced invasion front for Ruffe than has been indicated by conventional surveillance methods and we quantify rates of false negative detections (i.e. failure to detect DNA when it is present in a sample). Our results highlight the important role of eDNA surveillance as a sensitive tool to improve early detection efforts for aquatic invasive species and draw attention to the need for an improved understanding of detection errors. Based on axes that reflect the weight of eDNA evidence of species presence and the likelihood of secondary spread, we suggest a two-dimensional conceptual model that management agencies might find useful in considering responses to eDNA detections.     

Many eyes on the ground: citizen science is an effective early detection tool for biosecurity

Early detection of target non-indigenous species is one of the most important determinants of a successful eradication campaign. For early detection to be successful, and provide the highest probability of achieving eradication, intense surveillance is often required that can involve significant resources. Volunteer based monitoring or “citizen science” is one potential tool to address this problem. This study differs from standard citizen science projects because the participants are personnel or contractors of a company working on Barrow Island, Western Australia. We show that personnel can contribute successfully to a surveillance program aimed at detecting a broad taxonomic range of non-indigenous vertebrate and invertebrate species. Using data collected over a five year surveillance period on Barrow Island, we show that eighteen of the nineteen (95%) non-indigenous invertebrate species new to the island were detected by personnel working on the island, and that the number of detections made by these workers was significantly related to the number of personnel on the island at any one time. Most personnel detections (91%) were made inside buildings where the majority of active surveillance tools could not be implemented. For vertebrates, 4 NIS species detections (100% of detections) were made in the built environment by personnel. Although reporting of suspect non-indigenous species is voluntary, personnel are required to attend inductions and toolboxes where reporting of suspect biosecurity risk material is encouraged. These results demonstrate the value of industry led ‘citizen science’ programs, resulting in sustained stewardship and conservation of areas with high environmental value.     

The use of biomarkers in surveillance, medical screening, and intervention

Building on mechanistic information, much of molecular epidemiologic research has focused on validating biomarkers, that is, assessing their ability to accurately indicate exposure, effect, disease, or susceptibility. To be of use in surveillance, medical screening, or interventions, biomarkers must already be validated so that they can be used as outcomes or indicators that can serve a particular function. In surveillance, biomarkers can be used as indicators of hazard, exposure, disease, and population risk. However, to obtain rates for these measures, the population at risk will need to be assessed. In medical screening, biomarkers can serve as early indicators of disease in asymptomatic people. This allows for the identification of those who should receive diagnostic confirmation and early treatment. In intervention (which includes risk assessment and communication, risk management, and various prevention efforts), biomarkers can be used to assess the effectiveness of a prevention or control strategy as well as help determine whether the appropriate individuals are assigned to the correct intervention category. Biomarkers can be used to provide group and individual risk assessments that can be the basis for marshalling resources. Critical for using biomarkers in surveillance, medical screening, and intervention is the justification that the biomarkers can provide information not otherwise accessible by a less expensive and easier-to-obtain source of information, such as medical records, surveys, or vital statistics. The ability to use validated biomarkers in surveillance, medical screening, and intervention will depend on the extent to which a strategy for evidence-based procedures for biomarker knowledge transfer can be developed and implemented. This will require the interaction of researchers and decision-makers to collaborate on public health and medical issues.     

Inferring infection hazard in wildlife populations by linking data across individual and population scales

Our ability to infer unobservable disease‐dynamic processes such as force of infection (infection hazard for susceptible hosts) has transformed our understanding of disease transmission mechanisms and capacity to predict disease dynamics. Conventional methods for inferring FOI estimate a time‐averaged value and are based on population‐level processes. Because many pathogens exhibit epidemic cycling and FOI is the result of processes acting across the scales of individuals and populations, a flexible framework that extends to epidemic dynamics and links within‐host processes to FOI is needed. Specifically, within‐host antibody kinetics in wildlife hosts can be short‐lived and produce patterns that are repeatable across individuals, suggesting individual‐level antibody concentrations could be used to infer time since infection and hence FOI. Using simulations and case studies (influenza A in lesser snow geese and Yersinia pestis in coyotes), we argue that with careful experimental and surveillance design, the population‐level FOI signal can be recovered from individual‐level antibody kinetics, despite substantial individual‐level variation. In addition to improving inference, the cross‐scale quantitative antibody approach we describe can reveal insights into drivers of individual‐based variation in disease response, and the role of poorly understood processes such as secondary infections, in population‐level dynamics of disease.     

Influenza type A in humans,mammals and birds: determinants of virus virulence,host-range and interspecies transmission

The virulence of a virus is determined by its ability to adversely affect the host cell, host organism or population of host organisms. Influenza A viruses have been responsible for four pandemics of severe human respiratory disease this century. Avian species harbour a large reservoir of influenza virus strains, which can contribute genes to potential new pandemic human strains. The fundamental importance of understanding the role of each of these genes in determining virulence in birds and humans was dramatically emphasised by the recent direct transmission of avian influenza A viruses to humans, causing fatal infection but not community spread. An understanding of the factors involved in transmission between avian and mammalian species should assist in the development of better surveillance strategies for early recognition of influenza A virus strains having human pandemic potential, and possibly in the design of anti-viral strategies.     

Landscape genetics and the spatial distribution of chronic wasting disease

Predicting the spread of wildlife disease is critical for identifying populations at risk, targeting surveillance and designing proactive management programmes. We used a landscape genetics approach to identify landscape features that influenced gene flow and the distribution of chronic wasting disease (CWD) in Wisconsin white-tailed deer. CWD prevalence was negatively correlated with genetic differentiation of study area deer from deer in the area of disease origin (core-area). Genetic differentiation was greatest, and CWD prevalence lowest, in areas separated from the core-area by the Wisconsin River, indicating that this river reduced deer gene flow and probably disease spread. Features of the landscape that influence host dispersal and spatial patterns of disease can be identified based on host spatial genetic structure. Landscape genetics may be used to predict high-risk populations based on their genetic connection to infected populations and to target disease surveillance, control and preventative activities.     

Pathogen genomic surveillance elucidates the origins,transmission and evolution of emerging viral agents in China

In the past twenty years, numerous novel zoonotic viral agents with pandemic potential have emerged in China, such as the severe acute respiratory syndrome (SARS) coronavirus and, more recently, the avian-origin influenza A/H7N9 virus, which have caused outbreaks among humans with high morbidity and mortality. In addition, several emerging and re-emerging viral pathogens have also been imported into China from travelers, e.g. the Middle East respiratory syndrome (MERS) coronavirus and Zika virus (ZIKV). Herein, we review these emerging viral pathogens in China and focus on how surveillance by pathogen genomics has been employed to discover and annotate novel pathogenic agents, identify natural reservoirs, monitor the transmission events and delineate their evolution and adaption to the human host. We also highlight the application of genomic sequencing in the recent Ebola epidemics in Western Africa. In summary, genomic sequencing has become a standard research tool in the field of emerging infectious diseases which has been proven invaluable in containing these viral infections and reducing burden of disease in humans and animals. Genomic surveillance of pathogenic agents will serve as a key epidemiological and research tool in the modern era of precision infectious diseases and in the future studies of virosphere.     

Investigation of the genotype III to genotype I shift in Japanese encephalitis virus and the impact on human cases

Japanese encephalitis is a mosquito borne disease and is the leading cause of viral encephalitis in the Asia-Pacific area. The causative agent, Japanese encephalitis virus(JEV) can be phylogenetically classified into five genotypes based on nucleotide sequence. In recent years, genotype I(GI) has displaced genotype III(GIII) as the dominant lineage, but the mechanisms behind this displacement event requires elucidation. In an earlier study, we compared host variation over time between the two genotypes and observed that GI appears to have evolved to achieve more efficient infection in hosts in the replication cycle, with the tradeoff of reduced infectivity in secondary hosts such as humans. To further investigate this phenomenon, we collected JEV surveillance data on human cases and, together with sequence data, and generated genotype/case profiles from seven Asia-Pacific countries and regions to characterize the GI/GIII displacement event. We found that, when comprehensive and consistent vaccination and surveillance data was available, and the GIII to GI shift occurred within a well-defined time period, there was a statistically significant drop in JEV human cases. Our findings provide further support for the argument that GI is less effective in infecting humans, who represent a dead end host. However, experimental investigation is necessary to confirm this hypothesis. The study highlights the value of alternative approaches to investigation of epidemics, as well as the importance of effective data collection for disease surveillance and control.     

Identifying genetic markers of adaptation for surveillance of viral host jumps

Adaptation is often thought to affect the likelihood that a virus will be able to successfully emerge in a new host species. If so, surveillance for genetic markers of adaptation could help to predict the risk of disease emergence. However, adaptation is difficult to distinguish conclusively from the other processes that generate genetic change. In this Review we survey the research on the host jumps of influenza A, severe acute respiratory syndrome-coronavirus, canine parvovirus and Venezuelan equine encephalitis virus to illustrate the insights that can arise from combining genetic surveillance with microbiological experimentation in the context of epidemiological data. We argue that using a multidisciplinary approach for surveillance will provide a better understanding of when adaptations are required for host jumps and thus when predictive genetic markers may be present.     

Systems Approaches to Animal Disease Surveillance and Resource Allocation: Methodological Frameworks for Behavioral Analysis

While demands for animal disease surveillance systems are growing, there has been little applied research that has examined the interactions between resource allocation, cost-effectiveness, and behavioral considerations of actors throughout the livestock supply chain in a surveillance system context. These interactions are important as feedbacks between surveillance decisions and disease evolution may be modulated by their contextual drivers, influencing the cost-effectiveness of a given surveillance system. This paper identifies a number of key behavioral aspects involved in animal health surveillance systems and reviews some novel methodologies for their analysis. A generic framework for analysis is discussed, with exemplar results provided to demonstrate the utility of such an approach in guiding better disease control and surveillance decisions.     

Use of non‐island,shallow nearshore beach environments by Gulf Sturgeon (Acipenser oxyrinchus desotoi) within the Mississippi Sound,USA

Large sub‐adult/adult western population Gulf Sturgeon move to barrier islands in winter to feed whereas eastern fish move offshore or to nearshore non‐island environments; most small sub‐adults/juveniles remain in the estuarine system during winter. To test this, we used an acoustic data set deployed around the Port of Gulfport (hereafter Port footprint, east gate, west gate) within Mississippi Sound. We documented between three and six fish on each receiver totaling 12,285 detections for all 19 receivers between September 2012–May 2013. Only 30% of fish had both a high number of overall detections and a high number of detection days. In contrast, from October 2013–May 2014, between three and nine fish were detected on each receiver but with only 2,371 detections. Five fish (29.4%) had a high number of detections but a reduced number of detection days in the acoustic array; all fish appeared to be transients. Adults, unexpectedly, had the most prevalent occurrence and number of detection days in these shallow, non‐island beach environments contrary to our initial hypothesis. Our data suggests annually variable, regional‐scale use of beach environments not associated with barrier islands that likely serve as a travel corridor between drainages/offshore barrier islands, or as feeding zones; these movements may enhance the potential for mortality in Mississippi Sound.     

Emergence, spread, persistence and fade-out of sylvatic plague in Kazakhstan

Predicting the dynamics of zoonoses in wildlife is important not only for prevention of transmission to humans, but also for improving the general understanding of epidemiological processes. A large dataset on sylvatic plague in the Pre-Balkhash area of Kazakhstan (collected for surveillance purposes) provides a rare opportunity for detailed statistical modelling of an infectious disease. Previous work using these data has revealed a host abundance threshold for epizootics, and climatic influences on plague prevalence. Here, we present a model describing the local space-time dynamics of the disease at a spatial scale of 20 × 20 km(2) and a biannual temporal scale, distinguishing between invasion and persistence events. We used a Bayesian imputation method to account for uncertainties resulting from poor data in explanatory variables and response variables. Spatial autocorrelation in the data was accounted for in imputations and analyses through random effects. The results show (i) a clear effect of spatial transmission, (ii) a high probability of persistence compared with invasion, and (iii) a stronger influence of rodent abundance on invasion than on persistence. In particular, there was a substantial probability of persistence also at low host abundance.