Development of hazard site surveillance programs for forest invasive species: A case study from Brisbane, Australia

Hazard site surveillance is a system for post-border detection of new pest incursions, targeting sites that are considered potentially at high risk of such introductions. Globalisation, increased volumes of containerised freight and competition for space at domestic ports means that goods are increasingly being first opened at premises some distance from the port of entry, thus dispersing risk away from the main inspection point. Hazard site surveillance acts as a backstop to border control to ensure that new incursions are detected sufficiently early to allow the full range of management options, including eradication and containment, to be considered. This is particularly important for some of the more cryptic forest pests whose presence in a forest often is not discovered until populations are already high and the pest is well established. General requirements for a hazard site surveillance program are discussed using a program developed in Brisbane, Australia, in 2006 as a case study. Some early results from the Brisbane program are presented. In total 67 species and 5757 individuals of wood-boring beetles have been trapped and identified during the program to date. Scolytines are the most abundant taxa, making up 83% of the catch. No new exotics have been trapped but 19 of the species and 60% of all specimens caught are exotics that are already established in Australia.

Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.

Surveillance protocols for management of invasive plants: modelling Chilean needle grass (Nassella neesiana) in Australia

Aim: To develop a surveillance support model that enables prediction of areas susceptible to invasion, comparative analysis of surveillance methods and intensity and assessment of eradication feasibility. To apply the model to identify surveillance protocols for generalized invasion scenarios and for evaluating surveillance and control for a context-specific plant invasion. Location: Australia. Methods: We integrate a spatially explicit simulation model, including plant demography and dispersal vectors, within a Geographical Information System. We use the model to identify effective surveillance protocols using simulations of generalized plant life-forms spreading via different dispersal mechanisms in real landscapes. We then parameterize the surveillance support model for Chilean needle grass [CNG; Nassella neesiana (Trin. & Rupr.) Barkworth], a highly invasive tussock grass, which is an eradication target in south-eastern Queensland, Australia. Results: General surveillance protocols that can guide rapid response surveillance were identified; suitable habitat that is susceptible to invasion through particular dispersal syndromes should be targeted for surveillance using an adaptive seek-and-destroy method. The search radius of the adaptive method should be based on maximum expected dispersal distances. Protocols were used to define a surveillance strategy for CNG, but simulations indicated that despite effective and targeted surveillance, eradication is implausible at current intensities. Main conclusions: Several important surveillance protocols emerged and simulations indicated that effectiveness can be increased if they are followed in rapid response surveillance. If sufficient data are available, the surveillance support model should be parameterized to target areas susceptible to invasion and determine whether surveillance is effective and eradication is feasible. We discovered that for CNG, regardless of a carefully designed surveillance strategy, eradication is implausible at current intensities of surveillance and control and these efforts should be doubled if they are to be successful. This is crucial information in the face of environmentally and economically damaging invasive species and large, expensive and potentially ineffective control programmes.

Indicators of wellbeing in recreational video game players

Video game play is a popular entertainment choice, yet we have a limited understanding of the potential wellbeing benefits associated with recreational play. An online survey (final sample, n = 297) addresses this by investigating how the player experience related to wellbeing. The impact of amount of play, game genre, mode of play (social or solitary play) and the psychological experience of play (flow and need satisfaction) on a multi-dimensional measure of wellbeing (emotional, psychological and social) was examined via hierarchical regression. Age, gender, the play of casual games compared to shooters, and in-game experiences of flow, autonomy and relatedness were associated with increases in dimensions of wellbeing.

Discovering urban citizenship in the surveillance society

Cities and urban spaces around the world are changing rapidly from their origins in the industrialising world to a post-industrial, hard wired landscape. A further embellishment is the advent of mobile media technologies supported by both existing and new communications and computing technology which claim to put the urban dweller at the heart of a new, informed and ‘liberated’ seat of participatory urban governance. This networked, sensor enabled society permits flows of information in a multitude of directions ostensibly empowering the citizenry through ‘smart’ installations such as ‘talking bus stops’ detailing services, delays, transport interconnections and even weather conditions along desired routes. However, while there is considerable potential for creative and transformative kinds of citizen participation, there is also the momentum for ‘function-creep’, whereby vast amounts of data are garnered in a broad application of urban surveillance. This kind of monitoring and capacity for surveillance connects with attempts by civic authorities to regulate, restrict, rebrand and reframe urban public spaces into governable and predictable arenas of consumption. This article considers questions around the possibilities for retaining and revitalising forms of urban citizenship, set in the context of Marshall’s original premise of civil, social and political citizenship(s) in the middle of the last century, following World War Two and the coming of the modern welfare state.

Surveillance and monitoring for endemic and exotic virus diseases of cotton

The aims of this project will provide capacity in virology expertise to help protect Australian cotton from virus diseases including both existing and those that pose significant biosecurity threats. This project will also provide continued capacity in virology to support the cotton industry.

CRC30032 Enhancing surveillance with remotely controlled aircraft

Detecting spores with UAV.

Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions

Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.

Risk-based surveillance for avian influenza control along poultry market chains in South China: The value of social network analysis.

Over the past two decades, the poultry sector in China went through a phase of tremendous growth as well as rapid intensification and concentration. Highly pathogenic avian influenza virus (HPAIV) subtype H5N1 was first detected in 1996 in Guangdong province, South China and started spreading throughout Asia in early 2004. Since then, control of the disease in China has relied heavily on wide-scale preventive vaccination combined with movement control, quarantine and stamping out. This strategy has been successful in drastically reducing the number of outbreaks during the past 5 years. However, HPAIV H5N1 is still circulating and is regularly isolated in traditional live bird markets (LBMs) where viral infection can persist, which represent a public health hazard for people visiting them. The use of social network analysis in combination with epidemiological surveillance in South China has identified areas where the success of current strategies for HPAI control in the poultry production sector may benefit from better knowledge of poultry trading patterns and the LBM network configuration as well as their capacity for maintaining HPAIV H5N1 infection. We produced a set of LBM network maps and estimated the associated risk of HPAIV H5N1 within LBMs and along poultry market chains, providing new insights into how live poultry trade and infection are intertwined. More specifically, our study provides evidence that several biosecurity factors such as daily cage cleaning, daily cage disinfection or manure processing contribute to a reduction in HPAIV H5N1 presence in LBMs. Of significant importance is that the results of our study also show the association between social network indicators and the presence of HPAIV H5N1 in specific network configurations such as the one represented by the counties of origin of the birds traded in LBMs. This new information could be used to develop more targeted and effective control interventions.

Real-time PCR as a surveillance tool for the detection of Trichinella infection in muscle samples from wildlife

Trichinella nematodes are the causative agent of trichinellosis, a meat-borne zoonosis acquired by consuming undercooked, infected meat. Although most human infections are sourced from the domestic environment, the majority of Trichinella parasites circulate in the natural environment in carnivorous and scavenging wildlife. Surveillance using reliable and accurate diagnostic tools to detect Trichinella parasites in wildlife hosts is necessary to evaluate the prevalence and risk of transmission from wildlife to humans. Real-time PCR assays have previously been developed for the detection of European Trichinella species in commercial pork and wild fox muscle samples. We have expanded on the use of real-time PCR in Trichinella detection by developing an improved extraction method and SYBR green assay that detects all known Trichinella species in muscle samples from a greater variety of wildlife. We simulated low-level Trichinella infections in wild pig, fox, saltwater crocodile, wild cat and a native Australian marsupial using Trichinella pseudospiralis or Trichinella papuae ethanol-fixed larvae. Trichinella-specific primers targeted a conserved region of the small subunit of the ribosomal RNA and were tested for specificity against host and other parasite genomic DNAs. The analytical sensitivity of the assay was at least 100 fg using pure genomic T. pseudospiralis DNA serially diluted in water. The diagnostic sensitivity of the assay was evaluated by spiking log of each host muscle with T. pseudospiralis or T. papuae larvae at representative infections of 1.0, 0.5 and 0.1 larvae per gram, and shown to detect larvae at the lowest infection rate. A field sample evaluation on naturally infected muscle samples of wild pigs and Tasmanian devils showed complete agreement with the EU reference artificial digestion method (k-value = 1.00). Positive amplification of mouse tissue experimentally infected with T. spiralis indicated the assay could also be used on encapsulated species in situ. This real-time PCR assay offers an alternative highly specific and sensitive diagnostic method for use in Trichinella wildlife surveillance and could be adapted to wildlife hosts of any region. (C) 2012 Elsevier B.V. All rights reserved.

Evaluation of ELISA coupled with Western blot as a surveillance tool for Trichinella infection in wild boar (Sus scrofa)

Trichinella surveillance in wildlife relies on muscle digestion of large samples which are logistically difficult to store and transport in remote and tropical regions as well as labour-intensive to process. Serological methods such as enzyme-linked immunosorbent assays (ELISAs) offer rapid, cost-effective alternatives for surveillance but should be paired with additional tests because of the high false-positive rates encountered in wildlife. We investigated the utility of ELISAs coupled with Western blot (WB) in providing evidence of Trichinella exposure or infection in wild boar. Serum samples were collected from 673 wild boar from a high- and low-risk region for Trichinella introduction within mainland Australia, which is considered Trichinella-free. Sera were examined using both an 'in-house' and a commercially available indirect-ELISA that used excretory secretory (E/S) antigens. Cut-off values for positive results were determined using sera from the low-risk population. All wild boar from the high-risk region (352) and 139/321 (43.3%) of the wild boar from the low-risk region were tested by artificial digestion. Testing by Western blot using E/S antigens, and a Trichinella-specific real-time PCR was also carried out on all ELISA-positive samples. The two ELISAs correctly classified all positive controls as well as one naturally infected wild boar from Gabba Island in the Torres Strait. In both the high- and low-risk populations, the ELISA results showed substantial agreement (k-value = 0.66) that increased to very good (k-value = 0.82) when WB-positive only samples were compared. The results of testing sera collected from the Australian mainland showed the Trichinella seroprevalence was 3.5% (95% C.I. 0.0-8.0) and 2.3% (95% C.I. 0.0-5.6) using the in-house and commercial ELISA coupled with WB respectively. These estimates were significantly higher (P < 0.05) than the artificial digestion estimate of 0.0% (95% C.I. 0.0-1.1). Real-time PCR testing of muscle from seropositive animals did not detect Trichinella DNA in any mainland animals, but did reveal the presence of a second larvae-positive wild boar on Gabba Island, supporting its utility as an alternative, highly sensitive method in muscle examination. The serology results suggest Australian wildlife may have been exposed to Trichinella parasites. However, because of the possibility of non-specific reactions with other parasitic infections, more work using well-defined cohorts of positive and negative samples is required. Even if the specificity of the ELISAs is proven to be low, their ability to correctly classify the small number of true positive sera in this study indicates utility in screening wild boar populations for reactive sera which can be followed up with additional testing. (C) 2013 Elsevier B.V. All rights reserved.

Applications of a sugar-based surveillance system to track arboviruses in wild mosquito populations

Effective arbovirus surveillance is essential to ensure the implementation of control strategies, such as mosquito suppression, vaccination, or dissemination of public warnings. Traditional strategies employed for arbovirus surveillance, such as detection of virus or virus-specific antibodies in sentinel animals, or detection of virus in hematophagous arthropods, have limitations as an early-warning system. A system was recently developed that involves collecting mosquitoes in CO2-baited traps, where the insects expectorate virus on sugar-baited nucleic acid preservation cards. The cards are then submitted for virus detection using molecular assays. We report the application of this system for detecting flaviviruses and alphaviruses in wild mosquito populations in northern Australia. This study was the first to employ nonpowered passive box traps (PBTs) that were designed to house cards baited with honey as the sugar source. Overall, 20/144 (13.9%) of PBTs from different weeks contained at least one virus-positive card. West Nile virus Kunjin subtype (WNVKUN), Ross River virus (RRV), and Barmah Forest virus (BFV) were detected, being identified in 13/20, 5/20, and 2/20 of positive PBTs, respectively. Importantly, sentinel chickens deployed to detect flavivirus activity did not seroconvert at two Northern Territory sites where four PBTs yielded WNVKUN. Sufficient WNVKUN and RRV RNA was expectorated onto some of the honey-soaked cards to provide a template for gene sequencing, enhancing the utility of the sugar-bait surveillance system for investigating the ecology, emergence, and movement of arboviruses. © 2014, Mary Ann Liebert, Inc.

The Politics of Surveillance and Response to Disease Outbreaks: The New Frontier for States and Non-state Actors

The capacity to conduct international disease outbreak surveillance and share information about outbreaks quickly has empowered both State and Non-State Actors to take an active role in stopping the spread of disease by generating new technical means to identify potential pandemics through the creation of shared reporting platforms. Despite all the rhetoric about the importance of infectious disease surveillance, the concept itself has received relatively little critical attention from academics, practitioners, and policymakers. This book asks leading contributors in the field to engage with five key issues attached to international disease outbreak surveillance - transparency, local engagement, practical needs, integration, and appeal - to illuminate the political effect of these technologies on those who use surveillance, those who respond to surveillance, and those being monitored.

The politics of disease surveillance

The capacity to conduct international disease outbreak surveillance and share information about outbreaks quickly has empowered both State and Non-State Actors to take an active role in stopping the spread of disease by generating new technical means to identify potential pandemics through the creation of shared reporting platforms. Despite all the rhetoric about the importance of infectious disease surveillance, the concept itself has received relatively little critical attention from academics, practitioners, and policymakers. This book asks leading contributors in the field to engage with five key issues attached to international disease outbreak surveillance - transparency, local engagement, practical needs, integration, and appeal - to illuminate the political effect of these technologies on those who use surveillance, those who respond to surveillance, and those being monitored.

Robust automatic face clustering in news video

Clustering identities in a video is a useful task to aid in video search, annotation and retrieval, and cast identification. However, reliably clustering faces across multiple videos is challenging task due to variations in the appearance of the faces, as videos are captured in an uncontrolled environment. A person's appearance may vary due to session variations including: lighting and background changes, occlusions, changes in expression and make up. In this paper we propose the novel Local Total Variability Modelling (Local TVM) approach to cluster faces across a news video corpus; and incorporate this into a novel two stage video clustering system. We first cluster faces within a single video using colour, spatial and temporal cues; after which we use face track modelling and hierarchical agglomerative clustering to cluster faces across the entire corpus. We compare different face recognition approaches within this framework. Experiments on a news video database show that the Local TVM technique is able effectively model the session variation observed in the data, resulting in improved clustering performance, with much greater computational efficiency than other methods.