Quarantine and surveillance strategies for plant pathogen detection and control

Incursions of plant pests and diseases pose serious threats to food security, agricultural productivity and the natural environment. One of the challenges in confidently delimiting and eradicating incursions is how to choose from an arsenal of surveillance and quarantine approaches in order to best control multiple dispersal pathways. Anthropogenic spread (propagules carried on humans or transported on produce or equipment) can be controlled with quarantine measures, which in turn can vary in intensity. In contrast, environmental spread processes are more difficult to control, but often have a temporal signal (e.g. seasonality) which can introduce both challenges and opportunities for surveillance and control. This leads to complex decisions regarding when, where and how to search. Recent modelling investigations of surveillance performance have optimised the output of simulation models, and found that a risk-weighted randomised search can perform close to optimally. However, exactly how quarantine and surveillance strategies should change to reflect different dispersal modes remains largely unaddressed. Here we develop a spatial simulation model of a plant fungal-pathogen incursion into an agricultural region, and its subsequent surveillance and control. We include structural differences in dispersal via the interplay of biological, environmental and anthropogenic connectivity between host sites (farms). Our objective was to gain broad insights into the relative roles played by different spread modes in propagating an invasion, and how incorporating knowledge of these spread risks may improve approaches to quarantine restrictions and surveillance. We find that broad heuristic rules for quarantine restrictions fail to contain the pathogen due to residual connectivity between sites, but surveillance measures enable early detection and successfully lead to suppression of the pathogen in all farms. Alternative surveillance strategies attain similar levels of performance by incorporating environmental or anthropogenic dispersal risk in the prioritisation of sites. Our model provides the basis to develop essential insights into the effectiveness of different surveillance and quarantine decisions for fungal pathogen control. Parameterised for authentic settings it will aid our understanding of how the extent and resolution of interventions should suitably reflect the spatial structure of dispersal processes.

Sovereignty, surveillance and speeding: Considering the Panopticon as a method of policing

This paper argues that the Panopticon is an accurate model for and illustration of policing and security methods in the modern society. Initially, I overview the theoretical concept of the Panopticon as a structure of perceived universal surveillance which facilitates automatic obedience in its subjects as identified by the theorists Jeremy Bentham and Michel Foucault. The paper subsequently moves to identify how the Panopticon, despite being a theoretical construct, is nevertheless instantiated to an extent through the prevalence of security cameras as a means of sovereignly regulating human conduct; speeding is an ordinary example. It could even be contended that increasing surveillance according to the model of the Panopticon would reduce the frequency of offences. However, in the final analysis the paper considers that even if adopting an approach based on the Panopticon is a more effective method of policing, it is not necessarily a more desirable one.

Design of multimedia surveillance systems

This article addresses the problem of how to select the optimal combination of sensors and how to determine their optimal placement in a surveillance region in order to meet the given performance requirements at a minimal cost for a multimedia surveillance system. We propose to solve this problem by obtaining a performance vector, with its elements representing the performances of subtasks, for a given input combination of sensors and their placement. Then we show that the optimal sensor selection problem can be converted into the form of Integer Linear Programming problem (ILP) by using a linear model for computing the optimal performance vector corresponding to a sensor combination. Optimal performance vector corresponding to a sensor combination refers to the performance vector corresponding to the optimal placement of a sensor combination. To demonstrate the utility of our technique, we design and build a surveillance system consisting of PTZ (Pan-Tilt-Zoom) cameras and active motion sensors for capturing faces. Finally, we show experimentally that optimal placement of sensors based on the design maximizes the system performance.

Designing Dense Radar Networks for Weather Surveillance in Tropical Regions.

Design considerations are presented for a dense weather radar network to support multiple services including aviation. Conflicts, tradeoffs and optimization issues in the context of operation in a tropical region are brought out. The upcoming Indian radar network is used as a case study. Algorithms for data mosaicing are briefly outlined.

Surveillance in hereditary nonpolyposis colorectal cancer syndrome

Hereditary nonpolyposis colorectal cancer (HNPCC) is an inherited cancer predisposition syn-drome characterized by early onset colorectal cancer (CRC) and several other extra-colonic cancers, most commonly endometrial cancer (EC) and gastric cancer. Our aim was to evaluate the efficiency and results of the ongoing CRC and EC surveillance programs and to investigate the grounds for future gastric cancer screening by comparing the gastric biopsies of mutation positive and negative siblings in search for premalignant lesions. We also compared a new surveillance method, computerized tomographic colonoscopy (CTC) with optic colonoscopy. The patient material consisted of 579 family members from 111 Finnish HNPCC families al-most all harboring a known mismatch repair gene mutation. The efficacy of CRC and EC surveillance programs on HNPCC patients was evaluated by comparing the stage and survival of cancer cases detected with surveillance versus without. The performance of a new technique, CTC, was explored using a same-day colonoscopy as a reference standard. The use of intrauterine aspiration biopsies for EC surveillance was intro-duced for the first time in a HNPCC setting. Upper GI endoscopies were performed and biop-sies taken from mutation carriers and their mutation-negative siblings. The present surveillance program for CRC proved to be efficient. The CRC cases detected by surveillance were at a significantly more favorable stage than those in the non-surveilled group. This advantage was reflected in a significantly higher CRC-specific survival in the sur-veilled group. The performance of a new technique, CTC was found insufficient for polyp detection in this population in which every polyp, no matter the size, should be detected and removed. Colono-scopy was confirmed as a better surveillance modality than CTC. We could not observe any of the assumed differences in the gastric mucosa from mutation carriers and their mutation-negative siblings and no cases of gastric cancer were detected. The results gave no support for gastric surveillance. The EC surveillance program (transvaginal ultrasound and intra-uterine biopsy every 2-3 years) seemed to be efficient. It yielded several asymptomatic cancer cases and premalignant lesions. The stage distribution of the endometrial cancers in the group under surveillance tended to be more favorable than that of the mutation-positive, symptomatic EC patients who had no surveillance. None of the surveilled EC patients died of EC compared to six in the non-surveilled patients during the follow up. The improvement was, however, not statistically sig-nificant, thus far. Another observation was the good performance of endometrial aspiration biopsies used in this setting for the first time.

Using Bayesian networks to model surveillance in complex plant and animal health systems

In this chapter we consider biosecurity surveillance as part of a complex system comprising many different biological, environmental and human factors and their interactions. Modelling and analysis of surveillance strategies should take into account these complexities, and also facilitate the use and integration of the many types of different information that can provide insight into the system as a whole. After a brief discussion of a range of options, we focus on Bayesian networks for representing such complex systems. We summarize the features of Bayesian networks and describe these in the context of surveillance.

Surveillance of Surgical Site Infections following Major Hip and Knee Surgery in Finland

Background and aims. Since 1999, hospitals in the Finnish Hospital Infection Program (SIRO) have reported data on surgical site infections (SSI) following major hip and knee surgery. The purpose of this study was to obtain detailed information to support prevention efforts by analyzing SIRO data on SSIs, to evaluate possible factors affecting the surveillance results, and to assess the disease burden of postoperative prosthetic joint infections in Finland. Methods. Procedures under surveillance included total hip (THA) and total knee arthroplasties (TKA), and the open reduction and internal fixation (ORIF) of femur fractures. Hospitals prospectively collected data using common definitions and written protocol, and also performed postdischarge surveillance. In the validation study, a blinded retrospective chart review was performed and infection control nurses were interviewed. Patient charts of deep incisional and organ/space SSIs were reviewed, and data from three sources (SIRO, the Finnish Arthroplasty Register, and the Finnish Patient Insurance Centre) were linked for capture-recapture analyses. Results. During 1999-2002, the overall SSI rate was 3.3% after 11,812 orthopedic procedures (median length of stay, eight days). Of all SSIs, 56% were detected after discharge. The majority of deep incisional and organ/space SSIs (65/108, 60%) were detected on readmission. Positive and negative predictive values, sensitivity, and specificity for SIRO surveillance were 94% (95% CI, 89-99%), 99% (99-100%), 75% (56-93%), and 100% (97-100%), respectively. Of the 9,831 total joint replacements performed during 2001-2004, 7.2% (THA 5.2% and TKA 9.9%) of the implants were inserted in a simultaneous bilateral operation. Patients who underwent bilateral operations were younger, healthier, and more often males than those who underwent unilateral procedures. The rates of deep SSIs or mortality did not differ between bi- and uni-lateral THAs or TKAs. Four deep SSIs were reported following bilateral operations (antimicrobial prophylaxis administered 48-218 minutes before incision). In the three registers, altogether 129 prosthetic joint infections were identified after 13,482 THA and TKA during 1999-2004. After correction with the positive predictive value of SIRO (91%), a log-linear model provided an estimated overall prosthetic joint infection rate of 1.6% after THA and 1.3% after TKA. The sensitivity of the SIRO surveillance ranged from 36% to 57%. According to the estimation, nearly 200 prosthetic joint infections could occur in Finland each year (the average from 1999 to 2004) after THA and TKA. Conclusions. Postdischarge surveillance had a major impact on SSI rates after major hip and knee surgery. A minority of deep incisional and organ/space SSIs would be missed, however, if postdischarge surveillance by questionnaire was not performed. According to the validation study, most SSIs reported to SIRO were true infections. Some SSIs were missed, revealing some weakness in case finding. Variation in diagnostic practices may also affect SSI rates. No differences were found in deep SSI rates or mortality between bi- and unilateral THA and TKA. However, patient materials between these two groups differed. Bilateral operations require specific attention paid to their antimicrobial prophylaxis as well as to data management in the surveillance database. The true disease burden of prosthetic joint infections may be heavier than the rates from national nosocomial surveillance systems usually suggest.

Sentinel lymph node biopsy as a diagnostic tool in the treatment of breast cancer

The purpose of this study was to evaluate the use of sentinel node biopsy (SNB) in the axillary nodal staging in breast cancer. A special interest was in sentinel node (SN) visualization, intraoperative detection of SN metastases, the feasibility of SNB in patients with pure tubular carcinoma (PTC) and in those with ductal carcinoma in situ (DCIS) in core needle biopsy (CNB) and additionally in the detection of axillary recurrences after tumour negative SNB. Patients and methods. 1580 clinically stage T1-T2 node-negative breast cancer patients, who underwent lymphoscintigraphy (LS), SNB and breast surgery between June 2000 - 2004 at the Breast Surgery Unit. The CNB samples were obtained from women, who participated the biennial, population based mammography screening at the Mammography Screening Centre of Helsinki 2001 - 2004.In the follow- up, a cohort of 205 patients who avoided AC due to negative SNB findings were evaluated using ultrasonography one and three years after breast surgery. Results. The visualization rate of axillary SNs was not enhanced by adjusting radioisotope doses according to BMI. The sensitivity of the intraoperative diagnosis of SN metastases of invasive lobular carcinoma (ILC) was higher, 87%, with rapid, intraoperative immunohistochemistry (IHC) group compared to 66% without it. The prevalence of tumour positive SN findings was 27% in the 33 patients with breast tumours diagnosed as PTC. The median histological tumour size was similar in patients with or without axillary metastases. After the histopathological review, six out of 27 patients with true PTC had axillary metastases, with no significant change in the risk factors for axillary metastases. Of the 67 patients with DCIS in the preoperative percutaneous biopsy specimen , 30% had invasion in the surgical specimen. The strongest predictive factor for invasion was the visibility of the lesion in ultrasound. In the three year follow-up, axillary recurrence was found in only two (0.5%) of the total of 383 ultrasound examinations performed during the study, and only one of the 369 examinations revealed cancer. None of the ultrasound examinations were false positive, and no study participant was subjected to unnecessary surgery due to ultrasound monitoring. Conclusions. Adjusting the dose of the radioactive tracer according to patient BMI does not increase the visualization rate of SNs. The intraoperative diagnosis of SN metastases is enhanced by rapid IHC particularly in patients with ILC. SNB seems to be a feasible method for axillary staging of pure tubular carcinoma in patients with a low prevalence of axillary metatastases. SNB also appears to be a sensible method in patients undergoing mastectomy due to DCIS in CNB. It also seems useful in patients with lesions visible in breast US. During follow-up, routine monitoring of the ipsilateral axilla using US is not worthwhile among breast cancer patients who avoided AC due to negative SN findings.

Novel application of a discrete choice experiment to identify preferences for a national healthcare-associated infection surveillance programme: A cross-sectional study

Objective: To identify key stakeholder preferences and priorities when considering a national healthcare-associated infection (HAI) surveillance programme through the use of a discrete choice experiment (DCE). Setting: Australia does not have a national HAI surveillance programme. An online web-based DCE was developed and made available to participants in Australia. Participants: A sample of 184 purposively selected healthcare workers based on their senior leadership role in infection prevention in Australia. Primary and secondary outcomes: A DCE requiring respondents to select 1 HAI surveillance programme over another based on 5 different characteristics (or attributes) in repeated hypothetical scenarios. Data were analysed using a mixed logit model to evaluate preferences and identify the relative importance of each attribute. Results: A total of 122 participants completed the survey (response rate 66%) over a 5-week period. Excluding 22 who mismatched a duplicate choice scenario, analysis was conducted on 100 responses. The key findings included: 72% of stakeholders exhibited a preference for a surveillance programme with continuous mandatory core components (mean coefficient 0.640 (p<0.01)), 65% for a standard surveillance protocol where patient-level data are collected on infected and non-infected patients (mean coefficient 0.641 (p<0.01)), and 92% for hospital-level data that are publicly reported on a website and not associated with financial penalties (mean coefficient 1.663 (p<0.01)). Conclusions: The use of the DCE has provided a unique insight to key stakeholder priorities when considering a national HAI surveillance programme. The application of a DCE offers a meaningful method to explore and quantify preferences in this setting.

A design methodology for selecting and placement of sensors in multimedia surveillance systems

This paper addresses the problem of how to select the optimal number of sensors and how to determine their placement in a given monitored area for multimedia surveillance systems. We propose to solve this problem by obtaining a novel performance metric in terms of a probability measure for accomplishing the task as a function of set of sensors and their placement. This measure is then used to find the optimal set. The same measure can be used to analyze the degradation in system 's performance with respect to the failure of various sensors. We also build a surveillance system using the optimal set of sensors obtained based on the proposed design methodology. Experimental results show the effectiveness of the proposed design methodology in selecting the optimal set of sensors and their placement.

Boosting-based transfer learning for multi-view head-pose classification from surveillance videos

This work proposes a boosting-based transfer learning approach for head-pose classification from multiple, low-resolution views. Head-pose classification performance is adversely affected when the source (training) and target (test) data arise from different distributions (due to change in face appearance, lighting, etc). Under such conditions, we employ Xferboost, a Logitboost-based transfer learning framework that integrates knowledge from a few labeled target samples with the source model to effectively minimize misclassifications on the target data. Experiments confirm that the Xferboost framework can improve classification performance by up to 6%, when knowledge is transferred between the CLEAR and FBK four-view headpose datasets.

Monte Carlo simulation of light transport in tissue for optimizing light delivery in photoacoustic imaging of the sentinel lymph node

Noninvasive or minimally invasive identification of sentinel lymph node (SLN) is essential to reduce the surgical effects of SLN biopsy. Photoacoustic (PA) imaging of SLN in animal models has shown its promise for clinical use in the future. Here, we present a Monte Carlo simulation for light transport in the SLN for various light delivery configurations with a clinical ultrasound probe. Our simulation assumes a realistic tissue layer model and also can handle the transmission/reflectance at SLN-tissue boundary due to the mismatch of refractive index. Various light incidence angles show that for deeply situated SLNs the maximum absorption of light in the SLN is for normal incidence. We also show that if a part of the diffused reflected photons is reflected back into the skin using a reflector, the absorption of light in the SLN can be increased significantly to enhance the PA signal. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)